chore(i18n): sync translations with en-US

.github/dependabot.yml

@@ -1,6 +1,106 @@
 version: 2
 
 updates:
+  - package-ecosystem: "pip"
+    directory: "/api"
+    open-pull-requests-limit: 10
+    schedule:
+      interval: "weekly"
+    groups:
+      flask:
+        patterns:
+          - "flask"
+          - "flask-*"
+          - "werkzeug"
+          - "gunicorn"
+      google:
+        patterns:
+          - "google-*"
+          - "googleapis-*"
+      opentelemetry:
+        patterns:
+          - "opentelemetry-*"
+      pydantic:
+        patterns:
+          - "pydantic"
+          - "pydantic-*"
+      llm:
+        patterns:
+          - "langfuse"
+          - "langsmith"
+          - "litellm"
+          - "mlflow*"
+          - "opik"
+          - "weave*"
+          - "arize*"
+          - "tiktoken"
+          - "transformers"
+      database:
+        patterns:
+          - "sqlalchemy"
+          - "psycopg2*"
+          - "psycogreen"
+          - "redis*"
+          - "alembic*"
+      storage:
+        patterns:
+          - "boto3*"
+          - "botocore*"
+          - "azure-*"
+          - "bce-*"
+          - "cos-python-*"
+          - "esdk-obs-*"
+          - "google-cloud-storage"
+          - "opendal"
+          - "oss2"
+          - "supabase*"
+          - "tos*"
+      vdb:
+        patterns:
+          - "alibabacloud*"
+          - "chromadb"
+          - "clickhouse-*"
+          - "clickzetta-*"
+          - "couchbase"
+          - "elasticsearch"
+          - "opensearch-py"
+          - "oracledb"
+          - "pgvect*"
+          - "pymilvus"
+          - "pymochow"
+          - "pyobvector"
+          - "qdrant-client"
+          - "intersystems-*"
+          - "tablestore"
+          - "tcvectordb"
+          - "tidb-vector"
+          - "upstash-*"
+          - "volcengine-*"
+          - "weaviate-*"
+          - "xinference-*"
+          - "mo-vector"
+          - "mysql-connector-*"
+      dev:
+        patterns:
+          - "coverage"
+          - "dotenv-linter"
+          - "faker"
+          - "lxml-stubs"
+          - "basedpyright"
+          - "ruff"
+          - "pytest*"
+          - "types-*"
+          - "boto3-stubs"
+          - "hypothesis"
+          - "pandas-stubs"
+          - "scipy-stubs"
+          - "import-linter"
+          - "celery-types"
+          - "mypy*"
+          - "pyrefly"
+      python-packages:
+        patterns:
+          - "*"
   - package-ecosystem: "uv"
     directory: "/api"
     open-pull-requests-limit: 10

.github/pull_request_template.md

@@ -7,7 +7,6 @@
 ## Summary
 
 <!-- Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change. -->
-<!-- If this PR was created by an automated agent, add `From <Tool Name>` as the final line of the description. Example: `From Codex`. -->
 
 ## Screenshots
 
@@ -18,7 +17,7 @@
 ## Checklist
 
 - [ ] This change requires a documentation update, included: [Dify Document](https://github.com/langgenius/dify-docs)
-- [ ] I understand that this PR may be closed in case there was no previous discussion or issues. (This doesn't apply to typos!)
-- [ ] I've added a test for each change that was introduced, and I tried as much as possible to make a single atomic change.
-- [ ] I've updated the documentation accordingly.
-- [ ] I ran `make lint && make type-check` (backend) and `cd web && pnpm exec vp staged` (frontend) to appease the lint gods
+- [x] I understand that this PR may be closed in case there was no previous discussion or issues. (This doesn't apply to typos!)
+- [x] I've added a test for each change that was introduced, and I tried as much as possible to make a single atomic change.
+- [x] I've updated the documentation accordingly.
+- [x] I ran `make lint` and `make type-check` (backend) and `cd web && pnpm exec vp staged` (frontend) to appease the lint gods

.github/workflows/api-tests.yml

@@ -54,7 +54,7 @@ jobs:
         run: uv run --project api bash dev/pytest/pytest_unit_tests.sh
 
       - name: Upload unit coverage data
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
         with:
           name: api-coverage-unit
           path: coverage-unit
@@ -129,7 +129,7 @@ jobs:
             api/tests/test_containers_integration_tests
 
       - name: Upload integration coverage data
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
         with:
           name: api-coverage-integration
           path: coverage-integration

.github/workflows/build-push.yml

@@ -81,7 +81,7 @@ jobs:
 
       - name: Build Docker image
         id: build
-        uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
+        uses: docker/build-push-action@d08e5c354a6adb9ed34480a06d141179aa583294 # v7.0.0
         with:
           context: ${{ matrix.build_context }}
           file: ${{ matrix.file }}
@@ -101,7 +101,7 @@ jobs:
           touch "/tmp/digests/${sanitized_digest}"
 
       - name: Upload digest
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
         with:
           name: digests-${{ matrix.artifact_context }}-${{ env.PLATFORM_PAIR }}
           path: /tmp/digests/*

.github/workflows/docker-build.yml

@@ -50,7 +50,7 @@ jobs:
         uses: docker/setup-buildx-action@4d04d5d9486b7bd6fa91e7baf45bbb4f8b9deedd # v4.0.0
 
       - name: Build Docker Image
-        uses: docker/build-push-action@bcafcacb16a39f128d818304e6c9c0c18556b85f # v7.1.0
+        uses: docker/build-push-action@d08e5c354a6adb9ed34480a06d141179aa583294 # v7.0.0
         with:
           push: false
           context: ${{ matrix.context }}

.github/workflows/pyrefly-diff-comment.yml

@@ -21,7 +21,7 @@ jobs:
     if: ${{ github.event.workflow_run.conclusion == 'success' && github.event.workflow_run.pull_requests[0].head.repo.full_name != github.repository }}
     steps:
       - name: Download pyrefly diff artifact
-        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
+        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           script: |
@@ -49,7 +49,7 @@ jobs:
         run: unzip -o pyrefly_diff.zip
 
       - name: Post comment
-        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
+        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           script: |

.github/workflows/pyrefly-diff.yml

@@ -66,7 +66,7 @@ jobs:
           echo ${{ github.event.pull_request.number }} > pr_number.txt
 
       - name: Upload pyrefly diff
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
         with:
           name: pyrefly_diff
           path: |
@@ -75,7 +75,7 @@ jobs:
 
       - name: Comment PR with pyrefly diff
         if: ${{ github.event.pull_request.head.repo.full_name == github.repository && steps.line_count_check.outputs.same == 'false' }}
-        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
+        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           script: |

.github/workflows/pyrefly-type-coverage-comment.yml

@@ -1,118 +0,0 @@
-name: Comment with Pyrefly Type Coverage
-
-on:
-  workflow_run:
-    workflows:
-      - Pyrefly Type Coverage
-    types:
-      - completed
-
-permissions: {}
-
-jobs:
-  comment:
-    name: Comment PR with type coverage
-    runs-on: ubuntu-latest
-    permissions:
-      actions: read
-      contents: read
-      issues: write
-      pull-requests: write
-    if: ${{ github.event.workflow_run.conclusion == 'success' && github.event.workflow_run.pull_requests[0].head.repo.full_name != github.repository }}
-    steps:
-      - name: Checkout default branch (trusted code)
-        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-
-      - name: Setup Python & UV
-        uses: astral-sh/setup-uv@cec208311dfd045dd5311c1add060b2062131d57 # v8.0.0
-        with:
-          enable-cache: true
-
-      - name: Install dependencies
-        run: uv sync --project api --dev
-
-      - name: Download type coverage artifact
-        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          script: |
-            const fs = require('fs');
-            const artifacts = await github.rest.actions.listWorkflowRunArtifacts({
-              owner: context.repo.owner,
-              repo: context.repo.repo,
-              run_id: ${{ github.event.workflow_run.id }},
-            });
-            const match = artifacts.data.artifacts.find((artifact) =>
-              artifact.name === 'pyrefly_type_coverage'
-            );
-            if (!match) {
-              throw new Error('pyrefly_type_coverage artifact not found');
-            }
-            const download = await github.rest.actions.downloadArtifact({
-              owner: context.repo.owner,
-              repo: context.repo.repo,
-              artifact_id: match.id,
-              archive_format: 'zip',
-            });
-            fs.writeFileSync('pyrefly_type_coverage.zip', Buffer.from(download.data));
-
-      - name: Unzip artifact
-        run: unzip -o pyrefly_type_coverage.zip
-
-      - name: Render coverage markdown from structured data
-        id: render
-        run: |
-          comment_body="$(uv run --directory api python api/libs/pyrefly_type_coverage.py \
-            --base base_report.json \
-            < pr_report.json)"
-
-          {
-            echo "### Pyrefly Type Coverage"
-            echo ""
-            echo "$comment_body"
-          } > /tmp/type_coverage_comment.md
-
-      - name: Post comment
-        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          script: |
-            const fs = require('fs');
-            const body = fs.readFileSync('/tmp/type_coverage_comment.md', { encoding: 'utf8' });
-            let prNumber = null;
-            try {
-              prNumber = parseInt(fs.readFileSync('pr_number.txt', { encoding: 'utf8' }), 10);
-            } catch (err) {
-              const prs = context.payload.workflow_run.pull_requests || [];
-              if (prs.length > 0 && prs[0].number) {
-                prNumber = prs[0].number;
-              }
-            }
-            if (!prNumber) {
-              throw new Error('PR number not found in artifact or workflow_run payload');
-            }
-
-            // Update existing comment if one exists, otherwise create new
-            const { data: comments } = await github.rest.issues.listComments({
-              issue_number: prNumber,
-              owner: context.repo.owner,
-              repo: context.repo.repo,
-            });
-            const marker = '### Pyrefly Type Coverage';
-            const existing = comments.find(c => c.body.startsWith(marker));
-
-            if (existing) {
-              await github.rest.issues.updateComment({
-                comment_id: existing.id,
-                owner: context.repo.owner,
-                repo: context.repo.repo,
-                body,
-              });
-            } else {
-              await github.rest.issues.createComment({
-                issue_number: prNumber,
-                owner: context.repo.owner,
-                repo: context.repo.repo,
-                body,
-              });
-            }

.github/workflows/pyrefly-type-coverage.yml

@@ -1,120 +0,0 @@
-name: Pyrefly Type Coverage
-
-on:
-  pull_request:
-    paths:
-      - 'api/**/*.py'
-
-permissions:
-  contents: read
-
-jobs:
-  pyrefly-type-coverage:
-    runs-on: ubuntu-latest
-    permissions:
-      contents: read
-      issues: write
-      pull-requests: write
-    steps:
-      - name: Checkout PR branch
-        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
-        with:
-          fetch-depth: 0
-
-      - name: Setup Python & UV
-        uses: astral-sh/setup-uv@cec208311dfd045dd5311c1add060b2062131d57 # v8.0.0
-        with:
-          enable-cache: true
-
-      - name: Install dependencies
-        run: uv sync --project api --dev
-
-      - name: Run pyrefly report on PR branch
-        run: |
-          uv run --directory api --dev pyrefly report 2>/dev/null > /tmp/pyrefly_report_pr.tmp && \
-            mv /tmp/pyrefly_report_pr.tmp /tmp/pyrefly_report_pr.json || \
-            echo '{}' > /tmp/pyrefly_report_pr.json
-
-      - name: Save helper script from base branch
-        run: |
-          git show ${{ github.event.pull_request.base.sha }}:api/libs/pyrefly_type_coverage.py > /tmp/pyrefly_type_coverage.py 2>/dev/null \
-            || cp api/libs/pyrefly_type_coverage.py /tmp/pyrefly_type_coverage.py
-
-      - name: Checkout base branch
-        run: git checkout ${{ github.base_ref }}
-
-      - name: Run pyrefly report on base branch
-        run: |
-          uv run --directory api --dev pyrefly report 2>/dev/null > /tmp/pyrefly_report_base.tmp && \
-            mv /tmp/pyrefly_report_base.tmp /tmp/pyrefly_report_base.json || \
-            echo '{}' > /tmp/pyrefly_report_base.json
-
-      - name: Generate coverage comparison
-        id: coverage
-        run: |
-          comment_body="$(uv run --directory api python /tmp/pyrefly_type_coverage.py \
-            --base /tmp/pyrefly_report_base.json \
-            < /tmp/pyrefly_report_pr.json)"
-
-          {
-            echo "### Pyrefly Type Coverage"
-            echo ""
-            echo "$comment_body"
-          } | tee -a "$GITHUB_STEP_SUMMARY" > /tmp/type_coverage_comment.md
-
-          # Save structured data for the fork-PR comment workflow
-          cp /tmp/pyrefly_report_pr.json pr_report.json
-          cp /tmp/pyrefly_report_base.json base_report.json
-
-      - name: Save PR number
-        run: |
-          echo ${{ github.event.pull_request.number }} > pr_number.txt
-
-      - name: Upload type coverage artifact
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
-        with:
-          name: pyrefly_type_coverage
-          path: |
-            pr_report.json
-            base_report.json
-            pr_number.txt
-
-      - name: Comment PR with type coverage
-        if: ${{ github.event.pull_request.head.repo.full_name == github.repository }}
-        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          script: |
-            const fs = require('fs');
-            const marker = '### Pyrefly Type Coverage';
-            let body;
-            try {
-              body = fs.readFileSync('/tmp/type_coverage_comment.md', { encoding: 'utf8' });
-            } catch {
-              body = `${marker}\n\n_Coverage report unavailable._`;
-            }
-            const prNumber = context.payload.pull_request.number;
-
-            // Update existing comment if one exists, otherwise create new
-            const { data: comments } = await github.rest.issues.listComments({
-              issue_number: prNumber,
-              owner: context.repo.owner,
-              repo: context.repo.repo,
-            });
-            const existing = comments.find(c => c.body.startsWith(marker));
-
-            if (existing) {
-              await github.rest.issues.updateComment({
-                comment_id: existing.id,
-                owner: context.repo.owner,
-                repo: context.repo.repo,
-                body,
-              });
-            } else {
-              await github.rest.issues.createComment({
-                issue_number: prNumber,
-                owner: context.repo.owner,
-                repo: context.repo.repo,
-                body,
-              });
-            }

.github/workflows/stale.yml

@@ -23,8 +23,8 @@ jobs:
           days-before-issue-stale: 15
           days-before-issue-close: 3
           repo-token: ${{ secrets.GITHUB_TOKEN }}
-          stale-issue-message: "Closed due to inactivity. If you have any questions, you can reopen it."
-          stale-pr-message: "Closed due to inactivity. If you have any questions, you can reopen it."
+          stale-issue-message: "Close due to it's no longer active, if you have any questions, you can reopen it."
+          stale-pr-message: "Close due to it's no longer active, if you have any questions, you can reopen it."
           stale-issue-label: 'no-issue-activity'
           stale-pr-label: 'no-pr-activity'
-          any-of-labels: '🌚 invalid,🙋‍♂️ question,wont-fix,no-issue-activity,no-pr-activity,💪 enhancement,🤔 cant-reproduce,🙏 help wanted'
+          any-of-labels: 'duplicate,question,invalid,wontfix,no-issue-activity,no-pr-activity,enhancement,cant-reproduce,help-wanted'

.github/workflows/translate-i18n-claude.yml

@@ -158,7 +158,7 @@ jobs:
 
       - name: Run Claude Code for Translation Sync
         if: steps.context.outputs.CHANGED_FILES != ''
-        uses: anthropics/claude-code-action@b47fd721da662d48c5680e154ad16a73ed74d2e0 # v1.0.93
+        uses: anthropics/claude-code-action@6e2bd52842c65e914eba5c8badd17560bd26b5de # v1.0.89
         with:
           anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
           github_token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/trigger-i18n-sync.yml

@@ -56,7 +56,7 @@ jobs:
 
       - name: Trigger i18n sync workflow
         if: steps.detect.outputs.has_changes == 'true'
-        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
+        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
         env:
           BASE_SHA: ${{ steps.detect.outputs.base_sha }}
           HEAD_SHA: ${{ steps.detect.outputs.head_sha }}

.github/workflows/web-e2e.yml

@@ -53,7 +53,7 @@ jobs:
 
       - name: Upload Cucumber report
         if: ${{ !cancelled() }}
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
         with:
           name: cucumber-report
           path: e2e/cucumber-report
@@ -61,7 +61,7 @@ jobs:
 
       - name: Upload E2E logs
         if: ${{ !cancelled() }}
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
         with:
           name: e2e-logs
           path: e2e/.logs

.github/workflows/web-tests.yml

@@ -43,7 +43,7 @@ jobs:
 
       - name: Upload blob report
         if: ${{ !cancelled() }}
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
         with:
           name: blob-report-${{ matrix.shardIndex }}
           path: web/.vitest-reports/*

CONTRIBUTING.md

@@ -97,3 +97,8 @@ Feel free to reach out if you encounter any issues during the setup process.
 ## Getting Help
 
 If you ever get stuck or get a burning question while contributing, simply shoot your queries our way via the related GitHub issue, or hop onto our [Discord](https://discord.gg/8Tpq4AcN9c) for a quick chat.
+
+## Automated Agent Contributions
+
+> [!NOTE]
+> If you are an automated agent， just add 🤖🤖🤖 to the end of the PR title to opt-in.

api/.env.example

@@ -71,13 +71,6 @@ REDIS_USE_CLUSTERS=false
 REDIS_CLUSTERS=
 REDIS_CLUSTERS_PASSWORD=
 
-REDIS_RETRY_RETRIES=3
-REDIS_RETRY_BACKOFF_BASE=1.0
-REDIS_RETRY_BACKOFF_CAP=10.0
-REDIS_SOCKET_TIMEOUT=5.0
-REDIS_SOCKET_CONNECT_TIMEOUT=5.0
-REDIS_HEALTH_CHECK_INTERVAL=30
-
 # celery configuration
 CELERY_BROKER_URL=redis://:difyai123456@localhost:${REDIS_PORT}/1
 CELERY_BACKEND=redis
@@ -109,7 +102,6 @@ S3_BUCKET_NAME=your-bucket-name
 S3_ACCESS_KEY=your-access-key
 S3_SECRET_KEY=your-secret-key
 S3_REGION=your-region
-S3_ADDRESS_STYLE=auto
 
 # Workflow run and Conversation archive storage (S3-compatible)
 ARCHIVE_STORAGE_ENABLED=false

api/commands/account.py

@@ -2,6 +2,7 @@ import base64
 import secrets
 
 import click
+from sqlalchemy.orm import sessionmaker
 
 from constants.languages import languages
 from extensions.ext_database import db
@@ -24,31 +25,30 @@ def reset_password(email, new_password, password_confirm):
         return
     normalized_email = email.strip().lower()
 
-    account = AccountService.get_account_by_email_with_case_fallback(email.strip())
+    with sessionmaker(db.engine, expire_on_commit=False).begin() as session:
+        account = AccountService.get_account_by_email_with_case_fallback(email.strip(), session=session)
 
-    if not account:
-        click.echo(click.style(f"Account not found for email: {email}", fg="red"))
-        return
+        if not account:
+            click.echo(click.style(f"Account not found for email: {email}", fg="red"))
+            return
 
-    try:
-        valid_password(new_password)
-    except:
-        click.echo(click.style(f"Invalid password. Must match {password_pattern}", fg="red"))
-        return
+        try:
+            valid_password(new_password)
+        except:
+            click.echo(click.style(f"Invalid password. Must match {password_pattern}", fg="red"))
+            return
 
-    # generate password salt
-    salt = secrets.token_bytes(16)
-    base64_salt = base64.b64encode(salt).decode()
+        # generate password salt
+        salt = secrets.token_bytes(16)
+        base64_salt = base64.b64encode(salt).decode()
 
-    # encrypt password with salt
-    password_hashed = hash_password(new_password, salt)
-    base64_password_hashed = base64.b64encode(password_hashed).decode()
-    account = db.session.merge(account)
-    account.password = base64_password_hashed
-    account.password_salt = base64_salt
-    db.session.commit()
-    AccountService.reset_login_error_rate_limit(normalized_email)
-    click.echo(click.style("Password reset successfully.", fg="green"))
+        # encrypt password with salt
+        password_hashed = hash_password(new_password, salt)
+        base64_password_hashed = base64.b64encode(password_hashed).decode()
+        account.password = base64_password_hashed
+        account.password_salt = base64_salt
+        AccountService.reset_login_error_rate_limit(normalized_email)
+        click.echo(click.style("Password reset successfully.", fg="green"))
 
 
 @click.command("reset-email", help="Reset the account email.")
@@ -65,22 +65,21 @@ def reset_email(email, new_email, email_confirm):
         return
     normalized_new_email = new_email.strip().lower()
 
-    account = AccountService.get_account_by_email_with_case_fallback(email.strip())
+    with sessionmaker(db.engine, expire_on_commit=False).begin() as session:
+        account = AccountService.get_account_by_email_with_case_fallback(email.strip(), session=session)
 
-    if not account:
-        click.echo(click.style(f"Account not found for email: {email}", fg="red"))
-        return
+        if not account:
+            click.echo(click.style(f"Account not found for email: {email}", fg="red"))
+            return
 
-    try:
-        email_validate(normalized_new_email)
-    except:
-        click.echo(click.style(f"Invalid email: {new_email}", fg="red"))
-        return
+        try:
+            email_validate(normalized_new_email)
+        except:
+            click.echo(click.style(f"Invalid email: {new_email}", fg="red"))
+            return
 
-    account = db.session.merge(account)
-    account.email = normalized_new_email
-    db.session.commit()
-    click.echo(click.style("Email updated successfully.", fg="green"))
+        account.email = normalized_new_email
+        click.echo(click.style("Email updated successfully.", fg="green"))
 
 
 @click.command("create-tenant", help="Create account and tenant.")

api/configs/feature/__init__.py

@@ -287,27 +287,6 @@ class MarketplaceConfig(BaseSettings):
     )
 
 
-class CreatorsPlatformConfig(BaseSettings):
-    """
-    Configuration for creators platform
-    """
-
-    CREATORS_PLATFORM_FEATURES_ENABLED: bool = Field(
-        description="Enable or disable creators platform features",
-        default=True,
-    )
-
-    CREATORS_PLATFORM_API_URL: HttpUrl = Field(
-        description="Creators Platform API URL",
-        default=HttpUrl("https://creators.dify.ai"),
-    )
-
-    CREATORS_PLATFORM_OAUTH_CLIENT_ID: str = Field(
-        description="OAuth client_id for the Creators Platform app registered in Dify",
-        default="",
-    )
-
-
 class EndpointConfig(BaseSettings):
     """
     Configuration for various application endpoints and URLs
@@ -362,15 +341,6 @@ class FileAccessConfig(BaseSettings):
         default="",
     )
 
-    FILES_API_URL: str = Field(
-        description="Base URL for storage file ticket API endpoints."
-        " Used by sandbox containers (internal or external like e2b) that need"
-        " an absolute, routable address to upload/download files via the API."
-        " For all-in-one Docker deployments, set to http://localhost."
-        " For public sandbox environments, set to a public domain or IP.",
-        default="",
-    )
-
     FILES_ACCESS_TIMEOUT: int = Field(
         description="Expiration time in seconds for file access URLs",
         default=300,
@@ -1304,52 +1274,6 @@ class PositionConfig(BaseSettings):
         return {item.strip() for item in self.POSITION_TOOL_EXCLUDES.split(",") if item.strip() != ""}
 
 
-class CollaborationConfig(BaseSettings):
-    ENABLE_COLLABORATION_MODE: bool = Field(
-        description="Whether to enable collaboration mode features across the workspace",
-        default=False,
-    )
-
-
-class SandboxExpiredRecordsCleanConfig(BaseSettings):
-    SANDBOX_EXPIRED_RECORDS_CLEAN_GRACEFUL_PERIOD: NonNegativeInt = Field(
-        description="Graceful period in days for sandbox records clean after subscription expiration",
-        default=21,
-    )
-    SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_SIZE: PositiveInt = Field(
-        description="Maximum number of records to process in each batch",
-        default=1000,
-    )
-    SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_MAX_INTERVAL: PositiveInt = Field(
-        description="Maximum interval in milliseconds between batches",
-        default=200,
-    )
-    SANDBOX_EXPIRED_RECORDS_RETENTION_DAYS: PositiveInt = Field(
-        description="Retention days for sandbox expired workflow_run records and message records",
-        default=30,
-    )
-    SANDBOX_EXPIRED_RECORDS_CLEAN_TASK_LOCK_TTL: PositiveInt = Field(
-        description="Lock TTL for sandbox expired records clean task in seconds",
-        default=90000,
-    )
-
-
-class AgentV2UpgradeConfig(BaseSettings):
-    """Feature flags for transparent Agent V2 upgrade."""
-
-    AGENT_V2_TRANSPARENT_UPGRADE: bool = Field(
-        description="Transparently run old apps (chat/completion/agent-chat) through the Agent V2 workflow engine. "
-        "When enabled, old apps synthesize a virtual workflow at runtime instead of using legacy runners.",
-        default=False,
-    )
-
-    AGENT_V2_REPLACES_LLM: bool = Field(
-        description="Transparently replace LLM nodes in workflows with Agent V2 nodes at runtime. "
-        "LLMNodeData is remapped to AgentV2NodeData with tools=[] (identical behavior).",
-        default=False,
-    )
-
-
 class LoginConfig(BaseSettings):
     ENABLE_EMAIL_CODE_LOGIN: bool = Field(
         description="whether to enable email code login",
@@ -1419,6 +1343,29 @@ class TenantIsolatedTaskQueueConfig(BaseSettings):
     )
 
 
+class SandboxExpiredRecordsCleanConfig(BaseSettings):
+    SANDBOX_EXPIRED_RECORDS_CLEAN_GRACEFUL_PERIOD: NonNegativeInt = Field(
+        description="Graceful period in days for sandbox records clean after subscription expiration",
+        default=21,
+    )
+    SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_SIZE: PositiveInt = Field(
+        description="Maximum number of records to process in each batch",
+        default=1000,
+    )
+    SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_MAX_INTERVAL: PositiveInt = Field(
+        description="Maximum interval in milliseconds between batches",
+        default=200,
+    )
+    SANDBOX_EXPIRED_RECORDS_RETENTION_DAYS: PositiveInt = Field(
+        description="Retention days for sandbox expired workflow_run records and message records",
+        default=30,
+    )
+    SANDBOX_EXPIRED_RECORDS_CLEAN_TASK_LOCK_TTL: PositiveInt = Field(
+        description="Lock TTL for sandbox expired records clean task in seconds",
+        default=90000,
+    )
+
+
 class FeatureConfig(
     # place the configs in alphabet order
     AppExecutionConfig,
@@ -1429,7 +1376,6 @@ class FeatureConfig(
     AsyncWorkflowConfig,
     PluginConfig,
     MarketplaceConfig,
-    CreatorsPlatformConfig,
     DataSetConfig,
     EndpointConfig,
     FileAccessConfig,
@@ -1445,6 +1391,7 @@ class FeatureConfig(
     PositionConfig,
     RagEtlConfig,
     RepositoryConfig,
+    SandboxExpiredRecordsCleanConfig,
     SecurityConfig,
     TenantIsolatedTaskQueueConfig,
     ToolConfig,
@@ -1452,9 +1399,6 @@ class FeatureConfig(
     WorkflowConfig,
     WorkflowNodeExecutionConfig,
     WorkspaceConfig,
-    CollaborationConfig,
-    AgentV2UpgradeConfig,
-    SandboxExpiredRecordsCleanConfig,
     LoginConfig,
     AccountConfig,
     SwaggerUIConfig,

api/configs/middleware/__init__.py

@@ -1,5 +1,5 @@
 import os
-from typing import Any, Literal, TypedDict
+from typing import Any, Literal
 from urllib.parse import parse_qsl, quote_plus
 
 from pydantic import Field, NonNegativeFloat, NonNegativeInt, PositiveFloat, PositiveInt, computed_field
@@ -107,17 +107,6 @@ class KeywordStoreConfig(BaseSettings):
     )
 
 
-class SQLAlchemyEngineOptionsDict(TypedDict):
-    pool_size: int
-    max_overflow: int
-    pool_recycle: int
-    pool_pre_ping: bool
-    connect_args: dict[str, str]
-    pool_use_lifo: bool
-    pool_reset_on_return: None
-    pool_timeout: int
-
-
 class DatabaseConfig(BaseSettings):
     # Database type selector
     DB_TYPE: Literal["postgresql", "mysql", "oceanbase", "seekdb"] = Field(
@@ -220,11 +209,11 @@ class DatabaseConfig(BaseSettings):
 
     @computed_field  # type: ignore[prop-decorator]
     @property
-    def SQLALCHEMY_ENGINE_OPTIONS(self) -> SQLAlchemyEngineOptionsDict:
+    def SQLALCHEMY_ENGINE_OPTIONS(self) -> dict[str, Any]:
         # Parse DB_EXTRAS for 'options'
         db_extras_dict = dict(parse_qsl(self.DB_EXTRAS))
         options = db_extras_dict.get("options", "")
-        connect_args: dict[str, str] = {}
+        connect_args = {}
         # Use the dynamic SQLALCHEMY_DATABASE_URI_SCHEME property
         if self.SQLALCHEMY_DATABASE_URI_SCHEME.startswith("postgresql"):
             timezone_opt = "-c timezone=UTC"
@@ -234,7 +223,7 @@ class DatabaseConfig(BaseSettings):
                 merged_options = timezone_opt
             connect_args = {"options": merged_options}
 
-        result: SQLAlchemyEngineOptionsDict = {
+        return {
             "pool_size": self.SQLALCHEMY_POOL_SIZE,
             "max_overflow": self.SQLALCHEMY_MAX_OVERFLOW,
             "pool_recycle": self.SQLALCHEMY_POOL_RECYCLE,
@@ -244,7 +233,6 @@ class DatabaseConfig(BaseSettings):
             "pool_reset_on_return": None,
             "pool_timeout": self.SQLALCHEMY_POOL_TIMEOUT,
         }
-        return result
 
 
 class CeleryConfig(DatabaseConfig):

api/configs/middleware/cache/redis_config.py

@@ -117,37 +117,6 @@ class RedisConfig(BaseSettings):
         default=None,
     )
 
-    REDIS_RETRY_RETRIES: NonNegativeInt = Field(
-        description="Maximum number of retries per Redis command on "
-        "transient failures (ConnectionError, TimeoutError, socket.timeout)",
-        default=3,
-    )
-
-    REDIS_RETRY_BACKOFF_BASE: PositiveFloat = Field(
-        description="Base delay in seconds for exponential backoff between retries",
-        default=1.0,
-    )
-
-    REDIS_RETRY_BACKOFF_CAP: PositiveFloat = Field(
-        description="Maximum backoff delay in seconds between retries",
-        default=10.0,
-    )
-
-    REDIS_SOCKET_TIMEOUT: PositiveFloat | None = Field(
-        description="Socket timeout in seconds for Redis read/write operations",
-        default=5.0,
-    )
-
-    REDIS_SOCKET_CONNECT_TIMEOUT: PositiveFloat | None = Field(
-        description="Socket timeout in seconds for Redis connection establishment",
-        default=5.0,
-    )
-
-    REDIS_HEALTH_CHECK_INTERVAL: NonNegativeInt = Field(
-        description="Interval in seconds between Redis connection health checks (0 to disable)",
-        default=30,
-    )
-
     @field_validator("REDIS_MAX_CONNECTIONS", mode="before")
     @classmethod
     def _empty_string_to_none_for_max_conns(cls, v):

api/constants/model_template.py

@@ -81,20 +81,4 @@ default_app_templates: Mapping[AppMode, Mapping] = {
             },
         },
     },
-    # agent default mode (new agent backed by single-node workflow)
-    AppMode.AGENT: {
-        "app": {
-            "mode": AppMode.AGENT,
-            "enable_site": True,
-            "enable_api": True,
-        },
-        "model_config": {
-            "model": {
-                "provider": "openai",
-                "name": "gpt-4o",
-                "mode": "chat",
-                "completion_params": {},
-            },
-        },
-    },
 }

api/controllers/common/controller_schemas.py

@@ -1,5 +1,4 @@
 from typing import Any, Literal
-from uuid import UUID
 
 from pydantic import BaseModel, Field, model_validator
 
@@ -24,9 +23,9 @@ class ConversationRenamePayload(BaseModel):
 
 
 class MessageListQuery(BaseModel):
-    conversation_id: UUIDStrOrEmpty = Field(description="Conversation UUID")
-    first_id: UUIDStrOrEmpty | None = Field(default=None, description="First message ID for pagination")
-    limit: int = Field(default=20, ge=1, le=100, description="Number of messages to return (1-100)")
+    conversation_id: UUIDStrOrEmpty
+    first_id: UUIDStrOrEmpty | None = None
+    limit: int = Field(default=20, ge=1, le=100)
 
 
 class MessageFeedbackPayload(BaseModel):
@@ -49,56 +48,16 @@ class SavedMessageCreatePayload(BaseModel):
 # --- Workflow schemas ---
 
 
-class DefaultBlockConfigQuery(BaseModel):
-    q: str | None = None
-
-
-class WorkflowListQuery(BaseModel):
-    page: int = Field(default=1, ge=1, le=99999)
-    limit: int = Field(default=10, ge=1, le=100)
-    user_id: str | None = None
-    named_only: bool = False
-
-
 class WorkflowRunPayload(BaseModel):
     inputs: dict[str, Any]
     files: list[dict[str, Any]] | None = None
 
 
-class WorkflowUpdatePayload(BaseModel):
-    marked_name: str | None = Field(default=None, max_length=20)
-    marked_comment: str | None = Field(default=None, max_length=100)
-
-
-# --- Dataset schemas ---
-
-
-DOCUMENT_BATCH_DOWNLOAD_ZIP_MAX_DOCS = 100
-
-
-class ChildChunkCreatePayload(BaseModel):
-    content: str
-
-
-class ChildChunkUpdatePayload(BaseModel):
-    content: str
-
-
-class DocumentBatchDownloadZipPayload(BaseModel):
-    """Request payload for bulk downloading documents as a zip archive."""
-
-    document_ids: list[UUID] = Field(..., min_length=1, max_length=DOCUMENT_BATCH_DOWNLOAD_ZIP_MAX_DOCS)
-
-
-class MetadataUpdatePayload(BaseModel):
-    name: str
-
-
 # --- Audio schemas ---
 
 
 class TextToAudioPayload(BaseModel):
-    message_id: str | None = Field(default=None, description="Message ID")
-    voice: str | None = Field(default=None, description="Voice to use for TTS")
-    text: str | None = Field(default=None, description="Text to convert to audio")
-    streaming: bool | None = Field(default=None, description="Enable streaming response")
+    message_id: str | None = None
+    voice: str | None = None
+    text: str | None = None
+    streaming: bool | None = None

api/controllers/console/apikey.py

@@ -1,16 +1,12 @@
-from datetime import datetime
-
 import flask_restx
-from flask_restx import Resource
+from flask_restx import Resource, fields, marshal_with
 from flask_restx._http import HTTPStatus
-from pydantic import field_validator
 from sqlalchemy import delete, func, select
 from sqlalchemy.orm import sessionmaker
 from werkzeug.exceptions import Forbidden
 
-from controllers.common.schema import register_schema_models
 from extensions.ext_database import db
-from fields.base import ResponseModel
+from libs.helper import TimestampField
 from libs.login import current_account_with_tenant, login_required
 from models.dataset import Dataset
 from models.enums import ApiTokenType
@@ -20,31 +16,21 @@ from services.api_token_service import ApiTokenCache
 from . import console_ns
 from .wraps import account_initialization_required, edit_permission_required, setup_required
 
+api_key_fields = {
+    "id": fields.String,
+    "type": fields.String,
+    "token": fields.String,
+    "last_used_at": TimestampField,
+    "created_at": TimestampField,
+}
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
+api_key_item_model = console_ns.model("ApiKeyItem", api_key_fields)
 
+api_key_list = {"data": fields.List(fields.Nested(api_key_item_model), attribute="items")}
 
-class ApiKeyItem(ResponseModel):
-    id: str
-    type: str
-    token: str
-    last_used_at: int | None = None
-    created_at: int | None = None
-
-    @field_validator("last_used_at", "created_at", mode="before")
-    @classmethod
-    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
-
-
-class ApiKeyList(ResponseModel):
-    data: list[ApiKeyItem]
-
-
-register_schema_models(console_ns, ApiKeyItem, ApiKeyList)
+api_key_list_model = console_ns.model(
+    "ApiKeyList", {"data": fields.List(fields.Nested(api_key_item_model), attribute="items")}
+)
 
 
 def _get_resource(resource_id, tenant_id, resource_model):
@@ -68,6 +54,7 @@ class BaseApiKeyListResource(Resource):
     token_prefix: str | None = None
     max_keys = 10
 
+    @marshal_with(api_key_list_model)
     def get(self, resource_id):
         assert self.resource_id_field is not None, "resource_id_field must be set"
         resource_id = str(resource_id)
@@ -79,8 +66,9 @@ class BaseApiKeyListResource(Resource):
                 ApiToken.type == self.resource_type, getattr(ApiToken, self.resource_id_field) == resource_id
             )
         ).all()
-        return ApiKeyList.model_validate({"data": keys}, from_attributes=True).model_dump(mode="json")
+        return {"items": keys}
 
+    @marshal_with(api_key_item_model)
     @edit_permission_required
     def post(self, resource_id):
         assert self.resource_id_field is not None, "resource_id_field must be set"
@@ -112,7 +100,7 @@ class BaseApiKeyListResource(Resource):
         api_token.type = self.resource_type
         db.session.add(api_token)
         db.session.commit()
-        return ApiKeyItem.model_validate(api_token, from_attributes=True).model_dump(mode="json"), 201
+        return api_token, 201
 
 
 class BaseApiKeyResource(Resource):
@@ -159,7 +147,7 @@ class AppApiKeyListResource(BaseApiKeyListResource):
     @console_ns.doc("get_app_api_keys")
     @console_ns.doc(description="Get all API keys for an app")
     @console_ns.doc(params={"resource_id": "App ID"})
-    @console_ns.response(200, "API keys retrieved successfully", console_ns.models[ApiKeyList.__name__])
+    @console_ns.response(200, "Success", api_key_list_model)
     def get(self, resource_id):  # type: ignore
         """Get all API keys for an app"""
         return super().get(resource_id)
@@ -167,7 +155,7 @@ class AppApiKeyListResource(BaseApiKeyListResource):
     @console_ns.doc("create_app_api_key")
     @console_ns.doc(description="Create a new API key for an app")
     @console_ns.doc(params={"resource_id": "App ID"})
-    @console_ns.response(201, "API key created successfully", console_ns.models[ApiKeyItem.__name__])
+    @console_ns.response(201, "API key created successfully", api_key_item_model)
     @console_ns.response(400, "Maximum keys exceeded")
     def post(self, resource_id):  # type: ignore
         """Create a new API key for an app"""
@@ -199,7 +187,7 @@ class DatasetApiKeyListResource(BaseApiKeyListResource):
     @console_ns.doc("get_dataset_api_keys")
     @console_ns.doc(description="Get all API keys for a dataset")
     @console_ns.doc(params={"resource_id": "Dataset ID"})
-    @console_ns.response(200, "API keys retrieved successfully", console_ns.models[ApiKeyList.__name__])
+    @console_ns.response(200, "Success", api_key_list_model)
     def get(self, resource_id):  # type: ignore
         """Get all API keys for a dataset"""
         return super().get(resource_id)
@@ -207,7 +195,7 @@ class DatasetApiKeyListResource(BaseApiKeyListResource):
     @console_ns.doc("create_dataset_api_key")
     @console_ns.doc(description="Create a new API key for a dataset")
     @console_ns.doc(params={"resource_id": "Dataset ID"})
-    @console_ns.response(201, "API key created successfully", console_ns.models[ApiKeyItem.__name__])
+    @console_ns.response(201, "API key created successfully", api_key_item_model)
     @console_ns.response(400, "Maximum keys exceeded")
     def post(self, resource_id):  # type: ignore
         """Create a new API key for a dataset"""

api/controllers/console/app/annotation.py

@@ -25,13 +25,7 @@ from fields.annotation_fields import (
 )
 from libs.helper import uuid_value
 from libs.login import login_required
-from services.annotation_service import (
-    AppAnnotationService,
-    EnableAnnotationArgs,
-    UpdateAnnotationArgs,
-    UpdateAnnotationSettingArgs,
-    UpsertAnnotationArgs,
-)
+from services.annotation_service import AppAnnotationService
 
 DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
 
@@ -126,12 +120,7 @@ class AnnotationReplyActionApi(Resource):
         args = AnnotationReplyPayload.model_validate(console_ns.payload)
         match action:
             case "enable":
-                enable_args: EnableAnnotationArgs = {
-                    "score_threshold": args.score_threshold,
-                    "embedding_provider_name": args.embedding_provider_name,
-                    "embedding_model_name": args.embedding_model_name,
-                }
-                result = AppAnnotationService.enable_app_annotation(enable_args, app_id)
+                result = AppAnnotationService.enable_app_annotation(args.model_dump(), app_id)
             case "disable":
                 result = AppAnnotationService.disable_app_annotation(app_id)
         return result, 200
@@ -172,8 +161,7 @@ class AppAnnotationSettingUpdateApi(Resource):
 
         args = AnnotationSettingUpdatePayload.model_validate(console_ns.payload)
 
-        setting_args: UpdateAnnotationSettingArgs = {"score_threshold": args.score_threshold}
-        result = AppAnnotationService.update_app_annotation_setting(app_id, annotation_setting_id, setting_args)
+        result = AppAnnotationService.update_app_annotation_setting(app_id, annotation_setting_id, args.model_dump())
         return result, 200
 
 
@@ -249,16 +237,8 @@ class AnnotationApi(Resource):
     def post(self, app_id):
         app_id = str(app_id)
         args = CreateAnnotationPayload.model_validate(console_ns.payload)
-        upsert_args: UpsertAnnotationArgs = {}
-        if args.answer is not None:
-            upsert_args["answer"] = args.answer
-        if args.content is not None:
-            upsert_args["content"] = args.content
-        if args.message_id is not None:
-            upsert_args["message_id"] = args.message_id
-        if args.question is not None:
-            upsert_args["question"] = args.question
-        annotation = AppAnnotationService.up_insert_app_annotation_from_message(upsert_args, app_id)
+        data = args.model_dump(exclude_none=True)
+        annotation = AppAnnotationService.up_insert_app_annotation_from_message(data, app_id)
         return Annotation.model_validate(annotation, from_attributes=True).model_dump(mode="json")
 
     @setup_required
@@ -335,12 +315,9 @@ class AnnotationUpdateDeleteApi(Resource):
         app_id = str(app_id)
         annotation_id = str(annotation_id)
         args = UpdateAnnotationPayload.model_validate(console_ns.payload)
-        update_args: UpdateAnnotationArgs = {}
-        if args.answer is not None:
-            update_args["answer"] = args.answer
-        if args.question is not None:
-            update_args["question"] = args.question
-        annotation = AppAnnotationService.update_app_annotation_directly(update_args, app_id, annotation_id)
+        annotation = AppAnnotationService.update_app_annotation_directly(
+            args.model_dump(exclude_none=True), app_id, annotation_id
+        )
         return Annotation.model_validate(annotation, from_attributes=True).model_dump(mode="json")
 
     @setup_required

api/controllers/console/app/app.py

@@ -34,10 +34,9 @@ from fields.base import ResponseModel
 from libs.login import current_account_with_tenant, login_required
 from models import App, DatasetPermissionEnum, Workflow
 from models.model import IconType
-from services.app_dsl_service import AppDslService
+from services.app_dsl_service import AppDslService, ImportMode
 from services.app_service import AppService
 from services.enterprise.enterprise_service import EnterpriseService
-from services.entities.dsl_entities import ImportMode
 from services.entities.knowledge_entities.knowledge_entities import (
     DataSource,
     InfoList,
@@ -52,7 +51,7 @@ from services.entities.knowledge_entities.knowledge_entities import (
 )
 from services.feature_service import FeatureService
 
-ALLOW_CREATE_APP_MODES = ["chat", "agent-chat", "advanced-chat", "workflow", "completion", "agent"]
+ALLOW_CREATE_APP_MODES = ["chat", "agent-chat", "advanced-chat", "workflow", "completion"]
 
 register_enum_models(console_ns, IconType)
 
@@ -62,7 +61,7 @@ _logger = logging.getLogger(__name__)
 class AppListQuery(BaseModel):
     page: int = Field(default=1, ge=1, le=99999, description="Page number (1-99999)")
     limit: int = Field(default=20, ge=1, le=100, description="Page size (1-100)")
-    mode: Literal["completion", "chat", "advanced-chat", "workflow", "agent-chat", "agent", "channel", "all"] = Field(
+    mode: Literal["completion", "chat", "advanced-chat", "workflow", "agent-chat", "channel", "all"] = Field(
         default="all", description="App mode filter"
     )
     name: str | None = Field(default=None, description="Filter by app name")
@@ -94,9 +93,7 @@ class AppListQuery(BaseModel):
 class CreateAppPayload(BaseModel):
     name: str = Field(..., min_length=1, description="App name")
     description: str | None = Field(default=None, description="App description (max 400 chars)", max_length=400)
-    mode: Literal["chat", "agent-chat", "advanced-chat", "workflow", "completion", "agent"] = Field(
-        ..., description="App mode"
-    )
+    mode: Literal["chat", "agent-chat", "advanced-chat", "workflow", "completion"] = Field(..., description="App mode")
     icon_type: IconType | None = Field(default=None, description="Icon type")
     icon: str | None = Field(default=None, description="Icon")
     icon_background: str | None = Field(default=None, description="Icon background color")

api/controllers/console/app/app_import.py

@@ -1,8 +1,7 @@
-from flask_restx import Resource
+from flask_restx import Resource, fields, marshal_with
 from pydantic import BaseModel, Field
 from sqlalchemy.orm import sessionmaker
 
-from controllers.common.schema import register_schema_models
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import (
     account_initialization_required,
@@ -11,15 +10,34 @@ from controllers.console.wraps import (
     setup_required,
 )
 from extensions.ext_database import db
+from fields.app_fields import (
+    app_import_check_dependencies_fields,
+    app_import_fields,
+    leaked_dependency_fields,
+)
 from libs.login import current_account_with_tenant, login_required
 from models.model import App
-from services.app_dsl_service import AppDslService, Import
+from services.app_dsl_service import AppDslService, ImportStatus
 from services.enterprise.enterprise_service import EnterpriseService
-from services.entities.dsl_entities import CheckDependenciesResult, ImportStatus
 from services.feature_service import FeatureService
 
 from .. import console_ns
 
+# Register models for flask_restx to avoid dict type issues in Swagger
+# Register base model first
+leaked_dependency_model = console_ns.model("LeakedDependency", leaked_dependency_fields)
+
+app_import_model = console_ns.model("AppImport", app_import_fields)
+
+# For nested models, need to replace nested dict with registered model
+app_import_check_dependencies_fields_copy = app_import_check_dependencies_fields.copy()
+app_import_check_dependencies_fields_copy["leaked_dependencies"] = fields.List(fields.Nested(leaked_dependency_model))
+app_import_check_dependencies_model = console_ns.model(
+    "AppImportCheckDependencies", app_import_check_dependencies_fields_copy
+)
+
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
 
 class AppImportPayload(BaseModel):
     mode: str = Field(..., description="Import mode")
@@ -33,18 +51,18 @@ class AppImportPayload(BaseModel):
     app_id: str | None = Field(None)
 
 
-register_schema_models(console_ns, AppImportPayload, Import, CheckDependenciesResult)
+console_ns.schema_model(
+    AppImportPayload.__name__, AppImportPayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0)
+)
 
 
 @console_ns.route("/apps/imports")
 class AppImportApi(Resource):
     @console_ns.expect(console_ns.models[AppImportPayload.__name__])
-    @console_ns.response(200, "Import completed", console_ns.models[Import.__name__])
-    @console_ns.response(202, "Import pending confirmation", console_ns.models[Import.__name__])
-    @console_ns.response(400, "Import failed", console_ns.models[Import.__name__])
     @setup_required
     @login_required
     @account_initialization_required
+    @marshal_with(app_import_model)
     @cloud_edition_billing_resource_check("apps")
     @edit_permission_required
     def post(self):
@@ -74,22 +92,19 @@ class AppImportApi(Resource):
             EnterpriseService.WebAppAuth.update_app_access_mode(result.app_id, "private")
         # Return appropriate status code based on result
         status = result.status
-        match status:
-            case ImportStatus.FAILED:
-                return result.model_dump(mode="json"), 400
-            case ImportStatus.PENDING:
-                return result.model_dump(mode="json"), 202
-            case ImportStatus.COMPLETED | ImportStatus.COMPLETED_WITH_WARNINGS:
-                return result.model_dump(mode="json"), 200
+        if status == ImportStatus.FAILED:
+            return result.model_dump(mode="json"), 400
+        elif status == ImportStatus.PENDING:
+            return result.model_dump(mode="json"), 202
+        return result.model_dump(mode="json"), 200
 
 
 @console_ns.route("/apps/imports/<string:import_id>/confirm")
 class AppImportConfirmApi(Resource):
-    @console_ns.response(200, "Import confirmed", console_ns.models[Import.__name__])
-    @console_ns.response(400, "Import failed", console_ns.models[Import.__name__])
     @setup_required
     @login_required
     @account_initialization_required
+    @marshal_with(app_import_model)
     @edit_permission_required
     def post(self, import_id):
         # Check user role first
@@ -110,11 +125,11 @@ class AppImportConfirmApi(Resource):
 
 @console_ns.route("/apps/imports/<string:app_id>/check-dependencies")
 class AppImportCheckDependenciesApi(Resource):
-    @console_ns.response(200, "Dependencies checked", console_ns.models[CheckDependenciesResult.__name__])
     @setup_required
     @login_required
     @get_app_model
     @account_initialization_required
+    @marshal_with(app_import_check_dependencies_model)
     @edit_permission_required
     def get(self, app_model: App):
         with sessionmaker(db.engine).begin() as session:

api/controllers/console/app/completion.py

@@ -161,7 +161,7 @@ class ChatMessageApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     @edit_permission_required
     def post(self, app_model):
         args_model = ChatMessagePayload.model_validate(console_ns.payload)
@@ -215,7 +215,7 @@ class ChatMessageStopApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     def post(self, app_model, task_id):
         if not isinstance(current_user, Account):
             raise ValueError("current_user must be an Account instance")

api/controllers/console/app/mcp_server.py

@@ -1,27 +1,23 @@
 import json
-from datetime import datetime
-from typing import Any
 
-from flask_restx import Resource
-from pydantic import BaseModel, Field, field_validator
+from flask_restx import Resource, marshal_with
+from pydantic import BaseModel, Field
 from sqlalchemy import select
 from werkzeug.exceptions import NotFound
 
-from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, edit_permission_required, setup_required
 from extensions.ext_database import db
-from fields.base import ResponseModel
+from fields.app_fields import app_server_fields
 from libs.login import current_account_with_tenant, login_required
 from models.enums import AppMCPServerStatus
 from models.model import AppMCPServer
 
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
+# Register model for flask_restx to avoid dict type issues in Swagger
+app_server_model = console_ns.model("AppServer", app_server_fields)
 
 
 class MCPServerCreatePayload(BaseModel):
@@ -36,33 +32,8 @@ class MCPServerUpdatePayload(BaseModel):
     status: str | None = Field(default=None, description="Server status")
 
 
-class AppMCPServerResponse(ResponseModel):
-    id: str
-    name: str
-    server_code: str
-    description: str
-    status: str
-    parameters: dict[str, Any] | list[Any] | str
-    created_at: int | None = None
-    updated_at: int | None = None
-
-    @field_validator("parameters", mode="before")
-    @classmethod
-    def _parse_json_string(cls, value: Any) -> Any:
-        if isinstance(value, str):
-            try:
-                return json.loads(value)
-            except (json.JSONDecodeError, TypeError):
-                return value
-        return value
-
-    @field_validator("created_at", "updated_at", mode="before")
-    @classmethod
-    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
-
-
-register_schema_models(console_ns, MCPServerCreatePayload, MCPServerUpdatePayload, AppMCPServerResponse)
+for model in (MCPServerCreatePayload, MCPServerUpdatePayload):
+    console_ns.schema_model(model.__name__, model.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0))
 
 
 @console_ns.route("/apps/<uuid:app_id>/server")
@@ -70,27 +41,27 @@ class AppMCPServerController(Resource):
     @console_ns.doc("get_app_mcp_server")
     @console_ns.doc(description="Get MCP server configuration for an application")
     @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.response(200, "Server configuration", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(200, "MCP server configuration retrieved successfully", app_server_model)
     @login_required
     @account_initialization_required
     @setup_required
     @get_app_model
+    @marshal_with(app_server_model)
     def get(self, app_model):
         server = db.session.scalar(select(AppMCPServer).where(AppMCPServer.app_id == app_model.id).limit(1))
-        if server is None:
-            return {}
-        return AppMCPServerResponse.model_validate(server, from_attributes=True).model_dump(mode="json")
+        return server
 
     @console_ns.doc("create_app_mcp_server")
     @console_ns.doc(description="Create MCP server configuration for an application")
     @console_ns.doc(params={"app_id": "Application ID"})
     @console_ns.expect(console_ns.models[MCPServerCreatePayload.__name__])
-    @console_ns.response(200, "Server created", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(201, "MCP server configuration created successfully", app_server_model)
     @console_ns.response(403, "Insufficient permissions")
     @account_initialization_required
     @get_app_model
     @login_required
     @setup_required
+    @marshal_with(app_server_model)
     @edit_permission_required
     def post(self, app_model):
         _, current_tenant_id = current_account_with_tenant()
@@ -111,19 +82,20 @@ class AppMCPServerController(Resource):
         )
         db.session.add(server)
         db.session.commit()
-        return AppMCPServerResponse.model_validate(server, from_attributes=True).model_dump(mode="json")
+        return server
 
     @console_ns.doc("update_app_mcp_server")
     @console_ns.doc(description="Update MCP server configuration for an application")
     @console_ns.doc(params={"app_id": "Application ID"})
     @console_ns.expect(console_ns.models[MCPServerUpdatePayload.__name__])
-    @console_ns.response(200, "Server updated", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(200, "MCP server configuration updated successfully", app_server_model)
     @console_ns.response(403, "Insufficient permissions")
     @console_ns.response(404, "Server not found")
     @get_app_model
     @login_required
     @setup_required
     @account_initialization_required
+    @marshal_with(app_server_model)
     @edit_permission_required
     def put(self, app_model):
         payload = MCPServerUpdatePayload.model_validate(console_ns.payload or {})
@@ -146,7 +118,7 @@ class AppMCPServerController(Resource):
             except ValueError:
                 raise ValueError("Invalid status")
         db.session.commit()
-        return AppMCPServerResponse.model_validate(server, from_attributes=True).model_dump(mode="json")
+        return server
 
 
 @console_ns.route("/apps/<uuid:server_id>/server/refresh")
@@ -154,12 +126,13 @@ class AppMCPServerRefreshController(Resource):
     @console_ns.doc("refresh_app_mcp_server")
     @console_ns.doc(description="Refresh MCP server configuration and regenerate server code")
     @console_ns.doc(params={"server_id": "Server ID"})
-    @console_ns.response(200, "Server refreshed", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(200, "MCP server refreshed successfully", app_server_model)
     @console_ns.response(403, "Insufficient permissions")
     @console_ns.response(404, "Server not found")
     @setup_required
     @login_required
     @account_initialization_required
+    @marshal_with(app_server_model)
     @edit_permission_required
     def get(self, server_id):
         _, current_tenant_id = current_account_with_tenant()
@@ -172,4 +145,4 @@ class AppMCPServerRefreshController(Resource):
             raise NotFound()
         server.server_code = AppMCPServer.generate_server_code(16)
         db.session.commit()
-        return AppMCPServerResponse.model_validate(server, from_attributes=True).model_dump(mode="json")
+        return server

api/controllers/console/app/message.py

@@ -237,7 +237,7 @@ class ChatMessageListApi(Resource):
     @login_required
     @account_initialization_required
     @setup_required
-    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     @marshal_with(message_infinite_scroll_pagination_model)
     @edit_permission_required
     def get(self, app_model):
@@ -393,7 +393,7 @@ class MessageSuggestedQuestionApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     def get(self, app_model, message_id):
         current_user, _ = current_account_with_tenant()
         message_id = str(message_id)

api/controllers/console/app/model_config.py

@@ -1,11 +1,9 @@
 import json
-from typing import Any, cast
+from typing import cast
 
 from flask import request
-from flask_restx import Resource
-from pydantic import BaseModel, Field
+from flask_restx import Resource, fields
 
-from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, edit_permission_required, setup_required
@@ -20,30 +18,30 @@ from models.model import AppMode, AppModelConfig
 from services.app_model_config_service import AppModelConfigService
 
 
-class ModelConfigRequest(BaseModel):
-    provider: str | None = Field(default=None, description="Model provider")
-    model: str | None = Field(default=None, description="Model name")
-    configs: dict[str, Any] | None = Field(default=None, description="Model configuration parameters")
-    opening_statement: str | None = Field(default=None, description="Opening statement")
-    suggested_questions: list[str] | None = Field(default=None, description="Suggested questions")
-    more_like_this: dict[str, Any] | None = Field(default=None, description="More like this configuration")
-    speech_to_text: dict[str, Any] | None = Field(default=None, description="Speech to text configuration")
-    text_to_speech: dict[str, Any] | None = Field(default=None, description="Text to speech configuration")
-    retrieval_model: dict[str, Any] | None = Field(default=None, description="Retrieval model configuration")
-    tools: list[dict[str, Any]] | None = Field(default=None, description="Available tools")
-    dataset_configs: dict[str, Any] | None = Field(default=None, description="Dataset configurations")
-    agent_mode: dict[str, Any] | None = Field(default=None, description="Agent mode configuration")
-
-
-register_schema_models(console_ns, ModelConfigRequest)
-
-
 @console_ns.route("/apps/<uuid:app_id>/model-config")
 class ModelConfigResource(Resource):
     @console_ns.doc("update_app_model_config")
     @console_ns.doc(description="Update application model configuration")
     @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.expect(console_ns.models[ModelConfigRequest.__name__])
+    @console_ns.expect(
+        console_ns.model(
+            "ModelConfigRequest",
+            {
+                "provider": fields.String(description="Model provider"),
+                "model": fields.String(description="Model name"),
+                "configs": fields.Raw(description="Model configuration parameters"),
+                "opening_statement": fields.String(description="Opening statement"),
+                "suggested_questions": fields.List(fields.String(), description="Suggested questions"),
+                "more_like_this": fields.Raw(description="More like this configuration"),
+                "speech_to_text": fields.Raw(description="Speech to text configuration"),
+                "text_to_speech": fields.Raw(description="Text to speech configuration"),
+                "retrieval_model": fields.Raw(description="Retrieval model configuration"),
+                "tools": fields.List(fields.Raw(), description="Available tools"),
+                "dataset_configs": fields.Raw(description="Dataset configurations"),
+                "agent_mode": fields.Raw(description="Agent mode configuration"),
+            },
+        )
+    )
     @console_ns.response(200, "Model configuration updated successfully")
     @console_ns.response(400, "Invalid configuration")
     @console_ns.response(404, "App not found")

api/controllers/console/app/site.py

@@ -1,12 +1,11 @@
 from typing import Literal
 
-from flask_restx import Resource
+from flask_restx import Resource, marshal_with
 from pydantic import BaseModel, Field, field_validator
 from sqlalchemy import select
 from werkzeug.exceptions import NotFound
 
 from constants.languages import supported_language
-from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import (
@@ -16,11 +15,13 @@ from controllers.console.wraps import (
     setup_required,
 )
 from extensions.ext_database import db
-from fields.base import ResponseModel
+from fields.app_fields import app_site_fields
 from libs.datetime_utils import naive_utc_now
 from libs.login import current_account_with_tenant, login_required
 from models import Site
 
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
 
 class AppSiteUpdatePayload(BaseModel):
     title: str | None = Field(default=None)
@@ -48,26 +49,13 @@ class AppSiteUpdatePayload(BaseModel):
         return supported_language(value)
 
 
-class AppSiteResponse(ResponseModel):
-    app_id: str
-    access_token: str | None = Field(default=None, validation_alias="code")
-    code: str | None = None
-    title: str
-    icon: str | None = None
-    icon_background: str | None = None
-    description: str | None = None
-    default_language: str
-    customize_domain: str | None = None
-    copyright: str | None = None
-    privacy_policy: str | None = None
-    custom_disclaimer: str | None = None
-    customize_token_strategy: str
-    prompt_public: bool
-    show_workflow_steps: bool
-    use_icon_as_answer_icon: bool
+console_ns.schema_model(
+    AppSiteUpdatePayload.__name__,
+    AppSiteUpdatePayload.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0),
+)
 
-
-register_schema_models(console_ns, AppSiteUpdatePayload, AppSiteResponse)
+# Register model for flask_restx to avoid dict type issues in Swagger
+app_site_model = console_ns.model("AppSite", app_site_fields)
 
 
 @console_ns.route("/apps/<uuid:app_id>/site")
@@ -76,7 +64,7 @@ class AppSite(Resource):
     @console_ns.doc(description="Update application site configuration")
     @console_ns.doc(params={"app_id": "Application ID"})
     @console_ns.expect(console_ns.models[AppSiteUpdatePayload.__name__])
-    @console_ns.response(200, "Site configuration updated successfully", console_ns.models[AppSiteResponse.__name__])
+    @console_ns.response(200, "Site configuration updated successfully", app_site_model)
     @console_ns.response(403, "Insufficient permissions")
     @console_ns.response(404, "App not found")
     @setup_required
@@ -84,6 +72,7 @@ class AppSite(Resource):
     @edit_permission_required
     @account_initialization_required
     @get_app_model
+    @marshal_with(app_site_model)
     def post(self, app_model):
         args = AppSiteUpdatePayload.model_validate(console_ns.payload or {})
         current_user, _ = current_account_with_tenant()
@@ -117,7 +106,7 @@ class AppSite(Resource):
         site.updated_at = naive_utc_now()
         db.session.commit()
 
-        return AppSiteResponse.model_validate(site, from_attributes=True).model_dump(mode="json")
+        return site
 
 
 @console_ns.route("/apps/<uuid:app_id>/site/access-token-reset")
@@ -125,7 +114,7 @@ class AppSiteAccessTokenReset(Resource):
     @console_ns.doc("reset_app_site_access_token")
     @console_ns.doc(description="Reset access token for application site")
     @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.response(200, "Access token reset successfully", console_ns.models[AppSiteResponse.__name__])
+    @console_ns.response(200, "Access token reset successfully", app_site_model)
     @console_ns.response(403, "Insufficient permissions (admin/owner required)")
     @console_ns.response(404, "App or site not found")
     @setup_required
@@ -133,6 +122,7 @@ class AppSiteAccessTokenReset(Resource):
     @is_admin_or_owner_required
     @account_initialization_required
     @get_app_model
+    @marshal_with(app_site_model)
     def post(self, app_model):
         current_user, _ = current_account_with_tenant()
         site = db.session.scalar(select(Site).where(Site.app_id == app_model.id).limit(1))
@@ -145,4 +135,4 @@ class AppSiteAccessTokenReset(Resource):
         site.updated_at = naive_utc_now()
         db.session.commit()
 
-        return AppSiteResponse.model_validate(site, from_attributes=True).model_dump(mode="json")
+        return site

api/controllers/console/app/workflow.py

@@ -14,7 +14,6 @@ from sqlalchemy.orm import sessionmaker
 from werkzeug.exceptions import BadRequest, Forbidden, InternalServerError, NotFound
 
 import services
-from controllers.common.controller_schemas import DefaultBlockConfigQuery, WorkflowListQuery, WorkflowUpdatePayload
 from controllers.console import console_ns
 from controllers.console.app.error import ConversationCompletedError, DraftWorkflowNotExist, DraftWorkflowNotSync
 from controllers.console.app.workflow_run import workflow_run_node_execution_model
@@ -143,6 +142,10 @@ class PublishWorkflowPayload(BaseModel):
     marked_comment: str | None = Field(default=None, max_length=100)
 
 
+class DefaultBlockConfigQuery(BaseModel):
+    q: str | None = None
+
+
 class ConvertToWorkflowPayload(BaseModel):
     name: str | None = None
     icon_type: str | None = None
@@ -150,6 +153,18 @@ class ConvertToWorkflowPayload(BaseModel):
     icon_background: str | None = None
 
 
+class WorkflowListQuery(BaseModel):
+    page: int = Field(default=1, ge=1, le=99999)
+    limit: int = Field(default=10, ge=1, le=100)
+    user_id: str | None = None
+    named_only: bool = False
+
+
+class WorkflowUpdatePayload(BaseModel):
+    marked_name: str | None = Field(default=None, max_length=20)
+    marked_comment: str | None = Field(default=None, max_length=100)
+
+
 class DraftWorkflowTriggerRunPayload(BaseModel):
     node_id: str
 
@@ -206,7 +221,7 @@ class DraftWorkflowApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_model)
     @edit_permission_required
     def get(self, app_model: App):
@@ -226,7 +241,7 @@ class DraftWorkflowApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @console_ns.doc("sync_draft_workflow")
     @console_ns.doc(description="Sync draft workflow configuration")
     @console_ns.expect(console_ns.models[SyncDraftWorkflowPayload.__name__])
@@ -310,7 +325,7 @@ class AdvancedChatDraftWorkflowRunApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
     @edit_permission_required
     def post(self, app_model: App):
         """
@@ -356,7 +371,7 @@ class AdvancedChatDraftRunIterationNodeApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
     @edit_permission_required
     def post(self, app_model: App, node_id: str):
         """
@@ -432,7 +447,7 @@ class AdvancedChatDraftRunLoopNodeApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
     @edit_permission_required
     def post(self, app_model: App, node_id: str):
         """
@@ -534,7 +549,7 @@ class AdvancedChatDraftHumanInputFormPreviewApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
     @edit_permission_required
     def post(self, app_model: App, node_id: str):
         """
@@ -563,7 +578,7 @@ class AdvancedChatDraftHumanInputFormRunApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
     @edit_permission_required
     def post(self, app_model: App, node_id: str):
         """
@@ -718,7 +733,7 @@ class WorkflowTaskStopApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @edit_permission_required
     def post(self, app_model: App, task_id: str):
         """
@@ -746,7 +761,7 @@ class DraftWorkflowNodeRunApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_run_node_execution_model)
     @edit_permission_required
     def post(self, app_model: App, node_id: str):
@@ -792,7 +807,7 @@ class PublishedWorkflowApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_model)
     @edit_permission_required
     def get(self, app_model: App):
@@ -810,7 +825,7 @@ class PublishedWorkflowApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @edit_permission_required
     def post(self, app_model: App):
         """
@@ -854,7 +869,7 @@ class DefaultBlockConfigsApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @edit_permission_required
     def get(self, app_model: App):
         """
@@ -876,7 +891,7 @@ class DefaultBlockConfigApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @edit_permission_required
     def get(self, app_model: App, block_type: str):
         """
@@ -941,7 +956,7 @@ class PublishedAllWorkflowApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_pagination_model)
     @edit_permission_required
     def get(self, app_model: App):
@@ -990,7 +1005,7 @@ class DraftWorkflowRestoreApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @edit_permission_required
     def post(self, app_model: App, workflow_id: str):
         current_user, _ = current_account_with_tenant()
@@ -1028,7 +1043,7 @@ class WorkflowByIdApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_model)
     @edit_permission_required
     def patch(self, app_model: App, workflow_id: str):
@@ -1068,7 +1083,7 @@ class WorkflowByIdApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @edit_permission_required
     def delete(self, app_model: App, workflow_id: str):
         """
@@ -1103,7 +1118,7 @@ class DraftWorkflowNodeLastRunApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_run_node_execution_model)
     def get(self, app_model: App, node_id: str):
         srv = WorkflowService()

api/controllers/console/app/workflow_comment.py

@@ -1,322 +0,0 @@
-import logging
-
-from flask_restx import Resource, marshal_with
-from pydantic import BaseModel, Field, TypeAdapter
-
-from controllers.console import console_ns
-from controllers.console.app.wraps import get_app_model
-from controllers.console.wraps import account_initialization_required, setup_required
-from fields.member_fields import AccountWithRole
-from fields.workflow_comment_fields import (
-    workflow_comment_basic_fields,
-    workflow_comment_create_fields,
-    workflow_comment_detail_fields,
-    workflow_comment_reply_create_fields,
-    workflow_comment_reply_update_fields,
-    workflow_comment_resolve_fields,
-    workflow_comment_update_fields,
-)
-from libs.login import current_user, login_required
-from models import App
-from services.account_service import TenantService
-from services.workflow_comment_service import WorkflowCommentService
-
-logger = logging.getLogger(__name__)
-DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
-
-
-class WorkflowCommentCreatePayload(BaseModel):
-    position_x: float = Field(..., description="Comment X position")
-    position_y: float = Field(..., description="Comment Y position")
-    content: str = Field(..., description="Comment content")
-    mentioned_user_ids: list[str] = Field(default_factory=list, description="Mentioned user IDs")
-
-
-class WorkflowCommentUpdatePayload(BaseModel):
-    content: str = Field(..., description="Comment content")
-    position_x: float | None = Field(default=None, description="Comment X position")
-    position_y: float | None = Field(default=None, description="Comment Y position")
-    mentioned_user_ids: list[str] = Field(default_factory=list, description="Mentioned user IDs")
-
-
-class WorkflowCommentReplyCreatePayload(BaseModel):
-    content: str = Field(..., description="Reply content")
-    mentioned_user_ids: list[str] = Field(default_factory=list, description="Mentioned user IDs")
-
-
-class WorkflowCommentReplyUpdatePayload(BaseModel):
-    content: str = Field(..., description="Reply content")
-    mentioned_user_ids: list[str] = Field(default_factory=list, description="Mentioned user IDs")
-
-
-class WorkflowCommentMentionUsersResponse(BaseModel):
-    users: list[AccountWithRole] = Field(description="Mentionable users")
-
-
-for model in (
-    WorkflowCommentCreatePayload,
-    WorkflowCommentUpdatePayload,
-    WorkflowCommentReplyCreatePayload,
-    WorkflowCommentReplyUpdatePayload,
-):
-    console_ns.schema_model(model.__name__, model.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0))
-
-for model in (AccountWithRole, WorkflowCommentMentionUsersResponse):
-    console_ns.schema_model(model.__name__, model.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0))
-
-workflow_comment_basic_model = console_ns.model("WorkflowCommentBasic", workflow_comment_basic_fields)
-workflow_comment_detail_model = console_ns.model("WorkflowCommentDetail", workflow_comment_detail_fields)
-workflow_comment_create_model = console_ns.model("WorkflowCommentCreate", workflow_comment_create_fields)
-workflow_comment_update_model = console_ns.model("WorkflowCommentUpdate", workflow_comment_update_fields)
-workflow_comment_resolve_model = console_ns.model("WorkflowCommentResolve", workflow_comment_resolve_fields)
-workflow_comment_reply_create_model = console_ns.model(
-    "WorkflowCommentReplyCreate", workflow_comment_reply_create_fields
-)
-workflow_comment_reply_update_model = console_ns.model(
-    "WorkflowCommentReplyUpdate", workflow_comment_reply_update_fields
-)
-workflow_comment_mention_users_model = console_ns.models[WorkflowCommentMentionUsersResponse.__name__]
-
-
-@console_ns.route("/apps/<uuid:app_id>/workflow/comments")
-class WorkflowCommentListApi(Resource):
-    """API for listing and creating workflow comments."""
-
-    @console_ns.doc("list_workflow_comments")
-    @console_ns.doc(description="Get all comments for a workflow")
-    @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.response(200, "Comments retrieved successfully", workflow_comment_basic_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    @marshal_with(workflow_comment_basic_model, envelope="data")
-    def get(self, app_model: App):
-        """Get all comments for a workflow."""
-        comments = WorkflowCommentService.get_comments(tenant_id=current_user.current_tenant_id, app_id=app_model.id)
-
-        return comments
-
-    @console_ns.doc("create_workflow_comment")
-    @console_ns.doc(description="Create a new workflow comment")
-    @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.expect(console_ns.models[WorkflowCommentCreatePayload.__name__])
-    @console_ns.response(201, "Comment created successfully", workflow_comment_create_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    @marshal_with(workflow_comment_create_model)
-    def post(self, app_model: App):
-        """Create a new workflow comment."""
-        payload = WorkflowCommentCreatePayload.model_validate(console_ns.payload or {})
-
-        result = WorkflowCommentService.create_comment(
-            tenant_id=current_user.current_tenant_id,
-            app_id=app_model.id,
-            created_by=current_user.id,
-            content=payload.content,
-            position_x=payload.position_x,
-            position_y=payload.position_y,
-            mentioned_user_ids=payload.mentioned_user_ids,
-        )
-
-        return result, 201
-
-
-@console_ns.route("/apps/<uuid:app_id>/workflow/comments/<string:comment_id>")
-class WorkflowCommentDetailApi(Resource):
-    """API for managing individual workflow comments."""
-
-    @console_ns.doc("get_workflow_comment")
-    @console_ns.doc(description="Get a specific workflow comment")
-    @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
-    @console_ns.response(200, "Comment retrieved successfully", workflow_comment_detail_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    @marshal_with(workflow_comment_detail_model)
-    def get(self, app_model: App, comment_id: str):
-        """Get a specific workflow comment."""
-        comment = WorkflowCommentService.get_comment(
-            tenant_id=current_user.current_tenant_id, app_id=app_model.id, comment_id=comment_id
-        )
-
-        return comment
-
-    @console_ns.doc("update_workflow_comment")
-    @console_ns.doc(description="Update a workflow comment")
-    @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
-    @console_ns.expect(console_ns.models[WorkflowCommentUpdatePayload.__name__])
-    @console_ns.response(200, "Comment updated successfully", workflow_comment_update_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    @marshal_with(workflow_comment_update_model)
-    def put(self, app_model: App, comment_id: str):
-        """Update a workflow comment."""
-        payload = WorkflowCommentUpdatePayload.model_validate(console_ns.payload or {})
-
-        result = WorkflowCommentService.update_comment(
-            tenant_id=current_user.current_tenant_id,
-            app_id=app_model.id,
-            comment_id=comment_id,
-            user_id=current_user.id,
-            content=payload.content,
-            position_x=payload.position_x,
-            position_y=payload.position_y,
-            mentioned_user_ids=payload.mentioned_user_ids,
-        )
-
-        return result
-
-    @console_ns.doc("delete_workflow_comment")
-    @console_ns.doc(description="Delete a workflow comment")
-    @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
-    @console_ns.response(204, "Comment deleted successfully")
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    def delete(self, app_model: App, comment_id: str):
-        """Delete a workflow comment."""
-        WorkflowCommentService.delete_comment(
-            tenant_id=current_user.current_tenant_id,
-            app_id=app_model.id,
-            comment_id=comment_id,
-            user_id=current_user.id,
-        )
-
-        return {"result": "success"}, 204
-
-
-@console_ns.route("/apps/<uuid:app_id>/workflow/comments/<string:comment_id>/resolve")
-class WorkflowCommentResolveApi(Resource):
-    """API for resolving and reopening workflow comments."""
-
-    @console_ns.doc("resolve_workflow_comment")
-    @console_ns.doc(description="Resolve a workflow comment")
-    @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
-    @console_ns.response(200, "Comment resolved successfully", workflow_comment_resolve_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    @marshal_with(workflow_comment_resolve_model)
-    def post(self, app_model: App, comment_id: str):
-        """Resolve a workflow comment."""
-        comment = WorkflowCommentService.resolve_comment(
-            tenant_id=current_user.current_tenant_id,
-            app_id=app_model.id,
-            comment_id=comment_id,
-            user_id=current_user.id,
-        )
-
-        return comment
-
-
-@console_ns.route("/apps/<uuid:app_id>/workflow/comments/<string:comment_id>/replies")
-class WorkflowCommentReplyApi(Resource):
-    """API for managing comment replies."""
-
-    @console_ns.doc("create_workflow_comment_reply")
-    @console_ns.doc(description="Add a reply to a workflow comment")
-    @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
-    @console_ns.expect(console_ns.models[WorkflowCommentReplyCreatePayload.__name__])
-    @console_ns.response(201, "Reply created successfully", workflow_comment_reply_create_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    @marshal_with(workflow_comment_reply_create_model)
-    def post(self, app_model: App, comment_id: str):
-        """Add a reply to a workflow comment."""
-        # Validate comment access first
-        WorkflowCommentService.validate_comment_access(
-            comment_id=comment_id, tenant_id=current_user.current_tenant_id, app_id=app_model.id
-        )
-
-        payload = WorkflowCommentReplyCreatePayload.model_validate(console_ns.payload or {})
-
-        result = WorkflowCommentService.create_reply(
-            comment_id=comment_id,
-            content=payload.content,
-            created_by=current_user.id,
-            mentioned_user_ids=payload.mentioned_user_ids,
-        )
-
-        return result, 201
-
-
-@console_ns.route("/apps/<uuid:app_id>/workflow/comments/<string:comment_id>/replies/<string:reply_id>")
-class WorkflowCommentReplyDetailApi(Resource):
-    """API for managing individual comment replies."""
-
-    @console_ns.doc("update_workflow_comment_reply")
-    @console_ns.doc(description="Update a comment reply")
-    @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID", "reply_id": "Reply ID"})
-    @console_ns.expect(console_ns.models[WorkflowCommentReplyUpdatePayload.__name__])
-    @console_ns.response(200, "Reply updated successfully", workflow_comment_reply_update_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    @marshal_with(workflow_comment_reply_update_model)
-    def put(self, app_model: App, comment_id: str, reply_id: str):
-        """Update a comment reply."""
-        # Validate comment access first
-        WorkflowCommentService.validate_comment_access(
-            comment_id=comment_id, tenant_id=current_user.current_tenant_id, app_id=app_model.id
-        )
-
-        payload = WorkflowCommentReplyUpdatePayload.model_validate(console_ns.payload or {})
-
-        reply = WorkflowCommentService.update_reply(
-            reply_id=reply_id,
-            user_id=current_user.id,
-            content=payload.content,
-            mentioned_user_ids=payload.mentioned_user_ids,
-        )
-
-        return reply
-
-    @console_ns.doc("delete_workflow_comment_reply")
-    @console_ns.doc(description="Delete a comment reply")
-    @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID", "reply_id": "Reply ID"})
-    @console_ns.response(204, "Reply deleted successfully")
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    def delete(self, app_model: App, comment_id: str, reply_id: str):
-        """Delete a comment reply."""
-        # Validate comment access first
-        WorkflowCommentService.validate_comment_access(
-            comment_id=comment_id, tenant_id=current_user.current_tenant_id, app_id=app_model.id
-        )
-
-        WorkflowCommentService.delete_reply(reply_id=reply_id, user_id=current_user.id)
-
-        return {"result": "success"}, 204
-
-
-@console_ns.route("/apps/<uuid:app_id>/workflow/comments/mention-users")
-class WorkflowCommentMentionUsersApi(Resource):
-    """API for getting mentionable users for workflow comments."""
-
-    @console_ns.doc("workflow_comment_mention_users")
-    @console_ns.doc(description="Get all users in current tenant for mentions")
-    @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.response(200, "Mentionable users retrieved successfully", workflow_comment_mention_users_model)
-    @login_required
-    @setup_required
-    @account_initialization_required
-    @get_app_model()
-    def get(self, app_model: App):
-        """Get all users in current tenant for mentions."""
-        members = TenantService.get_tenant_members(current_user.current_tenant)
-        member_models = TypeAdapter(list[AccountWithRole]).validate_python(members, from_attributes=True)
-        response = WorkflowCommentMentionUsersResponse(users=member_models)
-        return response.model_dump(mode="json"), 200

api/controllers/console/app/workflow_draft_variable.py

@@ -1,7 +1,7 @@
 import logging
 from collections.abc import Callable
 from functools import wraps
-from typing import Any, TypedDict
+from typing import Any
 
 from flask import Response, request
 from flask_restx import Resource, fields, marshal, marshal_with
@@ -86,14 +86,7 @@ def _serialize_variable_type(workflow_draft_var: WorkflowDraftVariable) -> str:
     return value_type.exposed_type().value
 
 
-class FullContentDict(TypedDict):
-    size_bytes: int | None
-    value_type: str
-    length: int | None
-    download_url: str
-
-
-def _serialize_full_content(variable: WorkflowDraftVariable) -> FullContentDict | None:
+def _serialize_full_content(variable: WorkflowDraftVariable) -> dict | None:
     """Serialize full_content information for large variables."""
     if not variable.is_truncated():
         return None
@@ -101,13 +94,12 @@ def _serialize_full_content(variable: WorkflowDraftVariable) -> FullContentDict
     variable_file = variable.variable_file
     assert variable_file is not None
 
-    result: FullContentDict = {
+    return {
         "size_bytes": variable_file.size,
         "value_type": variable_file.value_type.exposed_type().value,
         "length": variable_file.length,
         "download_url": file_helpers.get_signed_file_url(variable_file.upload_file_id, as_attachment=True),
     }
-    return result
 
 
 def _ensure_variable_access(
@@ -216,7 +208,7 @@ def _api_prerequisite[**P, R](f: Callable[P, R]) -> Callable[P, R | Response]:
     @login_required
     @account_initialization_required
     @edit_permission_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @wraps(f)
     def wrapper(*args: P.args, **kwargs: P.kwargs) -> R | Response:
         return f(*args, **kwargs)
@@ -392,27 +384,24 @@ class VariableApi(Resource):
 
         new_value = None
         if raw_value is not None:
-            match variable.value_type:
-                case SegmentType.FILE:
-                    if not isinstance(raw_value, dict):
-                        raise InvalidArgumentError(description=f"expected dict for file, got {type(raw_value)}")
-                    raw_value = build_from_mapping(
-                        mapping=raw_value,
-                        tenant_id=app_model.tenant_id,
-                        access_controller=_file_access_controller,
-                    )
-                case SegmentType.ARRAY_FILE:
-                    if not isinstance(raw_value, list):
-                        raise InvalidArgumentError(description=f"expected list for files, got {type(raw_value)}")
-                    if len(raw_value) > 0 and not isinstance(raw_value[0], dict):
-                        raise InvalidArgumentError(description=f"expected dict for files[0], got {type(raw_value)}")
-                    raw_value = build_from_mappings(
-                        mappings=raw_value,
-                        tenant_id=app_model.tenant_id,
-                        access_controller=_file_access_controller,
-                    )
-                case _:
-                    pass
+            if variable.value_type == SegmentType.FILE:
+                if not isinstance(raw_value, dict):
+                    raise InvalidArgumentError(description=f"expected dict for file, got {type(raw_value)}")
+                raw_value = build_from_mapping(
+                    mapping=raw_value,
+                    tenant_id=app_model.tenant_id,
+                    access_controller=_file_access_controller,
+                )
+            elif variable.value_type == SegmentType.ARRAY_FILE:
+                if not isinstance(raw_value, list):
+                    raise InvalidArgumentError(description=f"expected list for files, got {type(raw_value)}")
+                if len(raw_value) > 0 and not isinstance(raw_value[0], dict):
+                    raise InvalidArgumentError(description=f"expected dict for files[0], got {type(raw_value)}")
+                raw_value = build_from_mappings(
+                    mappings=raw_value,
+                    tenant_id=app_model.tenant_id,
+                    access_controller=_file_access_controller,
+                )
             new_value = build_segment_with_type(variable.value_type, raw_value)
         draft_var_srv.update_variable(variable, name=new_name, value=new_value)
         db.session.commit()

api/controllers/console/app/workflow_run.py

@@ -207,7 +207,7 @@ class AdvancedChatAppWorkflowRunListApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
     @marshal_with(advanced_chat_workflow_run_pagination_model)
     def get(self, app_model: App):
         """
@@ -305,7 +305,7 @@ class AdvancedChatAppWorkflowRunCountApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT])
     @marshal_with(workflow_run_count_model)
     def get(self, app_model: App):
         """
@@ -349,7 +349,7 @@ class WorkflowRunListApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_run_pagination_model)
     def get(self, app_model: App):
         """
@@ -397,7 +397,7 @@ class WorkflowRunCountApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_run_count_model)
     def get(self, app_model: App):
         """
@@ -434,7 +434,7 @@ class WorkflowRunDetailApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_run_detail_model)
     def get(self, app_model: App, run_id):
         """
@@ -458,7 +458,7 @@ class WorkflowRunNodeExecutionListApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW, AppMode.AGENT])
+    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
     @marshal_with(workflow_run_node_execution_list_model)
     def get(self, app_model: App, run_id):
         """

api/controllers/console/auth/activate.py

@@ -1,9 +1,8 @@
 from flask import request
-from flask_restx import Resource
+from flask_restx import Resource, fields
 from pydantic import BaseModel, Field, field_validator
 
 from constants.languages import supported_language
-from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.error import AlreadyActivateError
 from extensions.ext_database import db
@@ -12,6 +11,8 @@ from libs.helper import EmailStr, timezone
 from models import AccountStatus
 from services.account_service import RegisterService
 
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
 
 class ActivateCheckQuery(BaseModel):
     workspace_id: str | None = Field(default=None)
@@ -38,16 +39,8 @@ class ActivatePayload(BaseModel):
         return timezone(value)
 
 
-class ActivationCheckResponse(BaseModel):
-    is_valid: bool = Field(description="Whether token is valid")
-    data: dict | None = Field(default=None, description="Activation data if valid")
-
-
-class ActivationResponse(BaseModel):
-    result: str = Field(description="Operation result")
-
-
-register_schema_models(console_ns, ActivateCheckQuery, ActivatePayload, ActivationCheckResponse, ActivationResponse)
+for model in (ActivateCheckQuery, ActivatePayload):
+    console_ns.schema_model(model.__name__, model.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0))
 
 
 @console_ns.route("/activate/check")
@@ -58,7 +51,13 @@ class ActivateCheckApi(Resource):
     @console_ns.response(
         200,
         "Success",
-        console_ns.models[ActivationCheckResponse.__name__],
+        console_ns.model(
+            "ActivationCheckResponse",
+            {
+                "is_valid": fields.Boolean(description="Whether token is valid"),
+                "data": fields.Raw(description="Activation data if valid"),
+            },
+        ),
     )
     def get(self):
         args = ActivateCheckQuery.model_validate(request.args.to_dict(flat=True))  # type: ignore
@@ -96,7 +95,12 @@ class ActivateApi(Resource):
     @console_ns.response(
         200,
         "Account activated successfully",
-        console_ns.models[ActivationResponse.__name__],
+        console_ns.model(
+            "ActivationResponse",
+            {
+                "result": fields.String(description="Operation result"),
+            },
+        ),
     )
     @console_ns.response(400, "Already activated or invalid token")
     def post(self):

api/controllers/console/auth/email_register.py

@@ -1,6 +1,7 @@
 from flask import request
 from flask_restx import Resource
 from pydantic import BaseModel, Field, field_validator
+from sqlalchemy.orm import sessionmaker
 
 from configs import dify_config
 from constants.languages import languages
@@ -13,6 +14,7 @@ from controllers.console.auth.error import (
     InvalidTokenError,
     PasswordMismatchError,
 )
+from extensions.ext_database import db
 from libs.helper import EmailStr, extract_remote_ip
 from libs.password import valid_password
 from models import Account
@@ -71,7 +73,8 @@ class EmailRegisterSendEmailApi(Resource):
         if dify_config.BILLING_ENABLED and BillingService.is_email_in_freeze(normalized_email):
             raise AccountInFreezeError()
 
-        account = AccountService.get_account_by_email_with_case_fallback(args.email)
+        with sessionmaker(db.engine).begin() as session:
+            account = AccountService.get_account_by_email_with_case_fallback(args.email, session=session)
         token = AccountService.send_email_register_email(email=normalized_email, account=account, language=language)
         return {"result": "success", "data": token}
 
@@ -142,16 +145,17 @@ class EmailRegisterResetApi(Resource):
         email = register_data.get("email", "")
         normalized_email = email.lower()
 
-        account = AccountService.get_account_by_email_with_case_fallback(email)
+        with sessionmaker(db.engine).begin() as session:
+            account = AccountService.get_account_by_email_with_case_fallback(email, session=session)
 
-        if account:
-            raise EmailAlreadyInUseError()
-        else:
-            account = self._create_new_account(normalized_email, args.password_confirm)
-            if not account:
-                raise AccountNotFoundError()
-            token_pair = AccountService.login(account=account, ip_address=extract_remote_ip(request))
-            AccountService.reset_login_error_rate_limit(normalized_email)
+            if account:
+                raise EmailAlreadyInUseError()
+            else:
+                account = self._create_new_account(normalized_email, args.password_confirm)
+                if not account:
+                    raise AccountNotFoundError()
+                token_pair = AccountService.login(account=account, ip_address=extract_remote_ip(request))
+                AccountService.reset_login_error_rate_limit(normalized_email)
 
         return {"result": "success", "data": token_pair.model_dump()}
 

api/controllers/console/auth/forgot_password.py

@@ -4,6 +4,7 @@ import secrets
 from flask import request
 from flask_restx import Resource
 from pydantic import BaseModel, Field
+from sqlalchemy.orm import sessionmaker
 
 from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
@@ -84,7 +85,8 @@ class ForgotPasswordSendEmailApi(Resource):
         else:
             language = "en-US"
 
-        account = AccountService.get_account_by_email_with_case_fallback(args.email)
+        with sessionmaker(db.engine).begin() as session:
+            account = AccountService.get_account_by_email_with_case_fallback(args.email, session=session)
 
         token = AccountService.send_reset_password_email(
             account=account,
@@ -182,18 +184,17 @@ class ForgotPasswordResetApi(Resource):
         password_hashed = hash_password(args.new_password, salt)
 
         email = reset_data.get("email", "")
-        account = AccountService.get_account_by_email_with_case_fallback(email)
+        with sessionmaker(db.engine).begin() as session:
+            account = AccountService.get_account_by_email_with_case_fallback(email, session=session)
 
-        if account:
-            account = db.session.merge(account)
-            self._update_existing_account(account, password_hashed, salt)
-            db.session.commit()
-        else:
-            raise AccountNotFound()
+            if account:
+                self._update_existing_account(account, password_hashed, salt, session)
+            else:
+                raise AccountNotFound()
 
         return {"result": "success"}
 
-    def _update_existing_account(self, account, password_hashed, salt):
+    def _update_existing_account(self, account, password_hashed, salt, session):
         # Update existing account credentials
         account.password = base64.b64encode(password_hashed).decode()
         account.password_salt = base64.b64encode(salt).decode()

api/controllers/console/auth/oauth.py

@@ -4,6 +4,7 @@ import urllib.parse
 import httpx
 from flask import current_app, redirect, request
 from flask_restx import Resource
+from sqlalchemy.orm import sessionmaker
 from werkzeug.exceptions import Unauthorized
 
 from configs import dify_config
@@ -179,7 +180,8 @@ def _get_account_by_openid_or_email(provider: str, user_info: OAuthUserInfo) ->
     account: Account | None = Account.get_by_openid(provider, user_info.id)
 
     if not account:
-        account = AccountService.get_account_by_email_with_case_fallback(user_info.email)
+        with sessionmaker(db.engine).begin() as session:
+            account = AccountService.get_account_by_email_with_case_fallback(user_info.email, session=session)
 
     return account
 

api/controllers/console/billing/billing.py

@@ -2,17 +2,18 @@ import base64
 from typing import Literal
 
 from flask import request
-from flask_restx import Resource
+from flask_restx import Resource, fields
 from pydantic import BaseModel, Field
 from werkzeug.exceptions import BadRequest
 
-from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.wraps import account_initialization_required, only_edition_cloud, setup_required
 from enums.cloud_plan import CloudPlan
 from libs.login import current_account_with_tenant, login_required
 from services.billing_service import BillingService
 
+DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
+
 
 class SubscriptionQuery(BaseModel):
     plan: Literal[CloudPlan.PROFESSIONAL, CloudPlan.TEAM] = Field(..., description="Subscription plan")
@@ -23,7 +24,8 @@ class PartnerTenantsPayload(BaseModel):
     click_id: str = Field(..., description="Click Id from partner referral link")
 
 
-register_schema_models(console_ns, SubscriptionQuery, PartnerTenantsPayload)
+for model in (SubscriptionQuery, PartnerTenantsPayload):
+    console_ns.schema_model(model.__name__, model.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0))
 
 
 @console_ns.route("/billing/subscription")
@@ -56,7 +58,12 @@ class PartnerTenants(Resource):
     @console_ns.doc("sync_partner_tenants_bindings")
     @console_ns.doc(description="Sync partner tenants bindings")
     @console_ns.doc(params={"partner_key": "Partner key"})
-    @console_ns.expect(console_ns.models[PartnerTenantsPayload.__name__])
+    @console_ns.expect(
+        console_ns.model(
+            "SyncPartnerTenantsBindingsRequest",
+            {"click_id": fields.String(required=True, description="Click Id from partner referral link")},
+        )
+    )
     @console_ns.response(200, "Tenants synced to partner successfully")
     @console_ns.response(400, "Invalid partner information")
     @setup_required

api/controllers/console/datasets/data_source.py

@@ -162,9 +162,7 @@ class DataSourceApi(Resource):
         binding_id = str(binding_id)
         with sessionmaker(db.engine, expire_on_commit=False).begin() as session:
             data_source_binding = session.execute(
-                select(DataSourceOauthBinding).where(
-                    DataSourceOauthBinding.id == binding_id, DataSourceOauthBinding.tenant_id == current_tenant_id
-                )
+                select(DataSourceOauthBinding).filter_by(id=binding_id, tenant_id=current_tenant_id)
             ).scalar_one_or_none()
         if data_source_binding is None:
             raise NotFound("Data source binding not found.")
@@ -224,11 +222,11 @@ class DataSourceNotionListApi(Resource):
                     raise ValueError("Dataset is not notion type.")
 
                 documents = session.scalars(
-                    select(Document).where(
-                        Document.dataset_id == query.dataset_id,
-                        Document.tenant_id == current_tenant_id,
-                        Document.data_source_type == "notion_import",
-                        Document.enabled.is_(True),
+                    select(Document).filter_by(
+                        dataset_id=query.dataset_id,
+                        tenant_id=current_tenant_id,
+                        data_source_type="notion_import",
+                        enabled=True,
                     )
                 ).all()
                 if documents:

api/controllers/console/datasets/datasets.py

@@ -11,7 +11,10 @@ import services
 from configs import dify_config
 from controllers.common.schema import get_or_create_model, register_schema_models
 from controllers.console import console_ns
-from controllers.console.apikey import ApiKeyItem, ApiKeyList
+from controllers.console.apikey import (
+    api_key_item_model,
+    api_key_list_model,
+)
 from controllers.console.app.error import ProviderNotInitializeError
 from controllers.console.datasets.error import DatasetInUseError, DatasetNameDuplicateError, IndexingEstimateError
 from controllers.console.wraps import (
@@ -782,23 +785,23 @@ class DatasetApiKeyApi(Resource):
 
     @console_ns.doc("get_dataset_api_keys")
     @console_ns.doc(description="Get dataset API keys")
-    @console_ns.response(200, "API keys retrieved successfully", console_ns.models[ApiKeyList.__name__])
+    @console_ns.response(200, "API keys retrieved successfully", api_key_list_model)
     @setup_required
     @login_required
     @account_initialization_required
+    @marshal_with(api_key_list_model)
     def get(self):
         _, current_tenant_id = current_account_with_tenant()
         keys = db.session.scalars(
             select(ApiToken).where(ApiToken.type == self.resource_type, ApiToken.tenant_id == current_tenant_id)
         ).all()
-        return ApiKeyList.model_validate({"data": keys}, from_attributes=True).model_dump(mode="json")
+        return {"items": keys}
 
-    @console_ns.response(200, "API key created successfully", console_ns.models[ApiKeyItem.__name__])
-    @console_ns.response(400, "Maximum keys exceeded")
     @setup_required
     @login_required
     @is_admin_or_owner_required
     @account_initialization_required
+    @marshal_with(api_key_item_model)
     def post(self):
         _, current_tenant_id = current_account_with_tenant()
 
@@ -825,7 +828,7 @@ class DatasetApiKeyApi(Resource):
         api_token.type = self.resource_type
         db.session.add(api_token)
         db.session.commit()
-        return ApiKeyItem.model_validate(api_token, from_attributes=True).model_dump(mode="json"), 200
+        return api_token, 200
 
 
 @console_ns.route("/datasets/api-keys/<uuid:api_key_id>")

api/controllers/console/datasets/datasets_document.py

@@ -4,6 +4,7 @@ from argparse import ArgumentTypeError
 from collections.abc import Sequence
 from contextlib import ExitStack
 from typing import Any, Literal, cast
+from uuid import UUID
 
 import sqlalchemy as sa
 from flask import request, send_file
@@ -15,7 +16,6 @@ from sqlalchemy import asc, desc, func, select
 from werkzeug.exceptions import Forbidden, NotFound
 
 import services
-from controllers.common.controller_schemas import DocumentBatchDownloadZipPayload
 from controllers.common.schema import get_or_create_model, register_schema_models
 from controllers.console import console_ns
 from core.errors.error import (
@@ -71,6 +71,9 @@ from ..wraps import (
 
 logger = logging.getLogger(__name__)
 
+# NOTE: Keep constants near the top of the module for discoverability.
+DOCUMENT_BATCH_DOWNLOAD_ZIP_MAX_DOCS = 100
+
 
 # Register models for flask_restx to avoid dict type issues in Swagger
 dataset_model = get_or_create_model("Dataset", dataset_fields)
@@ -107,6 +110,12 @@ class GenerateSummaryPayload(BaseModel):
     document_list: list[str]
 
 
+class DocumentBatchDownloadZipPayload(BaseModel):
+    """Request payload for bulk downloading documents as a zip archive."""
+
+    document_ids: list[UUID] = Field(..., min_length=1, max_length=DOCUMENT_BATCH_DOWNLOAD_ZIP_MAX_DOCS)
+
+
 class DocumentDatasetListParam(BaseModel):
     page: int = Field(1, title="Page", description="Page number.")
     limit: int = Field(20, title="Limit", description="Page size.")
@@ -271,7 +280,7 @@ class DatasetDocumentListApi(Resource):
         except services.errors.account.NoPermissionError as e:
             raise Forbidden(str(e))
 
-        query = select(Document).where(Document.dataset_id == str(dataset_id), Document.tenant_id == current_tenant_id)
+        query = select(Document).filter_by(dataset_id=str(dataset_id), tenant_id=current_tenant_id)
 
         if status:
             query = DocumentService.apply_display_status_filter(query, status)

api/controllers/console/datasets/datasets_segments.py

@@ -10,7 +10,6 @@ from werkzeug.exceptions import Forbidden, NotFound
 
 import services
 from configs import dify_config
-from controllers.common.controller_schemas import ChildChunkCreatePayload, ChildChunkUpdatePayload
 from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.error import ProviderNotInitializeError
@@ -83,6 +82,14 @@ class BatchImportPayload(BaseModel):
     upload_file_id: str
 
 
+class ChildChunkCreatePayload(BaseModel):
+    content: str
+
+
+class ChildChunkUpdatePayload(BaseModel):
+    content: str
+
+
 class ChildChunkBatchUpdatePayload(BaseModel):
     chunks: list[ChildChunkUpdateArgs]
 

api/controllers/console/datasets/external.py

@@ -227,11 +227,10 @@ class ExternalApiUseCheckApi(Resource):
     @login_required
     @account_initialization_required
     def get(self, external_knowledge_api_id):
-        _, current_tenant_id = current_account_with_tenant()
         external_knowledge_api_id = str(external_knowledge_api_id)
 
         external_knowledge_api_is_using, count = ExternalDatasetService.external_knowledge_api_use_check(
-            external_knowledge_api_id, current_tenant_id
+            external_knowledge_api_id
         )
         return {"is_using": external_knowledge_api_is_using, "count": count}, 200
 

api/controllers/console/datasets/metadata.py

@@ -1,9 +1,9 @@
 from typing import Literal
 
 from flask_restx import Resource, marshal_with
+from pydantic import BaseModel
 from werkzeug.exceptions import NotFound
 
-from controllers.common.controller_schemas import MetadataUpdatePayload
 from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.wraps import account_initialization_required, enterprise_license_required, setup_required
@@ -18,6 +18,11 @@ from services.entities.knowledge_entities.knowledge_entities import (
 )
 from services.metadata_service import MetadataService
 
+
+class MetadataUpdatePayload(BaseModel):
+    name: str
+
+
 register_schema_models(
     console_ns, MetadataArgs, MetadataOperationData, MetadataUpdatePayload, DocumentMetadataOperation, MetadataDetail
 )

api/controllers/console/datasets/rag_pipeline/rag_pipeline_draft_variable.py

@@ -223,27 +223,24 @@ class RagPipelineVariableApi(Resource):
 
         new_value = None
         if raw_value is not None:
-            match variable.value_type:
-                case SegmentType.FILE:
-                    if not isinstance(raw_value, dict):
-                        raise InvalidArgumentError(description=f"expected dict for file, got {type(raw_value)}")
-                    raw_value = build_from_mapping(
-                        mapping=raw_value,
-                        tenant_id=pipeline.tenant_id,
-                        access_controller=_file_access_controller,
-                    )
-                case SegmentType.ARRAY_FILE:
-                    if not isinstance(raw_value, list):
-                        raise InvalidArgumentError(description=f"expected list for files, got {type(raw_value)}")
-                    if len(raw_value) > 0 and not isinstance(raw_value[0], dict):
-                        raise InvalidArgumentError(description=f"expected dict for files[0], got {type(raw_value)}")
-                    raw_value = build_from_mappings(
-                        mappings=raw_value,
-                        tenant_id=pipeline.tenant_id,
-                        access_controller=_file_access_controller,
-                    )
-                case _:
-                    pass
+            if variable.value_type == SegmentType.FILE:
+                if not isinstance(raw_value, dict):
+                    raise InvalidArgumentError(description=f"expected dict for file, got {type(raw_value)}")
+                raw_value = build_from_mapping(
+                    mapping=raw_value,
+                    tenant_id=pipeline.tenant_id,
+                    access_controller=_file_access_controller,
+                )
+            elif variable.value_type == SegmentType.ARRAY_FILE:
+                if not isinstance(raw_value, list):
+                    raise InvalidArgumentError(description=f"expected list for files, got {type(raw_value)}")
+                if len(raw_value) > 0 and not isinstance(raw_value[0], dict):
+                    raise InvalidArgumentError(description=f"expected dict for files[0], got {type(raw_value)}")
+                raw_value = build_from_mappings(
+                    mappings=raw_value,
+                    tenant_id=pipeline.tenant_id,
+                    access_controller=_file_access_controller,
+                )
             new_value = build_segment_with_type(variable.value_type, raw_value)
         draft_var_srv.update_variable(variable, name=new_name, value=new_value)
         db.session.commit()

api/controllers/console/datasets/rag_pipeline/rag_pipeline_import.py

@@ -19,7 +19,7 @@ from fields.rag_pipeline_fields import (
 )
 from libs.login import current_account_with_tenant, login_required
 from models.dataset import Pipeline
-from services.entities.dsl_entities import ImportStatus
+from services.app_dsl_service import ImportStatus
 from services.rag_pipeline.rag_pipeline_dsl_service import RagPipelineDslService
 
 
@@ -83,13 +83,11 @@ class RagPipelineImportApi(Resource):
 
         # Return appropriate status code based on result
         status = result.status
-        match status:
-            case ImportStatus.FAILED:
-                return result.model_dump(mode="json"), 400
-            case ImportStatus.PENDING:
-                return result.model_dump(mode="json"), 202
-            case ImportStatus.COMPLETED | ImportStatus.COMPLETED_WITH_WARNINGS:
-                return result.model_dump(mode="json"), 200
+        if status == ImportStatus.FAILED:
+            return result.model_dump(mode="json"), 400
+        elif status == ImportStatus.PENDING:
+            return result.model_dump(mode="json"), 202
+        return result.model_dump(mode="json"), 200
 
 
 @console_ns.route("/rag/pipelines/imports/<string:import_id>/confirm")

api/controllers/console/datasets/rag_pipeline/rag_pipeline_workflow.py

@@ -10,7 +10,6 @@ from sqlalchemy.orm import sessionmaker
 from werkzeug.exceptions import BadRequest, Forbidden, InternalServerError, NotFound
 
 import services
-from controllers.common.controller_schemas import DefaultBlockConfigQuery, WorkflowListQuery, WorkflowUpdatePayload
 from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.error import (
@@ -95,6 +94,22 @@ class PublishedWorkflowRunPayload(DraftWorkflowRunPayload):
     original_document_id: str | None = None
 
 
+class DefaultBlockConfigQuery(BaseModel):
+    q: str | None = None
+
+
+class WorkflowListQuery(BaseModel):
+    page: int = Field(default=1, ge=1, le=99999)
+    limit: int = Field(default=10, ge=1, le=100)
+    user_id: str | None = None
+    named_only: bool = False
+
+
+class WorkflowUpdatePayload(BaseModel):
+    marked_name: str | None = Field(default=None, max_length=20)
+    marked_comment: str | None = Field(default=None, max_length=100)
+
+
 class NodeIdQuery(BaseModel):
     node_id: str
 
@@ -346,6 +361,89 @@ class PublishedRagPipelineRunApi(Resource):
             raise InvokeRateLimitHttpError(ex.description)
 
 
+# class RagPipelinePublishedDatasourceNodeRunStatusApi(Resource):
+#     @setup_required
+#     @login_required
+#     @account_initialization_required
+#     @get_rag_pipeline
+#     def post(self, pipeline: Pipeline, node_id: str):
+#         """
+#         Run rag pipeline datasource
+#         """
+#         # The role of the current user in the ta table must be admin, owner, or editor
+#         if not current_user.has_edit_permission:
+#             raise Forbidden()
+#
+#         if not isinstance(current_user, Account):
+#             raise Forbidden()
+#
+#         parser = (reqparse.RequestParser()
+#             .add_argument("job_id", type=str, required=True, nullable=False, location="json")
+#             .add_argument("datasource_type", type=str, required=True, location="json")
+#         )
+#         args = parser.parse_args()
+#
+#         job_id = args.get("job_id")
+#         if job_id == None:
+#             raise ValueError("missing job_id")
+#         datasource_type = args.get("datasource_type")
+#         if datasource_type == None:
+#             raise ValueError("missing datasource_type")
+#
+#         rag_pipeline_service = RagPipelineService()
+#         result = rag_pipeline_service.run_datasource_workflow_node_status(
+#             pipeline=pipeline,
+#             node_id=node_id,
+#             job_id=job_id,
+#             account=current_user,
+#             datasource_type=datasource_type,
+#             is_published=True
+#         )
+#
+#         return result
+
+
+# class RagPipelineDraftDatasourceNodeRunStatusApi(Resource):
+#     @setup_required
+#     @login_required
+#     @account_initialization_required
+#     @get_rag_pipeline
+#     def post(self, pipeline: Pipeline, node_id: str):
+#         """
+#         Run rag pipeline datasource
+#         """
+#         # The role of the current user in the ta table must be admin, owner, or editor
+#         if not current_user.has_edit_permission:
+#             raise Forbidden()
+#
+#         if not isinstance(current_user, Account):
+#             raise Forbidden()
+#
+#         parser = (reqparse.RequestParser()
+#             .add_argument("job_id", type=str, required=True, nullable=False, location="json")
+#             .add_argument("datasource_type", type=str, required=True, location="json")
+#         )
+#         args = parser.parse_args()
+#
+#         job_id = args.get("job_id")
+#         if job_id == None:
+#             raise ValueError("missing job_id")
+#         datasource_type = args.get("datasource_type")
+#         if datasource_type == None:
+#             raise ValueError("missing datasource_type")
+#
+#         rag_pipeline_service = RagPipelineService()
+#         result = rag_pipeline_service.run_datasource_workflow_node_status(
+#             pipeline=pipeline,
+#             node_id=node_id,
+#             job_id=job_id,
+#             account=current_user,
+#             datasource_type=datasource_type,
+#             is_published=False
+#         )
+#
+#         return result
+#
 @console_ns.route("/rag/pipelines/<uuid:pipeline_id>/workflows/published/datasource/nodes/<string:node_id>/run")
 class RagPipelinePublishedDatasourceNodeRunApi(Resource):
     @console_ns.expect(console_ns.models[DatasourceNodeRunPayload.__name__])

api/controllers/console/human_input_form.py

@@ -7,8 +7,7 @@ import logging
 from collections.abc import Generator
 
 from flask import Response, jsonify, request
-from flask_restx import Resource
-from pydantic import BaseModel
+from flask_restx import Resource, reqparse
 from sqlalchemy import select
 from sqlalchemy.orm import Session, sessionmaker
 
@@ -34,11 +33,6 @@ from services.workflow_event_snapshot_service import build_workflow_event_stream
 logger = logging.getLogger(__name__)
 
 
-class HumanInputFormSubmitPayload(BaseModel):
-    inputs: dict
-    action: str
-
-
 def _jsonify_form_definition(form: Form) -> Response:
     payload = form.get_definition().model_dump()
     payload["expiration_time"] = int(form.expiration_time.timestamp())
@@ -90,7 +84,10 @@ class ConsoleHumanInputFormApi(Resource):
             "action": "Approve"
         }
         """
-        payload = HumanInputFormSubmitPayload.model_validate(request.get_json())
+        parser = reqparse.RequestParser()
+        parser.add_argument("inputs", type=dict, required=True, location="json")
+        parser.add_argument("action", type=str, required=True, location="json")
+        args = parser.parse_args()
         current_user, _ = current_account_with_tenant()
 
         service = HumanInputService(db.engine)
@@ -110,8 +107,8 @@ class ConsoleHumanInputFormApi(Resource):
         service.submit_form_by_token(
             recipient_type=recipient_type,
             form_token=form_token,
-            selected_action_id=payload.action,
-            form_data=payload.inputs,
+            selected_action_id=args["action"],
+            form_data=args["inputs"],
             submission_user_id=current_user.id,
         )
 
@@ -171,13 +168,12 @@ class ConsoleWorkflowEventsApi(Resource):
         else:
             msg_generator = MessageGenerator()
             generator: BaseAppGenerator
-            match app.mode:
-                case AppMode.ADVANCED_CHAT:
-                    generator = AdvancedChatAppGenerator()
-                case AppMode.WORKFLOW:
-                    generator = WorkflowAppGenerator()
-                case _:
-                    raise InvalidArgumentError(f"cannot subscribe to workflow run, workflow_run_id={workflow_run.id}")
+            if app.mode == AppMode.ADVANCED_CHAT:
+                generator = AdvancedChatAppGenerator()
+            elif app.mode == AppMode.WORKFLOW:
+                generator = WorkflowAppGenerator()
+            else:
+                raise InvalidArgumentError(f"cannot subscribe to workflow run, workflow_run_id={workflow_run.id}")
 
             include_state_snapshot = request.args.get("include_state_snapshot", "false").lower() == "true"
 

api/controllers/console/socketio/__init__.py

@@ -1 +0,0 @@
-

api/controllers/console/socketio/workflow.py

@@ -1,119 +0,0 @@
-import logging
-from collections.abc import Callable
-from typing import cast
-
-from flask import Request as FlaskRequest
-
-from extensions.ext_socketio import sio
-from libs.passport import PassportService
-from libs.token import extract_access_token
-from repositories.workflow_collaboration_repository import WorkflowCollaborationRepository
-from services.account_service import AccountService
-from services.workflow_collaboration_service import WorkflowCollaborationService
-
-repository = WorkflowCollaborationRepository()
-collaboration_service = WorkflowCollaborationService(repository, sio)
-
-
-def _sio_on(event: str) -> Callable[[Callable[..., object]], Callable[..., object]]:
-    return cast(Callable[[Callable[..., object]], Callable[..., object]], sio.on(event))
-
-
-@_sio_on("connect")
-def socket_connect(sid, environ, auth):
-    """
-    WebSocket connect event, do authentication here.
-    """
-    try:
-        request_environ = FlaskRequest(environ)
-        token = extract_access_token(request_environ)
-    except Exception:
-        logging.exception("Failed to extract token")
-        token = None
-
-    if not token:
-        logging.warning("Socket connect rejected: missing token (sid=%s)", sid)
-        return False
-
-    try:
-        decoded = PassportService().verify(token)
-        user_id = decoded.get("user_id")
-        if not user_id:
-            logging.warning("Socket connect rejected: missing user_id (sid=%s)", sid)
-            return False
-
-        with sio.app.app_context():
-            user = AccountService.load_logged_in_account(account_id=user_id)
-            if not user:
-                logging.warning("Socket connect rejected: user not found (user_id=%s, sid=%s)", user_id, sid)
-                return False
-            if not user.has_edit_permission:
-                logging.warning("Socket connect rejected: no edit permission (user_id=%s, sid=%s)", user_id, sid)
-                return False
-
-            collaboration_service.save_session(sid, user)
-            return True
-
-    except Exception:
-        logging.exception("Socket authentication failed")
-        return False
-
-
-@_sio_on("user_connect")
-def handle_user_connect(sid, data):
-    """
-    Handle user connect event. Each session (tab) is treated as an independent collaborator.
-    """
-    workflow_id = data.get("workflow_id")
-    if not workflow_id:
-        return {"msg": "workflow_id is required"}, 400
-
-    result = collaboration_service.register_session(workflow_id, sid)
-    if not result:
-        return {"msg": "unauthorized"}, 401
-
-    user_id, is_leader = result
-    return {"msg": "connected", "user_id": user_id, "sid": sid, "isLeader": is_leader}
-
-
-@_sio_on("disconnect")
-def handle_disconnect(sid):
-    """
-    Handle session disconnect event. Remove the specific session from online users.
-    """
-    collaboration_service.disconnect_session(sid)
-
-
-@_sio_on("collaboration_event")
-def handle_collaboration_event(sid, data):
-    """
-    Handle general collaboration events, include:
-    1. mouse_move
-    2. vars_and_features_update
-    3. sync_request (ask leader to update graph)
-    4. app_state_update
-    5. mcp_server_update
-    6. workflow_update
-    7. comments_update
-    8. node_panel_presence
-    9. skill_file_active
-    10. skill_sync_request
-    11. skill_resync_request
-    """
-    return collaboration_service.relay_collaboration_event(sid, data)
-
-
-@_sio_on("graph_event")
-def handle_graph_event(sid, data):
-    """
-    Handle graph events - simple broadcast relay.
-    """
-    return collaboration_service.relay_graph_event(sid, data)
-
-
-@_sio_on("skill_event")
-def handle_skill_event(sid, data):
-    """
-    Handle skill events - simple broadcast relay.
-    """
-    return collaboration_service.relay_skill_event(sid, data)

api/controllers/console/workspace/account.py

@@ -8,6 +8,7 @@ from flask import request
 from flask_restx import Resource, fields, marshal_with
 from pydantic import BaseModel, Field, field_validator, model_validator
 from sqlalchemy import select
+from sqlalchemy.orm import sessionmaker
 
 from configs import dify_config
 from constants.languages import supported_language
@@ -561,7 +562,8 @@ class ChangeEmailSendEmailApi(Resource):
 
             user_email = current_user.email
         else:
-            account = AccountService.get_account_by_email_with_case_fallback(args.email)
+            with sessionmaker(db.engine).begin() as session:
+                account = AccountService.get_account_by_email_with_case_fallback(args.email, session=session)
             if account is None:
                 raise AccountNotFound()
             email_for_sending = account.email

api/controllers/console/workspace/dsl.py

@@ -1,67 +0,0 @@
-import json
-
-import httpx
-import yaml
-from flask import request
-from flask_restx import Resource
-from pydantic import BaseModel
-from sqlalchemy.orm import Session
-from werkzeug.exceptions import Forbidden
-
-from controllers.console import console_ns
-from controllers.console.wraps import account_initialization_required, setup_required
-from core.plugin.impl.exc import PluginPermissionDeniedError
-from extensions.ext_database import db
-from libs.login import current_account_with_tenant, login_required
-from models.model import App
-from models.workflow import Workflow
-from services.app_dsl_service import AppDslService
-
-
-class DSLPredictRequest(BaseModel):
-    app_id: str
-    current_node_id: str
-
-
-@console_ns.route("/workspaces/current/dsl/predict")
-class DSLPredictApi(Resource):
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def post(self):
-        user, _ = current_account_with_tenant()
-        if not user.is_admin_or_owner:
-            raise Forbidden()
-
-        args = DSLPredictRequest.model_validate(request.get_json())
-
-        app_id: str = args.app_id
-        current_node_id: str = args.current_node_id
-
-        with Session(db.engine) as session:
-            app = session.query(App).filter_by(id=app_id).first()
-            workflow = session.query(Workflow).filter_by(app_id=app_id, version=Workflow.VERSION_DRAFT).first()
-
-        if not app:
-            raise ValueError("App not found")
-        if not workflow:
-            raise ValueError("Workflow not found")
-
-        try:
-            i = 0
-            for node_id, _ in workflow.walk_nodes():
-                if node_id == current_node_id:
-                    break
-                i += 1
-
-            dsl = yaml.safe_load(AppDslService.export_dsl(app_model=app))
-
-            response = httpx.post(
-                "http://spark-832c:8000/predict",
-                json={"graph_data": dsl, "source_node_index": i},
-            )
-            return {
-                "nodes": json.loads(response.json()),
-            }
-        except PluginPermissionDeniedError as e:
-            raise ValueError(e.description) from e

api/controllers/files/storage_files.py

@@ -1,80 +0,0 @@
-"""Token-based file proxy controller for storage operations.
-
-This controller handles file download and upload operations using opaque UUID tokens.
-The token maps to the real storage key in Redis, so the actual storage path is never
-exposed in the URL.
-
-Routes:
-    GET  /files/storage-files/{token} - Download a file
-    PUT  /files/storage-files/{token} - Upload a file
-
-The operation type (download/upload) is determined by the ticket stored in Redis,
-not by the HTTP method. This ensures a download ticket cannot be used for upload
-and vice versa.
-"""
-
-from urllib.parse import quote
-
-from flask import Response, request
-from flask_restx import Resource
-from werkzeug.exceptions import Forbidden, NotFound, RequestEntityTooLarge
-
-from controllers.files import files_ns
-from extensions.ext_storage import storage
-from services.storage_ticket_service import StorageTicketService
-
-
-@files_ns.route("/storage-files/<string:token>")
-class StorageFilesApi(Resource):
-    """Handle file operations through token-based URLs."""
-
-    def get(self, token: str):
-        """Download a file using a token.
-
-        The ticket must have op="download", otherwise returns 403.
-        """
-        ticket = StorageTicketService.get_ticket(token)
-        if ticket is None:
-            raise Forbidden("Invalid or expired token")
-
-        if ticket.op != "download":
-            raise Forbidden("This token is not valid for download")
-
-        try:
-            generator = storage.load_stream(ticket.storage_key)
-        except FileNotFoundError:
-            raise NotFound("File not found")
-
-        filename = ticket.filename or ticket.storage_key.rsplit("/", 1)[-1]
-        encoded_filename = quote(filename)
-
-        return Response(
-            generator,
-            mimetype="application/octet-stream",
-            direct_passthrough=True,
-            headers={
-                "Content-Disposition": f"attachment; filename*=UTF-8''{encoded_filename}",
-            },
-        )
-
-    def put(self, token: str):
-        """Upload a file using a token.
-
-        The ticket must have op="upload", otherwise returns 403.
-        If the request body exceeds max_bytes, returns 413.
-        """
-        ticket = StorageTicketService.get_ticket(token)
-        if ticket is None:
-            raise Forbidden("Invalid or expired token")
-
-        if ticket.op != "upload":
-            raise Forbidden("This token is not valid for upload")
-
-        content = request.get_data()
-
-        if ticket.max_bytes is not None and len(content) > ticket.max_bytes:
-            raise RequestEntityTooLarge(f"Upload exceeds maximum size of {ticket.max_bytes} bytes")
-
-        storage.save(ticket.storage_key, content)
-
-        return Response(status=204)

api/controllers/inner_api/app/dsl.py

@@ -18,8 +18,7 @@ from controllers.inner_api.wraps import enterprise_inner_api_only
 from extensions.ext_database import db
 from models import Account, App
 from models.account import AccountStatus
-from services.app_dsl_service import AppDslService
-from services.entities.dsl_entities import ImportMode, ImportStatus
+from services.app_dsl_service import AppDslService, ImportMode, ImportStatus
 
 
 class InnerAppDSLImportPayload(BaseModel):

api/controllers/inner_api/plugin/wraps.py

@@ -94,9 +94,10 @@ def get_user_tenant[**P, R](view_func: Callable[P, R]) -> Callable[P, R]:
 
 
 def plugin_data[**P, R](
+    view: Callable[P, R] | None = None,
     *,
     payload_type: type[BaseModel],
-) -> Callable[[Callable[P, R]], Callable[P, R]]:
+) -> Callable[P, R] | Callable[[Callable[P, R]], Callable[P, R]]:
     def decorator(view_func: Callable[P, R]) -> Callable[P, R]:
         @wraps(view_func)
         def decorated_view(*args: P.args, **kwargs: P.kwargs) -> R:
@@ -115,4 +116,7 @@ def plugin_data[**P, R](
 
         return decorated_view
 
-    return decorator
+    if view is None:
+        return decorator
+    else:
+        return decorator(view)

api/controllers/service_api/app/annotation.py

@@ -12,12 +12,7 @@ from controllers.service_api.wraps import validate_app_token
 from extensions.ext_redis import redis_client
 from fields.annotation_fields import Annotation, AnnotationList
 from models.model import App
-from services.annotation_service import (
-    AppAnnotationService,
-    EnableAnnotationArgs,
-    InsertAnnotationArgs,
-    UpdateAnnotationArgs,
-)
+from services.annotation_service import AppAnnotationService
 
 
 class AnnotationCreatePayload(BaseModel):
@@ -51,15 +46,10 @@ class AnnotationReplyActionApi(Resource):
     @validate_app_token
     def post(self, app_model: App, action: Literal["enable", "disable"]):
         """Enable or disable annotation reply feature."""
-        payload = AnnotationReplyActionPayload.model_validate(service_api_ns.payload or {})
+        args = AnnotationReplyActionPayload.model_validate(service_api_ns.payload or {}).model_dump()
         match action:
             case "enable":
-                enable_args: EnableAnnotationArgs = {
-                    "score_threshold": payload.score_threshold,
-                    "embedding_provider_name": payload.embedding_provider_name,
-                    "embedding_model_name": payload.embedding_model_name,
-                }
-                result = AppAnnotationService.enable_app_annotation(enable_args, app_model.id)
+                result = AppAnnotationService.enable_app_annotation(args, app_model.id)
             case "disable":
                 result = AppAnnotationService.disable_app_annotation(app_model.id)
         return result, 200
@@ -145,9 +135,8 @@ class AnnotationListApi(Resource):
     @validate_app_token
     def post(self, app_model: App):
         """Create a new annotation."""
-        payload = AnnotationCreatePayload.model_validate(service_api_ns.payload or {})
-        insert_args: InsertAnnotationArgs = {"question": payload.question, "answer": payload.answer}
-        annotation = AppAnnotationService.insert_app_annotation_directly(insert_args, app_model.id)
+        args = AnnotationCreatePayload.model_validate(service_api_ns.payload or {}).model_dump()
+        annotation = AppAnnotationService.insert_app_annotation_directly(args, app_model.id)
         response = Annotation.model_validate(annotation, from_attributes=True)
         return response.model_dump(mode="json"), HTTPStatus.CREATED
 
@@ -175,9 +164,8 @@ class AnnotationUpdateDeleteApi(Resource):
     @edit_permission_required
     def put(self, app_model: App, annotation_id: str):
         """Update an existing annotation."""
-        payload = AnnotationCreatePayload.model_validate(service_api_ns.payload or {})
-        update_args: UpdateAnnotationArgs = {"question": payload.question, "answer": payload.answer}
-        annotation = AppAnnotationService.update_app_annotation_directly(update_args, app_model.id, annotation_id)
+        args = AnnotationCreatePayload.model_validate(service_api_ns.payload or {}).model_dump()
+        annotation = AppAnnotationService.update_app_annotation_directly(args, app_model.id, annotation_id)
         response = Annotation.model_validate(annotation, from_attributes=True)
         return response.model_dump(mode="json")
 

api/controllers/service_api/app/audio.py

@@ -3,10 +3,10 @@ import logging
 from flask import request
 from flask_restx import Resource
 from graphon.model_runtime.errors.invoke import InvokeError
+from pydantic import BaseModel, Field
 from werkzeug.exceptions import InternalServerError
 
 import services
-from controllers.common.controller_schemas import TextToAudioPayload
 from controllers.common.schema import register_schema_model
 from controllers.service_api import service_api_ns
 from controllers.service_api.app.error import (
@@ -86,6 +86,13 @@ class AudioApi(Resource):
             raise InternalServerError()
 
 
+class TextToAudioPayload(BaseModel):
+    message_id: str | None = Field(default=None, description="Message ID")
+    voice: str | None = Field(default=None, description="Voice to use for TTS")
+    text: str | None = Field(default=None, description="Text to convert to audio")
+    streaming: bool | None = Field(default=None, description="Enable streaming response")
+
+
 register_schema_model(service_api_ns, TextToAudioPayload)
 
 

api/controllers/service_api/app/completion.py

@@ -194,7 +194,7 @@ class ChatApi(Resource):
         Supports conversation management and both blocking and streaming response modes.
         """
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         payload = ChatRequestPayload.model_validate(service_api_ns.payload or {})
@@ -258,7 +258,7 @@ class ChatStopApi(Resource):
     def post(self, app_model: App, end_user: EndUser, task_id: str):
         """Stop a running chat message generation."""
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         AppTaskService.stop_task(

api/controllers/service_api/app/conversation.py

@@ -98,7 +98,7 @@ class ConversationApi(Resource):
         Supports pagination using last_id and limit parameters.
         """
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         query_args = ConversationListQuery.model_validate(request.args.to_dict())
@@ -142,7 +142,7 @@ class ConversationDetailApi(Resource):
     def delete(self, app_model: App, end_user: EndUser, c_id):
         """Delete a specific conversation."""
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -171,7 +171,7 @@ class ConversationRenameApi(Resource):
     def post(self, app_model: App, end_user: EndUser, c_id):
         """Rename a conversation or auto-generate a name."""
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -213,7 +213,7 @@ class ConversationVariablesApi(Resource):
         """
         # conversational variable only for chat app
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         conversation_id = str(c_id)
@@ -252,7 +252,7 @@ class ConversationVariableDetailApi(Resource):
         The value must match the variable's expected type.
         """
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         conversation_id = str(c_id)

api/controllers/service_api/app/message.py

@@ -53,7 +53,7 @@ class MessageListApi(Resource):
         Retrieves messages with pagination support using first_id.
         """
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         query_args = MessageListQuery.model_validate(request.args.to_dict())
@@ -158,7 +158,7 @@ class MessageSuggestedApi(Resource):
         """
         message_id = str(message_id)
         app_mode = AppMode.value_of(app_model.mode)
-        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT, AppMode.AGENT}:
+        if app_mode not in {AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT}:
             raise NotChatAppError()
 
         try:

api/controllers/service_api/dataset/document.py

@@ -10,7 +10,6 @@ from sqlalchemy import desc, func, select
 from werkzeug.exceptions import Forbidden, NotFound
 
 import services
-from controllers.common.controller_schemas import DocumentBatchDownloadZipPayload
 from controllers.common.errors import (
     FilenameNotExistsError,
     FileTooLargeError,
@@ -101,6 +100,15 @@ class DocumentListQuery(BaseModel):
     status: str | None = Field(default=None, description="Document status filter")
 
 
+DOCUMENT_BATCH_DOWNLOAD_ZIP_MAX_DOCS = 100
+
+
+class DocumentBatchDownloadZipPayload(BaseModel):
+    """Request payload for bulk downloading uploaded documents as a ZIP archive."""
+
+    document_ids: list[UUID] = Field(..., min_length=1, max_length=DOCUMENT_BATCH_DOWNLOAD_ZIP_MAX_DOCS)
+
+
 register_enum_models(service_api_ns, RetrievalMethod)
 
 register_schema_models(
@@ -519,7 +527,7 @@ class DocumentListApi(DatasetApiResource):
         if not dataset:
             raise NotFound("Dataset not found.")
 
-        query = select(Document).where(Document.dataset_id == dataset_id, Document.tenant_id == tenant_id)
+        query = select(Document).filter_by(dataset_id=str(dataset_id), tenant_id=tenant_id)
 
         if query_params.status:
             query = DocumentService.apply_display_status_filter(query, query_params.status)

api/controllers/service_api/dataset/metadata.py

@@ -2,9 +2,9 @@ from typing import Literal
 
 from flask_login import current_user
 from flask_restx import marshal
+from pydantic import BaseModel
 from werkzeug.exceptions import NotFound
 
-from controllers.common.controller_schemas import MetadataUpdatePayload
 from controllers.common.schema import register_schema_model, register_schema_models
 from controllers.service_api import service_api_ns
 from controllers.service_api.wraps import DatasetApiResource, cloud_edition_billing_rate_limit_check
@@ -18,6 +18,11 @@ from services.entities.knowledge_entities.knowledge_entities import (
 )
 from services.metadata_service import MetadataService
 
+
+class MetadataUpdatePayload(BaseModel):
+    name: str
+
+
 register_schema_model(service_api_ns, MetadataUpdatePayload)
 register_schema_models(
     service_api_ns,

api/controllers/service_api/dataset/segment.py

@@ -8,7 +8,6 @@ from sqlalchemy import select
 from werkzeug.exceptions import NotFound
 
 from configs import dify_config
-from controllers.common.controller_schemas import ChildChunkCreatePayload, ChildChunkUpdatePayload
 from controllers.common.schema import register_schema_models
 from controllers.service_api import service_api_ns
 from controllers.service_api.app.error import ProviderNotInitializeError
@@ -70,12 +69,20 @@ class SegmentUpdatePayload(BaseModel):
     segment: SegmentUpdateArgs
 
 
+class ChildChunkCreatePayload(BaseModel):
+    content: str
+
+
 class ChildChunkListQuery(BaseModel):
     limit: int = Field(default=20, ge=1)
     keyword: str | None = None
     page: int = Field(default=1, ge=1)
 
 
+class ChildChunkUpdatePayload(BaseModel):
+    content: str
+
+
 register_schema_models(
     service_api_ns,
     SegmentCreatePayload,

api/controllers/web/forgot_password.py

@@ -3,6 +3,7 @@ import secrets
 
 from flask import request
 from flask_restx import Resource
+from sqlalchemy.orm import sessionmaker
 
 from controllers.common.schema import register_schema_models
 from controllers.console.auth.error import (
@@ -61,7 +62,9 @@ class ForgotPasswordSendEmailApi(Resource):
         else:
             language = "en-US"
 
-        account = AccountService.get_account_by_email_with_case_fallback(request_email)
+        with sessionmaker(db.engine).begin() as session:
+            account = AccountService.get_account_by_email_with_case_fallback(request_email, session=session)
+        token = None
         if account is None:
             raise AuthenticationFailedError()
         else:
@@ -158,14 +161,13 @@ class ForgotPasswordResetApi(Resource):
 
         email = reset_data.get("email", "")
 
-        account = AccountService.get_account_by_email_with_case_fallback(email)
+        with sessionmaker(db.engine).begin() as session:
+            account = AccountService.get_account_by_email_with_case_fallback(email, session=session)
 
-        if account:
-            account = db.session.merge(account)
-            self._update_existing_account(account, password_hashed, salt)
-            db.session.commit()
-        else:
-            raise AuthenticationFailedError()
+            if account:
+                self._update_existing_account(account, password_hashed, salt)
+            else:
+                raise AuthenticationFailedError()
 
         return {"result": "success"}
 

api/controllers/web/human_input_form.py

@@ -7,8 +7,7 @@ import logging
 from datetime import datetime
 
 from flask import Response, request
-from flask_restx import Resource
-from pydantic import BaseModel
+from flask_restx import Resource, reqparse
 from sqlalchemy import select
 from werkzeug.exceptions import Forbidden
 
@@ -24,12 +23,6 @@ from services.human_input_service import Form, FormNotFoundError, HumanInputServ
 
 logger = logging.getLogger(__name__)
 
-
-class HumanInputFormSubmitPayload(BaseModel):
-    inputs: dict
-    action: str
-
-
 _FORM_SUBMIT_RATE_LIMITER = RateLimiter(
     prefix="web_form_submit_rate_limit",
     max_attempts=dify_config.WEB_FORM_SUBMIT_RATE_LIMIT_MAX_ATTEMPTS,
@@ -119,7 +112,10 @@ class HumanInputFormApi(Resource):
             "action": "Approve"
         }
         """
-        payload = HumanInputFormSubmitPayload.model_validate(request.get_json())
+        parser = reqparse.RequestParser()
+        parser.add_argument("inputs", type=dict, required=True, location="json")
+        parser.add_argument("action", type=str, required=True, location="json")
+        args = parser.parse_args()
 
         ip_address = extract_remote_ip(request)
         if _FORM_SUBMIT_RATE_LIMITER.is_rate_limited(ip_address):
@@ -139,8 +135,8 @@ class HumanInputFormApi(Resource):
             service.submit_form_by_token(
                 recipient_type=recipient_type,
                 form_token=form_token,
-                selected_action_id=payload.action,
-                form_data=payload.inputs,
+                selected_action_id=args["action"],
+                form_data=args["inputs"],
                 submission_end_user_id=None,
                 # submission_end_user_id=_end_user.id,
             )

api/controllers/web/message.py

@@ -3,10 +3,10 @@ from typing import Literal
 
 from flask import request
 from graphon.model_runtime.errors.invoke import InvokeError
-from pydantic import BaseModel, Field, TypeAdapter
+from pydantic import BaseModel, Field, TypeAdapter, field_validator
 from werkzeug.exceptions import InternalServerError, NotFound
 
-from controllers.common.controller_schemas import MessageFeedbackPayload, MessageListQuery
+from controllers.common.controller_schemas import MessageFeedbackPayload
 from controllers.common.schema import register_schema_models
 from controllers.web import web_ns
 from controllers.web.error import (
@@ -25,6 +25,7 @@ from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotIni
 from fields.conversation_fields import ResultResponse
 from fields.message_fields import SuggestedQuestionsResponse, WebMessageInfiniteScrollPagination, WebMessageListItem
 from libs import helper
+from libs.helper import uuid_value
 from models.enums import FeedbackRating
 from models.model import AppMode
 from services.app_generate_service import AppGenerateService
@@ -40,6 +41,19 @@ from services.message_service import MessageService
 logger = logging.getLogger(__name__)
 
 
+class MessageListQuery(BaseModel):
+    conversation_id: str = Field(description="Conversation UUID")
+    first_id: str | None = Field(default=None, description="First message ID for pagination")
+    limit: int = Field(default=20, ge=1, le=100, description="Number of messages to return (1-100)")
+
+    @field_validator("conversation_id", "first_id")
+    @classmethod
+    def validate_uuid(cls, value: str | None) -> str | None:
+        if value is None:
+            return value
+        return uuid_value(value)
+
+
 class MessageMoreLikeThisQuery(BaseModel):
     response_mode: Literal["blocking", "streaming"] = Field(
         description="Response mode",

api/controllers/web/passport.py

@@ -138,15 +138,12 @@ def exchange_token_for_existing_web_user(app_code: str, enterprise_user_decoded:
     if not app_model or app_model.status != "normal" or not app_model.enable_site:
         raise NotFound()
 
-    match auth_type:
-        case WebAppAuthType.PUBLIC:
-            return _exchange_for_public_app_token(app_model, site, enterprise_user_decoded)
-        case WebAppAuthType.EXTERNAL:
-            if user_auth_type != "external":
-                raise WebAppAuthRequiredError("Please login as external user.")
-        case WebAppAuthType.INTERNAL:
-            if user_auth_type != "internal":
-                raise WebAppAuthRequiredError("Please login as internal user.")
+    if auth_type == WebAppAuthType.PUBLIC:
+        return _exchange_for_public_app_token(app_model, site, enterprise_user_decoded)
+    elif auth_type == WebAppAuthType.EXTERNAL and user_auth_type != "external":
+        raise WebAppAuthRequiredError("Please login as external user.")
+    elif auth_type == WebAppAuthType.INTERNAL and user_auth_type != "internal":
+        raise WebAppAuthRequiredError("Please login as internal user.")
 
     end_user = None
     if end_user_id:

api/controllers/web/workflow_events.py

@@ -72,13 +72,12 @@ class WorkflowEventsApi(WebApiResource):
             app_mode = AppMode.value_of(app_model.mode)
             msg_generator = MessageGenerator()
             generator: BaseAppGenerator
-            match app_mode:
-                case AppMode.ADVANCED_CHAT:
-                    generator = AdvancedChatAppGenerator()
-                case AppMode.WORKFLOW:
-                    generator = WorkflowAppGenerator()
-                case _:
-                    raise InvalidArgumentError(f"cannot subscribe to workflow run, workflow_run_id={workflow_run.id}")
+            if app_mode == AppMode.ADVANCED_CHAT:
+                generator = AdvancedChatAppGenerator()
+            elif app_mode == AppMode.WORKFLOW:
+                generator = WorkflowAppGenerator()
+            else:
+                raise InvalidArgumentError(f"cannot subscribe to workflow run, workflow_run_id={workflow_run.id}")
 
             include_state_snapshot = request.args.get("include_state_snapshot", "false").lower() == "true"
 

api/core/agent/agent_app_runner.py

@@ -1,399 +0,0 @@
-import logging
-from collections.abc import Generator
-from copy import deepcopy
-from typing import Any, cast
-
-from core.agent.base_agent_runner import BaseAgentRunner
-from core.agent.entities import AgentEntity, AgentLog, AgentResult, ExecutionContext
-from core.agent.patterns.strategy_factory import StrategyFactory
-from core.app.apps.base_app_queue_manager import PublishFrom
-from core.app.entities.queue_entities import QueueAgentThoughtEvent, QueueMessageEndEvent, QueueMessageFileEvent
-from core.prompt.agent_history_prompt_transform import AgentHistoryPromptTransform
-from core.tools.__base.tool import Tool
-from core.tools.entities.tool_entities import ToolInvokeMeta
-from core.tools.tool_engine import ToolEngine
-from graphon.file import file_manager
-from graphon.model_runtime.entities import (
-    AssistantPromptMessage,
-    LLMResult,
-    LLMResultChunk,
-    LLMUsage,
-    PromptMessage,
-    PromptMessageContentType,
-    SystemPromptMessage,
-    TextPromptMessageContent,
-    UserPromptMessage,
-)
-from graphon.model_runtime.entities.message_entities import ImagePromptMessageContent, PromptMessageContentUnionTypes
-from graphon.model_runtime.entities.model_entities import ModelFeature
-from graphon.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from models.model import Message
-
-logger = logging.getLogger(__name__)
-
-
-class AgentAppRunner(BaseAgentRunner):
-
-    @property
-    def model_features(self) -> list[ModelFeature]:
-        llm_model = cast(LargeLanguageModel, self.model_instance.model_type_instance)
-        model_schema = llm_model.get_model_schema(self.model_instance.model_name, self.model_instance.credentials)
-        if not model_schema:
-            return []
-        return list(model_schema.features or [])
-
-    def build_execution_context(self) -> ExecutionContext:
-        return ExecutionContext(
-            user_id=self.user_id,
-            app_id=self.application_generate_entity.app_config.app_id,
-            conversation_id=self.conversation.id if self.conversation else None,
-            message_id=self.message.id if self.message else None,
-            tenant_id=self.tenant_id,
-        )
-    def _create_tool_invoke_hook(self, message: Message):
-        """
-        Create a tool invoke hook that uses ToolEngine.agent_invoke.
-        This hook handles file creation and returns proper meta information.
-        """
-        # Get trace manager from app generate entity
-        trace_manager = self.application_generate_entity.trace_manager
-
-        def tool_invoke_hook(
-            tool: Tool, tool_args: dict[str, Any], tool_name: str
-        ) -> tuple[str, list[str], ToolInvokeMeta]:
-            """Hook that uses agent_invoke for proper file and meta handling."""
-            tool_invoke_response, message_files, tool_invoke_meta = ToolEngine.agent_invoke(
-                tool=tool,
-                tool_parameters=tool_args,
-                user_id=self.user_id,
-                tenant_id=self.tenant_id,
-                message=message,
-                invoke_from=self.application_generate_entity.invoke_from,
-                agent_tool_callback=self.agent_callback,
-                trace_manager=trace_manager,
-                app_id=self.application_generate_entity.app_config.app_id,
-                message_id=message.id,
-                conversation_id=self.conversation.id,
-            )
-
-            # Publish files and track IDs
-            for message_file_id in message_files:
-                self.queue_manager.publish(
-                    QueueMessageFileEvent(message_file_id=message_file_id),
-                    PublishFrom.APPLICATION_MANAGER,
-                )
-                self._current_message_file_ids.append(message_file_id)
-
-            return tool_invoke_response, message_files, tool_invoke_meta
-
-        return tool_invoke_hook
-
-    def run(self, message: Message, query: str, **kwargs: Any) -> Generator[LLMResultChunk, None, None]:
-        """
-        Run Agent application
-        """
-        self.query = query
-        app_generate_entity = self.application_generate_entity
-
-        app_config = self.app_config
-        assert app_config is not None, "app_config is required"
-        assert app_config.agent is not None, "app_config.agent is required"
-
-        # convert tools into ModelRuntime Tool format
-        tool_instances, _ = self._init_prompt_tools()
-
-        assert app_config.agent
-
-        # Create tool invoke hook for agent_invoke
-        tool_invoke_hook = self._create_tool_invoke_hook(message)
-
-        # Get instruction for ReAct strategy
-        instruction = self.app_config.prompt_template.simple_prompt_template or ""
-
-        # Use factory to create appropriate strategy
-        strategy = StrategyFactory.create_strategy(
-            model_features=self.model_features,
-            model_instance=self.model_instance,
-            tools=list(tool_instances.values()),
-            files=list(self.files),
-            max_iterations=app_config.agent.max_iteration,
-            context=self.build_execution_context(),
-            agent_strategy=self.config.strategy,
-            tool_invoke_hook=tool_invoke_hook,
-            instruction=instruction,
-        )
-
-        # Initialize state variables
-        current_agent_thought_id: str | None = None
-        has_published_thought = False
-        current_tool_name: str | None = None
-        self._current_message_file_ids: list[str] = []
-
-        # organize prompt messages
-        prompt_messages = self._organize_prompt_messages()
-
-        # Run strategy
-        generator = strategy.run(
-            prompt_messages=prompt_messages,
-            model_parameters=app_generate_entity.model_conf.parameters,
-            stop=app_generate_entity.model_conf.stop,
-            stream=True,
-        )
-
-        # Consume generator and collect result
-        result: AgentResult | None = None
-        try:
-            while True:
-                try:
-                    output = next(generator)
-                except StopIteration as e:
-                    # Generator finished, get the return value
-                    result = e.value
-                    break
-
-                if isinstance(output, LLMResultChunk):
-                    # Handle LLM chunk
-                    if current_agent_thought_id and not has_published_thought:
-                        self.queue_manager.publish(
-                            QueueAgentThoughtEvent(agent_thought_id=current_agent_thought_id),
-                            PublishFrom.APPLICATION_MANAGER,
-                        )
-                        has_published_thought = True
-
-                    yield output
-
-                elif isinstance(output, AgentLog):
-                    # Handle Agent Log using log_type for type-safe dispatch
-                    if output.status == AgentLog.LogStatus.START:
-                        if output.log_type == AgentLog.LogType.ROUND:
-                            # Start of a new round
-                            message_file_ids: list[str] = []
-                            current_agent_thought_id = self.create_agent_thought(
-                                message_id=message.id,
-                                message="",
-                                tool_name="",
-                                tool_input="",
-                                messages_ids=message_file_ids,
-                            )
-                            has_published_thought = False
-
-                        elif output.log_type == AgentLog.LogType.TOOL_CALL:
-                            if current_agent_thought_id is None:
-                                continue
-
-                            # Tool call start - extract data from structured fields
-                            current_tool_name = output.data.get("tool_name", "")
-                            tool_input = output.data.get("tool_args", {})
-
-                            self.save_agent_thought(
-                                agent_thought_id=current_agent_thought_id,
-                                tool_name=current_tool_name,
-                                tool_input=tool_input,
-                                thought=None,
-                                observation=None,
-                                tool_invoke_meta=None,
-                                answer=None,
-                                messages_ids=[],
-                            )
-                            self.queue_manager.publish(
-                                QueueAgentThoughtEvent(agent_thought_id=current_agent_thought_id),
-                                PublishFrom.APPLICATION_MANAGER,
-                            )
-
-                    elif output.status == AgentLog.LogStatus.SUCCESS:
-                        if output.log_type == AgentLog.LogType.THOUGHT:
-                            if current_agent_thought_id is None:
-                                continue
-
-                            thought_text = output.data.get("thought")
-                            self.save_agent_thought(
-                                agent_thought_id=current_agent_thought_id,
-                                tool_name=None,
-                                tool_input=None,
-                                thought=thought_text,
-                                observation=None,
-                                tool_invoke_meta=None,
-                                answer=None,
-                                messages_ids=[],
-                            )
-                            self.queue_manager.publish(
-                                QueueAgentThoughtEvent(agent_thought_id=current_agent_thought_id),
-                                PublishFrom.APPLICATION_MANAGER,
-                            )
-
-                        elif output.log_type == AgentLog.LogType.TOOL_CALL:
-                            if current_agent_thought_id is None:
-                                continue
-
-                            # Tool call finished
-                            tool_output = output.data.get("output")
-                            # Get meta from strategy output (now properly populated)
-                            tool_meta = output.data.get("meta")
-
-                            # Wrap tool_meta with tool_name as key (required by agent_service)
-                            if tool_meta and current_tool_name:
-                                tool_meta = {current_tool_name: tool_meta}
-
-                            self.save_agent_thought(
-                                agent_thought_id=current_agent_thought_id,
-                                tool_name=None,
-                                tool_input=None,
-                                thought=None,
-                                observation=tool_output,
-                                tool_invoke_meta=tool_meta,
-                                answer=None,
-                                messages_ids=self._current_message_file_ids,
-                            )
-                            # Clear message file ids after saving
-                            self._current_message_file_ids = []
-                            current_tool_name = None
-
-                            self.queue_manager.publish(
-                                QueueAgentThoughtEvent(agent_thought_id=current_agent_thought_id),
-                                PublishFrom.APPLICATION_MANAGER,
-                            )
-
-                        elif output.log_type == AgentLog.LogType.ROUND:
-                            if current_agent_thought_id is None:
-                                continue
-
-                            # Round finished - save LLM usage and answer
-                            llm_usage = output.metadata.get(AgentLog.LogMetadata.LLM_USAGE)
-                            llm_result = output.data.get("llm_result")
-                            final_answer = output.data.get("final_answer")
-
-                            self.save_agent_thought(
-                                agent_thought_id=current_agent_thought_id,
-                                tool_name=None,
-                                tool_input=None,
-                                thought=llm_result,
-                                observation=None,
-                                tool_invoke_meta=None,
-                                answer=final_answer,
-                                messages_ids=[],
-                                llm_usage=llm_usage,
-                            )
-                            self.queue_manager.publish(
-                                QueueAgentThoughtEvent(agent_thought_id=current_agent_thought_id),
-                                PublishFrom.APPLICATION_MANAGER,
-                            )
-
-        except Exception:
-            # Re-raise any other exceptions
-            raise
-
-        # Process final result
-        if isinstance(result, AgentResult):
-            final_answer = result.text
-            usage = result.usage or LLMUsage.empty_usage()
-
-            # Publish end event
-            self.queue_manager.publish(
-                QueueMessageEndEvent(
-                    llm_result=LLMResult(
-                        model=self.model_instance.model_name,
-                        prompt_messages=prompt_messages,
-                        message=AssistantPromptMessage(content=final_answer),
-                        usage=usage,
-                        system_fingerprint="",
-                    )
-                ),
-                PublishFrom.APPLICATION_MANAGER,
-            )
-
-    def _init_system_message(self, prompt_template: str, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
-        """
-        Initialize system message
-        """
-        if not prompt_template:
-            return prompt_messages or []
-
-        prompt_messages = prompt_messages or []
-
-        if prompt_messages and isinstance(prompt_messages[0], SystemPromptMessage):
-            prompt_messages[0] = SystemPromptMessage(content=prompt_template)
-            return prompt_messages
-
-        if not prompt_messages:
-            return [SystemPromptMessage(content=prompt_template)]
-
-        prompt_messages.insert(0, SystemPromptMessage(content=prompt_template))
-        return prompt_messages
-
-    def _organize_user_query(self, query: str, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
-        """
-        Organize user query
-        """
-        if self.files:
-            # get image detail config
-            image_detail_config = (
-                self.application_generate_entity.file_upload_config.image_config.detail
-                if (
-                    self.application_generate_entity.file_upload_config
-                    and self.application_generate_entity.file_upload_config.image_config
-                )
-                else None
-            )
-            image_detail_config = image_detail_config or ImagePromptMessageContent.DETAIL.LOW
-
-            prompt_message_contents: list[PromptMessageContentUnionTypes] = []
-            for file in self.files:
-                prompt_message_contents.append(
-                    file_manager.to_prompt_message_content(
-                        file,
-                        image_detail_config=image_detail_config,
-                    )
-                )
-            prompt_message_contents.append(TextPromptMessageContent(data=query))
-
-            prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
-        else:
-            prompt_messages.append(UserPromptMessage(content=query))
-
-        return prompt_messages
-
-    def _clear_user_prompt_image_messages(self, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
-        """
-        As for now, gpt supports both fc and vision at the first iteration.
-        We need to remove the image messages from the prompt messages at the first iteration.
-        """
-        prompt_messages = deepcopy(prompt_messages)
-
-        for prompt_message in prompt_messages:
-            if isinstance(prompt_message, UserPromptMessage):
-                if isinstance(prompt_message.content, list):
-                    prompt_message.content = "\n".join(
-                        [
-                            content.data
-                            if content.type == PromptMessageContentType.TEXT
-                            else "[image]"
-                            if content.type == PromptMessageContentType.IMAGE
-                            else "[file]"
-                            for content in prompt_message.content
-                        ]
-                    )
-
-        return prompt_messages
-
-    def _organize_prompt_messages(self):
-        # For ReAct strategy, use the agent prompt template
-        if self.config.strategy == AgentEntity.Strategy.CHAIN_OF_THOUGHT and self.config.prompt:
-            prompt_template = self.config.prompt.first_prompt
-        else:
-            prompt_template = self.app_config.prompt_template.simple_prompt_template or ""
-
-        self.history_prompt_messages = self._init_system_message(prompt_template, self.history_prompt_messages)
-        query_prompt_messages = self._organize_user_query(self.query or "", [])
-
-        self.history_prompt_messages = AgentHistoryPromptTransform(
-            model_config=self.model_config,
-            prompt_messages=[*query_prompt_messages, *self._current_thoughts],
-            history_messages=self.history_prompt_messages,
-            memory=self.memory,
-        ).get_prompt()
-
-        prompt_messages = [*self.history_prompt_messages, *query_prompt_messages, *self._current_thoughts]
-        if len(self._current_thoughts) != 0:
-            # clear messages after the first iteration
-            prompt_messages = self._clear_user_prompt_image_messages(prompt_messages)
-        return prompt_messages

api/core/agent/cot_agent_runner.py

@@ -2,7 +2,7 @@ import json
 import logging
 from abc import ABC, abstractmethod
 from collections.abc import Generator, Mapping, Sequence
-from typing import Any, TypedDict
+from typing import Any
 
 from graphon.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
 from graphon.model_runtime.entities.message_entities import (
@@ -29,13 +29,6 @@ from models.model import Message
 logger = logging.getLogger(__name__)
 
 
-class ActionDict(TypedDict):
-    """Shape produced by AgentScratchpadUnit.Action.to_dict()."""
-
-    action: str
-    action_input: dict[str, Any] | str
-
-
 class CotAgentRunner(BaseAgentRunner, ABC):
     _is_first_iteration = True
     _ignore_observation_providers = ["wenxin"]
@@ -338,7 +331,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
 
         return tool_invoke_response, tool_invoke_meta
 
-    def _convert_dict_to_action(self, action: ActionDict) -> AgentScratchpadUnit.Action:
+    def _convert_dict_to_action(self, action: dict) -> AgentScratchpadUnit.Action:
         """
         convert dict to action
         """

api/core/agent/entities.py

@@ -1,5 +1,3 @@
-import uuid
-from collections.abc import Mapping
 from enum import StrEnum
 from typing import Any, Union
 
@@ -94,79 +92,3 @@ class AgentInvokeMessage(ToolInvokeMessage):
     """
 
     pass
-
-
-class ExecutionContext(BaseModel):
-    """Execution context containing trace and audit information.
-
-    Carries IDs and metadata needed for tracing, auditing, and correlation
-    but not part of the core business logic.
-    """
-
-    user_id: str | None = None
-    app_id: str | None = None
-    conversation_id: str | None = None
-    message_id: str | None = None
-    tenant_id: str | None = None
-
-    @classmethod
-    def create_minimal(cls, user_id: str | None = None) -> "ExecutionContext":
-        return cls(user_id=user_id)
-
-    def to_dict(self) -> dict[str, Any]:
-        return {
-            "user_id": self.user_id,
-            "app_id": self.app_id,
-            "conversation_id": self.conversation_id,
-            "message_id": self.message_id,
-            "tenant_id": self.tenant_id,
-        }
-
-    def with_updates(self, **kwargs) -> "ExecutionContext":
-        data = self.to_dict()
-        data.update(kwargs)
-        return ExecutionContext(**{k: v for k, v in data.items() if k in ExecutionContext.model_fields})
-
-
-class AgentLog(BaseModel):
-    """Structured log entry for agent execution tracing."""
-
-    class LogType(StrEnum):
-        ROUND = "round"
-        THOUGHT = "thought"
-        TOOL_CALL = "tool_call"
-
-    class LogMetadata(StrEnum):
-        STARTED_AT = "started_at"
-        FINISHED_AT = "finished_at"
-        ELAPSED_TIME = "elapsed_time"
-        TOTAL_PRICE = "total_price"
-        TOTAL_TOKENS = "total_tokens"
-        PROVIDER = "provider"
-        CURRENCY = "currency"
-        LLM_USAGE = "llm_usage"
-        ICON = "icon"
-        ICON_DARK = "icon_dark"
-
-    class LogStatus(StrEnum):
-        START = "start"
-        ERROR = "error"
-        SUCCESS = "success"
-
-    id: str = Field(default_factory=lambda: str(uuid.uuid4()))
-    label: str = Field(...)
-    log_type: LogType = Field(...)
-    parent_id: str | None = Field(default=None)
-    error: str | None = Field(default=None)
-    status: LogStatus = Field(...)
-    data: Mapping[str, Any] = Field(...)
-    metadata: Mapping[LogMetadata, Any] = Field(default={})
-
-
-class AgentResult(BaseModel):
-    """Agent execution result."""
-
-    text: str = Field(default="")
-    files: list[Any] = Field(default_factory=list)
-    usage: Any | None = Field(default=None)
-    finish_reason: str | None = Field(default=None)

api/core/agent/patterns/__init__.py

@@ -1,19 +0,0 @@
-"""Agent patterns module.
-
-This module provides different strategies for agent execution:
-- FunctionCallStrategy: Uses native function/tool calling
-- ReActStrategy: Uses ReAct (Reasoning + Acting) approach
-- StrategyFactory: Factory for creating strategies based on model features
-"""
-
-from .base import AgentPattern
-from .function_call import FunctionCallStrategy
-from .react import ReActStrategy
-from .strategy_factory import StrategyFactory
-
-__all__ = [
-    "AgentPattern",
-    "FunctionCallStrategy",
-    "ReActStrategy",
-    "StrategyFactory",
-]

api/core/agent/patterns/base.py

@@ -1,506 +0,0 @@
-"""Base class for agent strategies."""
-
-from __future__ import annotations
-
-import json
-import re
-import time
-from abc import ABC, abstractmethod
-from collections.abc import Callable, Generator
-from typing import TYPE_CHECKING, Any
-
-from core.agent.entities import AgentLog, AgentResult, ExecutionContext
-from core.model_manager import ModelInstance
-from core.tools.entities.tool_entities import ToolInvokeMessage, ToolInvokeMeta
-from graphon.file import File
-from graphon.model_runtime.entities import (
-    AssistantPromptMessage,
-    LLMResult,
-    LLMResultChunk,
-    LLMResultChunkDelta,
-    PromptMessage,
-    PromptMessageTool,
-)
-from graphon.model_runtime.entities.llm_entities import LLMUsage
-from graphon.model_runtime.entities.message_entities import TextPromptMessageContent
-
-if TYPE_CHECKING:
-    from core.tools.__base.tool import Tool
-
-# Type alias for tool invoke hook
-# Returns: (response_content, message_file_ids, tool_invoke_meta)
-ToolInvokeHook = Callable[["Tool", dict[str, Any], str], tuple[str, list[str], ToolInvokeMeta]]
-
-
-class AgentPattern(ABC):
-    """Base class for agent execution strategies."""
-
-    def __init__(
-        self,
-        model_instance: ModelInstance,
-        tools: list[Tool],
-        context: ExecutionContext,
-        max_iterations: int = 10,
-        workflow_call_depth: int = 0,
-        files: list[File] = [],
-        tool_invoke_hook: ToolInvokeHook | None = None,
-    ):
-        """Initialize the agent strategy."""
-        self.model_instance = model_instance
-        self.tools = tools
-        self.context = context
-        self.max_iterations = min(max_iterations, 99)  # Cap at 99 iterations
-        self.workflow_call_depth = workflow_call_depth
-        self.files: list[File] = files
-        self.tool_invoke_hook = tool_invoke_hook
-
-    @abstractmethod
-    def run(
-        self,
-        prompt_messages: list[PromptMessage],
-        model_parameters: dict[str, Any],
-        stop: list[str] = [],
-        stream: bool = True,
-    ) -> Generator[LLMResultChunk | AgentLog, None, AgentResult]:
-        """Execute the agent strategy."""
-        pass
-
-    def _accumulate_usage(self, total_usage: dict[str, Any], delta_usage: LLMUsage) -> None:
-        """Accumulate LLM usage statistics."""
-        if not total_usage.get("usage"):
-            # Create a copy to avoid modifying the original
-            total_usage["usage"] = LLMUsage(
-                prompt_tokens=delta_usage.prompt_tokens,
-                prompt_unit_price=delta_usage.prompt_unit_price,
-                prompt_price_unit=delta_usage.prompt_price_unit,
-                prompt_price=delta_usage.prompt_price,
-                completion_tokens=delta_usage.completion_tokens,
-                completion_unit_price=delta_usage.completion_unit_price,
-                completion_price_unit=delta_usage.completion_price_unit,
-                completion_price=delta_usage.completion_price,
-                total_tokens=delta_usage.total_tokens,
-                total_price=delta_usage.total_price,
-                currency=delta_usage.currency,
-                latency=delta_usage.latency,
-            )
-        else:
-            current: LLMUsage = total_usage["usage"]
-            current.prompt_tokens += delta_usage.prompt_tokens
-            current.completion_tokens += delta_usage.completion_tokens
-            current.total_tokens += delta_usage.total_tokens
-            current.prompt_price += delta_usage.prompt_price
-            current.completion_price += delta_usage.completion_price
-            current.total_price += delta_usage.total_price
-
-    def _extract_content(self, content: Any) -> str:
-        """Extract text content from message content."""
-        if isinstance(content, list):
-            # Content items are PromptMessageContentUnionTypes
-            text_parts = []
-            for c in content:
-                # Check if it's a TextPromptMessageContent (which has data attribute)
-                if isinstance(c, TextPromptMessageContent):
-                    text_parts.append(c.data)
-            return "".join(text_parts)
-        return str(content)
-
-    def _has_tool_calls(self, chunk: LLMResultChunk) -> bool:
-        """Check if chunk contains tool calls."""
-        # LLMResultChunk always has delta attribute
-        return bool(chunk.delta.message and chunk.delta.message.tool_calls)
-
-    def _has_tool_calls_result(self, result: LLMResult) -> bool:
-        """Check if result contains tool calls (non-streaming)."""
-        # LLMResult always has message attribute
-        return bool(result.message and result.message.tool_calls)
-
-    def _extract_tool_calls(self, chunk: LLMResultChunk) -> list[tuple[str, str, dict[str, Any]]]:
-        """Extract tool calls from streaming chunk."""
-        tool_calls: list[tuple[str, str, dict[str, Any]]] = []
-        if chunk.delta.message and chunk.delta.message.tool_calls:
-            for tool_call in chunk.delta.message.tool_calls:
-                if tool_call.function:
-                    try:
-                        args = json.loads(tool_call.function.arguments) if tool_call.function.arguments else {}
-                    except json.JSONDecodeError:
-                        args = {}
-                    tool_calls.append((tool_call.id or "", tool_call.function.name, args))
-        return tool_calls
-
-    def _extract_tool_calls_result(self, result: LLMResult) -> list[tuple[str, str, dict[str, Any]]]:
-        """Extract tool calls from non-streaming result."""
-        tool_calls = []
-        if result.message and result.message.tool_calls:
-            for tool_call in result.message.tool_calls:
-                if tool_call.function:
-                    try:
-                        args = json.loads(tool_call.function.arguments) if tool_call.function.arguments else {}
-                    except json.JSONDecodeError:
-                        args = {}
-                    tool_calls.append((tool_call.id or "", tool_call.function.name, args))
-        return tool_calls
-
-    def _extract_text_from_message(self, message: PromptMessage) -> str:
-        """Extract text content from a prompt message."""
-        # PromptMessage always has content attribute
-        content = message.content
-        if isinstance(content, str):
-            return content
-        elif isinstance(content, list):
-            # Extract text from content list
-            text_parts = []
-            for item in content:
-                if isinstance(item, TextPromptMessageContent):
-                    text_parts.append(item.data)
-            return " ".join(text_parts)
-        return ""
-
-    def _get_tool_metadata(self, tool_instance: Tool) -> dict[AgentLog.LogMetadata, Any]:
-        """Get metadata for a tool including provider and icon info."""
-        from core.tools.tool_manager import ToolManager
-
-        metadata: dict[AgentLog.LogMetadata, Any] = {}
-        if tool_instance.entity and tool_instance.entity.identity:
-            identity = tool_instance.entity.identity
-            if identity.provider:
-                metadata[AgentLog.LogMetadata.PROVIDER] = identity.provider
-
-            # Get icon using ToolManager for proper URL generation
-            tenant_id = self.context.tenant_id
-            if tenant_id and identity.provider:
-                try:
-                    provider_type = tool_instance.tool_provider_type()
-                    icon = ToolManager.get_tool_icon(tenant_id, provider_type, identity.provider)
-                    if isinstance(icon, str):
-                        metadata[AgentLog.LogMetadata.ICON] = icon
-                    elif isinstance(icon, dict):
-                        # Handle icon dict with background/content or light/dark variants
-                        metadata[AgentLog.LogMetadata.ICON] = icon
-                except Exception:
-                    # Fallback to identity.icon if ToolManager fails
-                    if identity.icon:
-                        metadata[AgentLog.LogMetadata.ICON] = identity.icon
-            elif identity.icon:
-                metadata[AgentLog.LogMetadata.ICON] = identity.icon
-        return metadata
-
-    def _create_log(
-        self,
-        label: str,
-        log_type: AgentLog.LogType,
-        status: AgentLog.LogStatus,
-        data: dict[str, Any] | None = None,
-        parent_id: str | None = None,
-        extra_metadata: dict[AgentLog.LogMetadata, Any] | None = None,
-    ) -> AgentLog:
-        """Create a new AgentLog with standard metadata."""
-        metadata: dict[AgentLog.LogMetadata, Any] = {
-            AgentLog.LogMetadata.STARTED_AT: time.perf_counter(),
-        }
-        if extra_metadata:
-            metadata.update(extra_metadata)
-
-        return AgentLog(
-            label=label,
-            log_type=log_type,
-            status=status,
-            data=data or {},
-            parent_id=parent_id,
-            metadata=metadata,
-        )
-
-    def _finish_log(
-        self,
-        log: AgentLog,
-        data: dict[str, Any] | None = None,
-        usage: LLMUsage | None = None,
-    ) -> AgentLog:
-        """Finish an AgentLog by updating its status and metadata."""
-        log.status = AgentLog.LogStatus.SUCCESS
-
-        if data is not None:
-            log.data = data
-
-        # Calculate elapsed time
-        started_at = log.metadata.get(AgentLog.LogMetadata.STARTED_AT, time.perf_counter())
-        finished_at = time.perf_counter()
-
-        # Update metadata
-        log.metadata = {
-            **log.metadata,
-            AgentLog.LogMetadata.FINISHED_AT: finished_at,
-            # Calculate elapsed time in seconds
-            AgentLog.LogMetadata.ELAPSED_TIME: round(finished_at - started_at, 4),
-        }
-
-        # Add usage information if provided
-        if usage:
-            log.metadata.update(
-                {
-                    AgentLog.LogMetadata.TOTAL_PRICE: usage.total_price,
-                    AgentLog.LogMetadata.CURRENCY: usage.currency,
-                    AgentLog.LogMetadata.TOTAL_TOKENS: usage.total_tokens,
-                    AgentLog.LogMetadata.LLM_USAGE: usage,
-                }
-            )
-
-        return log
-
-    def _replace_file_references(self, tool_args: dict[str, Any]) -> dict[str, Any]:
-        """
-        Replace file references in tool arguments with actual File objects.
-
-        Args:
-            tool_args: Dictionary of tool arguments
-
-        Returns:
-            Updated tool arguments with file references replaced
-        """
-        # Process each argument in the dictionary
-        processed_args: dict[str, Any] = {}
-        for key, value in tool_args.items():
-            processed_args[key] = self._process_file_reference(value)
-        return processed_args
-
-    def _process_file_reference(self, data: Any) -> Any:
-        """
-        Recursively process data to replace file references.
-        Supports both single file [File: file_id] and multiple files [Files: file_id1, file_id2, ...].
-
-        Args:
-            data: The data to process (can be dict, list, str, or other types)
-
-        Returns:
-            Processed data with file references replaced
-        """
-        single_file_pattern = re.compile(r"^\[File:\s*([^\]]+)\]$")
-        multiple_files_pattern = re.compile(r"^\[Files:\s*([^\]]+)\]$")
-
-        if isinstance(data, dict):
-            # Process dictionary recursively
-            return {key: self._process_file_reference(value) for key, value in data.items()}
-        elif isinstance(data, list):
-            # Process list recursively
-            return [self._process_file_reference(item) for item in data]
-        elif isinstance(data, str):
-            # Check for single file pattern [File: file_id]
-            single_match = single_file_pattern.match(data.strip())
-            if single_match:
-                file_id = single_match.group(1).strip()
-                # Find the file in self.files
-                for file in self.files:
-                    if file.id and str(file.id) == file_id:
-                        return file
-                # If file not found, return original value
-                return data
-
-            # Check for multiple files pattern [Files: file_id1, file_id2, ...]
-            multiple_match = multiple_files_pattern.match(data.strip())
-            if multiple_match:
-                file_ids_str = multiple_match.group(1).strip()
-                # Split by comma and strip whitespace
-                file_ids = [fid.strip() for fid in file_ids_str.split(",")]
-
-                # Find all matching files
-                matched_files: list[File] = []
-                for file_id in file_ids:
-                    for file in self.files:
-                        if file.id and str(file.id) == file_id:
-                            matched_files.append(file)
-                            break
-
-                # Return list of files if any were found, otherwise return original
-                return matched_files or data
-
-            return data
-        else:
-            # Return other types as-is
-            return data
-
-    def _create_text_chunk(self, text: str, prompt_messages: list[PromptMessage]) -> LLMResultChunk:
-        """Create a text chunk for streaming."""
-        return LLMResultChunk(
-            model=self.model_instance.model_name,
-            prompt_messages=prompt_messages,
-            delta=LLMResultChunkDelta(
-                index=0,
-                message=AssistantPromptMessage(content=text),
-                usage=None,
-            ),
-            system_fingerprint="",
-        )
-
-    def _invoke_tool(
-        self,
-        tool_instance: Tool,
-        tool_args: dict[str, Any],
-        tool_name: str,
-    ) -> tuple[str, list[File], ToolInvokeMeta | None]:
-        """
-        Invoke a tool and collect its response.
-
-        Args:
-            tool_instance: The tool instance to invoke
-            tool_args: Tool arguments
-            tool_name: Name of the tool
-
-        Returns:
-            Tuple of (response_content, tool_files, tool_invoke_meta)
-        """
-        # Process tool_args to replace file references with actual File objects
-        tool_args = self._replace_file_references(tool_args)
-
-        # If a tool invoke hook is set, use it instead of generic_invoke
-        if self.tool_invoke_hook:
-            response_content, _, tool_invoke_meta = self.tool_invoke_hook(tool_instance, tool_args, tool_name)
-            # Note: message_file_ids are stored in DB, we don't convert them to File objects here
-            # The caller (AgentAppRunner) handles file publishing
-            return response_content, [], tool_invoke_meta
-
-        # Default: use generic_invoke for workflow scenarios
-        # Import here to avoid circular import
-        from core.tools.tool_engine import DifyWorkflowCallbackHandler, ToolEngine
-
-        tool_response = ToolEngine.generic_invoke(
-            tool=tool_instance,
-            tool_parameters=tool_args,
-            user_id=self.context.user_id or "",
-            workflow_tool_callback=DifyWorkflowCallbackHandler(),
-            workflow_call_depth=self.workflow_call_depth,
-            app_id=self.context.app_id,
-            conversation_id=self.context.conversation_id,
-            message_id=self.context.message_id,
-        )
-
-        # Collect response and files
-        response_content = ""
-        tool_files: list[File] = []
-
-        for response in tool_response:
-            if response.type == ToolInvokeMessage.MessageType.TEXT:
-                assert isinstance(response.message, ToolInvokeMessage.TextMessage)
-                response_content += response.message.text
-
-            elif response.type == ToolInvokeMessage.MessageType.LINK:
-                # Handle link messages
-                if isinstance(response.message, ToolInvokeMessage.TextMessage):
-                    response_content += f"[Link: {response.message.text}]"
-
-            elif response.type == ToolInvokeMessage.MessageType.IMAGE:
-                # Handle image URL messages
-                if isinstance(response.message, ToolInvokeMessage.TextMessage):
-                    response_content += f"[Image: {response.message.text}]"
-
-            elif response.type == ToolInvokeMessage.MessageType.IMAGE_LINK:
-                # Handle image link messages
-                if isinstance(response.message, ToolInvokeMessage.TextMessage):
-                    response_content += f"[Image: {response.message.text}]"
-
-            elif response.type == ToolInvokeMessage.MessageType.BINARY_LINK:
-                # Handle binary file link messages
-                if isinstance(response.message, ToolInvokeMessage.TextMessage):
-                    filename = response.meta.get("filename", "file") if response.meta else "file"
-                    response_content += f"[File: {filename} - {response.message.text}]"
-
-            elif response.type == ToolInvokeMessage.MessageType.JSON:
-                # Handle JSON messages
-                if isinstance(response.message, ToolInvokeMessage.JsonMessage):
-                    response_content += json.dumps(response.message.json_object, ensure_ascii=False, indent=2)
-
-            elif response.type == ToolInvokeMessage.MessageType.BLOB:
-                # Handle blob messages - convert to text representation
-                if isinstance(response.message, ToolInvokeMessage.BlobMessage):
-                    mime_type = (
-                        response.meta.get("mime_type", "application/octet-stream")
-                        if response.meta
-                        else "application/octet-stream"
-                    )
-                    size = len(response.message.blob)
-                    response_content += f"[Binary data: {mime_type}, size: {size} bytes]"
-
-            elif response.type == ToolInvokeMessage.MessageType.VARIABLE:
-                # Handle variable messages
-                if isinstance(response.message, ToolInvokeMessage.VariableMessage):
-                    var_name = response.message.variable_name
-                    var_value = response.message.variable_value
-                    if isinstance(var_value, str):
-                        response_content += var_value
-                    else:
-                        response_content += f"[Variable {var_name}: {json.dumps(var_value, ensure_ascii=False)}]"
-
-            elif response.type == ToolInvokeMessage.MessageType.BLOB_CHUNK:
-                # Handle blob chunk messages - these are parts of a larger blob
-                if isinstance(response.message, ToolInvokeMessage.BlobChunkMessage):
-                    response_content += f"[Blob chunk {response.message.sequence}: {len(response.message.blob)} bytes]"
-
-            elif response.type == ToolInvokeMessage.MessageType.RETRIEVER_RESOURCES:
-                # Handle retriever resources messages
-                if isinstance(response.message, ToolInvokeMessage.RetrieverResourceMessage):
-                    response_content += response.message.context
-
-            elif response.type == ToolInvokeMessage.MessageType.FILE:
-                # Extract file from meta
-                if response.meta and "file" in response.meta:
-                    file = response.meta["file"]
-                    if isinstance(file, File):
-                        # Check if file is for model or tool output
-                        if response.meta.get("target") == "self":
-                            # File is for model - add to files for next prompt
-                            self.files.append(file)
-                            response_content += f"File '{file.filename}' has been loaded into your context."
-                        else:
-                            # File is tool output
-                            tool_files.append(file)
-
-        return response_content, tool_files, None
-
-    def _validate_tool_args(self, tool_instance: Tool, tool_args: dict[str, Any]) -> str | None:
-        """Validate tool arguments against the tool's required parameters.
-
-        Checks that all required LLM-facing parameters are present and non-empty
-        before actual execution, preventing wasted tool invocations when the model
-        generates calls with missing arguments (e.g. empty ``{}``).
-
-        Returns:
-            Error message if validation fails, None if all required parameters are satisfied.
-        """
-        prompt_tool = tool_instance.to_prompt_message_tool()
-        required_params: list[str] = prompt_tool.parameters.get("required", [])
-
-        if not required_params:
-            return None
-
-        missing = [
-            p
-            for p in required_params
-            if p not in tool_args
-            or tool_args[p] is None
-            or (isinstance(tool_args[p], str) and not tool_args[p].strip())
-        ]
-
-        if not missing:
-            return None
-
-        return (
-            f"Missing required parameter(s): {', '.join(missing)}. "
-            f"Please provide all required parameters before calling this tool."
-        )
-
-    def _find_tool_by_name(self, tool_name: str) -> Tool | None:
-        """Find a tool instance by its name."""
-        for tool in self.tools:
-            if tool.entity.identity.name == tool_name:
-                return tool
-        return None
-
-    def _convert_tools_to_prompt_format(self) -> list[PromptMessageTool]:
-        """Convert tools to prompt message format."""
-        prompt_tools: list[PromptMessageTool] = []
-        for tool in self.tools:
-            prompt_tools.append(tool.to_prompt_message_tool())
-        return prompt_tools
-
-    def _update_usage_with_empty(self, llm_usage: dict[str, Any]) -> None:
-        """Initialize usage tracking with empty usage if not set."""
-        if "usage" not in llm_usage or llm_usage["usage"] is None:
-            llm_usage["usage"] = LLMUsage.empty_usage()

api/core/agent/patterns/function_call.py

@@ -1,358 +0,0 @@
-"""Function Call strategy implementation.
-
-Implements the Function Call agent pattern where the LLM uses native tool-calling
-capability to invoke tools. Includes pre-execution parameter validation that
-intercepts invalid calls (e.g. empty arguments) before they reach tool backends,
-and avoids counting purely-invalid rounds against the iteration budget.
-"""
-
-import json
-import logging
-from collections.abc import Generator
-from typing import Any, Union
-
-from core.agent.entities import AgentLog, AgentResult
-from core.tools.entities.tool_entities import ToolInvokeMeta
-from graphon.file import File
-from graphon.model_runtime.entities import (
-    AssistantPromptMessage,
-    LLMResult,
-    LLMResultChunk,
-    LLMResultChunkDelta,
-    LLMUsage,
-    PromptMessage,
-    PromptMessageTool,
-    ToolPromptMessage,
-)
-
-from .base import AgentPattern
-
-logger = logging.getLogger(__name__)
-
-
-class FunctionCallStrategy(AgentPattern):
-    """Function Call strategy using model's native tool calling capability."""
-
-    def run(
-        self,
-        prompt_messages: list[PromptMessage],
-        model_parameters: dict[str, Any],
-        stop: list[str] = [],
-        stream: bool = True,
-    ) -> Generator[LLMResultChunk | AgentLog, None, AgentResult]:
-        """Execute the function call agent strategy."""
-        # Convert tools to prompt format
-        prompt_tools: list[PromptMessageTool] = self._convert_tools_to_prompt_format()
-
-        # Initialize tracking
-        iteration_step: int = 1
-        max_iterations: int = self.max_iterations + 1
-        function_call_state: bool = True
-        total_usage: dict[str, LLMUsage | None] = {"usage": None}
-        messages: list[PromptMessage] = list(prompt_messages)  # Create mutable copy
-        final_text: str = ""
-        finish_reason: str | None = None
-        output_files: list[File] = []  # Track files produced by tools
-        # Consecutive rounds where ALL tool calls failed parameter validation.
-        # When this happens the round is "free" (iteration_step not incremented)
-        # up to a safety cap to prevent infinite loops.
-        consecutive_validation_failures: int = 0
-        max_validation_retries: int = 3
-
-        while function_call_state and iteration_step <= max_iterations:
-            function_call_state = False
-            round_log = self._create_log(
-                label=f"ROUND {iteration_step}",
-                log_type=AgentLog.LogType.ROUND,
-                status=AgentLog.LogStatus.START,
-                data={},
-            )
-            yield round_log
-            # On last iteration, remove tools to force final answer
-            current_tools: list[PromptMessageTool] = [] if iteration_step == max_iterations else prompt_tools
-            model_log = self._create_log(
-                label=f"{self.model_instance.model_name} Thought",
-                log_type=AgentLog.LogType.THOUGHT,
-                status=AgentLog.LogStatus.START,
-                data={},
-                parent_id=round_log.id,
-                extra_metadata={
-                    AgentLog.LogMetadata.PROVIDER: self.model_instance.provider,
-                },
-            )
-            yield model_log
-
-            # Track usage for this round only
-            round_usage: dict[str, LLMUsage | None] = {"usage": None}
-
-            # Invoke model
-            chunks: Union[Generator[LLMResultChunk, None, None], LLMResult] = self.model_instance.invoke_llm(
-                prompt_messages=messages,
-                model_parameters=model_parameters,
-                tools=current_tools,
-                stop=stop,
-                stream=stream,
-                callbacks=[],
-            )
-
-            # Process response
-            tool_calls, response_content, chunk_finish_reason = yield from self._handle_chunks(
-                chunks, round_usage, model_log
-            )
-            messages.append(self._create_assistant_message(response_content, tool_calls))
-
-            # Accumulate to total usage
-            round_usage_value = round_usage.get("usage")
-            if round_usage_value:
-                self._accumulate_usage(total_usage, round_usage_value)
-
-            # Update final text if no tool calls (this is likely the final answer)
-            if not tool_calls:
-                final_text = response_content
-
-            # Update finish reason
-            if chunk_finish_reason:
-                finish_reason = chunk_finish_reason
-
-            # Process tool calls
-            tool_outputs: dict[str, str] = {}
-            all_validation_errors: bool = True
-            if tool_calls:
-                function_call_state = True
-                # Execute tools (with pre-execution parameter validation)
-                for tool_call_id, tool_name, tool_args in tool_calls:
-                    tool_response, tool_files, _, is_validation_error = yield from self._handle_tool_call(
-                        tool_name, tool_args, tool_call_id, messages, round_log
-                    )
-                    tool_outputs[tool_name] = tool_response
-                    output_files.extend(tool_files)
-                    if not is_validation_error:
-                        all_validation_errors = False
-            else:
-                all_validation_errors = False
-
-            yield self._finish_log(
-                round_log,
-                data={
-                    "llm_result": response_content,
-                    "tool_calls": [
-                        {"name": tc[1], "args": tc[2], "output": tool_outputs.get(tc[1], "")} for tc in tool_calls
-                    ]
-                    if tool_calls
-                    else [],
-                    "final_answer": final_text if not function_call_state else None,
-                },
-                usage=round_usage.get("usage"),
-            )
-
-            # Skip iteration counter when every tool call in this round failed validation,
-            # giving the model a free retry — but cap retries to prevent infinite loops.
-            if tool_calls and all_validation_errors:
-                consecutive_validation_failures += 1
-                if consecutive_validation_failures >= max_validation_retries:
-                    logger.warning(
-                        "Agent hit %d consecutive validation-only rounds, forcing iteration increment",
-                        consecutive_validation_failures,
-                    )
-                    iteration_step += 1
-                    consecutive_validation_failures = 0
-                else:
-                    logger.info(
-                        "All tool calls failed validation (attempt %d/%d), not counting iteration",
-                        consecutive_validation_failures,
-                        max_validation_retries,
-                    )
-            else:
-                consecutive_validation_failures = 0
-                iteration_step += 1
-
-        # Return final result
-        from core.agent.entities import AgentResult
-
-        return AgentResult(
-            text=final_text,
-            files=output_files,
-            usage=total_usage.get("usage") or LLMUsage.empty_usage(),
-            finish_reason=finish_reason,
-        )
-
-    def _handle_chunks(
-        self,
-        chunks: Union[Generator[LLMResultChunk, None, None], LLMResult],
-        llm_usage: dict[str, LLMUsage | None],
-        start_log: AgentLog,
-    ) -> Generator[
-        LLMResultChunk | AgentLog,
-        None,
-        tuple[list[tuple[str, str, dict[str, Any]]], str, str | None],
-    ]:
-        """Handle LLM response chunks and extract tool calls and content.
-
-        Returns a tuple of (tool_calls, response_content, finish_reason).
-        """
-        tool_calls: list[tuple[str, str, dict[str, Any]]] = []
-        response_content: str = ""
-        finish_reason: str | None = None
-        if not isinstance(chunks, LLMResult):
-            # Streaming response
-            for chunk in chunks:
-                # Extract tool calls
-                if self._has_tool_calls(chunk):
-                    tool_calls.extend(self._extract_tool_calls(chunk))
-
-                # Extract content
-                if chunk.delta.message and chunk.delta.message.content:
-                    response_content += self._extract_content(chunk.delta.message.content)
-
-                # Track usage
-                if chunk.delta.usage:
-                    self._accumulate_usage(llm_usage, chunk.delta.usage)
-
-                # Capture finish reason
-                if chunk.delta.finish_reason:
-                    finish_reason = chunk.delta.finish_reason
-
-                yield chunk
-        else:
-            # Non-streaming response
-            result: LLMResult = chunks
-
-            if self._has_tool_calls_result(result):
-                tool_calls.extend(self._extract_tool_calls_result(result))
-
-            if result.message and result.message.content:
-                response_content += self._extract_content(result.message.content)
-
-            if result.usage:
-                self._accumulate_usage(llm_usage, result.usage)
-
-            # Convert to streaming format
-            yield LLMResultChunk(
-                model=result.model,
-                prompt_messages=result.prompt_messages,
-                delta=LLMResultChunkDelta(index=0, message=result.message, usage=result.usage),
-            )
-        yield self._finish_log(
-            start_log,
-            data={
-                "result": response_content,
-            },
-            usage=llm_usage.get("usage"),
-        )
-        return tool_calls, response_content, finish_reason
-
-    def _create_assistant_message(
-        self, content: str, tool_calls: list[tuple[str, str, dict[str, Any]]] | None = None
-    ) -> AssistantPromptMessage:
-        """Create assistant message with tool calls."""
-        if tool_calls is None:
-            return AssistantPromptMessage(content=content)
-        return AssistantPromptMessage(
-            content=content or "",
-            tool_calls=[
-                AssistantPromptMessage.ToolCall(
-                    id=tc[0],
-                    type="function",
-                    function=AssistantPromptMessage.ToolCall.ToolCallFunction(name=tc[1], arguments=json.dumps(tc[2])),
-                )
-                for tc in tool_calls
-            ],
-        )
-
-    def _handle_tool_call(
-        self,
-        tool_name: str,
-        tool_args: dict[str, Any],
-        tool_call_id: str,
-        messages: list[PromptMessage],
-        round_log: AgentLog,
-    ) -> Generator[AgentLog, None, tuple[str, list[File], ToolInvokeMeta | None, bool]]:
-        """Handle a single tool call and return response with files, meta, and validation status.
-
-        Validates required parameters before execution. When validation fails the tool
-        is never invoked — a synthetic error is fed back to the model so it can self-correct
-        without consuming a real iteration.
-
-        Returns:
-            (response_content, tool_files, tool_invoke_meta, is_validation_error).
-            ``is_validation_error`` is True when the call was rejected due to missing
-            required parameters, allowing the caller to skip the iteration counter.
-        """
-        # Find tool
-        tool_instance = self._find_tool_by_name(tool_name)
-        if not tool_instance:
-            raise ValueError(f"Tool {tool_name} not found")
-
-        # Get tool metadata (provider, icon, etc.)
-        tool_metadata = self._get_tool_metadata(tool_instance)
-
-        # Create tool call log
-        tool_call_log = self._create_log(
-            label=f"CALL {tool_name}",
-            log_type=AgentLog.LogType.TOOL_CALL,
-            status=AgentLog.LogStatus.START,
-            data={
-                "tool_call_id": tool_call_id,
-                "tool_name": tool_name,
-                "tool_args": tool_args,
-            },
-            parent_id=round_log.id,
-            extra_metadata=tool_metadata,
-        )
-        yield tool_call_log
-
-        # Validate required parameters before execution to avoid wasted invocations
-        validation_error = self._validate_tool_args(tool_instance, tool_args)
-        if validation_error:
-            tool_call_log.status = AgentLog.LogStatus.ERROR
-            tool_call_log.error = validation_error
-            tool_call_log.data = {**tool_call_log.data, "error": validation_error}
-            yield tool_call_log
-
-            messages.append(ToolPromptMessage(content=validation_error, tool_call_id=tool_call_id, name=tool_name))
-            return validation_error, [], None, True
-
-        # Invoke tool using base class method with error handling
-        try:
-            response_content, tool_files, tool_invoke_meta = self._invoke_tool(tool_instance, tool_args, tool_name)
-
-            yield self._finish_log(
-                tool_call_log,
-                data={
-                    **tool_call_log.data,
-                    "output": response_content,
-                    "files": len(tool_files),
-                    "meta": tool_invoke_meta.to_dict() if tool_invoke_meta else None,
-                },
-            )
-            final_content = response_content or "Tool executed successfully"
-            # Add tool response to messages
-            messages.append(
-                ToolPromptMessage(
-                    content=final_content,
-                    tool_call_id=tool_call_id,
-                    name=tool_name,
-                )
-            )
-            return response_content, tool_files, tool_invoke_meta, False
-        except Exception as e:
-            # Tool invocation failed, yield error log
-            error_message = str(e)
-            tool_call_log.status = AgentLog.LogStatus.ERROR
-            tool_call_log.error = error_message
-            tool_call_log.data = {
-                **tool_call_log.data,
-                "error": error_message,
-            }
-            yield tool_call_log
-
-            # Add error message to conversation
-            error_content = f"Tool execution failed: {error_message}"
-            messages.append(
-                ToolPromptMessage(
-                    content=error_content,
-                    tool_call_id=tool_call_id,
-                    name=tool_name,
-                )
-            )
-            return error_content, [], None, False

api/core/agent/patterns/react.py

@@ -1,418 +0,0 @@
-"""ReAct strategy implementation."""
-
-from __future__ import annotations
-
-import json
-from collections.abc import Generator
-from typing import TYPE_CHECKING, Any, Union
-
-from core.agent.entities import AgentLog, AgentResult, AgentScratchpadUnit, ExecutionContext
-from core.agent.output_parser.cot_output_parser import CotAgentOutputParser
-from core.model_manager import ModelInstance
-from graphon.file import File
-from graphon.model_runtime.entities import (
-    AssistantPromptMessage,
-    LLMResult,
-    LLMResultChunk,
-    LLMResultChunkDelta,
-    PromptMessage,
-    SystemPromptMessage,
-)
-
-from .base import AgentPattern, ToolInvokeHook
-
-if TYPE_CHECKING:
-    from core.tools.__base.tool import Tool
-
-
-class ReActStrategy(AgentPattern):
-    """ReAct strategy using reasoning and acting approach."""
-
-    def __init__(
-        self,
-        model_instance: ModelInstance,
-        tools: list[Tool],
-        context: ExecutionContext,
-        max_iterations: int = 10,
-        workflow_call_depth: int = 0,
-        files: list[File] = [],
-        tool_invoke_hook: ToolInvokeHook | None = None,
-        instruction: str = "",
-    ):
-        """Initialize the ReAct strategy with instruction support."""
-        super().__init__(
-            model_instance=model_instance,
-            tools=tools,
-            context=context,
-            max_iterations=max_iterations,
-            workflow_call_depth=workflow_call_depth,
-            files=files,
-            tool_invoke_hook=tool_invoke_hook,
-        )
-        self.instruction = instruction
-
-    def run(
-        self,
-        prompt_messages: list[PromptMessage],
-        model_parameters: dict[str, Any],
-        stop: list[str] = [],
-        stream: bool = True,
-    ) -> Generator[LLMResultChunk | AgentLog, None, AgentResult]:
-        """Execute the ReAct agent strategy."""
-        # Initialize tracking
-        agent_scratchpad: list[AgentScratchpadUnit] = []
-        iteration_step: int = 1
-        max_iterations: int = self.max_iterations + 1
-        react_state: bool = True
-        total_usage: dict[str, Any] = {"usage": None}
-        output_files: list[File] = []  # Track files produced by tools
-        final_text: str = ""
-        finish_reason: str | None = None
-
-        # Add "Observation" to stop sequences
-        if "Observation" not in stop:
-            stop = stop.copy()
-            stop.append("Observation")
-
-        while react_state and iteration_step <= max_iterations:
-            react_state = False
-            round_log = self._create_log(
-                label=f"ROUND {iteration_step}",
-                log_type=AgentLog.LogType.ROUND,
-                status=AgentLog.LogStatus.START,
-                data={},
-            )
-            yield round_log
-
-            # Build prompt with/without tools based on iteration
-            include_tools = iteration_step < max_iterations
-            current_messages = self._build_prompt_with_react_format(
-                prompt_messages, agent_scratchpad, include_tools, self.instruction
-            )
-
-            model_log = self._create_log(
-                label=f"{self.model_instance.model_name} Thought",
-                log_type=AgentLog.LogType.THOUGHT,
-                status=AgentLog.LogStatus.START,
-                data={},
-                parent_id=round_log.id,
-                extra_metadata={
-                    AgentLog.LogMetadata.PROVIDER: self.model_instance.provider,
-                },
-            )
-            yield model_log
-
-            # Track usage for this round only
-            round_usage: dict[str, Any] = {"usage": None}
-
-            # Use current messages directly (files are handled by base class if needed)
-            messages_to_use = current_messages
-
-            # Invoke model
-            chunks: Union[Generator[LLMResultChunk, None, None], LLMResult] = self.model_instance.invoke_llm(
-                prompt_messages=messages_to_use,
-                model_parameters=model_parameters,
-                stop=stop,
-                stream=stream,
-                callbacks=[],
-            )
-
-            # Process response
-            scratchpad, chunk_finish_reason = yield from self._handle_chunks(
-                chunks, round_usage, model_log, current_messages
-            )
-            agent_scratchpad.append(scratchpad)
-
-            # Accumulate to total usage
-            round_usage_value = round_usage.get("usage")
-            if round_usage_value:
-                self._accumulate_usage(total_usage, round_usage_value)
-
-            # Update finish reason
-            if chunk_finish_reason:
-                finish_reason = chunk_finish_reason
-
-            # Check if we have an action to execute
-            if scratchpad.action and scratchpad.action.action_name.lower() != "final answer":
-                react_state = True
-                # Execute tool
-                observation, tool_files = yield from self._handle_tool_call(
-                    scratchpad.action, current_messages, round_log
-                )
-                scratchpad.observation = observation
-                # Track files produced by tools
-                output_files.extend(tool_files)
-
-                # Add observation to scratchpad for display
-                yield self._create_text_chunk(f"\nObservation: {observation}\n", current_messages)
-            else:
-                # Extract final answer
-                if scratchpad.action and scratchpad.action.action_input:
-                    final_answer = scratchpad.action.action_input
-                    if isinstance(final_answer, dict):
-                        final_answer = json.dumps(final_answer, ensure_ascii=False)
-                    final_text = str(final_answer)
-                elif scratchpad.thought:
-                    # If no action but we have thought, use thought as final answer
-                    final_text = scratchpad.thought
-
-            yield self._finish_log(
-                round_log,
-                data={
-                    "thought": scratchpad.thought,
-                    "action": scratchpad.action_str if scratchpad.action else None,
-                    "observation": scratchpad.observation or None,
-                    "final_answer": final_text if not react_state else None,
-                },
-                usage=round_usage.get("usage"),
-            )
-            iteration_step += 1
-
-        # Return final result
-
-        from core.agent.entities import AgentResult
-
-        return AgentResult(
-            text=final_text, files=output_files, usage=total_usage.get("usage"), finish_reason=finish_reason
-        )
-
-    def _build_prompt_with_react_format(
-        self,
-        original_messages: list[PromptMessage],
-        agent_scratchpad: list[AgentScratchpadUnit],
-        include_tools: bool = True,
-        instruction: str = "",
-    ) -> list[PromptMessage]:
-        """Build prompt messages with ReAct format."""
-        # Copy messages to avoid modifying original
-        messages = list(original_messages)
-
-        # Find and update the system prompt that should already exist
-        system_prompt_found = False
-        for i, msg in enumerate(messages):
-            if isinstance(msg, SystemPromptMessage):
-                system_prompt_found = True
-                # The system prompt from frontend already has the template, just replace placeholders
-
-                # Format tools
-                tools_str = ""
-                tool_names = []
-                if include_tools and self.tools:
-                    # Convert tools to prompt message tools format
-                    prompt_tools = [tool.to_prompt_message_tool() for tool in self.tools]
-                    tool_names = [tool.name for tool in prompt_tools]
-
-                    # Format tools as JSON for comprehensive information
-                    from graphon.model_runtime.utils.encoders import jsonable_encoder
-
-                    tools_str = json.dumps(jsonable_encoder(prompt_tools), indent=2)
-                    tool_names_str = ", ".join(f'"{name}"' for name in tool_names)
-                else:
-                    tools_str = "No tools available"
-                    tool_names_str = ""
-
-                # Replace placeholders in the existing system prompt
-                updated_content = msg.content
-                assert isinstance(updated_content, str)
-                updated_content = updated_content.replace("{{instruction}}", instruction)
-                updated_content = updated_content.replace("{{tools}}", tools_str)
-                updated_content = updated_content.replace("{{tool_names}}", tool_names_str)
-
-                # Create new SystemPromptMessage with updated content
-                messages[i] = SystemPromptMessage(content=updated_content)
-                break
-
-        # If no system prompt found, that's unexpected but add scratchpad anyway
-        if not system_prompt_found:
-            # This shouldn't happen if frontend is working correctly
-            pass
-
-        # Format agent scratchpad
-        scratchpad_str = ""
-        if agent_scratchpad:
-            scratchpad_parts: list[str] = []
-            for unit in agent_scratchpad:
-                if unit.thought:
-                    scratchpad_parts.append(f"Thought: {unit.thought}")
-                if unit.action_str:
-                    scratchpad_parts.append(f"Action:\n```\n{unit.action_str}\n```")
-                if unit.observation:
-                    scratchpad_parts.append(f"Observation: {unit.observation}")
-            scratchpad_str = "\n".join(scratchpad_parts)
-
-        # If there's a scratchpad, append it to the last message
-        if scratchpad_str:
-            messages.append(AssistantPromptMessage(content=scratchpad_str))
-
-        return messages
-
-    def _handle_chunks(
-        self,
-        chunks: Union[Generator[LLMResultChunk, None, None], LLMResult],
-        llm_usage: dict[str, Any],
-        model_log: AgentLog,
-        current_messages: list[PromptMessage],
-    ) -> Generator[
-        LLMResultChunk | AgentLog,
-        None,
-        tuple[AgentScratchpadUnit, str | None],
-    ]:
-        """Handle LLM response chunks and extract action/thought.
-
-        Returns a tuple of (scratchpad_unit, finish_reason).
-        """
-        usage_dict: dict[str, Any] = {}
-
-        # Convert non-streaming to streaming format if needed
-        if isinstance(chunks, LLMResult):
-            result = chunks
-
-            def result_to_chunks() -> Generator[LLMResultChunk, None, None]:
-                yield LLMResultChunk(
-                    model=result.model,
-                    prompt_messages=result.prompt_messages,
-                    delta=LLMResultChunkDelta(
-                        index=0,
-                        message=result.message,
-                        usage=result.usage,
-                        finish_reason=None,
-                    ),
-                    system_fingerprint=result.system_fingerprint or "",
-                )
-
-            streaming_chunks = result_to_chunks()
-        else:
-            streaming_chunks = chunks
-
-        react_chunks = CotAgentOutputParser.handle_react_stream_output(streaming_chunks, usage_dict)
-
-        # Initialize scratchpad unit
-        scratchpad = AgentScratchpadUnit(
-            agent_response="",
-            thought="",
-            action_str="",
-            observation="",
-            action=None,
-        )
-
-        finish_reason: str | None = None
-
-        # Process chunks
-        for chunk in react_chunks:
-            if isinstance(chunk, AgentScratchpadUnit.Action):
-                # Action detected
-                action_str = json.dumps(chunk.model_dump())
-                scratchpad.agent_response = (scratchpad.agent_response or "") + action_str
-                scratchpad.action_str = action_str
-                scratchpad.action = chunk
-
-                yield self._create_text_chunk(json.dumps(chunk.model_dump()), current_messages)
-            else:
-                # Text chunk
-                chunk_text = str(chunk)
-                scratchpad.agent_response = (scratchpad.agent_response or "") + chunk_text
-                scratchpad.thought = (scratchpad.thought or "") + chunk_text
-
-                yield self._create_text_chunk(chunk_text, current_messages)
-
-        # Update usage
-        if usage_dict.get("usage"):
-            if llm_usage.get("usage"):
-                self._accumulate_usage(llm_usage, usage_dict["usage"])
-            else:
-                llm_usage["usage"] = usage_dict["usage"]
-
-        # Clean up thought
-        scratchpad.thought = (scratchpad.thought or "").strip() or "I am thinking about how to help you"
-
-        # Finish model log
-        yield self._finish_log(
-            model_log,
-            data={
-                "thought": scratchpad.thought,
-                "action": scratchpad.action_str if scratchpad.action else None,
-            },
-            usage=llm_usage.get("usage"),
-        )
-
-        return scratchpad, finish_reason
-
-    def _handle_tool_call(
-        self,
-        action: AgentScratchpadUnit.Action,
-        prompt_messages: list[PromptMessage],
-        round_log: AgentLog,
-    ) -> Generator[AgentLog, None, tuple[str, list[File]]]:
-        """Handle tool call and return observation with files."""
-        tool_name = action.action_name
-        tool_args: dict[str, Any] | str = action.action_input
-
-        # Find tool instance first to get metadata
-        tool_instance = self._find_tool_by_name(tool_name)
-        tool_metadata = self._get_tool_metadata(tool_instance) if tool_instance else {}
-
-        # Start tool log with tool metadata
-        tool_log = self._create_log(
-            label=f"CALL {tool_name}",
-            log_type=AgentLog.LogType.TOOL_CALL,
-            status=AgentLog.LogStatus.START,
-            data={
-                "tool_name": tool_name,
-                "tool_args": tool_args,
-            },
-            parent_id=round_log.id,
-            extra_metadata=tool_metadata,
-        )
-        yield tool_log
-
-        if not tool_instance:
-            # Finish tool log with error
-            yield self._finish_log(
-                tool_log,
-                data={
-                    **tool_log.data,
-                    "error": f"Tool {tool_name} not found",
-                },
-            )
-            return f"Tool {tool_name} not found", []
-
-        # Ensure tool_args is a dict
-        tool_args_dict: dict[str, Any]
-        if isinstance(tool_args, str):
-            try:
-                tool_args_dict = json.loads(tool_args)
-            except json.JSONDecodeError:
-                tool_args_dict = {"input": tool_args}
-        elif not isinstance(tool_args, dict):
-            tool_args_dict = {"input": str(tool_args)}
-        else:
-            tool_args_dict = tool_args
-
-        # Invoke tool using base class method with error handling
-        try:
-            response_content, tool_files, tool_invoke_meta = self._invoke_tool(tool_instance, tool_args_dict, tool_name)
-
-            # Finish tool log
-            yield self._finish_log(
-                tool_log,
-                data={
-                    **tool_log.data,
-                    "output": response_content,
-                    "files": len(tool_files),
-                    "meta": tool_invoke_meta.to_dict() if tool_invoke_meta else None,
-                },
-            )
-
-            return response_content or "Tool executed successfully", tool_files
-        except Exception as e:
-            # Tool invocation failed, yield error log
-            error_message = str(e)
-            tool_log.status = AgentLog.LogStatus.ERROR
-            tool_log.error = error_message
-            tool_log.data = {
-                **tool_log.data,
-                "error": error_message,
-            }
-            yield tool_log
-
-            return f"Tool execution failed: {error_message}", []

api/core/agent/patterns/strategy_factory.py

@@ -1,108 +0,0 @@
-"""Strategy factory for creating agent strategies."""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-from core.agent.entities import AgentEntity, ExecutionContext
-from core.model_manager import ModelInstance
-from graphon.file.models import File
-from graphon.model_runtime.entities.model_entities import ModelFeature
-
-from .base import AgentPattern, ToolInvokeHook
-from .function_call import FunctionCallStrategy
-from .react import ReActStrategy
-
-if TYPE_CHECKING:
-    from core.tools.__base.tool import Tool
-
-
-class StrategyFactory:
-    """Factory for creating agent strategies based on model features."""
-
-    # Tool calling related features
-    TOOL_CALL_FEATURES = {ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL, ModelFeature.STREAM_TOOL_CALL}
-
-    @staticmethod
-    def create_strategy(
-        model_features: list[ModelFeature],
-        model_instance: ModelInstance,
-        context: ExecutionContext,
-        tools: list[Tool],
-        files: list[File],
-        max_iterations: int = 10,
-        workflow_call_depth: int = 0,
-        agent_strategy: AgentEntity.Strategy | None = None,
-        tool_invoke_hook: ToolInvokeHook | None = None,
-        instruction: str = "",
-    ) -> AgentPattern:
-        """
-        Create an appropriate strategy based on model features.
-
-        Args:
-            model_features: List of model features/capabilities
-            model_instance: Model instance to use
-            context: Execution context containing trace/audit information
-            tools: Available tools
-            files: Available files
-            max_iterations: Maximum iterations for the strategy
-            workflow_call_depth: Depth of workflow calls
-            agent_strategy: Optional explicit strategy override
-            tool_invoke_hook: Optional hook for custom tool invocation (e.g., agent_invoke)
-            instruction: Optional instruction for ReAct strategy
-
-        Returns:
-            AgentStrategy instance
-        """
-
-        # If explicit strategy is provided and it's Function Calling, try to use it if supported
-        if agent_strategy == AgentEntity.Strategy.FUNCTION_CALLING:
-            if set(model_features) & StrategyFactory.TOOL_CALL_FEATURES:
-                return FunctionCallStrategy(
-                    model_instance=model_instance,
-                    context=context,
-                    tools=tools,
-                    files=files,
-                    max_iterations=max_iterations,
-                    workflow_call_depth=workflow_call_depth,
-                    tool_invoke_hook=tool_invoke_hook,
-                )
-            # Fallback to ReAct if FC is requested but not supported
-
-        # If explicit strategy is Chain of Thought (ReAct)
-        if agent_strategy == AgentEntity.Strategy.CHAIN_OF_THOUGHT:
-            return ReActStrategy(
-                model_instance=model_instance,
-                context=context,
-                tools=tools,
-                files=files,
-                max_iterations=max_iterations,
-                workflow_call_depth=workflow_call_depth,
-                tool_invoke_hook=tool_invoke_hook,
-                instruction=instruction,
-            )
-
-        # Default auto-selection logic
-        if set(model_features) & StrategyFactory.TOOL_CALL_FEATURES:
-            # Model supports native function calling
-            return FunctionCallStrategy(
-                model_instance=model_instance,
-                context=context,
-                tools=tools,
-                files=files,
-                max_iterations=max_iterations,
-                workflow_call_depth=workflow_call_depth,
-                tool_invoke_hook=tool_invoke_hook,
-            )
-        else:
-            # Use ReAct strategy for models without function calling
-            return ReActStrategy(
-                model_instance=model_instance,
-                context=context,
-                tools=tools,
-                files=files,
-                max_iterations=max_iterations,
-                workflow_call_depth=workflow_call_depth,
-                tool_invoke_hook=tool_invoke_hook,
-                instruction=instruction,
-            )

api/core/app/apps/advanced_chat/app_generator.py

@@ -177,14 +177,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 # always enable retriever resource in debugger mode
                 app_config.additional_features.show_retrieve_source = True  # type: ignore
 
-            # Resolve parent_message_id for thread continuity
-            if invoke_from == InvokeFrom.SERVICE_API:
-                parent_message_id: str | None = UUID_NIL
-            else:
-                parent_message_id = args.get("parent_message_id")
-                if not parent_message_id and conversation:
-                    parent_message_id = self._resolve_latest_message_id(conversation.id)
-
             # init application generate entity
             application_generate_entity = AdvancedChatAppGenerateEntity(
                 task_id=str(uuid.uuid4()),
@@ -196,7 +188,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 ),
                 query=query,
                 files=list(file_objs),
-                parent_message_id=parent_message_id,
+                parent_message_id=args.get("parent_message_id") if invoke_from != InvokeFrom.SERVICE_API else UUID_NIL,
                 user_id=user.id,
                 stream=streaming,
                 invoke_from=invoke_from,
@@ -697,17 +689,3 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             else:
                 logger.exception("Failed to process generate task pipeline, conversation_id: %s", conversation.id)
                 raise e
-
-    @staticmethod
-    def _resolve_latest_message_id(conversation_id: str) -> str | None:
-        """Auto-resolve parent_message_id to the latest message when client doesn't provide one."""
-        from sqlalchemy import select
-
-        stmt = (
-            select(Message.id)
-            .where(Message.conversation_id == conversation_id)
-            .order_by(Message.created_at.desc())
-            .limit(1)
-        )
-        latest_id = db.session.scalar(stmt)
-        return str(latest_id) if latest_id else None

api/core/app/apps/advanced_chat/app_runner.py

@@ -10,7 +10,7 @@ from graphon.runtime import GraphRuntimeState, VariablePool
 from graphon.variable_loader import VariableLoader
 from graphon.variables.variables import Variable
 from sqlalchemy import select
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import Session
 
 from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfig
 from core.app.apps.base_app_queue_manager import AppQueueManager
@@ -363,7 +363,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
 
         :return: List of conversation variables ready for use
         """
-        with sessionmaker(bind=db.engine).begin() as session:
+        with Session(db.engine) as session:
             existing_variables = self._load_existing_conversation_variables(session)
 
             if not existing_variables:
@@ -376,6 +376,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
             # Convert to Variable objects for use in the workflow
             conversation_variables = [var.to_variable() for var in existing_variables]
 
+            session.commit()
             return cast(list[Variable], conversation_variables)
 
     def _load_existing_conversation_variables(self, session: Session) -> list[ConversationVariable]:

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -16,7 +16,7 @@ from graphon.model_runtime.utils.encoders import jsonable_encoder
 from graphon.nodes import BuiltinNodeTypes
 from graphon.runtime import GraphRuntimeState
 from sqlalchemy import select
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
@@ -328,8 +328,13 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
     @contextmanager
     def _database_session(self):
         """Context manager for database sessions."""
-        with sessionmaker(bind=db.engine, expire_on_commit=False).begin() as session:
-            yield session
+        with Session(db.engine, expire_on_commit=False) as session:
+            try:
+                yield session
+                session.commit()
+            except Exception:
+                session.rollback()
+                raise
 
     def _ensure_workflow_initialized(self):
         """Fluent validation for workflow state."""

api/core/app/apps/agent_chat/app_runner.py

@@ -1,12 +1,15 @@
 import logging
 from typing import cast
 
-from graphon.model_runtime.entities.model_entities import ModelFeature
+from graphon.model_runtime.entities.llm_entities import LLMMode
+from graphon.model_runtime.entities.model_entities import ModelFeature, ModelPropertyKey
 from graphon.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from sqlalchemy import select
 
-from core.agent.agent_app_runner import AgentAppRunner
+from core.agent.cot_chat_agent_runner import CotChatAgentRunner
+from core.agent.cot_completion_agent_runner import CotCompletionAgentRunner
 from core.agent.entities import AgentEntity
+from core.agent.fc_agent_runner import FunctionCallAgentRunner
 from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfig
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
 from core.app.apps.base_app_runner import AppRunner
@@ -189,8 +192,24 @@ class AgentChatAppRunner(AppRunner):
         message_result = db.session.scalar(msg_stmt)
         if message_result is None:
             raise ValueError("Message not found")
+        db.session.close()
 
-        runner = AgentAppRunner(
+        runner_cls: type[FunctionCallAgentRunner] | type[CotChatAgentRunner] | type[CotCompletionAgentRunner]
+        # start agent runner
+        if agent_entity.strategy == AgentEntity.Strategy.CHAIN_OF_THOUGHT:
+            # check LLM mode
+            if model_schema.model_properties.get(ModelPropertyKey.MODE) == LLMMode.CHAT:
+                runner_cls = CotChatAgentRunner
+            elif model_schema.model_properties.get(ModelPropertyKey.MODE) == LLMMode.COMPLETION:
+                runner_cls = CotCompletionAgentRunner
+            else:
+                raise ValueError(f"Invalid LLM mode: {model_schema.model_properties.get(ModelPropertyKey.MODE)}")
+        elif agent_entity.strategy == AgentEntity.Strategy.FUNCTION_CALLING:
+            runner_cls = FunctionCallAgentRunner
+        else:
+            raise ValueError(f"Invalid agent strategy: {agent_entity.strategy}")
+
+        runner = runner_cls(
             tenant_id=app_config.tenant_id,
             application_generate_entity=application_generate_entity,
             conversation=conversation_result,

api/core/app/apps/common/legacy_response_adapter.py

@@ -1,53 +0,0 @@
-"""Legacy Response Adapter for transparent upgrade.
-
-When old apps (chat/completion/agent-chat) run through the Agent V2
-workflow engine via transparent upgrade, the SSE events are in workflow
-format (workflow_started, node_started, etc.). This adapter filters out
-workflow-specific events and passes through only the events that old
-clients expect (message, message_end, etc.).
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-from collections.abc import Generator
-
-logger = logging.getLogger(__name__)
-
-WORKFLOW_ONLY_EVENTS = frozenset({
-    "workflow_started",
-    "workflow_finished",
-    "node_started",
-    "node_finished",
-    "iteration_started",
-    "iteration_next",
-    "iteration_completed",
-})
-
-
-def adapt_workflow_stream_for_legacy(
-    stream: Generator[str, None, None],
-) -> Generator[str, None, None]:
-    """Filter workflow-specific SSE events from a streaming response.
-
-    Passes through message, message_end, agent_log, error, ping events.
-    Suppresses workflow_started, workflow_finished, node_started, node_finished.
-
-    This makes the SSE stream look more like what old easy-UI apps produce,
-    while still carrying the actual LLM response content.
-    """
-    for chunk in stream:
-        if not chunk or not chunk.strip():
-            yield chunk
-            continue
-
-        try:
-            if chunk.startswith("data: "):
-                data = json.loads(chunk[6:])
-                event = data.get("event", "")
-                if event in WORKFLOW_ONLY_EVENTS:
-                    continue
-            yield chunk
-        except (json.JSONDecodeError, TypeError):
-            yield chunk

api/core/app/apps/pipeline/pipeline_runner.py

@@ -2,6 +2,7 @@ import logging
 import time
 from typing import cast
 
+from graphon.entities import GraphInitParams
 from graphon.enums import WorkflowType
 from graphon.graph import Graph
 from graphon.graph_events import GraphEngineEvent, GraphRunFailedEvent
@@ -21,7 +22,7 @@ from core.app.entities.app_invoke_entities import (
 )
 from core.app.workflow.layers.persistence import PersistenceWorkflowInfo, WorkflowPersistenceLayer
 from core.repositories.factory import WorkflowExecutionRepository, WorkflowNodeExecutionRepository
-from core.workflow.node_factory import DifyGraphInitContext, DifyNodeFactory, get_default_root_node_id
+from core.workflow.node_factory import DifyNodeFactory, get_default_root_node_id
 from core.workflow.system_variables import build_bootstrap_variables, build_system_variables
 from core.workflow.variable_pool_initializer import add_node_inputs_to_pool, add_variables_to_pool
 from core.workflow.workflow_entry import WorkflowEntry
@@ -264,23 +265,22 @@ class PipelineRunner(WorkflowBasedAppRunner):
         # graph_config["nodes"] = real_run_nodes
         # graph_config["edges"] = real_edges
         # init graph
-        # Create explicit graph init context for Graph.init.
-        run_context = build_dify_run_context(
-            tenant_id=workflow.tenant_id,
-            app_id=self._app_id,
-            user_id=self.application_generate_entity.user_id,
-            user_from=user_from,
-            invoke_from=invoke_from,
-        )
-        graph_init_context = DifyGraphInitContext(
+        # Create required parameters for Graph.init
+        graph_init_params = GraphInitParams(
             workflow_id=workflow.id,
             graph_config=graph_config,
-            run_context=run_context,
+            run_context=build_dify_run_context(
+                tenant_id=workflow.tenant_id,
+                app_id=self._app_id,
+                user_id=self.application_generate_entity.user_id,
+                user_from=user_from,
+                invoke_from=invoke_from,
+            ),
             call_depth=0,
         )
 
-        node_factory = DifyNodeFactory.from_graph_init_context(
-            graph_init_context=graph_init_context,
+        node_factory = DifyNodeFactory(
+            graph_init_params=graph_init_params,
             graph_runtime_state=graph_runtime_state,
         )
         if start_node_id is None:

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -7,7 +7,7 @@ from typing import Union
 from graphon.entities import WorkflowStartReason
 from graphon.enums import WorkflowExecutionStatus
 from graphon.runtime import GraphRuntimeState
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
 from core.app.apps.base_app_queue_manager import AppQueueManager
@@ -252,8 +252,13 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
     @contextmanager
     def _database_session(self):
         """Context manager for database sessions."""
-        with sessionmaker(bind=db.engine, expire_on_commit=False).begin() as session:
-            yield session
+        with Session(db.engine, expire_on_commit=False) as session:
+            try:
+                yield session
+                session.commit()
+            except Exception:
+                session.rollback()
+                raise
 
     def _ensure_workflow_initialized(self):
         """Fluent validation for workflow state."""

api/core/app/apps/workflow_app_runner.py

@@ -3,6 +3,7 @@ import time
 from collections.abc import Mapping, Sequence
 from typing import Any, cast
 
+from graphon.entities import GraphInitParams
 from graphon.entities.graph_config import NodeConfigDictAdapter
 from graphon.entities.pause_reason import HumanInputRequired
 from graphon.graph import Graph
@@ -66,12 +67,7 @@ from core.app.entities.queue_entities import (
     QueueWorkflowSucceededEvent,
 )
 from core.rag.entities import RetrievalSourceMetadata
-from core.workflow.node_factory import (
-    DifyGraphInitContext,
-    DifyNodeFactory,
-    get_default_root_node_id,
-    resolve_workflow_node_class,
-)
+from core.workflow.node_factory import DifyNodeFactory, get_default_root_node_id, resolve_workflow_node_class
 from core.workflow.system_variables import (
     build_bootstrap_variables,
     default_system_variables,
@@ -131,23 +127,24 @@ class WorkflowBasedAppRunner:
         if not isinstance(graph_config.get("edges"), list):
             raise ValueError("edges in workflow graph must be a list")
 
-        # Create explicit graph init context for Graph.init.
-        run_context = build_dify_run_context(
-            tenant_id=tenant_id or "",
-            app_id=self._app_id,
-            user_id=user_id,
-            user_from=user_from,
-            invoke_from=invoke_from,
-        )
-        graph_init_context = DifyGraphInitContext(
+        # Create required parameters for Graph.init
+        graph_init_params = GraphInitParams(
             workflow_id=workflow_id,
             graph_config=graph_config,
-            run_context=run_context,
+            run_context=build_dify_run_context(
+                tenant_id=tenant_id or "",
+                app_id=self._app_id,
+                user_id=user_id,
+                user_from=user_from,
+                invoke_from=invoke_from,
+            ),
             call_depth=0,
         )
 
-        node_factory = DifyNodeFactory.from_graph_init_context(
-            graph_init_context=graph_init_context,
+        # Use the provided graph_runtime_state for consistent state management
+
+        node_factory = DifyNodeFactory(
+            graph_init_params=graph_init_params,
             graph_runtime_state=graph_runtime_state,
         )
 
@@ -292,23 +289,22 @@ class WorkflowBasedAppRunner:
 
         typed_node_configs = [NodeConfigDictAdapter.validate_python(node) for node in node_configs]
 
-        # Create explicit graph init context for Graph.init.
-        run_context = build_dify_run_context(
-            tenant_id=workflow.tenant_id,
-            app_id=self._app_id,
-            user_id=user_id,
-            user_from=UserFrom.ACCOUNT,
-            invoke_from=InvokeFrom.DEBUGGER,
-        )
-        graph_init_context = DifyGraphInitContext(
+        # Create required parameters for Graph.init
+        graph_init_params = GraphInitParams(
             workflow_id=workflow.id,
             graph_config=graph_config,
-            run_context=run_context,
+            run_context=build_dify_run_context(
+                tenant_id=workflow.tenant_id,
+                app_id=self._app_id,
+                user_id=user_id,
+                user_from=UserFrom.ACCOUNT,
+                invoke_from=InvokeFrom.DEBUGGER,
+            ),
             call_depth=0,
         )
 
-        node_factory = DifyNodeFactory.from_graph_init_context(
-            graph_init_context=graph_init_context,
+        node_factory = DifyNodeFactory(
+            graph_init_params=graph_init_params,
             graph_runtime_state=graph_runtime_state,
         )
 

api/core/app/entities/app_invoke_entities.py

@@ -1,6 +1,6 @@
 from collections.abc import Mapping, Sequence
 from enum import StrEnum
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Optional
 
 from graphon.file import File, FileUploadConfig
 from graphon.model_runtime.entities.model_entities import AIModelEntity
@@ -131,7 +131,7 @@ class AppGenerateEntity(BaseModel):
     extras: dict[str, Any] = Field(default_factory=dict)
 
     # tracing instance
-    trace_manager: "TraceQueueManager | None" = Field(default=None, exclude=True, repr=False)
+    trace_manager: Optional["TraceQueueManager"] = Field(default=None, exclude=True, repr=False)
 
 
 class EasyUIBasedAppGenerateEntity(AppGenerateEntity):

api/core/app/entities/llm_generation_entities.py

@@ -1,72 +0,0 @@
-"""
-LLM Generation Detail entities.
-
-Defines the structure for storing and transmitting LLM generation details
-including reasoning content, tool calls, and their sequence.
-"""
-
-from typing import Literal
-
-from pydantic import BaseModel, Field
-
-
-class ContentSegment(BaseModel):
-    """Represents a content segment in the generation sequence."""
-
-    type: Literal["content"] = "content"
-    start: int = Field(..., description="Start position in the text")
-    end: int = Field(..., description="End position in the text")
-
-
-class ReasoningSegment(BaseModel):
-    """Represents a reasoning segment in the generation sequence."""
-
-    type: Literal["reasoning"] = "reasoning"
-    index: int = Field(..., description="Index into reasoning_content array")
-
-
-class ToolCallSegment(BaseModel):
-    """Represents a tool call segment in the generation sequence."""
-
-    type: Literal["tool_call"] = "tool_call"
-    index: int = Field(..., description="Index into tool_calls array")
-
-
-SequenceSegment = ContentSegment | ReasoningSegment | ToolCallSegment
-
-
-class ToolCallDetail(BaseModel):
-    """Represents a tool call with its arguments and result."""
-
-    id: str = Field(default="", description="Unique identifier for the tool call")
-    name: str = Field(..., description="Name of the tool")
-    arguments: str = Field(default="", description="JSON string of tool arguments")
-    result: str = Field(default="", description="Result from the tool execution")
-    elapsed_time: float | None = Field(default=None, description="Elapsed time in seconds")
-    icon: str | dict | None = Field(default=None, description="Icon of the tool")
-    icon_dark: str | dict | None = Field(default=None, description="Dark theme icon of the tool")
-
-
-class LLMGenerationDetailData(BaseModel):
-    """
-    Domain model for LLM generation detail.
-
-    Contains the structured data for reasoning content, tool calls,
-    and their display sequence.
-    """
-
-    reasoning_content: list[str] = Field(default_factory=list, description="List of reasoning segments")
-    tool_calls: list[ToolCallDetail] = Field(default_factory=list, description="List of tool call details")
-    sequence: list[SequenceSegment] = Field(default_factory=list, description="Display order of segments")
-
-    def is_empty(self) -> bool:
-        """Check if there's any meaningful generation detail."""
-        return not self.reasoning_content and not self.tool_calls
-
-    def to_response_dict(self) -> dict:
-        """Convert to dictionary for API response."""
-        return {
-            "reasoning_content": self.reasoning_content,
-            "tool_calls": [tc.model_dump() for tc in self.tool_calls],
-            "sequence": [seg.model_dump() for seg in self.sequence],
-        }

api/core/app/llm/quota.py

@@ -1,6 +1,6 @@
 from graphon.model_runtime.entities.llm_entities import LLMUsage
 from sqlalchemy import update
-from sqlalchemy.orm import sessionmaker
+from sqlalchemy.orm import Session
 
 from configs import dify_config
 from core.entities.model_entities import ModelStatus
@@ -57,37 +57,37 @@ def deduct_llm_quota(*, tenant_id: str, model_instance: ModelInstance, usage: LL
             used_quota = 1
 
     if used_quota is not None and system_configuration.current_quota_type is not None:
-        match system_configuration.current_quota_type:
-            case ProviderQuotaType.TRIAL:
-                from services.credit_pool_service import CreditPoolService
+        if system_configuration.current_quota_type == ProviderQuotaType.TRIAL:
+            from services.credit_pool_service import CreditPoolService
 
-                CreditPoolService.check_and_deduct_credits(
-                    tenant_id=tenant_id,
-                    credits_required=used_quota,
-                )
-            case ProviderQuotaType.PAID:
-                from services.credit_pool_service import CreditPoolService
+            CreditPoolService.check_and_deduct_credits(
+                tenant_id=tenant_id,
+                credits_required=used_quota,
+            )
+        elif system_configuration.current_quota_type == ProviderQuotaType.PAID:
+            from services.credit_pool_service import CreditPoolService
 
-                CreditPoolService.check_and_deduct_credits(
-                    tenant_id=tenant_id,
-                    credits_required=used_quota,
-                    pool_type="paid",
-                )
-            case ProviderQuotaType.FREE:
-                with sessionmaker(bind=db.engine).begin() as session:
-                    stmt = (
-                        update(Provider)
-                        .where(
-                            Provider.tenant_id == tenant_id,
-                            # TODO: Use provider name with prefix after the data migration.
-                            Provider.provider_name == ModelProviderID(model_instance.provider).provider_name,
-                            Provider.provider_type == ProviderType.SYSTEM.value,
-                            Provider.quota_type == system_configuration.current_quota_type,
-                            Provider.quota_limit > Provider.quota_used,
-                        )
-                        .values(
-                            quota_used=Provider.quota_used + used_quota,
-                            last_used=naive_utc_now(),
-                        )
+            CreditPoolService.check_and_deduct_credits(
+                tenant_id=tenant_id,
+                credits_required=used_quota,
+                pool_type="paid",
+            )
+        else:
+            with Session(db.engine) as session:
+                stmt = (
+                    update(Provider)
+                    .where(
+                        Provider.tenant_id == tenant_id,
+                        # TODO: Use provider name with prefix after the data migration.
+                        Provider.provider_name == ModelProviderID(model_instance.provider).provider_name,
+                        Provider.provider_type == ProviderType.SYSTEM.value,
+                        Provider.quota_type == system_configuration.current_quota_type,
+                        Provider.quota_limit > Provider.quota_used,
                     )
-                    session.execute(stmt)
+                    .values(
+                        quota_used=Provider.quota_used + used_quota,
+                        last_used=naive_utc_now(),
+                    )
+                )
+                session.execute(stmt)
+                session.commit()

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -12,7 +12,7 @@ from graphon.model_runtime.entities.message_entities import (
 )
 from graphon.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from sqlalchemy import select
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import Session
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
@@ -266,8 +266,9 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
             event = message.event
 
             if isinstance(event, QueueErrorEvent):
-                with sessionmaker(bind=db.engine).begin() as session:
+                with Session(db.engine) as session:
                     err = self.handle_error(event=event, session=session, message_id=self._message_id)
+                    session.commit()
                 yield self.error_to_stream_response(err)
                 break
             elif isinstance(event, QueueStopEvent | QueueMessageEndEvent):
@@ -287,9 +288,10 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
                         answer=output_moderation_answer
                     )
 
-                with sessionmaker(bind=db.engine).begin() as session:
+                with Session(db.engine) as session:
                     # Save message
                     self._save_message(session=session, trace_manager=trace_manager)
+                    session.commit()
                 message_end_resp = self._message_end_to_stream_response()
                 yield message_end_resp
             elif isinstance(event, QueueRetrieverResourcesEvent):

api/core/app/task_pipeline/message_file_utils.py

@@ -40,44 +40,41 @@ def prepare_file_dict(message_file: MessageFile, upload_files_map: dict[str, Upl
     size = 0
     extension = ""
 
-    match message_file.transfer_method:
-        case FileTransferMethod.REMOTE_URL:
+    if message_file.transfer_method == FileTransferMethod.REMOTE_URL:
+        url = message_file.url
+        if message_file.url:
+            filename = message_file.url.split("/")[-1].split("?")[0]
+            if "." in filename:
+                extension = "." + filename.rsplit(".", 1)[1]
+    elif message_file.transfer_method == FileTransferMethod.LOCAL_FILE:
+        if upload_file:
+            url = file_helpers.get_signed_file_url(upload_file_id=str(upload_file.id))
+            filename = upload_file.name
+            mime_type = upload_file.mime_type or "application/octet-stream"
+            size = upload_file.size or 0
+            extension = f".{upload_file.extension}" if upload_file.extension else ""
+        elif message_file.upload_file_id:
+            url = file_helpers.get_signed_file_url(upload_file_id=str(message_file.upload_file_id))
+    elif message_file.transfer_method == FileTransferMethod.TOOL_FILE and message_file.url:
+        if message_file.url.startswith(("http://", "https://")):
             url = message_file.url
-            if message_file.url:
-                filename = message_file.url.split("/")[-1].split("?")[0]
-                if "." in filename:
-                    extension = "." + filename.rsplit(".", 1)[1]
-        case FileTransferMethod.LOCAL_FILE:
-            if upload_file:
-                url = file_helpers.get_signed_file_url(upload_file_id=str(upload_file.id))
-                filename = upload_file.name
-                mime_type = upload_file.mime_type or "application/octet-stream"
-                size = upload_file.size or 0
-                extension = f".{upload_file.extension}" if upload_file.extension else ""
-            elif message_file.upload_file_id:
-                url = file_helpers.get_signed_file_url(upload_file_id=str(message_file.upload_file_id))
-        case FileTransferMethod.TOOL_FILE if message_file.url:
-            if message_file.url.startswith(("http://", "https://")):
-                url = message_file.url
-                filename = message_file.url.split("/")[-1].split("?")[0]
-                if "." in filename:
-                    extension = "." + filename.rsplit(".", 1)[1]
-            else:
-                url_parts = message_file.url.split("/")
-                if url_parts:
-                    file_part = url_parts[-1].split("?")[0]
-                    if "." in file_part:
-                        tool_file_id, ext = file_part.rsplit(".", 1)
-                        extension = f".{ext}"
-                        if len(extension) > MAX_TOOL_FILE_EXTENSION_LENGTH:
-                            extension = ".bin"
-                    else:
-                        tool_file_id = file_part
+            filename = message_file.url.split("/")[-1].split("?")[0]
+            if "." in filename:
+                extension = "." + filename.rsplit(".", 1)[1]
+        else:
+            url_parts = message_file.url.split("/")
+            if url_parts:
+                file_part = url_parts[-1].split("?")[0]
+                if "." in file_part:
+                    tool_file_id, ext = file_part.rsplit(".", 1)
+                    extension = f".{ext}"
+                    if len(extension) > MAX_TOOL_FILE_EXTENSION_LENGTH:
                         extension = ".bin"
-                    url = sign_tool_file(tool_file_id=tool_file_id, extension=extension)
-                    filename = file_part
-        case FileTransferMethod.TOOL_FILE | FileTransferMethod.DATASOURCE_FILE:
-            pass
+                else:
+                    tool_file_id = file_part
+                    extension = ".bin"
+                url = sign_tool_file(tool_file_id=tool_file_id, extension=extension)
+                filename = file_part
 
     transfer_method_value = message_file.transfer_method.value
     remote_url = message_file.url if message_file.transfer_method == FileTransferMethod.REMOTE_URL else ""

api/core/datasource/entities/api_entities.py

@@ -1,10 +1,10 @@
-from typing import Any, Literal, TypedDict
+from typing import Literal, Optional
 
 from graphon.model_runtime.utils.encoders import jsonable_encoder
 from pydantic import BaseModel, Field, field_validator
 
 from core.datasource.entities.datasource_entities import DatasourceParameter
-from core.tools.entities.common_entities import I18nObject, I18nObjectDict
+from core.tools.entities.common_entities import I18nObject
 
 
 class DatasourceApiEntity(BaseModel):
@@ -17,24 +17,7 @@ class DatasourceApiEntity(BaseModel):
     output_schema: dict | None = None
 
 
-ToolProviderTypeApiLiteral = Literal["builtin", "api", "workflow"] | None
-
-
-class DatasourceProviderApiEntityDict(TypedDict):
-    id: str
-    author: str
-    name: str
-    plugin_id: str | None
-    plugin_unique_identifier: str | None
-    description: I18nObjectDict
-    icon: str | dict
-    label: I18nObjectDict
-    type: str
-    team_credentials: dict | None
-    is_team_authorization: bool
-    allow_delete: bool
-    datasources: list[Any]
-    labels: list[str]
+ToolProviderTypeApiLiteral = Optional[Literal["builtin", "api", "workflow"]]
 
 
 class DatasourceProviderApiEntity(BaseModel):
@@ -59,7 +42,7 @@ class DatasourceProviderApiEntity(BaseModel):
     def convert_none_to_empty_list(cls, v):
         return v if v is not None else []
 
-    def to_dict(self) -> DatasourceProviderApiEntityDict:
+    def to_dict(self) -> dict:
         # -------------
         # overwrite datasource parameter types for temp fix
         datasources = jsonable_encoder(self.datasources)
@@ -70,7 +53,7 @@ class DatasourceProviderApiEntity(BaseModel):
                         parameter["type"] = "files"
         # -------------
 
-        result: DatasourceProviderApiEntityDict = {
+        return {
             "id": self.id,
             "author": self.author,
             "name": self.name,
@@ -86,4 +69,3 @@ class DatasourceProviderApiEntity(BaseModel):
             "datasources": datasources,
             "labels": self.labels,
         }
-        return result

api/core/datasource/entities/datasource_entities.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 import enum
 from enum import StrEnum
-from typing import Any, TypedDict
+from typing import Any
 
 from pydantic import BaseModel, Field, ValidationInfo, field_validator
 from yarl import URL
@@ -179,12 +179,6 @@ class DatasourceProviderEntityWithPlugin(DatasourceProviderEntity):
     datasources: list[DatasourceEntity] = Field(default_factory=list)
 
 
-class DatasourceInvokeMetaDict(TypedDict):
-    time_cost: float
-    error: str | None
-    tool_config: dict[str, Any] | None
-
-
 class DatasourceInvokeMeta(BaseModel):
     """
     Datasource invoke meta
@@ -208,13 +202,12 @@ class DatasourceInvokeMeta(BaseModel):
         """
         return cls(time_cost=0.0, error=error, tool_config={})
 
-    def to_dict(self) -> DatasourceInvokeMetaDict:
-        result: DatasourceInvokeMetaDict = {
+    def to_dict(self) -> dict:
+        return {
             "time_cost": self.time_cost,
             "error": self.error,
             "tool_config": self.tool_config,
         }
-        return result
 
 
 class DatasourceLabel(BaseModel):

api/core/datasource/utils/message_transformer.py

@@ -71,8 +71,8 @@ class DatasourceFileMessageTransformer:
                 if not isinstance(message.message, DatasourceMessage.BlobMessage):
                     raise ValueError("unexpected message type")
 
-                if not isinstance(message.message.blob, bytes):
-                    raise TypeError(f"Expected blob to be bytes, got {type(message.message.blob).__name__}")
+                # FIXME: should do a type check here.
+                assert isinstance(message.message.blob, bytes)
                 tool_file_manager = ToolFileManager()
                 blob_tool_file: ToolFile | None = tool_file_manager.create_file_by_raw(
                     user_id=user_id,

api/core/extension/extensible.py

@@ -32,9 +32,9 @@ class Extensible:
 
     name: str
     tenant_id: str
-    config: dict[str, Any] | None = None
+    config: dict | None = None
 
-    def __init__(self, tenant_id: str, config: dict[str, Any] | None = None):
+    def __init__(self, tenant_id: str, config: dict | None = None):
         self.tenant_id = tenant_id
         self.config = config
 

api/core/external_data_tool/api/api.py

@@ -1,6 +1,3 @@
-from collections.abc import Mapping
-from typing import Any, TypedDict
-
 from sqlalchemy import select
 
 from core.extension.api_based_extension_requestor import APIBasedExtensionRequestor
@@ -10,16 +7,6 @@ from extensions.ext_database import db
 from models.api_based_extension import APIBasedExtension, APIBasedExtensionPoint
 
 
-class ApiToolConfig(TypedDict, total=False):
-    """Expected config shape for ApiExternalDataTool.
-
-    Not used directly in method signatures (base class accepts dict[str, Any]);
-    kept here to document the keys this tool reads from config.
-    """
-
-    api_based_extension_id: str
-
-
 class ApiExternalDataTool(ExternalDataTool):
     """
     The api external data tool.
@@ -29,7 +16,7 @@ class ApiExternalDataTool(ExternalDataTool):
     """the unique name of external data tool"""
 
     @classmethod
-    def validate_config(cls, tenant_id: str, config: dict[str, Any]):
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 
@@ -50,7 +37,7 @@ class ApiExternalDataTool(ExternalDataTool):
         if not api_based_extension:
             raise ValueError("api_based_extension_id is invalid")
 
-    def query(self, inputs: Mapping[str, Any], query: str | None = None) -> str:
+    def query(self, inputs: dict, query: str | None = None) -> str:
         """
         Query the external data tool.
 

api/core/external_data_tool/base.py

@@ -1,6 +1,4 @@
 from abc import ABC, abstractmethod
-from collections.abc import Mapping
-from typing import Any
 
 from core.extension.extensible import Extensible, ExtensionModule
 
@@ -17,14 +15,14 @@ class ExternalDataTool(Extensible, ABC):
     variable: str
     """the tool variable name of app tool"""
 
-    def __init__(self, tenant_id: str, app_id: str, variable: str, config: dict[str, Any] | None = None):
+    def __init__(self, tenant_id: str, app_id: str, variable: str, config: dict | None = None):
         super().__init__(tenant_id, config)
         self.app_id = app_id
         self.variable = variable
 
     @classmethod
     @abstractmethod
-    def validate_config(cls, tenant_id: str, config: dict[str, Any]):
+    def validate_config(cls, tenant_id: str, config: dict):
         """
         Validate the incoming form config data.
 
@@ -35,7 +33,7 @@ class ExternalDataTool(Extensible, ABC):
         raise NotImplementedError
 
     @abstractmethod
-    def query(self, inputs: Mapping[str, Any], query: str | None = None) -> str:
+    def query(self, inputs: dict, query: str | None = None) -> str:
         """
         Query the external data tool.
 

api/core/helper/creators.py

@@ -1,75 +0,0 @@
-"""
-Helper module for Creators Platform integration.
-
-Provides functionality to upload DSL files to the Creators Platform
-and generate redirect URLs with OAuth authorization codes.
-"""
-
-import logging
-from urllib.parse import urlencode
-
-import httpx
-from yarl import URL
-
-from configs import dify_config
-
-logger = logging.getLogger(__name__)
-
-creators_platform_api_url = URL(str(dify_config.CREATORS_PLATFORM_API_URL))
-
-
-def upload_dsl(dsl_file_bytes: bytes, filename: str = "template.yaml") -> str:
-    """Upload a DSL file to the Creators Platform anonymous upload endpoint.
-
-    Args:
-        dsl_file_bytes: Raw bytes of the DSL file (YAML or ZIP).
-        filename: Original filename for the upload.
-
-    Returns:
-        The claim_code string used to retrieve the DSL later.
-
-    Raises:
-        httpx.HTTPStatusError: If the upload request fails.
-        ValueError: If the response does not contain a valid claim_code.
-    """
-    url = str(creators_platform_api_url / "api/v1/templates/anonymous-upload")
-    response = httpx.post(url, files={"file": (filename, dsl_file_bytes)}, timeout=30)
-    response.raise_for_status()
-
-    data = response.json()
-    claim_code = data.get("data", {}).get("claim_code")
-    if not claim_code:
-        raise ValueError("Creators Platform did not return a valid claim_code")
-
-    return claim_code
-
-
-def get_redirect_url(user_account_id: str, claim_code: str) -> str:
-    """Generate the redirect URL to the Creators Platform frontend.
-
-    Redirects to the Creators Platform root page with the dsl_claim_code.
-    If CREATORS_PLATFORM_OAUTH_CLIENT_ID is configured (Dify Cloud),
-    also signs an OAuth authorization code so the frontend can
-    automatically authenticate the user via the OAuth callback.
-
-    For self-hosted Dify without OAuth client_id configured, only the
-    dsl_claim_code is passed and the user must log in manually.
-
-    Args:
-        user_account_id: The Dify user account ID.
-        claim_code: The claim_code obtained from upload_dsl().
-
-    Returns:
-        The full redirect URL string.
-    """
-    base_url = str(dify_config.CREATORS_PLATFORM_API_URL).rstrip("/")
-    params: dict[str, str] = {"dsl_claim_code": claim_code}
-
-    client_id = str(dify_config.CREATORS_PLATFORM_OAUTH_CLIENT_ID or "")
-    if client_id:
-        from services.oauth_server import OAuthServerService
-
-        oauth_code = OAuthServerService.sign_oauth_authorization_code(client_id, user_account_id)
-        params["oauth_code"] = oauth_code
-
-    return f"{base_url}?{urlencode(params)}"

api/core/llm_generator/context_models.py

@@ -1,62 +0,0 @@
-from typing import Any
-
-from pydantic import BaseModel, ConfigDict, Field
-
-
-class VariableSelectorPayload(BaseModel):
-    model_config = ConfigDict(extra="forbid")
-
-    variable: str = Field(..., description="Variable name used in generated code")
-    value_selector: list[str] = Field(..., description="Path to upstream node output, format: [node_id, output_name]")
-
-
-class CodeOutputPayload(BaseModel):
-    model_config = ConfigDict(extra="forbid")
-
-    type: str = Field(..., description="Output variable type")
-
-
-class CodeContextPayload(BaseModel):
-    # From web/app/components/workflow/nodes/tool/components/context-generate-modal/index.tsx (code node snapshot).
-    model_config = ConfigDict(extra="forbid")
-
-    code: str = Field(..., description="Existing code in the Code node")
-    outputs: dict[str, CodeOutputPayload] | None = Field(
-        default=None, description="Existing output definitions for the Code node"
-    )
-    variables: list[VariableSelectorPayload] | None = Field(
-        default=None, description="Existing variable selectors used by the Code node"
-    )
-
-
-class AvailableVarPayload(BaseModel):
-    # From web/app/components/workflow/nodes/_base/hooks/use-available-var-list.ts (available variables).
-    model_config = ConfigDict(extra="forbid", populate_by_name=True)
-
-    value_selector: list[str] = Field(..., description="Path to upstream node output")
-    type: str = Field(..., description="Variable type, e.g. string, number, array[object]")
-    description: str | None = Field(default=None, description="Optional variable description")
-    node_id: str | None = Field(default=None, description="Source node ID")
-    node_title: str | None = Field(default=None, description="Source node title")
-    node_type: str | None = Field(default=None, description="Source node type")
-    json_schema: dict[str, Any] | None = Field(
-        default=None,
-        alias="schema",
-        description="Optional JSON schema for object variables",
-    )
-
-
-class ParameterInfoPayload(BaseModel):
-    # From web/app/components/workflow/nodes/tool/use-config.ts (ToolParameter metadata).
-    model_config = ConfigDict(extra="forbid")
-
-    name: str = Field(..., description="Target parameter name")
-    type: str = Field(default="string", description="Target parameter type")
-    description: str = Field(default="", description="Parameter description")
-    required: bool | None = Field(default=None, description="Whether the parameter is required")
-    options: list[str] | None = Field(default=None, description="Allowed option values")
-    min: float | None = Field(default=None, description="Minimum numeric value")
-    max: float | None = Field(default=None, description="Maximum numeric value")
-    default: str | int | float | bool | None = Field(default=None, description="Default value")
-    multiple: bool | None = Field(default=None, description="Whether the parameter accepts multiple values")
-    label: str | None = Field(default=None, description="Optional display label")

api/core/llm_generator/output_models.py

@@ -1,67 +0,0 @@
-from __future__ import annotations
-
-from pydantic import BaseModel, ConfigDict, Field
-
-from graphon.variables.types import SegmentType
-
-
-class SuggestedQuestionsOutput(BaseModel):
-    """Output model for suggested questions generation."""
-
-    model_config = ConfigDict(extra="forbid")
-
-    questions: list[str] = Field(
-        min_length=3,
-        max_length=3,
-        description="Exactly 3 suggested follow-up questions for the user",
-    )
-
-
-class VariableSelectorOutput(BaseModel):
-    """Variable selector mapping code variable to upstream node output.
-
-    Note: Separate from VariableSelector to ensure 'additionalProperties: false'
-    in JSON schema for OpenAI/Azure strict mode.
-    """
-
-    model_config = ConfigDict(extra="forbid")
-
-    variable: str = Field(description="Variable name used in the generated code")
-    value_selector: list[str] = Field(description="Path to upstream node output, format: [node_id, output_name]")
-
-
-class CodeNodeOutputItem(BaseModel):
-    """Single output variable definition.
-
-    Note: OpenAI/Azure strict mode requires 'additionalProperties: false' and
-    does not support dynamic object keys, so outputs use array format.
-    """
-
-    model_config = ConfigDict(extra="forbid")
-
-    name: str = Field(description="Output variable name returned by the main function")
-    type: SegmentType = Field(description="Data type of the output variable")
-
-
-class CodeNodeStructuredOutput(BaseModel):
-    """Structured output for code node generation."""
-
-    model_config = ConfigDict(extra="forbid")
-
-    variables: list[VariableSelectorOutput] = Field(
-        description="Input variables mapping code variables to upstream node outputs"
-    )
-    code: str = Field(description="Generated code with a main function that processes inputs and returns outputs")
-    outputs: list[CodeNodeOutputItem] = Field(
-        description="Output variable definitions specifying name and type for each return value"
-    )
-    message: str = Field(description="Brief explanation of what the generated code does")
-
-
-class InstructionModifyOutput(BaseModel):
-    """Output model for instruction-based prompt modification."""
-
-    model_config = ConfigDict(extra="forbid")
-
-    modified: str = Field(description="The modified prompt content after applying the instruction")
-    message: str = Field(description="Brief explanation of what changes were made")