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5 Commits
0.15.7
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feat/retry
| Author | SHA1 | Date | |
|---|---|---|---|
| 81375088e9 | |||
| cfade297e8 | |||
| 8933dd85bf | |||
| ae5e8d3160 | |||
| fc6c0317a5 |
2
.github/actions/setup-poetry/action.yml
vendored
2
.github/actions/setup-poetry/action.yml
vendored
@ -8,7 +8,7 @@ inputs:
|
||||
poetry-version:
|
||||
description: Poetry version to set up
|
||||
required: true
|
||||
default: '2.0.1'
|
||||
default: '1.8.4'
|
||||
poetry-lockfile:
|
||||
description: Path to the Poetry lockfile to restore cache from
|
||||
required: true
|
||||
|
||||
16
.github/workflows/api-tests.yml
vendored
16
.github/workflows/api-tests.yml
vendored
@ -42,23 +42,25 @@ jobs:
|
||||
run: poetry install -C api --with dev
|
||||
|
||||
- name: Check dependencies in pyproject.toml
|
||||
run: poetry run -P api bash dev/pytest/pytest_artifacts.sh
|
||||
run: poetry run -C api bash dev/pytest/pytest_artifacts.sh
|
||||
|
||||
- name: Run Unit tests
|
||||
run: poetry run -P api bash dev/pytest/pytest_unit_tests.sh
|
||||
run: poetry run -C api bash dev/pytest/pytest_unit_tests.sh
|
||||
|
||||
- name: Run ModelRuntime
|
||||
run: poetry run -P api bash dev/pytest/pytest_model_runtime.sh
|
||||
run: poetry run -C api bash dev/pytest/pytest_model_runtime.sh
|
||||
|
||||
- name: Run dify config tests
|
||||
run: poetry run -P api python dev/pytest/pytest_config_tests.py
|
||||
run: poetry run -C api python dev/pytest/pytest_config_tests.py
|
||||
|
||||
- name: Run Tool
|
||||
run: poetry run -P api bash dev/pytest/pytest_tools.sh
|
||||
run: poetry run -C api bash dev/pytest/pytest_tools.sh
|
||||
|
||||
- name: Run mypy
|
||||
run: |
|
||||
poetry run -C api python -m mypy --install-types --non-interactive .
|
||||
pushd api
|
||||
poetry run python -m mypy --install-types --non-interactive .
|
||||
popd
|
||||
|
||||
- name: Set up dotenvs
|
||||
run: |
|
||||
@ -78,4 +80,4 @@ jobs:
|
||||
ssrf_proxy
|
||||
|
||||
- name: Run Workflow
|
||||
run: poetry run -P api bash dev/pytest/pytest_workflow.sh
|
||||
run: poetry run -C api bash dev/pytest/pytest_workflow.sh
|
||||
|
||||
4
.github/workflows/build-push.yml
vendored
4
.github/workflows/build-push.yml
vendored
@ -5,8 +5,8 @@ on:
|
||||
branches:
|
||||
- "main"
|
||||
- "deploy/dev"
|
||||
tags:
|
||||
- "*"
|
||||
release:
|
||||
types: [published]
|
||||
|
||||
concurrency:
|
||||
group: build-push-${{ github.head_ref || github.run_id }}
|
||||
|
||||
47
.github/workflows/docker-build.yml
vendored
47
.github/workflows/docker-build.yml
vendored
@ -1,47 +0,0 @@
|
||||
name: Build docker image
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
branches:
|
||||
- "main"
|
||||
paths:
|
||||
- api/Dockerfile
|
||||
- web/Dockerfile
|
||||
|
||||
concurrency:
|
||||
group: docker-build-${{ github.head_ref || github.run_id }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
build-docker:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- service_name: "api-amd64"
|
||||
platform: linux/amd64
|
||||
context: "api"
|
||||
- service_name: "api-arm64"
|
||||
platform: linux/arm64
|
||||
context: "api"
|
||||
- service_name: "web-amd64"
|
||||
platform: linux/amd64
|
||||
context: "web"
|
||||
- service_name: "web-arm64"
|
||||
platform: linux/arm64
|
||||
context: "web"
|
||||
steps:
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
|
||||
- name: Build Docker Image
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
push: false
|
||||
context: "{{defaultContext}}:${{ matrix.context }}"
|
||||
platforms: ${{ matrix.platform }}
|
||||
cache-from: type=gha
|
||||
cache-to: type=gha,mode=max
|
||||
33
.github/workflows/style.yml
vendored
33
.github/workflows/style.yml
vendored
@ -38,12 +38,12 @@ jobs:
|
||||
if: steps.changed-files.outputs.any_changed == 'true'
|
||||
run: |
|
||||
poetry run -C api ruff --version
|
||||
poetry run -C api ruff check ./
|
||||
poetry run -C api ruff format --check ./
|
||||
poetry run -C api ruff check ./api
|
||||
poetry run -C api ruff format --check ./api
|
||||
|
||||
- name: Dotenv check
|
||||
if: steps.changed-files.outputs.any_changed == 'true'
|
||||
run: poetry run -P api dotenv-linter ./api/.env.example ./web/.env.example
|
||||
run: poetry run -C api dotenv-linter ./api/.env.example ./web/.env.example
|
||||
|
||||
- name: Lint hints
|
||||
if: failure()
|
||||
@ -82,33 +82,6 @@ jobs:
|
||||
if: steps.changed-files.outputs.any_changed == 'true'
|
||||
run: yarn run lint
|
||||
|
||||
docker-compose-template:
|
||||
name: Docker Compose Template
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Check changed files
|
||||
id: changed-files
|
||||
uses: tj-actions/changed-files@v45
|
||||
with:
|
||||
files: |
|
||||
docker/generate_docker_compose
|
||||
docker/.env.example
|
||||
docker/docker-compose-template.yaml
|
||||
docker/docker-compose.yaml
|
||||
|
||||
- name: Generate Docker Compose
|
||||
if: steps.changed-files.outputs.any_changed == 'true'
|
||||
run: |
|
||||
cd docker
|
||||
./generate_docker_compose
|
||||
|
||||
- name: Check for changes
|
||||
if: steps.changed-files.outputs.any_changed == 'true'
|
||||
run: git diff --exit-code
|
||||
|
||||
superlinter:
|
||||
name: SuperLinter
|
||||
|
||||
2
.github/workflows/vdb-tests.yml
vendored
2
.github/workflows/vdb-tests.yml
vendored
@ -70,4 +70,4 @@ jobs:
|
||||
tidb
|
||||
|
||||
- name: Test Vector Stores
|
||||
run: poetry run -P api bash dev/pytest/pytest_vdb.sh
|
||||
run: poetry run -C api bash dev/pytest/pytest_vdb.sh
|
||||
|
||||
@ -1,3 +0,0 @@
|
||||
{
|
||||
"MD024": false
|
||||
}
|
||||
32
CHANGELOG.md
32
CHANGELOG.md
@ -1,32 +0,0 @@
|
||||
# Changelog
|
||||
|
||||
All notable changes to Dify will be documented in this file.
|
||||
|
||||
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
|
||||
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
|
||||
|
||||
## [0.15.7] - 2025-04-27
|
||||
|
||||
### Added
|
||||
|
||||
- Added support for GPT-4.1 in model providers (#18912)
|
||||
- Added support for Amazon Bedrock DeepSeek-R1 model (#18908)
|
||||
- Added support for Amazon Bedrock Claude Sonnet 3.7 model (#18788)
|
||||
- Refined version compatibility logic in app DSL service
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed issue with creating apps from template categories (#18807, #18868)
|
||||
- Fixed DSL version check when creating apps from explore templates (#18872, #18878)
|
||||
|
||||
## [0.15.6] - 2025-04-22
|
||||
|
||||
### Security
|
||||
|
||||
- Fixed clickjacking vulnerability (#18552)
|
||||
- Fixed reset password security issue (#18366)
|
||||
- Updated reset password token when email code verification succeeds (#18362)
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed Vertex AI Gemini 2.0 Flash 001 schema (#18405)
|
||||
@ -25,9 +25,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="follow on LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="follow on LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="follow on LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="seguir en X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="seguir en LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Descargas de Docker" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="suivre sur X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="suivre sur LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Tirages Docker" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="X(Twitter)でフォロー"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="LinkedInでフォロー"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="follow on LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="follow on LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -25,9 +25,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="follow on LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -22,9 +22,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="follow on X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="follow on LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="X(Twitter)'da takip et"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="LinkedIn'da takip et"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Çekmeleri" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
@ -65,6 +62,8 @@ Görsel bir arayüz üzerinde güçlü AI iş akışları oluşturun ve test edi
|
||||
|
||||
|
||||
|
||||
Özür dilerim, haklısınız. Daha anlamlı ve akıcı bir çeviri yapmaya çalışayım. İşte güncellenmiş çeviri:
|
||||
|
||||
**3. Prompt IDE**:
|
||||
Komut istemlerini oluşturmak, model performansını karşılaştırmak ve sohbet tabanlı uygulamalara metin-konuşma gibi ek özellikler eklemek için kullanıcı dostu bir arayüz.
|
||||
|
||||
@ -151,6 +150,8 @@ Görsel bir arayüz üzerinde güçlü AI iş akışları oluşturun ve test edi
|
||||
## Dify'ı Kullanma
|
||||
|
||||
- **Cloud </br>**
|
||||
İşte verdiğiniz metnin Türkçe çevirisi, kod bloğu içinde:
|
||||
-
|
||||
Herkesin sıfır kurulumla denemesi için bir [Dify Cloud](https://dify.ai) hizmeti sunuyoruz. Bu hizmet, kendi kendine dağıtılan versiyonun tüm yeteneklerini sağlar ve sandbox planında 200 ücretsiz GPT-4 çağrısı içerir.
|
||||
|
||||
- **Dify Topluluk Sürümünü Kendi Sunucunuzda Barındırma</br>**
|
||||
@ -176,6 +177,8 @@ GitHub'da Dify'a yıldız verin ve yeni sürümlerden anında haberdar olun.
|
||||
>- RAM >= 4GB
|
||||
|
||||
</br>
|
||||
İşte verdiğiniz metnin Türkçe çevirisi, kod bloğu içinde:
|
||||
|
||||
Dify sunucusunu başlatmanın en kolay yolu, [docker-compose.yml](docker/docker-compose.yaml) dosyamızı çalıştırmaktır. Kurulum komutunu çalıştırmadan önce, makinenizde [Docker](https://docs.docker.com/get-docker/) ve [Docker Compose](https://docs.docker.com/compose/install/)'un kurulu olduğundan emin olun:
|
||||
|
||||
```bash
|
||||
|
||||
@ -21,9 +21,6 @@
|
||||
<a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
|
||||
alt="theo dõi trên X(Twitter)"></a>
|
||||
<a href="https://www.linkedin.com/company/langgenius/" target="_blank">
|
||||
<img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff"
|
||||
alt="theo dõi trên LinkedIn"></a>
|
||||
<a href="https://hub.docker.com/u/langgenius" target="_blank">
|
||||
<img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
|
||||
<a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
|
||||
|
||||
@ -23,9 +23,6 @@ FILES_ACCESS_TIMEOUT=300
|
||||
# Access token expiration time in minutes
|
||||
ACCESS_TOKEN_EXPIRE_MINUTES=60
|
||||
|
||||
# Refresh token expiration time in days
|
||||
REFRESH_TOKEN_EXPIRE_DAYS=30
|
||||
|
||||
# celery configuration
|
||||
CELERY_BROKER_URL=redis://:difyai123456@localhost:6379/1
|
||||
|
||||
@ -430,7 +427,4 @@ CREATE_TIDB_SERVICE_JOB_ENABLED=false
|
||||
# Maximum number of submitted thread count in a ThreadPool for parallel node execution
|
||||
MAX_SUBMIT_COUNT=100
|
||||
# Lockout duration in seconds
|
||||
LOGIN_LOCKOUT_DURATION=86400
|
||||
|
||||
# Prevent Clickjacking
|
||||
ALLOW_EMBED=false
|
||||
LOGIN_LOCKOUT_DURATION=86400
|
||||
@ -53,12 +53,10 @@ ignore = [
|
||||
"FURB152", # math-constant
|
||||
"UP007", # non-pep604-annotation
|
||||
"UP032", # f-string
|
||||
"UP045", # non-pep604-annotation-optional
|
||||
"B005", # strip-with-multi-characters
|
||||
"B006", # mutable-argument-default
|
||||
"B007", # unused-loop-control-variable
|
||||
"B026", # star-arg-unpacking-after-keyword-arg
|
||||
"B903", # class-as-data-structure
|
||||
"B904", # raise-without-from-inside-except
|
||||
"B905", # zip-without-explicit-strict
|
||||
"N806", # non-lowercase-variable-in-function
|
||||
@ -87,11 +85,11 @@ ignore = [
|
||||
]
|
||||
"tests/*" = [
|
||||
"F811", # redefined-while-unused
|
||||
"F401", # unused-import
|
||||
]
|
||||
|
||||
[lint.pyflakes]
|
||||
allowed-unused-imports = [
|
||||
extend-generics = [
|
||||
"_pytest.monkeypatch",
|
||||
"tests.integration_tests",
|
||||
"tests.unit_tests",
|
||||
]
|
||||
|
||||
@ -4,7 +4,7 @@ FROM python:3.12-slim-bookworm AS base
|
||||
WORKDIR /app/api
|
||||
|
||||
# Install Poetry
|
||||
ENV POETRY_VERSION=2.0.1
|
||||
ENV POETRY_VERSION=1.8.4
|
||||
|
||||
# if you located in China, you can use aliyun mirror to speed up
|
||||
# RUN pip install --no-cache-dir poetry==${POETRY_VERSION} -i https://mirrors.aliyun.com/pypi/simple/
|
||||
@ -48,18 +48,16 @@ ENV TZ=UTC
|
||||
|
||||
WORKDIR /app/api
|
||||
|
||||
RUN \
|
||||
apt-get update \
|
||||
# Install dependencies
|
||||
&& apt-get install -y --no-install-recommends \
|
||||
# basic environment
|
||||
curl nodejs libgmp-dev libmpfr-dev libmpc-dev \
|
||||
# For Security
|
||||
expat libldap-2.5-0 perl libsqlite3-0 zlib1g \
|
||||
# install a chinese font to support the use of tools like matplotlib
|
||||
fonts-noto-cjk \
|
||||
# install libmagic to support the use of python-magic guess MIMETYPE
|
||||
libmagic1 \
|
||||
RUN apt-get update \
|
||||
&& apt-get install -y --no-install-recommends curl nodejs libgmp-dev libmpfr-dev libmpc-dev \
|
||||
# if you located in China, you can use aliyun mirror to speed up
|
||||
# && echo "deb http://mirrors.aliyun.com/debian testing main" > /etc/apt/sources.list \
|
||||
&& echo "deb http://deb.debian.org/debian testing main" > /etc/apt/sources.list \
|
||||
&& apt-get update \
|
||||
# For Security
|
||||
&& apt-get install -y --no-install-recommends expat=2.6.4-1 libldap-2.5-0=2.5.18+dfsg-3+b1 perl=5.40.0-8 libsqlite3-0=3.46.1-1 zlib1g=1:1.3.dfsg+really1.3.1-1+b1 \
|
||||
# install a chinese font to support the use of tools like matplotlib
|
||||
&& apt-get install -y fonts-noto-cjk \
|
||||
&& apt-get autoremove -y \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
@ -78,6 +76,7 @@ COPY . /app/api/
|
||||
COPY docker/entrypoint.sh /entrypoint.sh
|
||||
RUN chmod +x /entrypoint.sh
|
||||
|
||||
|
||||
ARG COMMIT_SHA
|
||||
ENV COMMIT_SHA=${COMMIT_SHA}
|
||||
|
||||
|
||||
@ -79,5 +79,5 @@
|
||||
2. Run the tests locally with mocked system environment variables in `tool.pytest_env` section in `pyproject.toml`
|
||||
|
||||
```bash
|
||||
poetry run -P api bash dev/pytest/pytest_all_tests.sh
|
||||
poetry run -C api bash dev/pytest/pytest_all_tests.sh
|
||||
```
|
||||
|
||||
29
api/app.py
29
api/app.py
@ -1,8 +1,12 @@
|
||||
import os
|
||||
import sys
|
||||
from libs import version_utils
|
||||
|
||||
# preparation before creating app
|
||||
version_utils.check_supported_python_version()
|
||||
|
||||
|
||||
def is_db_command():
|
||||
import sys
|
||||
|
||||
if len(sys.argv) > 1 and sys.argv[0].endswith("flask") and sys.argv[1] == "db":
|
||||
return True
|
||||
return False
|
||||
@ -14,25 +18,10 @@ if is_db_command():
|
||||
|
||||
app = create_migrations_app()
|
||||
else:
|
||||
# It seems that JetBrains Python debugger does not work well with gevent,
|
||||
# so we need to disable gevent in debug mode.
|
||||
# If you are using debugpy and set GEVENT_SUPPORT=True, you can debug with gevent.
|
||||
if (flask_debug := os.environ.get("FLASK_DEBUG", "0")) and flask_debug.lower() in {"false", "0", "no"}:
|
||||
from gevent import monkey # type: ignore
|
||||
|
||||
# gevent
|
||||
monkey.patch_all()
|
||||
|
||||
from grpc.experimental import gevent as grpc_gevent # type: ignore
|
||||
|
||||
# grpc gevent
|
||||
grpc_gevent.init_gevent()
|
||||
|
||||
import psycogreen.gevent # type: ignore
|
||||
|
||||
psycogreen.gevent.patch_psycopg()
|
||||
|
||||
from app_factory import create_app
|
||||
from libs import threadings_utils
|
||||
|
||||
threadings_utils.apply_gevent_threading_patch()
|
||||
|
||||
app = create_app()
|
||||
celery = app.extensions["celery"]
|
||||
|
||||
@ -146,7 +146,7 @@ class EndpointConfig(BaseSettings):
|
||||
)
|
||||
|
||||
CONSOLE_WEB_URL: str = Field(
|
||||
description="Base URL for the console web interface,used for frontend references and CORS configuration",
|
||||
description="Base URL for the console web interface," "used for frontend references and CORS configuration",
|
||||
default="",
|
||||
)
|
||||
|
||||
@ -488,11 +488,6 @@ class AuthConfig(BaseSettings):
|
||||
default=60,
|
||||
)
|
||||
|
||||
REFRESH_TOKEN_EXPIRE_DAYS: PositiveFloat = Field(
|
||||
description="Expiration time for refresh tokens in days",
|
||||
default=30,
|
||||
)
|
||||
|
||||
LOGIN_LOCKOUT_DURATION: PositiveInt = Field(
|
||||
description="Time (in seconds) a user must wait before retrying login after exceeding the rate limit.",
|
||||
default=86400,
|
||||
@ -606,7 +601,7 @@ class RagEtlConfig(BaseSettings):
|
||||
|
||||
UNSTRUCTURED_API_KEY: Optional[str] = Field(
|
||||
description="API key for Unstructured.io service",
|
||||
default="",
|
||||
default=None,
|
||||
)
|
||||
|
||||
SCARF_NO_ANALYTICS: Optional[str] = Field(
|
||||
@ -672,11 +667,6 @@ class IndexingConfig(BaseSettings):
|
||||
default=4000,
|
||||
)
|
||||
|
||||
CHILD_CHUNKS_PREVIEW_NUMBER: PositiveInt = Field(
|
||||
description="Maximum number of child chunks to preview",
|
||||
default=50,
|
||||
)
|
||||
|
||||
|
||||
class MultiModalTransferConfig(BaseSettings):
|
||||
MULTIMODAL_SEND_FORMAT: Literal["base64", "url"] = Field(
|
||||
@ -775,13 +765,6 @@ class LoginConfig(BaseSettings):
|
||||
)
|
||||
|
||||
|
||||
class AccountConfig(BaseSettings):
|
||||
ACCOUNT_DELETION_TOKEN_EXPIRY_MINUTES: PositiveInt = Field(
|
||||
description="Duration in minutes for which a account deletion token remains valid",
|
||||
default=5,
|
||||
)
|
||||
|
||||
|
||||
class FeatureConfig(
|
||||
# place the configs in alphabet order
|
||||
AppExecutionConfig,
|
||||
@ -809,7 +792,6 @@ class FeatureConfig(
|
||||
WorkflowNodeExecutionConfig,
|
||||
WorkspaceConfig,
|
||||
LoginConfig,
|
||||
AccountConfig,
|
||||
# hosted services config
|
||||
HostedServiceConfig,
|
||||
CeleryBeatConfig,
|
||||
|
||||
@ -1,40 +1,9 @@
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import Field, NonNegativeInt, computed_field
|
||||
from pydantic import Field, NonNegativeInt
|
||||
from pydantic_settings import BaseSettings
|
||||
|
||||
|
||||
class HostedCreditConfig(BaseSettings):
|
||||
HOSTED_MODEL_CREDIT_CONFIG: str = Field(
|
||||
description="Model credit configuration in format 'model:credits,model:credits', e.g., 'gpt-4:20,gpt-4o:10'",
|
||||
default="",
|
||||
)
|
||||
|
||||
def get_model_credits(self, model_name: str) -> int:
|
||||
"""
|
||||
Get credit value for a specific model name.
|
||||
Returns 1 if model is not found in configuration (default credit).
|
||||
|
||||
:param model_name: The name of the model to search for
|
||||
:return: The credit value for the model
|
||||
"""
|
||||
if not self.HOSTED_MODEL_CREDIT_CONFIG:
|
||||
return 1
|
||||
|
||||
try:
|
||||
credit_map = dict(
|
||||
item.strip().split(":", 1) for item in self.HOSTED_MODEL_CREDIT_CONFIG.split(",") if ":" in item
|
||||
)
|
||||
|
||||
# Search for matching model pattern
|
||||
for pattern, credit in credit_map.items():
|
||||
if pattern.strip() == model_name:
|
||||
return int(credit)
|
||||
return 1 # Default quota if no match found
|
||||
except (ValueError, AttributeError):
|
||||
return 1 # Return default quota if parsing fails
|
||||
|
||||
|
||||
class HostedOpenAiConfig(BaseSettings):
|
||||
"""
|
||||
Configuration for hosted OpenAI service
|
||||
@ -212,7 +181,7 @@ class HostedFetchAppTemplateConfig(BaseSettings):
|
||||
"""
|
||||
|
||||
HOSTED_FETCH_APP_TEMPLATES_MODE: str = Field(
|
||||
description="Mode for fetching app templates: remote, db, or builtin default to remote,",
|
||||
description="Mode for fetching app templates: remote, db, or builtin" " default to remote,",
|
||||
default="remote",
|
||||
)
|
||||
|
||||
@ -233,7 +202,5 @@ class HostedServiceConfig(
|
||||
HostedZhipuAIConfig,
|
||||
# moderation
|
||||
HostedModerationConfig,
|
||||
# credit config
|
||||
HostedCreditConfig,
|
||||
):
|
||||
pass
|
||||
|
||||
@ -33,9 +33,3 @@ class MilvusConfig(BaseSettings):
|
||||
description="Name of the Milvus database to connect to (default is 'default')",
|
||||
default="default",
|
||||
)
|
||||
|
||||
MILVUS_ENABLE_HYBRID_SEARCH: bool = Field(
|
||||
description="Enable hybrid search features (requires Milvus >= 2.5.0). Set to false for compatibility with "
|
||||
"older versions",
|
||||
default=True,
|
||||
)
|
||||
|
||||
@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
|
||||
|
||||
CURRENT_VERSION: str = Field(
|
||||
description="Dify version",
|
||||
default="0.15.7",
|
||||
default="0.14.2",
|
||||
)
|
||||
|
||||
COMMIT_SHA: str = Field(
|
||||
|
||||
@ -1,32 +1,12 @@
|
||||
import mimetypes
|
||||
import os
|
||||
import platform
|
||||
import re
|
||||
import urllib.parse
|
||||
import warnings
|
||||
from collections.abc import Mapping
|
||||
from typing import Any
|
||||
from uuid import uuid4
|
||||
|
||||
import httpx
|
||||
|
||||
try:
|
||||
import magic
|
||||
except ImportError:
|
||||
if platform.system() == "Windows":
|
||||
warnings.warn(
|
||||
"To use python-magic guess MIMETYPE, you need to run `pip install python-magic-bin`", stacklevel=2
|
||||
)
|
||||
elif platform.system() == "Darwin":
|
||||
warnings.warn("To use python-magic guess MIMETYPE, you need to run `brew install libmagic`", stacklevel=2)
|
||||
elif platform.system() == "Linux":
|
||||
warnings.warn(
|
||||
"To use python-magic guess MIMETYPE, you need to run `sudo apt-get install libmagic1`", stacklevel=2
|
||||
)
|
||||
else:
|
||||
warnings.warn("To use python-magic guess MIMETYPE, you need to install `libmagic`", stacklevel=2)
|
||||
magic = None # type: ignore
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from configs import dify_config
|
||||
@ -67,13 +47,6 @@ def guess_file_info_from_response(response: httpx.Response):
|
||||
# If guessing fails, use Content-Type from response headers
|
||||
mimetype = response.headers.get("Content-Type", "application/octet-stream")
|
||||
|
||||
# Use python-magic to guess MIME type if still unknown or generic
|
||||
if mimetype == "application/octet-stream" and magic is not None:
|
||||
try:
|
||||
mimetype = magic.from_buffer(response.content[:1024], mime=True)
|
||||
except magic.MagicException:
|
||||
pass
|
||||
|
||||
extension = os.path.splitext(filename)[1]
|
||||
|
||||
# Ensure filename has an extension
|
||||
|
||||
@ -56,7 +56,7 @@ class InsertExploreAppListApi(Resource):
|
||||
|
||||
app = App.query.filter(App.id == args["app_id"]).first()
|
||||
if not app:
|
||||
raise NotFound(f"App '{args['app_id']}' is not found")
|
||||
raise NotFound(f'App \'{args["app_id"]}\' is not found')
|
||||
|
||||
site = app.site
|
||||
if not site:
|
||||
|
||||
@ -57,13 +57,12 @@ class AppListApi(Resource):
|
||||
)
|
||||
parser.add_argument("name", type=str, location="args", required=False)
|
||||
parser.add_argument("tag_ids", type=uuid_list, location="args", required=False)
|
||||
parser.add_argument("is_created_by_me", type=inputs.boolean, location="args", required=False)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
# get app list
|
||||
app_service = AppService()
|
||||
app_pagination = app_service.get_paginate_apps(current_user.id, current_user.current_tenant_id, args)
|
||||
app_pagination = app_service.get_paginate_apps(current_user.current_tenant_id, args)
|
||||
if not app_pagination:
|
||||
return {"data": [], "total": 0, "page": 1, "limit": 20, "has_more": False}
|
||||
|
||||
|
||||
@ -22,7 +22,7 @@ from controllers.console.wraps import account_initialization_required, setup_req
|
||||
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
|
||||
from core.model_runtime.errors.invoke import InvokeError
|
||||
from libs.login import login_required
|
||||
from models import App, AppMode
|
||||
from models.model import AppMode
|
||||
from services.audio_service import AudioService
|
||||
from services.errors.audio import (
|
||||
AudioTooLargeServiceError,
|
||||
@ -79,7 +79,7 @@ class ChatMessageTextApi(Resource):
|
||||
@login_required
|
||||
@account_initialization_required
|
||||
@get_app_model
|
||||
def post(self, app_model: App):
|
||||
def post(self, app_model):
|
||||
from werkzeug.exceptions import InternalServerError
|
||||
|
||||
try:
|
||||
@ -98,13 +98,9 @@ class ChatMessageTextApi(Resource):
|
||||
and app_model.workflow.features_dict
|
||||
):
|
||||
text_to_speech = app_model.workflow.features_dict.get("text_to_speech")
|
||||
if text_to_speech is None:
|
||||
raise ValueError("TTS is not enabled")
|
||||
voice = args.get("voice") or text_to_speech.get("voice")
|
||||
else:
|
||||
try:
|
||||
if app_model.app_model_config is None:
|
||||
raise ValueError("AppModelConfig not found")
|
||||
voice = args.get("voice") or app_model.app_model_config.text_to_speech_dict.get("voice")
|
||||
except Exception:
|
||||
voice = None
|
||||
|
||||
@ -20,6 +20,7 @@ from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpErr
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.errors.error import (
|
||||
AppInvokeQuotaExceededError,
|
||||
ModelCurrentlyNotSupportError,
|
||||
ProviderTokenNotInitError,
|
||||
QuotaExceededError,
|
||||
@ -75,7 +76,7 @@ class CompletionMessageApi(Resource):
|
||||
raise ProviderModelCurrentlyNotSupportError()
|
||||
except InvokeError as e:
|
||||
raise CompletionRequestError(e.description)
|
||||
except ValueError as e:
|
||||
except (ValueError, AppInvokeQuotaExceededError) as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception("internal server error.")
|
||||
@ -140,7 +141,7 @@ class ChatMessageApi(Resource):
|
||||
raise InvokeRateLimitHttpError(ex.description)
|
||||
except InvokeError as e:
|
||||
raise CompletionRequestError(e.description)
|
||||
except ValueError as e:
|
||||
except (ValueError, AppInvokeQuotaExceededError) as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception("internal server error.")
|
||||
|
||||
@ -273,7 +273,8 @@ FROM
|
||||
messages m
|
||||
ON c.id = m.conversation_id
|
||||
WHERE
|
||||
c.app_id = :app_id"""
|
||||
c.override_model_configs IS NULL
|
||||
AND c.app_id = :app_id"""
|
||||
arg_dict = {"tz": account.timezone, "app_id": app_model.id}
|
||||
|
||||
timezone = pytz.timezone(account.timezone)
|
||||
|
||||
@ -2,7 +2,7 @@ import json
|
||||
import logging
|
||||
|
||||
from flask import abort, request
|
||||
from flask_restful import Resource, inputs, marshal_with, reqparse # type: ignore
|
||||
from flask_restful import Resource, marshal_with, reqparse # type: ignore
|
||||
from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
|
||||
|
||||
import services
|
||||
@ -14,7 +14,7 @@ from controllers.console.wraps import account_initialization_required, setup_req
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from factories import variable_factory
|
||||
from fields.workflow_fields import workflow_fields, workflow_pagination_fields
|
||||
from fields.workflow_fields import workflow_fields
|
||||
from fields.workflow_run_fields import workflow_run_node_execution_fields
|
||||
from libs import helper
|
||||
from libs.helper import TimestampField, uuid_value
|
||||
@ -440,29 +440,29 @@ class WorkflowConfigApi(Resource):
|
||||
}
|
||||
|
||||
|
||||
class PublishedAllWorkflowApi(Resource):
|
||||
class DraftWorkflowNodeRetriableApi(Resource):
|
||||
@setup_required
|
||||
@login_required
|
||||
@account_initialization_required
|
||||
@get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
|
||||
@marshal_with(workflow_pagination_fields)
|
||||
def get(self, app_model: App):
|
||||
@marshal_with(workflow_run_node_execution_fields)
|
||||
def post(self, app_model: App, node_id: str):
|
||||
"""
|
||||
Get published workflows
|
||||
Run draft workflow node
|
||||
"""
|
||||
# The role of the current user in the ta table must be admin, owner, or editor
|
||||
if not current_user.is_editor:
|
||||
raise Forbidden()
|
||||
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("page", type=inputs.int_range(1, 99999), required=False, default=1, location="args")
|
||||
parser.add_argument("limit", type=inputs.int_range(1, 100), required=False, default=20, location="args")
|
||||
parser.add_argument("inputs", type=dict, required=True, nullable=False, location="json")
|
||||
args = parser.parse_args()
|
||||
page = args.get("page")
|
||||
limit = args.get("limit")
|
||||
workflow_service = WorkflowService()
|
||||
workflows, has_more = workflow_service.get_all_published_workflow(app_model=app_model, page=page, limit=limit)
|
||||
workflow_node_execution = workflow_service.run_retriable_draft_workflow_node(
|
||||
app_model=app_model, node_id=node_id, user_inputs=args.get("inputs", {}), account=current_user
|
||||
)
|
||||
|
||||
return {"items": workflows, "page": page, "limit": limit, "has_more": has_more}
|
||||
return workflow_node_execution
|
||||
|
||||
|
||||
api.add_resource(DraftWorkflowApi, "/apps/<uuid:app_id>/workflows/draft")
|
||||
@ -479,9 +479,9 @@ api.add_resource(
|
||||
WorkflowDraftRunIterationNodeApi, "/apps/<uuid:app_id>/workflows/draft/iteration/nodes/<string:node_id>/run"
|
||||
)
|
||||
api.add_resource(PublishedWorkflowApi, "/apps/<uuid:app_id>/workflows/publish")
|
||||
api.add_resource(PublishedAllWorkflowApi, "/apps/<uuid:app_id>/workflows")
|
||||
api.add_resource(DefaultBlockConfigsApi, "/apps/<uuid:app_id>/workflows/default-workflow-block-configs")
|
||||
api.add_resource(
|
||||
DefaultBlockConfigApi, "/apps/<uuid:app_id>/workflows/default-workflow-block-configs/<string:block_type>"
|
||||
)
|
||||
api.add_resource(ConvertToWorkflowApi, "/apps/<uuid:app_id>/convert-to-workflow")
|
||||
api.add_resource(DraftWorkflowNodeRetriableApi, "/apps/<uuid:app_id>/workflows/draft/retry/nodes/<string:node_id>/run")
|
||||
|
||||
@ -53,9 +53,3 @@ class EmailCodeLoginRateLimitExceededError(BaseHTTPException):
|
||||
error_code = "email_code_login_rate_limit_exceeded"
|
||||
description = "Too many login emails have been sent. Please try again in 5 minutes."
|
||||
code = 429
|
||||
|
||||
|
||||
class EmailCodeAccountDeletionRateLimitExceededError(BaseHTTPException):
|
||||
error_code = "email_code_account_deletion_rate_limit_exceeded"
|
||||
description = "Too many account deletion emails have been sent. Please try again in 5 minutes."
|
||||
code = 429
|
||||
|
||||
@ -6,23 +6,26 @@ from flask_restful import Resource, reqparse # type: ignore
|
||||
|
||||
from constants.languages import languages
|
||||
from controllers.console import api
|
||||
from controllers.console.auth.error import EmailCodeError, InvalidEmailError, InvalidTokenError, PasswordMismatchError
|
||||
from controllers.console.error import AccountInFreezeError, AccountNotFound, EmailSendIpLimitError
|
||||
from controllers.console.wraps import email_password_login_enabled, setup_required
|
||||
from controllers.console.auth.error import (
|
||||
EmailCodeError,
|
||||
InvalidEmailError,
|
||||
InvalidTokenError,
|
||||
PasswordMismatchError,
|
||||
)
|
||||
from controllers.console.error import AccountNotFound, EmailSendIpLimitError
|
||||
from controllers.console.wraps import setup_required
|
||||
from events.tenant_event import tenant_was_created
|
||||
from extensions.ext_database import db
|
||||
from libs.helper import email, extract_remote_ip
|
||||
from libs.password import hash_password, valid_password
|
||||
from models.account import Account
|
||||
from services.account_service import AccountService, TenantService
|
||||
from services.errors.account import AccountRegisterError
|
||||
from services.errors.workspace import WorkSpaceNotAllowedCreateError
|
||||
from services.feature_service import FeatureService
|
||||
|
||||
|
||||
class ForgotPasswordSendEmailApi(Resource):
|
||||
@setup_required
|
||||
@email_password_login_enabled
|
||||
def post(self):
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("email", type=email, required=True, location="json")
|
||||
@ -54,7 +57,6 @@ class ForgotPasswordSendEmailApi(Resource):
|
||||
|
||||
class ForgotPasswordCheckApi(Resource):
|
||||
@setup_required
|
||||
@email_password_login_enabled
|
||||
def post(self):
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("email", type=str, required=True, location="json")
|
||||
@ -74,20 +76,11 @@ class ForgotPasswordCheckApi(Resource):
|
||||
if args["code"] != token_data.get("code"):
|
||||
raise EmailCodeError()
|
||||
|
||||
# Verified, revoke the first token
|
||||
AccountService.revoke_reset_password_token(args["token"])
|
||||
|
||||
# Refresh token data by generating a new token
|
||||
_, new_token = AccountService.generate_reset_password_token(
|
||||
user_email, code=args["code"], additional_data={"phase": "reset"}
|
||||
)
|
||||
|
||||
return {"is_valid": True, "email": token_data.get("email"), "token": new_token}
|
||||
return {"is_valid": True, "email": token_data.get("email")}
|
||||
|
||||
|
||||
class ForgotPasswordResetApi(Resource):
|
||||
@setup_required
|
||||
@email_password_login_enabled
|
||||
def post(self):
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("token", type=str, required=True, nullable=False, location="json")
|
||||
@ -106,9 +99,6 @@ class ForgotPasswordResetApi(Resource):
|
||||
|
||||
if reset_data is None:
|
||||
raise InvalidTokenError()
|
||||
# Must use token in reset phase
|
||||
if reset_data.get("phase", "") != "reset":
|
||||
raise InvalidTokenError()
|
||||
|
||||
AccountService.revoke_reset_password_token(token)
|
||||
|
||||
@ -139,8 +129,6 @@ class ForgotPasswordResetApi(Resource):
|
||||
)
|
||||
except WorkSpaceNotAllowedCreateError:
|
||||
pass
|
||||
except AccountRegisterError as are:
|
||||
raise AccountInFreezeError()
|
||||
|
||||
return {"result": "success"}
|
||||
|
||||
|
||||
@ -5,7 +5,6 @@ from flask import request
|
||||
from flask_restful import Resource, reqparse # type: ignore
|
||||
|
||||
import services
|
||||
from configs import dify_config
|
||||
from constants.languages import languages
|
||||
from controllers.console import api
|
||||
from controllers.console.auth.error import (
|
||||
@ -17,19 +16,16 @@ from controllers.console.auth.error import (
|
||||
)
|
||||
from controllers.console.error import (
|
||||
AccountBannedError,
|
||||
AccountInFreezeError,
|
||||
AccountNotFound,
|
||||
EmailSendIpLimitError,
|
||||
NotAllowedCreateWorkspace,
|
||||
)
|
||||
from controllers.console.wraps import email_password_login_enabled, setup_required
|
||||
from controllers.console.wraps import setup_required
|
||||
from events.tenant_event import tenant_was_created
|
||||
from libs.helper import email, extract_remote_ip
|
||||
from libs.password import valid_password
|
||||
from models.account import Account
|
||||
from services.account_service import AccountService, RegisterService, TenantService
|
||||
from services.billing_service import BillingService
|
||||
from services.errors.account import AccountRegisterError
|
||||
from services.errors.workspace import WorkSpaceNotAllowedCreateError
|
||||
from services.feature_service import FeatureService
|
||||
|
||||
@ -38,7 +34,6 @@ class LoginApi(Resource):
|
||||
"""Resource for user login."""
|
||||
|
||||
@setup_required
|
||||
@email_password_login_enabled
|
||||
def post(self):
|
||||
"""Authenticate user and login."""
|
||||
parser = reqparse.RequestParser()
|
||||
@ -49,9 +44,6 @@ class LoginApi(Resource):
|
||||
parser.add_argument("language", type=str, required=False, default="en-US", location="json")
|
||||
args = parser.parse_args()
|
||||
|
||||
if dify_config.BILLING_ENABLED and BillingService.is_email_in_freeze(args["email"]):
|
||||
raise AccountInFreezeError()
|
||||
|
||||
is_login_error_rate_limit = AccountService.is_login_error_rate_limit(args["email"])
|
||||
if is_login_error_rate_limit:
|
||||
raise EmailPasswordLoginLimitError()
|
||||
@ -111,7 +103,6 @@ class LogoutApi(Resource):
|
||||
|
||||
class ResetPasswordSendEmailApi(Resource):
|
||||
@setup_required
|
||||
@email_password_login_enabled
|
||||
def post(self):
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("email", type=email, required=True, location="json")
|
||||
@ -122,10 +113,8 @@ class ResetPasswordSendEmailApi(Resource):
|
||||
language = "zh-Hans"
|
||||
else:
|
||||
language = "en-US"
|
||||
try:
|
||||
account = AccountService.get_user_through_email(args["email"])
|
||||
except AccountRegisterError as are:
|
||||
raise AccountInFreezeError()
|
||||
|
||||
account = AccountService.get_user_through_email(args["email"])
|
||||
if account is None:
|
||||
if FeatureService.get_system_features().is_allow_register:
|
||||
token = AccountService.send_reset_password_email(email=args["email"], language=language)
|
||||
@ -153,11 +142,8 @@ class EmailCodeLoginSendEmailApi(Resource):
|
||||
language = "zh-Hans"
|
||||
else:
|
||||
language = "en-US"
|
||||
try:
|
||||
account = AccountService.get_user_through_email(args["email"])
|
||||
except AccountRegisterError as are:
|
||||
raise AccountInFreezeError()
|
||||
|
||||
account = AccountService.get_user_through_email(args["email"])
|
||||
if account is None:
|
||||
if FeatureService.get_system_features().is_allow_register:
|
||||
token = AccountService.send_email_code_login_email(email=args["email"], language=language)
|
||||
@ -191,10 +177,7 @@ class EmailCodeLoginApi(Resource):
|
||||
raise EmailCodeError()
|
||||
|
||||
AccountService.revoke_email_code_login_token(args["token"])
|
||||
try:
|
||||
account = AccountService.get_user_through_email(user_email)
|
||||
except AccountRegisterError as are:
|
||||
raise AccountInFreezeError()
|
||||
account = AccountService.get_user_through_email(user_email)
|
||||
if account:
|
||||
tenant = TenantService.get_join_tenants(account)
|
||||
if not tenant:
|
||||
@ -213,8 +196,6 @@ class EmailCodeLoginApi(Resource):
|
||||
)
|
||||
except WorkSpaceNotAllowedCreateError:
|
||||
return NotAllowedCreateWorkspace()
|
||||
except AccountRegisterError as are:
|
||||
raise AccountInFreezeError()
|
||||
token_pair = AccountService.login(account, ip_address=extract_remote_ip(request))
|
||||
AccountService.reset_login_error_rate_limit(args["email"])
|
||||
return {"result": "success", "data": token_pair.model_dump()}
|
||||
|
||||
@ -16,7 +16,7 @@ from libs.oauth import GitHubOAuth, GoogleOAuth, OAuthUserInfo
|
||||
from models import Account
|
||||
from models.account import AccountStatus
|
||||
from services.account_service import AccountService, RegisterService, TenantService
|
||||
from services.errors.account import AccountNotFoundError, AccountRegisterError
|
||||
from services.errors.account import AccountNotFoundError
|
||||
from services.errors.workspace import WorkSpaceNotAllowedCreateError, WorkSpaceNotFoundError
|
||||
from services.feature_service import FeatureService
|
||||
|
||||
@ -99,8 +99,6 @@ class OAuthCallback(Resource):
|
||||
f"{dify_config.CONSOLE_WEB_URL}/signin"
|
||||
"?message=Workspace not found, please contact system admin to invite you to join in a workspace."
|
||||
)
|
||||
except AccountRegisterError as e:
|
||||
return redirect(f"{dify_config.CONSOLE_WEB_URL}/signin?message={e.description}")
|
||||
|
||||
# Check account status
|
||||
if account.status == AccountStatus.BANNED.value:
|
||||
|
||||
@ -52,12 +52,12 @@ class DatasetListApi(Resource):
|
||||
# provider = request.args.get("provider", default="vendor")
|
||||
search = request.args.get("keyword", default=None, type=str)
|
||||
tag_ids = request.args.getlist("tag_ids")
|
||||
include_all = request.args.get("include_all", default="false").lower() == "true"
|
||||
|
||||
if ids:
|
||||
datasets, total = DatasetService.get_datasets_by_ids(ids, current_user.current_tenant_id)
|
||||
else:
|
||||
datasets, total = DatasetService.get_datasets(
|
||||
page, limit, current_user.current_tenant_id, current_user, search, tag_ids, include_all
|
||||
page, limit, current_user.current_tenant_id, current_user, search, tag_ids
|
||||
)
|
||||
|
||||
# check embedding setting
|
||||
@ -457,7 +457,7 @@ class DatasetIndexingEstimateApi(Resource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider " "in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
@ -619,7 +619,9 @@ class DatasetRetrievalSettingApi(Resource):
|
||||
vector_type = dify_config.VECTOR_STORE
|
||||
match vector_type:
|
||||
case (
|
||||
VectorType.RELYT
|
||||
VectorType.MILVUS
|
||||
| VectorType.RELYT
|
||||
| VectorType.PGVECTOR
|
||||
| VectorType.TIDB_VECTOR
|
||||
| VectorType.CHROMA
|
||||
| VectorType.TENCENT
|
||||
@ -638,12 +640,10 @@ class DatasetRetrievalSettingApi(Resource):
|
||||
| VectorType.MYSCALE
|
||||
| VectorType.ORACLE
|
||||
| VectorType.ELASTICSEARCH
|
||||
| VectorType.ELASTICSEARCH_JA
|
||||
| VectorType.PGVECTOR
|
||||
| VectorType.TIDB_ON_QDRANT
|
||||
| VectorType.LINDORM
|
||||
| VectorType.COUCHBASE
|
||||
| VectorType.MILVUS
|
||||
):
|
||||
return {
|
||||
"retrieval_method": [
|
||||
@ -683,7 +683,6 @@ class DatasetRetrievalSettingMockApi(Resource):
|
||||
| VectorType.MYSCALE
|
||||
| VectorType.ORACLE
|
||||
| VectorType.ELASTICSEARCH
|
||||
| VectorType.ELASTICSEARCH_JA
|
||||
| VectorType.COUCHBASE
|
||||
| VectorType.PGVECTOR
|
||||
| VectorType.LINDORM
|
||||
|
||||
@ -257,8 +257,7 @@ class DatasetDocumentListApi(Resource):
|
||||
parser.add_argument("original_document_id", type=str, required=False, location="json")
|
||||
parser.add_argument("doc_form", type=str, default="text_model", required=False, nullable=False, location="json")
|
||||
parser.add_argument("retrieval_model", type=dict, required=False, nullable=False, location="json")
|
||||
parser.add_argument("embedding_model", type=str, required=False, nullable=True, location="json")
|
||||
parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
|
||||
|
||||
parser.add_argument(
|
||||
"doc_language", type=str, default="English", required=False, nullable=False, location="json"
|
||||
)
|
||||
@ -350,7 +349,8 @@ class DatasetInitApi(Resource):
|
||||
)
|
||||
except InvokeAuthorizationError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
@ -525,7 +525,8 @@ class DocumentBatchIndexingEstimateApi(DocumentResource):
|
||||
return response.model_dump(), 200
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
|
||||
@ -168,7 +168,8 @@ class DatasetDocumentSegmentApi(Resource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
@ -216,7 +217,8 @@ class DatasetDocumentSegmentAddApi(Resource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
@ -265,7 +267,8 @@ class DatasetDocumentSegmentUpdateApi(Resource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
@ -365,9 +368,9 @@ class DatasetDocumentSegmentBatchImportApi(Resource):
|
||||
result = []
|
||||
for index, row in df.iterrows():
|
||||
if document.doc_form == "qa_model":
|
||||
data = {"content": row.iloc[0], "answer": row.iloc[1]}
|
||||
data = {"content": row[0], "answer": row[1]}
|
||||
else:
|
||||
data = {"content": row.iloc[0]}
|
||||
data = {"content": row[0]}
|
||||
result.append(data)
|
||||
if len(result) == 0:
|
||||
raise ValueError("The CSV file is empty.")
|
||||
@ -434,7 +437,8 @@ class ChildChunkAddApi(Resource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
|
||||
@ -92,12 +92,3 @@ class UnauthorizedAndForceLogout(BaseHTTPException):
|
||||
error_code = "unauthorized_and_force_logout"
|
||||
description = "Unauthorized and force logout."
|
||||
code = 401
|
||||
|
||||
|
||||
class AccountInFreezeError(BaseHTTPException):
|
||||
error_code = "account_in_freeze"
|
||||
code = 400
|
||||
description = (
|
||||
"This email account has been deleted within the past 30 days"
|
||||
"and is temporarily unavailable for new account registration."
|
||||
)
|
||||
|
||||
@ -18,11 +18,7 @@ from controllers.console.explore.error import NotChatAppError, NotCompletionAppE
|
||||
from controllers.console.explore.wraps import InstalledAppResource
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.errors.error import (
|
||||
ModelCurrentlyNotSupportError,
|
||||
ProviderTokenNotInitError,
|
||||
QuotaExceededError,
|
||||
)
|
||||
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
|
||||
from core.model_runtime.errors.invoke import InvokeError
|
||||
from extensions.ext_database import db
|
||||
from libs import helper
|
||||
|
||||
@ -32,7 +32,7 @@ class ConversationListApi(InstalledAppResource):
|
||||
|
||||
pinned = None
|
||||
if "pinned" in args and args["pinned"] is not None:
|
||||
pinned = args["pinned"] == "true"
|
||||
pinned = True if args["pinned"] == "true" else False
|
||||
|
||||
try:
|
||||
with Session(db.engine) as session:
|
||||
|
||||
@ -50,7 +50,7 @@ class MessageListApi(InstalledAppResource):
|
||||
|
||||
try:
|
||||
return MessageService.pagination_by_first_id(
|
||||
app_model, current_user, args["conversation_id"], args["first_id"], args["limit"]
|
||||
app_model, current_user, args["conversation_id"], args["first_id"], args["limit"], "desc"
|
||||
)
|
||||
except services.errors.conversation.ConversationNotExistsError:
|
||||
raise NotFound("Conversation Not Exists.")
|
||||
@ -66,17 +66,10 @@ class MessageFeedbackApi(InstalledAppResource):
|
||||
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("rating", type=str, choices=["like", "dislike", None], location="json")
|
||||
parser.add_argument("content", type=str, location="json")
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
MessageService.create_feedback(
|
||||
app_model=app_model,
|
||||
message_id=message_id,
|
||||
user=current_user,
|
||||
rating=args.get("rating"),
|
||||
content=args.get("content"),
|
||||
)
|
||||
MessageService.create_feedback(app_model, message_id, current_user, args.get("rating"), args.get("content"))
|
||||
except services.errors.message.MessageNotExistsError:
|
||||
raise NotFound("Message Not Exists.")
|
||||
|
||||
|
||||
@ -13,11 +13,7 @@ from controllers.console.explore.error import NotWorkflowAppError
|
||||
from controllers.console.explore.wraps import InstalledAppResource
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.errors.error import (
|
||||
ModelCurrentlyNotSupportError,
|
||||
ProviderTokenNotInitError,
|
||||
QuotaExceededError,
|
||||
)
|
||||
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
|
||||
from core.model_runtime.errors.invoke import InvokeError
|
||||
from libs import helper
|
||||
from libs.login import current_user
|
||||
|
||||
@ -11,7 +11,6 @@ from controllers.console import api
|
||||
from controllers.console.workspace.error import (
|
||||
AccountAlreadyInitedError,
|
||||
CurrentPasswordIncorrectError,
|
||||
InvalidAccountDeletionCodeError,
|
||||
InvalidInvitationCodeError,
|
||||
RepeatPasswordNotMatchError,
|
||||
)
|
||||
@ -22,7 +21,6 @@ from libs.helper import TimestampField, timezone
|
||||
from libs.login import login_required
|
||||
from models import AccountIntegrate, InvitationCode
|
||||
from services.account_service import AccountService
|
||||
from services.billing_service import BillingService
|
||||
from services.errors.account import CurrentPasswordIncorrectError as ServiceCurrentPasswordIncorrectError
|
||||
|
||||
|
||||
@ -244,54 +242,6 @@ class AccountIntegrateApi(Resource):
|
||||
return {"data": integrate_data}
|
||||
|
||||
|
||||
class AccountDeleteVerifyApi(Resource):
|
||||
@setup_required
|
||||
@login_required
|
||||
@account_initialization_required
|
||||
def get(self):
|
||||
account = current_user
|
||||
|
||||
token, code = AccountService.generate_account_deletion_verification_code(account)
|
||||
AccountService.send_account_deletion_verification_email(account, code)
|
||||
|
||||
return {"result": "success", "data": token}
|
||||
|
||||
|
||||
class AccountDeleteApi(Resource):
|
||||
@setup_required
|
||||
@login_required
|
||||
@account_initialization_required
|
||||
def post(self):
|
||||
account = current_user
|
||||
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("token", type=str, required=True, location="json")
|
||||
parser.add_argument("code", type=str, required=True, location="json")
|
||||
args = parser.parse_args()
|
||||
|
||||
if not AccountService.verify_account_deletion_code(args["token"], args["code"]):
|
||||
raise InvalidAccountDeletionCodeError()
|
||||
|
||||
AccountService.delete_account(account)
|
||||
|
||||
return {"result": "success"}
|
||||
|
||||
|
||||
class AccountDeleteUpdateFeedbackApi(Resource):
|
||||
@setup_required
|
||||
def post(self):
|
||||
account = current_user
|
||||
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("email", type=str, required=True, location="json")
|
||||
parser.add_argument("feedback", type=str, required=True, location="json")
|
||||
args = parser.parse_args()
|
||||
|
||||
BillingService.update_account_deletion_feedback(args["email"], args["feedback"])
|
||||
|
||||
return {"result": "success"}
|
||||
|
||||
|
||||
# Register API resources
|
||||
api.add_resource(AccountInitApi, "/account/init")
|
||||
api.add_resource(AccountProfileApi, "/account/profile")
|
||||
@ -302,8 +252,5 @@ api.add_resource(AccountInterfaceThemeApi, "/account/interface-theme")
|
||||
api.add_resource(AccountTimezoneApi, "/account/timezone")
|
||||
api.add_resource(AccountPasswordApi, "/account/password")
|
||||
api.add_resource(AccountIntegrateApi, "/account/integrates")
|
||||
api.add_resource(AccountDeleteVerifyApi, "/account/delete/verify")
|
||||
api.add_resource(AccountDeleteApi, "/account/delete")
|
||||
api.add_resource(AccountDeleteUpdateFeedbackApi, "/account/delete/feedback")
|
||||
# api.add_resource(AccountEmailApi, '/account/email')
|
||||
# api.add_resource(AccountEmailVerifyApi, '/account/email-verify')
|
||||
|
||||
@ -35,9 +35,3 @@ class AccountNotInitializedError(BaseHTTPException):
|
||||
error_code = "account_not_initialized"
|
||||
description = "The account has not been initialized yet. Please proceed with the initialization process first."
|
||||
code = 400
|
||||
|
||||
|
||||
class InvalidAccountDeletionCodeError(BaseHTTPException):
|
||||
error_code = "invalid_account_deletion_code"
|
||||
description = "Invalid account deletion code."
|
||||
code = 400
|
||||
|
||||
@ -122,7 +122,7 @@ class MemberUpdateRoleApi(Resource):
|
||||
return {"code": "invalid-role", "message": "Invalid role"}, 400
|
||||
|
||||
member = db.session.get(Account, str(member_id))
|
||||
if not member:
|
||||
if member:
|
||||
abort(404)
|
||||
|
||||
try:
|
||||
|
||||
@ -154,16 +154,3 @@ def enterprise_license_required(view):
|
||||
return view(*args, **kwargs)
|
||||
|
||||
return decorated
|
||||
|
||||
|
||||
def email_password_login_enabled(view):
|
||||
@wraps(view)
|
||||
def decorated(*args, **kwargs):
|
||||
features = FeatureService.get_system_features()
|
||||
if features.enable_email_password_login:
|
||||
return view(*args, **kwargs)
|
||||
|
||||
# otherwise, return 403
|
||||
abort(403)
|
||||
|
||||
return decorated
|
||||
|
||||
@ -1,5 +1,3 @@
|
||||
import json
|
||||
|
||||
from flask_restful import Resource, reqparse # type: ignore
|
||||
|
||||
from controllers.console.wraps import setup_required
|
||||
@ -31,34 +29,4 @@ class EnterpriseWorkspace(Resource):
|
||||
return {"message": "enterprise workspace created."}
|
||||
|
||||
|
||||
class EnterpriseWorkspaceNoOwnerEmail(Resource):
|
||||
@setup_required
|
||||
@inner_api_only
|
||||
def post(self):
|
||||
parser = reqparse.RequestParser()
|
||||
parser.add_argument("name", type=str, required=True, location="json")
|
||||
args = parser.parse_args()
|
||||
|
||||
tenant = TenantService.create_tenant(args["name"], is_from_dashboard=True)
|
||||
|
||||
tenant_was_created.send(tenant)
|
||||
|
||||
resp = {
|
||||
"id": tenant.id,
|
||||
"name": tenant.name,
|
||||
"encrypt_public_key": tenant.encrypt_public_key,
|
||||
"plan": tenant.plan,
|
||||
"status": tenant.status,
|
||||
"custom_config": json.loads(tenant.custom_config) if tenant.custom_config else {},
|
||||
"created_at": tenant.created_at.isoformat() if tenant.created_at else None,
|
||||
"updated_at": tenant.updated_at.isoformat() if tenant.updated_at else None,
|
||||
}
|
||||
|
||||
return {
|
||||
"message": "enterprise workspace created.",
|
||||
"tenant": resp,
|
||||
}
|
||||
|
||||
|
||||
api.add_resource(EnterpriseWorkspace, "/enterprise/workspace")
|
||||
api.add_resource(EnterpriseWorkspaceNoOwnerEmail, "/enterprise/workspace/ownerless")
|
||||
|
||||
@ -7,4 +7,4 @@ api = ExternalApi(bp)
|
||||
|
||||
from . import index
|
||||
from .app import app, audio, completion, conversation, file, message, workflow
|
||||
from .dataset import dataset, document, hit_testing, segment, upload_file
|
||||
from .dataset import dataset, document, hit_testing, segment
|
||||
|
||||
@ -18,6 +18,7 @@ from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.errors.error import (
|
||||
AppInvokeQuotaExceededError,
|
||||
ModelCurrentlyNotSupportError,
|
||||
ProviderTokenNotInitError,
|
||||
QuotaExceededError,
|
||||
@ -73,7 +74,7 @@ class CompletionApi(Resource):
|
||||
raise ProviderModelCurrentlyNotSupportError()
|
||||
except InvokeError as e:
|
||||
raise CompletionRequestError(e.description)
|
||||
except ValueError as e:
|
||||
except (ValueError, AppInvokeQuotaExceededError) as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception("internal server error.")
|
||||
@ -132,7 +133,7 @@ class ChatApi(Resource):
|
||||
raise ProviderModelCurrentlyNotSupportError()
|
||||
except InvokeError as e:
|
||||
raise CompletionRequestError(e.description)
|
||||
except ValueError as e:
|
||||
except (ValueError, AppInvokeQuotaExceededError) as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception("internal server error.")
|
||||
|
||||
@ -108,13 +108,7 @@ class MessageFeedbackApi(Resource):
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
MessageService.create_feedback(
|
||||
app_model=app_model,
|
||||
message_id=message_id,
|
||||
user=end_user,
|
||||
rating=args.get("rating"),
|
||||
content=args.get("content"),
|
||||
)
|
||||
MessageService.create_feedback(app_model, message_id, end_user, args.get("rating"), args.get("content"))
|
||||
except services.errors.message.MessageNotExistsError:
|
||||
raise NotFound("Message Not Exists.")
|
||||
|
||||
|
||||
@ -16,6 +16,7 @@ from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.errors.error import (
|
||||
AppInvokeQuotaExceededError,
|
||||
ModelCurrentlyNotSupportError,
|
||||
ProviderTokenNotInitError,
|
||||
QuotaExceededError,
|
||||
@ -93,7 +94,7 @@ class WorkflowRunApi(Resource):
|
||||
raise ProviderModelCurrentlyNotSupportError()
|
||||
except InvokeError as e:
|
||||
raise CompletionRequestError(e.description)
|
||||
except ValueError as e:
|
||||
except (ValueError, AppInvokeQuotaExceededError) as e:
|
||||
raise e
|
||||
except Exception as e:
|
||||
logging.exception("internal server error.")
|
||||
|
||||
@ -31,11 +31,8 @@ class DatasetListApi(DatasetApiResource):
|
||||
# provider = request.args.get("provider", default="vendor")
|
||||
search = request.args.get("keyword", default=None, type=str)
|
||||
tag_ids = request.args.getlist("tag_ids")
|
||||
include_all = request.args.get("include_all", default="false").lower() == "true"
|
||||
|
||||
datasets, total = DatasetService.get_datasets(
|
||||
page, limit, tenant_id, current_user, search, tag_ids, include_all
|
||||
)
|
||||
datasets, total = DatasetService.get_datasets(page, limit, tenant_id, current_user, search, tag_ids)
|
||||
# check embedding setting
|
||||
provider_manager = ProviderManager()
|
||||
configurations = provider_manager.get_configurations(tenant_id=current_user.current_tenant_id)
|
||||
|
||||
@ -8,17 +8,12 @@ from werkzeug.exceptions import NotFound
|
||||
import services.dataset_service
|
||||
from controllers.common.errors import FilenameNotExistsError
|
||||
from controllers.service_api import api
|
||||
from controllers.service_api.app.error import (
|
||||
FileTooLargeError,
|
||||
NoFileUploadedError,
|
||||
ProviderNotInitializeError,
|
||||
TooManyFilesError,
|
||||
UnsupportedFileTypeError,
|
||||
)
|
||||
from controllers.service_api.app.error import ProviderNotInitializeError
|
||||
from controllers.service_api.dataset.error import (
|
||||
ArchivedDocumentImmutableError,
|
||||
DocumentIndexingError,
|
||||
InvalidMetadataError,
|
||||
NoFileUploadedError,
|
||||
TooManyFilesError,
|
||||
)
|
||||
from controllers.service_api.wraps import DatasetApiResource, cloud_edition_billing_resource_check
|
||||
from core.errors.error import ProviderTokenNotInitError
|
||||
@ -51,9 +46,6 @@ class DocumentAddByTextApi(DatasetApiResource):
|
||||
"indexing_technique", type=str, choices=Dataset.INDEXING_TECHNIQUE_LIST, nullable=False, location="json"
|
||||
)
|
||||
parser.add_argument("retrieval_model", type=dict, required=False, nullable=False, location="json")
|
||||
parser.add_argument("doc_type", type=str, required=False, nullable=True, location="json")
|
||||
parser.add_argument("doc_metadata", type=dict, required=False, nullable=True, location="json")
|
||||
|
||||
args = parser.parse_args()
|
||||
dataset_id = str(dataset_id)
|
||||
tenant_id = str(tenant_id)
|
||||
@ -65,28 +57,6 @@ class DocumentAddByTextApi(DatasetApiResource):
|
||||
if not dataset.indexing_technique and not args["indexing_technique"]:
|
||||
raise ValueError("indexing_technique is required.")
|
||||
|
||||
# Validate metadata if provided
|
||||
if args.get("doc_type") or args.get("doc_metadata"):
|
||||
if not args.get("doc_type") or not args.get("doc_metadata"):
|
||||
raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
|
||||
|
||||
if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
|
||||
raise InvalidMetadataError(
|
||||
"Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
|
||||
)
|
||||
|
||||
if not isinstance(args["doc_metadata"], dict):
|
||||
raise InvalidMetadataError("doc_metadata must be a dictionary")
|
||||
|
||||
# Validate metadata schema based on doc_type
|
||||
if args["doc_type"] != "others":
|
||||
metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
|
||||
for key, value in args["doc_metadata"].items():
|
||||
if key in metadata_schema and not isinstance(value, metadata_schema[key]):
|
||||
raise InvalidMetadataError(f"Invalid type for metadata field {key}")
|
||||
# set to MetaDataConfig
|
||||
args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
|
||||
|
||||
text = args.get("text")
|
||||
name = args.get("name")
|
||||
if text is None or name is None:
|
||||
@ -133,8 +103,6 @@ class DocumentUpdateByTextApi(DatasetApiResource):
|
||||
"doc_language", type=str, default="English", required=False, nullable=False, location="json"
|
||||
)
|
||||
parser.add_argument("retrieval_model", type=dict, required=False, nullable=False, location="json")
|
||||
parser.add_argument("doc_type", type=str, required=False, nullable=True, location="json")
|
||||
parser.add_argument("doc_metadata", type=dict, required=False, nullable=True, location="json")
|
||||
args = parser.parse_args()
|
||||
dataset_id = str(dataset_id)
|
||||
tenant_id = str(tenant_id)
|
||||
@ -143,32 +111,6 @@ class DocumentUpdateByTextApi(DatasetApiResource):
|
||||
if not dataset:
|
||||
raise ValueError("Dataset is not exist.")
|
||||
|
||||
# indexing_technique is already set in dataset since this is an update
|
||||
args["indexing_technique"] = dataset.indexing_technique
|
||||
|
||||
# Validate metadata if provided
|
||||
if args.get("doc_type") or args.get("doc_metadata"):
|
||||
if not args.get("doc_type") or not args.get("doc_metadata"):
|
||||
raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
|
||||
|
||||
if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
|
||||
raise InvalidMetadataError(
|
||||
"Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
|
||||
)
|
||||
|
||||
if not isinstance(args["doc_metadata"], dict):
|
||||
raise InvalidMetadataError("doc_metadata must be a dictionary")
|
||||
|
||||
# Validate metadata schema based on doc_type
|
||||
if args["doc_type"] != "others":
|
||||
metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
|
||||
for key, value in args["doc_metadata"].items():
|
||||
if key in metadata_schema and not isinstance(value, metadata_schema[key]):
|
||||
raise InvalidMetadataError(f"Invalid type for metadata field {key}")
|
||||
|
||||
# set to MetaDataConfig
|
||||
args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
|
||||
|
||||
if args["text"]:
|
||||
text = args.get("text")
|
||||
name = args.get("name")
|
||||
@ -215,30 +157,6 @@ class DocumentAddByFileApi(DatasetApiResource):
|
||||
args["doc_form"] = "text_model"
|
||||
if "doc_language" not in args:
|
||||
args["doc_language"] = "English"
|
||||
|
||||
# Validate metadata if provided
|
||||
if args.get("doc_type") or args.get("doc_metadata"):
|
||||
if not args.get("doc_type") or not args.get("doc_metadata"):
|
||||
raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
|
||||
|
||||
if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
|
||||
raise InvalidMetadataError(
|
||||
"Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
|
||||
)
|
||||
|
||||
if not isinstance(args["doc_metadata"], dict):
|
||||
raise InvalidMetadataError("doc_metadata must be a dictionary")
|
||||
|
||||
# Validate metadata schema based on doc_type
|
||||
if args["doc_type"] != "others":
|
||||
metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
|
||||
for key, value in args["doc_metadata"].items():
|
||||
if key in metadata_schema and not isinstance(value, metadata_schema[key]):
|
||||
raise InvalidMetadataError(f"Invalid type for metadata field {key}")
|
||||
|
||||
# set to MetaDataConfig
|
||||
args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
|
||||
|
||||
# get dataset info
|
||||
dataset_id = str(dataset_id)
|
||||
tenant_id = str(tenant_id)
|
||||
@ -268,10 +186,7 @@ class DocumentAddByFileApi(DatasetApiResource):
|
||||
user=current_user,
|
||||
source="datasets",
|
||||
)
|
||||
data_source = {
|
||||
"type": "upload_file",
|
||||
"info_list": {"data_source_type": "upload_file", "file_info_list": {"file_ids": [upload_file.id]}},
|
||||
}
|
||||
data_source = {"type": "upload_file", "info_list": {"file_info_list": {"file_ids": [upload_file.id]}}}
|
||||
args["data_source"] = data_source
|
||||
# validate args
|
||||
knowledge_config = KnowledgeConfig(**args)
|
||||
@ -306,29 +221,6 @@ class DocumentUpdateByFileApi(DatasetApiResource):
|
||||
if "doc_language" not in args:
|
||||
args["doc_language"] = "English"
|
||||
|
||||
# Validate metadata if provided
|
||||
if args.get("doc_type") or args.get("doc_metadata"):
|
||||
if not args.get("doc_type") or not args.get("doc_metadata"):
|
||||
raise InvalidMetadataError("Both doc_type and doc_metadata must be provided when adding metadata")
|
||||
|
||||
if args["doc_type"] not in DocumentService.DOCUMENT_METADATA_SCHEMA:
|
||||
raise InvalidMetadataError(
|
||||
"Invalid doc_type. Must be one of: " + ", ".join(DocumentService.DOCUMENT_METADATA_SCHEMA.keys())
|
||||
)
|
||||
|
||||
if not isinstance(args["doc_metadata"], dict):
|
||||
raise InvalidMetadataError("doc_metadata must be a dictionary")
|
||||
|
||||
# Validate metadata schema based on doc_type
|
||||
if args["doc_type"] != "others":
|
||||
metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[args["doc_type"]]
|
||||
for key, value in args["doc_metadata"].items():
|
||||
if key in metadata_schema and not isinstance(value, metadata_schema[key]):
|
||||
raise InvalidMetadataError(f"Invalid type for metadata field {key}")
|
||||
|
||||
# set to MetaDataConfig
|
||||
args["metadata"] = {"doc_type": args["doc_type"], "doc_metadata": args["doc_metadata"]}
|
||||
|
||||
# get dataset info
|
||||
dataset_id = str(dataset_id)
|
||||
tenant_id = str(tenant_id)
|
||||
@ -346,22 +238,14 @@ class DocumentUpdateByFileApi(DatasetApiResource):
|
||||
if not file.filename:
|
||||
raise FilenameNotExistsError
|
||||
|
||||
try:
|
||||
upload_file = FileService.upload_file(
|
||||
filename=file.filename,
|
||||
content=file.read(),
|
||||
mimetype=file.mimetype,
|
||||
user=current_user,
|
||||
source="datasets",
|
||||
)
|
||||
except services.errors.file.FileTooLargeError as file_too_large_error:
|
||||
raise FileTooLargeError(file_too_large_error.description)
|
||||
except services.errors.file.UnsupportedFileTypeError:
|
||||
raise UnsupportedFileTypeError()
|
||||
data_source = {
|
||||
"type": "upload_file",
|
||||
"info_list": {"data_source_type": "upload_file", "file_info_list": {"file_ids": [upload_file.id]}},
|
||||
}
|
||||
upload_file = FileService.upload_file(
|
||||
filename=file.filename,
|
||||
content=file.read(),
|
||||
mimetype=file.mimetype,
|
||||
user=current_user,
|
||||
source="datasets",
|
||||
)
|
||||
data_source = {"type": "upload_file", "info_list": {"file_info_list": {"file_ids": [upload_file.id]}}}
|
||||
args["data_source"] = data_source
|
||||
# validate args
|
||||
args["original_document_id"] = str(document_id)
|
||||
|
||||
@ -53,7 +53,8 @@ class SegmentApi(DatasetApiResource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
@ -94,7 +95,8 @@ class SegmentApi(DatasetApiResource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
@ -173,7 +175,8 @@ class DatasetSegmentApi(DatasetApiResource):
|
||||
)
|
||||
except LLMBadRequestError:
|
||||
raise ProviderNotInitializeError(
|
||||
"No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
|
||||
"No Embedding Model available. Please configure a valid provider "
|
||||
"in the Settings -> Model Provider."
|
||||
)
|
||||
except ProviderTokenNotInitError as ex:
|
||||
raise ProviderNotInitializeError(ex.description)
|
||||
|
||||
@ -1,54 +0,0 @@
|
||||
from werkzeug.exceptions import NotFound
|
||||
|
||||
from controllers.service_api import api
|
||||
from controllers.service_api.wraps import (
|
||||
DatasetApiResource,
|
||||
)
|
||||
from core.file import helpers as file_helpers
|
||||
from extensions.ext_database import db
|
||||
from models.dataset import Dataset
|
||||
from models.model import UploadFile
|
||||
from services.dataset_service import DocumentService
|
||||
|
||||
|
||||
class UploadFileApi(DatasetApiResource):
|
||||
def get(self, tenant_id, dataset_id, document_id):
|
||||
"""Get upload file."""
|
||||
# check dataset
|
||||
dataset_id = str(dataset_id)
|
||||
tenant_id = str(tenant_id)
|
||||
dataset = db.session.query(Dataset).filter(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id).first()
|
||||
if not dataset:
|
||||
raise NotFound("Dataset not found.")
|
||||
# check document
|
||||
document_id = str(document_id)
|
||||
document = DocumentService.get_document(dataset.id, document_id)
|
||||
if not document:
|
||||
raise NotFound("Document not found.")
|
||||
# check upload file
|
||||
if document.data_source_type != "upload_file":
|
||||
raise ValueError(f"Document data source type ({document.data_source_type}) is not upload_file.")
|
||||
data_source_info = document.data_source_info_dict
|
||||
if data_source_info and "upload_file_id" in data_source_info:
|
||||
file_id = data_source_info["upload_file_id"]
|
||||
upload_file = db.session.query(UploadFile).filter(UploadFile.id == file_id).first()
|
||||
if not upload_file:
|
||||
raise NotFound("UploadFile not found.")
|
||||
else:
|
||||
raise ValueError("Upload file id not found in document data source info.")
|
||||
|
||||
url = file_helpers.get_signed_file_url(upload_file_id=upload_file.id)
|
||||
return {
|
||||
"id": upload_file.id,
|
||||
"name": upload_file.name,
|
||||
"size": upload_file.size,
|
||||
"extension": upload_file.extension,
|
||||
"url": url,
|
||||
"download_url": f"{url}&as_attachment=true",
|
||||
"mime_type": upload_file.mime_type,
|
||||
"created_by": upload_file.created_by,
|
||||
"created_at": upload_file.created_at.timestamp(),
|
||||
}, 200
|
||||
|
||||
|
||||
api.add_resource(UploadFileApi, "/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/upload-file")
|
||||
@ -1,5 +1,5 @@
|
||||
from collections.abc import Callable
|
||||
from datetime import UTC, datetime, timedelta
|
||||
from datetime import UTC, datetime
|
||||
from enum import Enum
|
||||
from functools import wraps
|
||||
from typing import Optional
|
||||
@ -8,8 +8,6 @@ from flask import current_app, request
|
||||
from flask_login import user_logged_in # type: ignore
|
||||
from flask_restful import Resource # type: ignore
|
||||
from pydantic import BaseModel
|
||||
from sqlalchemy import select, update
|
||||
from sqlalchemy.orm import Session
|
||||
from werkzeug.exceptions import Forbidden, Unauthorized
|
||||
|
||||
from extensions.ext_database import db
|
||||
@ -176,7 +174,7 @@ def validate_dataset_token(view=None):
|
||||
return decorator
|
||||
|
||||
|
||||
def validate_and_get_api_token(scope: str | None = None):
|
||||
def validate_and_get_api_token(scope=None):
|
||||
"""
|
||||
Validate and get API token.
|
||||
"""
|
||||
@ -190,29 +188,20 @@ def validate_and_get_api_token(scope: str | None = None):
|
||||
if auth_scheme != "bearer":
|
||||
raise Unauthorized("Authorization scheme must be 'Bearer'")
|
||||
|
||||
current_time = datetime.now(UTC).replace(tzinfo=None)
|
||||
cutoff_time = current_time - timedelta(minutes=1)
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
update_stmt = (
|
||||
update(ApiToken)
|
||||
.where(
|
||||
ApiToken.token == auth_token,
|
||||
(ApiToken.last_used_at.is_(None) | (ApiToken.last_used_at < cutoff_time)),
|
||||
ApiToken.type == scope,
|
||||
)
|
||||
.values(last_used_at=current_time)
|
||||
.returning(ApiToken)
|
||||
api_token = (
|
||||
db.session.query(ApiToken)
|
||||
.filter(
|
||||
ApiToken.token == auth_token,
|
||||
ApiToken.type == scope,
|
||||
)
|
||||
result = session.execute(update_stmt)
|
||||
api_token = result.scalar_one_or_none()
|
||||
.first()
|
||||
)
|
||||
|
||||
if not api_token:
|
||||
stmt = select(ApiToken).where(ApiToken.token == auth_token, ApiToken.type == scope)
|
||||
api_token = session.scalar(stmt)
|
||||
if not api_token:
|
||||
raise Unauthorized("Access token is invalid")
|
||||
else:
|
||||
session.commit()
|
||||
if not api_token:
|
||||
raise Unauthorized("Access token is invalid")
|
||||
|
||||
api_token.last_used_at = datetime.now(UTC).replace(tzinfo=None)
|
||||
db.session.commit()
|
||||
|
||||
return api_token
|
||||
|
||||
@ -240,7 +229,7 @@ def create_or_update_end_user_for_user_id(app_model: App, user_id: Optional[str]
|
||||
tenant_id=app_model.tenant_id,
|
||||
app_id=app_model.id,
|
||||
type="service_api",
|
||||
is_anonymous=user_id == "DEFAULT-USER",
|
||||
is_anonymous=True if user_id == "DEFAULT-USER" else False,
|
||||
session_id=user_id,
|
||||
)
|
||||
db.session.add(end_user)
|
||||
|
||||
@ -19,11 +19,7 @@ from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpErr
|
||||
from controllers.web.wraps import WebApiResource
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.errors.error import (
|
||||
ModelCurrentlyNotSupportError,
|
||||
ProviderTokenNotInitError,
|
||||
QuotaExceededError,
|
||||
)
|
||||
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
|
||||
from core.model_runtime.errors.invoke import InvokeError
|
||||
from libs import helper
|
||||
from libs.helper import uuid_value
|
||||
|
||||
@ -39,7 +39,7 @@ class ConversationListApi(WebApiResource):
|
||||
|
||||
pinned = None
|
||||
if "pinned" in args and args["pinned"] is not None:
|
||||
pinned = args["pinned"] == "true"
|
||||
pinned = True if args["pinned"] == "true" else False
|
||||
|
||||
try:
|
||||
with Session(db.engine) as session:
|
||||
|
||||
@ -91,7 +91,7 @@ class MessageListApi(WebApiResource):
|
||||
|
||||
try:
|
||||
return MessageService.pagination_by_first_id(
|
||||
app_model, end_user, args["conversation_id"], args["first_id"], args["limit"]
|
||||
app_model, end_user, args["conversation_id"], args["first_id"], args["limit"], "desc"
|
||||
)
|
||||
except services.errors.conversation.ConversationNotExistsError:
|
||||
raise NotFound("Conversation Not Exists.")
|
||||
|
||||
@ -14,11 +14,7 @@ from controllers.web.error import (
|
||||
from controllers.web.wraps import WebApiResource
|
||||
from core.app.apps.base_app_queue_manager import AppQueueManager
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom
|
||||
from core.errors.error import (
|
||||
ModelCurrentlyNotSupportError,
|
||||
ProviderTokenNotInitError,
|
||||
QuotaExceededError,
|
||||
)
|
||||
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
|
||||
from core.model_runtime.errors.invoke import InvokeError
|
||||
from libs import helper
|
||||
from models.model import App, AppMode, EndUser
|
||||
|
||||
@ -339,13 +339,13 @@ class BaseAgentRunner(AppRunner):
|
||||
raise ValueError(f"Agent thought {agent_thought.id} not found")
|
||||
agent_thought = queried_thought
|
||||
|
||||
if thought:
|
||||
if thought is not None:
|
||||
agent_thought.thought = thought
|
||||
|
||||
if tool_name:
|
||||
if tool_name is not None:
|
||||
agent_thought.tool = tool_name
|
||||
|
||||
if tool_input:
|
||||
if tool_input is not None:
|
||||
if isinstance(tool_input, dict):
|
||||
try:
|
||||
tool_input = json.dumps(tool_input, ensure_ascii=False)
|
||||
@ -354,7 +354,7 @@ class BaseAgentRunner(AppRunner):
|
||||
|
||||
agent_thought.tool_input = tool_input
|
||||
|
||||
if observation:
|
||||
if observation is not None:
|
||||
if isinstance(observation, dict):
|
||||
try:
|
||||
observation = json.dumps(observation, ensure_ascii=False)
|
||||
@ -363,7 +363,7 @@ class BaseAgentRunner(AppRunner):
|
||||
|
||||
agent_thought.observation = observation
|
||||
|
||||
if answer:
|
||||
if answer is not None:
|
||||
agent_thought.answer = answer
|
||||
|
||||
if messages_ids is not None and len(messages_ids) > 0:
|
||||
|
||||
@ -104,6 +104,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
|
||||
|
||||
# recalc llm max tokens
|
||||
prompt_messages = self._organize_prompt_messages()
|
||||
self.recalc_llm_max_tokens(self.model_config, prompt_messages)
|
||||
# invoke model
|
||||
chunks = model_instance.invoke_llm(
|
||||
prompt_messages=prompt_messages,
|
||||
@ -171,7 +172,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
|
||||
|
||||
self.save_agent_thought(
|
||||
agent_thought=agent_thought,
|
||||
tool_name=(scratchpad.action.action_name if scratchpad.action and not scratchpad.is_final() else ""),
|
||||
tool_name=scratchpad.action.action_name if scratchpad.action else "",
|
||||
tool_input={scratchpad.action.action_name: scratchpad.action.action_input} if scratchpad.action else {},
|
||||
tool_invoke_meta={},
|
||||
thought=scratchpad.thought or "",
|
||||
|
||||
@ -84,6 +84,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
|
||||
|
||||
# recalc llm max tokens
|
||||
prompt_messages = self._organize_prompt_messages()
|
||||
self.recalc_llm_max_tokens(self.model_config, prompt_messages)
|
||||
# invoke model
|
||||
chunks: Union[Generator[LLMResultChunk, None, None], LLMResult] = model_instance.invoke_llm(
|
||||
prompt_messages=prompt_messages,
|
||||
|
||||
@ -21,7 +21,7 @@ from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
|
||||
from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
|
||||
from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity, InvokeFrom
|
||||
from core.app.entities.task_entities import ChatbotAppBlockingResponse, ChatbotAppStreamResponse
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
|
||||
from core.ops.ops_trace_manager import TraceQueueManager
|
||||
from core.prompt.utils.get_thread_messages_length import get_thread_messages_length
|
||||
from extensions.ext_database import db
|
||||
@ -336,7 +336,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
|
||||
except ValidationError as e:
|
||||
logger.exception("Validation Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
except ValueError as e:
|
||||
except (ValueError, InvokeError) as e:
|
||||
if dify_config.DEBUG:
|
||||
logger.exception("Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
|
||||
@ -67,17 +67,24 @@ from models.account import Account
|
||||
from models.enums import CreatedByRole
|
||||
from models.workflow import (
|
||||
Workflow,
|
||||
WorkflowNodeExecution,
|
||||
WorkflowRunStatus,
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class AdvancedChatAppGenerateTaskPipeline:
|
||||
class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleManage, MessageCycleManage):
|
||||
"""
|
||||
AdvancedChatAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
|
||||
"""
|
||||
|
||||
_task_state: WorkflowTaskState
|
||||
_application_generate_entity: AdvancedChatAppGenerateEntity
|
||||
_workflow_system_variables: dict[SystemVariableKey, Any]
|
||||
_wip_workflow_node_executions: dict[str, WorkflowNodeExecution]
|
||||
_conversation_name_generate_thread: Optional[Thread] = None
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
application_generate_entity: AdvancedChatAppGenerateEntity,
|
||||
@ -89,7 +96,7 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
stream: bool,
|
||||
dialogue_count: int,
|
||||
) -> None:
|
||||
self._base_task_pipeline = BasedGenerateTaskPipeline(
|
||||
super().__init__(
|
||||
application_generate_entity=application_generate_entity,
|
||||
queue_manager=queue_manager,
|
||||
stream=stream,
|
||||
@ -106,35 +113,32 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
else:
|
||||
raise NotImplementedError(f"User type not supported: {type(user)}")
|
||||
|
||||
self._workflow_cycle_manager = WorkflowCycleManage(
|
||||
application_generate_entity=application_generate_entity,
|
||||
workflow_system_variables={
|
||||
SystemVariableKey.QUERY: message.query,
|
||||
SystemVariableKey.FILES: application_generate_entity.files,
|
||||
SystemVariableKey.CONVERSATION_ID: conversation.id,
|
||||
SystemVariableKey.USER_ID: user_session_id,
|
||||
SystemVariableKey.DIALOGUE_COUNT: dialogue_count,
|
||||
SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
|
||||
SystemVariableKey.WORKFLOW_ID: workflow.id,
|
||||
SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
|
||||
},
|
||||
)
|
||||
|
||||
self._task_state = WorkflowTaskState()
|
||||
self._message_cycle_manager = MessageCycleManage(
|
||||
application_generate_entity=application_generate_entity, task_state=self._task_state
|
||||
)
|
||||
|
||||
self._application_generate_entity = application_generate_entity
|
||||
self._workflow_id = workflow.id
|
||||
self._workflow_features_dict = workflow.features_dict
|
||||
|
||||
self._conversation_id = conversation.id
|
||||
self._conversation_mode = conversation.mode
|
||||
|
||||
self._message_id = message.id
|
||||
self._message_created_at = int(message.created_at.timestamp())
|
||||
self._conversation_name_generate_thread: Thread | None = None
|
||||
|
||||
self._workflow_system_variables = {
|
||||
SystemVariableKey.QUERY: message.query,
|
||||
SystemVariableKey.FILES: application_generate_entity.files,
|
||||
SystemVariableKey.CONVERSATION_ID: conversation.id,
|
||||
SystemVariableKey.USER_ID: user_session_id,
|
||||
SystemVariableKey.DIALOGUE_COUNT: dialogue_count,
|
||||
SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
|
||||
SystemVariableKey.WORKFLOW_ID: workflow.id,
|
||||
SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
|
||||
}
|
||||
|
||||
self._task_state = WorkflowTaskState()
|
||||
self._wip_workflow_node_executions = {}
|
||||
|
||||
self._conversation_name_generate_thread = None
|
||||
self._recorded_files: list[Mapping[str, Any]] = []
|
||||
self._workflow_run_id: str = ""
|
||||
self._workflow_run_id = ""
|
||||
|
||||
def process(self) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
|
||||
"""
|
||||
@ -142,13 +146,13 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
:return:
|
||||
"""
|
||||
# start generate conversation name thread
|
||||
self._conversation_name_generate_thread = self._message_cycle_manager._generate_conversation_name(
|
||||
self._conversation_name_generate_thread = self._generate_conversation_name(
|
||||
conversation_id=self._conversation_id, query=self._application_generate_entity.query
|
||||
)
|
||||
|
||||
generator = self._wrapper_process_stream_response(trace_manager=self._application_generate_entity.trace_manager)
|
||||
|
||||
if self._base_task_pipeline._stream:
|
||||
if self._stream:
|
||||
return self._to_stream_response(generator)
|
||||
else:
|
||||
return self._to_blocking_response(generator)
|
||||
@ -265,26 +269,24 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
# init fake graph runtime state
|
||||
graph_runtime_state: Optional[GraphRuntimeState] = None
|
||||
|
||||
for queue_message in self._base_task_pipeline._queue_manager.listen():
|
||||
for queue_message in self._queue_manager.listen():
|
||||
event = queue_message.event
|
||||
|
||||
if isinstance(event, QueuePingEvent):
|
||||
yield self._base_task_pipeline._ping_stream_response()
|
||||
yield self._ping_stream_response()
|
||||
elif isinstance(event, QueueErrorEvent):
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
err = self._base_task_pipeline._handle_error(
|
||||
event=event, session=session, message_id=self._message_id
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
err = self._handle_error(event=event, session=session, message_id=self._message_id)
|
||||
session.commit()
|
||||
yield self._base_task_pipeline._error_to_stream_response(err)
|
||||
yield self._error_to_stream_response(err)
|
||||
break
|
||||
elif isinstance(event, QueueWorkflowStartedEvent):
|
||||
# override graph runtime state
|
||||
graph_runtime_state = event.graph_runtime_state
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
with Session(db.engine) as session:
|
||||
# init workflow run
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_start(
|
||||
workflow_run = self._handle_workflow_run_start(
|
||||
session=session,
|
||||
workflow_id=self._workflow_id,
|
||||
user_id=self._user_id,
|
||||
@ -295,7 +297,7 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not message:
|
||||
raise ValueError(f"Message not found: {self._message_id}")
|
||||
message.workflow_run_id = workflow_run.id
|
||||
workflow_start_resp = self._workflow_cycle_manager._workflow_start_to_stream_response(
|
||||
workflow_start_resp = self._workflow_start_to_stream_response(
|
||||
session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
|
||||
)
|
||||
session.commit()
|
||||
@ -308,14 +310,12 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
workflow_node_execution = self._handle_workflow_node_execution_retried(
|
||||
session=session, workflow_run=workflow_run, event=event
|
||||
)
|
||||
node_retry_resp = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
|
||||
node_retry_resp = self._workflow_node_retry_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -329,15 +329,13 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
workflow_node_execution = self._handle_node_execution_start(
|
||||
session=session, workflow_run=workflow_run, event=event
|
||||
)
|
||||
|
||||
node_start_resp = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
|
||||
node_start_resp = self._workflow_node_start_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -350,16 +348,12 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
elif isinstance(event, QueueNodeSucceededEvent):
|
||||
# Record files if it's an answer node or end node
|
||||
if event.node_type in [NodeType.ANSWER, NodeType.END]:
|
||||
self._recorded_files.extend(
|
||||
self._workflow_cycle_manager._fetch_files_from_node_outputs(event.outputs or {})
|
||||
)
|
||||
self._recorded_files.extend(self._fetch_files_from_node_outputs(event.outputs or {}))
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
|
||||
session=session, event=event
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
workflow_node_execution = self._handle_workflow_node_execution_success(session=session, event=event)
|
||||
|
||||
node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
|
||||
node_finish_resp = self._workflow_node_finish_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -370,12 +364,10 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if node_finish_resp:
|
||||
yield node_finish_resp
|
||||
elif isinstance(event, QueueNodeFailedEvent | QueueNodeInIterationFailedEvent | QueueNodeExceptionEvent):
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
|
||||
session=session, event=event
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
workflow_node_execution = self._handle_workflow_node_execution_failed(session=session, event=event)
|
||||
|
||||
node_finish_resp = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
|
||||
node_finish_resp = self._workflow_node_finish_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -389,17 +381,13 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
parallel_start_resp = (
|
||||
self._workflow_cycle_manager._workflow_parallel_branch_start_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
parallel_start_resp = self._workflow_parallel_branch_start_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
|
||||
yield parallel_start_resp
|
||||
@ -407,17 +395,13 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
parallel_finish_resp = (
|
||||
self._workflow_cycle_manager._workflow_parallel_branch_finished_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
parallel_finish_resp = self._workflow_parallel_branch_finished_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
|
||||
yield parallel_finish_resp
|
||||
@ -425,11 +409,9 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
iter_start_resp = self._workflow_cycle_manager._workflow_iteration_start_to_stream_response(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
iter_start_resp = self._workflow_iteration_start_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -441,11 +423,9 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
iter_next_resp = self._workflow_cycle_manager._workflow_iteration_next_to_stream_response(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
iter_next_resp = self._workflow_iteration_next_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -457,11 +437,9 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
iter_finish_resp = self._workflow_cycle_manager._workflow_iteration_completed_to_stream_response(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
iter_finish_resp = self._workflow_iteration_completed_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -476,8 +454,8 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
if not graph_runtime_state:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_success(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._handle_workflow_run_success(
|
||||
session=session,
|
||||
workflow_run_id=self._workflow_run_id,
|
||||
start_at=graph_runtime_state.start_at,
|
||||
@ -488,23 +466,21 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
trace_manager=trace_manager,
|
||||
)
|
||||
|
||||
workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
|
||||
workflow_finish_resp = self._workflow_finish_to_stream_response(
|
||||
session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
|
||||
)
|
||||
session.commit()
|
||||
|
||||
yield workflow_finish_resp
|
||||
self._base_task_pipeline._queue_manager.publish(
|
||||
QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE
|
||||
)
|
||||
self._queue_manager.publish(QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE)
|
||||
elif isinstance(event, QueueWorkflowPartialSuccessEvent):
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
if not graph_runtime_state:
|
||||
raise ValueError("graph runtime state not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_partial_success(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._handle_workflow_run_partial_success(
|
||||
session=session,
|
||||
workflow_run_id=self._workflow_run_id,
|
||||
start_at=graph_runtime_state.start_at,
|
||||
@ -515,23 +491,21 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
conversation_id=None,
|
||||
trace_manager=trace_manager,
|
||||
)
|
||||
workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
|
||||
workflow_finish_resp = self._workflow_finish_to_stream_response(
|
||||
session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
|
||||
)
|
||||
session.commit()
|
||||
|
||||
yield workflow_finish_resp
|
||||
self._base_task_pipeline._queue_manager.publish(
|
||||
QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE
|
||||
)
|
||||
self._queue_manager.publish(QueueAdvancedChatMessageEndEvent(), PublishFrom.TASK_PIPELINE)
|
||||
elif isinstance(event, QueueWorkflowFailedEvent):
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
if not graph_runtime_state:
|
||||
raise ValueError("graph runtime state not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._handle_workflow_run_failed(
|
||||
session=session,
|
||||
workflow_run_id=self._workflow_run_id,
|
||||
start_at=graph_runtime_state.start_at,
|
||||
@ -543,22 +517,20 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
trace_manager=trace_manager,
|
||||
exceptions_count=event.exceptions_count,
|
||||
)
|
||||
workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
|
||||
workflow_finish_resp = self._workflow_finish_to_stream_response(
|
||||
session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
|
||||
)
|
||||
err_event = QueueErrorEvent(error=ValueError(f"Run failed: {workflow_run.error}"))
|
||||
err = self._base_task_pipeline._handle_error(
|
||||
event=err_event, session=session, message_id=self._message_id
|
||||
)
|
||||
err = self._handle_error(event=err_event, session=session, message_id=self._message_id)
|
||||
session.commit()
|
||||
|
||||
yield workflow_finish_resp
|
||||
yield self._base_task_pipeline._error_to_stream_response(err)
|
||||
yield self._error_to_stream_response(err)
|
||||
break
|
||||
elif isinstance(event, QueueStopEvent):
|
||||
if self._workflow_run_id and graph_runtime_state:
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._handle_workflow_run_failed(
|
||||
session=session,
|
||||
workflow_run_id=self._workflow_run_id,
|
||||
start_at=graph_runtime_state.start_at,
|
||||
@ -569,7 +541,7 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
conversation_id=self._conversation_id,
|
||||
trace_manager=trace_manager,
|
||||
)
|
||||
workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
|
||||
workflow_finish_resp = self._workflow_finish_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -583,18 +555,18 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
yield self._message_end_to_stream_response()
|
||||
break
|
||||
elif isinstance(event, QueueRetrieverResourcesEvent):
|
||||
self._message_cycle_manager._handle_retriever_resources(event)
|
||||
self._handle_retriever_resources(event)
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
with Session(db.engine) as session:
|
||||
message = self._get_message(session=session)
|
||||
message.message_metadata = (
|
||||
json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
|
||||
)
|
||||
session.commit()
|
||||
elif isinstance(event, QueueAnnotationReplyEvent):
|
||||
self._message_cycle_manager._handle_annotation_reply(event)
|
||||
self._handle_annotation_reply(event)
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
with Session(db.engine) as session:
|
||||
message = self._get_message(session=session)
|
||||
message.message_metadata = (
|
||||
json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
|
||||
@ -615,27 +587,23 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
tts_publisher.publish(queue_message)
|
||||
|
||||
self._task_state.answer += delta_text
|
||||
yield self._message_cycle_manager._message_to_stream_response(
|
||||
yield self._message_to_stream_response(
|
||||
answer=delta_text, message_id=self._message_id, from_variable_selector=event.from_variable_selector
|
||||
)
|
||||
elif isinstance(event, QueueMessageReplaceEvent):
|
||||
# published by moderation
|
||||
yield self._message_cycle_manager._message_replace_to_stream_response(answer=event.text)
|
||||
yield self._message_replace_to_stream_response(answer=event.text)
|
||||
elif isinstance(event, QueueAdvancedChatMessageEndEvent):
|
||||
if not graph_runtime_state:
|
||||
raise ValueError("graph runtime state not initialized.")
|
||||
|
||||
output_moderation_answer = self._base_task_pipeline._handle_output_moderation_when_task_finished(
|
||||
self._task_state.answer
|
||||
)
|
||||
output_moderation_answer = self._handle_output_moderation_when_task_finished(self._task_state.answer)
|
||||
if output_moderation_answer:
|
||||
self._task_state.answer = output_moderation_answer
|
||||
yield self._message_cycle_manager._message_replace_to_stream_response(
|
||||
answer=output_moderation_answer
|
||||
)
|
||||
yield self._message_replace_to_stream_response(answer=output_moderation_answer)
|
||||
|
||||
# Save message
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
with Session(db.engine) as session:
|
||||
self._save_message(session=session, graph_runtime_state=graph_runtime_state)
|
||||
session.commit()
|
||||
|
||||
@ -653,7 +621,7 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
def _save_message(self, *, session: Session, graph_runtime_state: Optional[GraphRuntimeState] = None) -> None:
|
||||
message = self._get_message(session=session)
|
||||
message.answer = self._task_state.answer
|
||||
message.provider_response_latency = time.perf_counter() - self._base_task_pipeline._start_at
|
||||
message.provider_response_latency = time.perf_counter() - self._start_at
|
||||
message.message_metadata = (
|
||||
json.dumps(jsonable_encoder(self._task_state.metadata)) if self._task_state.metadata else None
|
||||
)
|
||||
@ -717,20 +685,20 @@ class AdvancedChatAppGenerateTaskPipeline:
|
||||
:param text: text
|
||||
:return: True if output moderation should direct output, otherwise False
|
||||
"""
|
||||
if self._base_task_pipeline._output_moderation_handler:
|
||||
if self._base_task_pipeline._output_moderation_handler.should_direct_output():
|
||||
if self._output_moderation_handler:
|
||||
if self._output_moderation_handler.should_direct_output():
|
||||
# stop subscribe new token when output moderation should direct output
|
||||
self._task_state.answer = self._base_task_pipeline._output_moderation_handler.get_final_output()
|
||||
self._base_task_pipeline._queue_manager.publish(
|
||||
self._task_state.answer = self._output_moderation_handler.get_final_output()
|
||||
self._queue_manager.publish(
|
||||
QueueTextChunkEvent(text=self._task_state.answer), PublishFrom.TASK_PIPELINE
|
||||
)
|
||||
|
||||
self._base_task_pipeline._queue_manager.publish(
|
||||
self._queue_manager.publish(
|
||||
QueueStopEvent(stopped_by=QueueStopEvent.StopBy.OUTPUT_MODERATION), PublishFrom.TASK_PIPELINE
|
||||
)
|
||||
return True
|
||||
else:
|
||||
self._base_task_pipeline._output_moderation_handler.append_new_token(text)
|
||||
self._output_moderation_handler.append_new_token(text)
|
||||
|
||||
return False
|
||||
|
||||
|
||||
@ -18,7 +18,7 @@ from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskSt
|
||||
from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
|
||||
from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
|
||||
from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, InvokeFrom
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
|
||||
from core.ops.ops_trace_manager import TraceQueueManager
|
||||
from extensions.ext_database import db
|
||||
from factories import file_factory
|
||||
@ -245,7 +245,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
|
||||
except ValidationError as e:
|
||||
logger.exception("Validation Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
except ValueError as e:
|
||||
except (ValueError, InvokeError) as e:
|
||||
if dify_config.DEBUG:
|
||||
logger.exception("Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
|
||||
@ -55,6 +55,20 @@ class AgentChatAppRunner(AppRunner):
|
||||
query = application_generate_entity.query
|
||||
files = application_generate_entity.files
|
||||
|
||||
# Pre-calculate the number of tokens of the prompt messages,
|
||||
# and return the rest number of tokens by model context token size limit and max token size limit.
|
||||
# If the rest number of tokens is not enough, raise exception.
|
||||
# Include: prompt template, inputs, query(optional), files(optional)
|
||||
# Not Include: memory, external data, dataset context
|
||||
self.get_pre_calculate_rest_tokens(
|
||||
app_record=app_record,
|
||||
model_config=application_generate_entity.model_conf,
|
||||
prompt_template_entity=app_config.prompt_template,
|
||||
inputs=inputs,
|
||||
files=files,
|
||||
query=query,
|
||||
)
|
||||
|
||||
memory = None
|
||||
if application_generate_entity.conversation_id:
|
||||
# get memory of conversation (read-only)
|
||||
@ -188,7 +202,7 @@ class AgentChatAppRunner(AppRunner):
|
||||
# change function call strategy based on LLM model
|
||||
llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
|
||||
model_schema = llm_model.get_model_schema(model_instance.model, model_instance.credentials)
|
||||
if not model_schema:
|
||||
if not model_schema or not model_schema.features:
|
||||
raise ValueError("Model schema not found")
|
||||
|
||||
if {ModelFeature.MULTI_TOOL_CALL, ModelFeature.TOOL_CALL}.intersection(model_schema.features or []):
|
||||
|
||||
@ -167,7 +167,8 @@ class AppQueueManager:
|
||||
else:
|
||||
if isinstance(data, DeclarativeMeta) or hasattr(data, "_sa_instance_state"):
|
||||
raise TypeError(
|
||||
"Critical Error: Passing SQLAlchemy Model instances that cause thread safety issues is not allowed."
|
||||
"Critical Error: Passing SQLAlchemy Model instances "
|
||||
"that cause thread safety issues is not allowed."
|
||||
)
|
||||
|
||||
|
||||
|
||||
@ -15,8 +15,10 @@ from core.app.features.annotation_reply.annotation_reply import AnnotationReplyF
|
||||
from core.app.features.hosting_moderation.hosting_moderation import HostingModerationFeature
|
||||
from core.external_data_tool.external_data_fetch import ExternalDataFetch
|
||||
from core.memory.token_buffer_memory import TokenBufferMemory
|
||||
from core.model_manager import ModelInstance
|
||||
from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
|
||||
from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage
|
||||
from core.model_runtime.entities.model_entities import ModelPropertyKey
|
||||
from core.model_runtime.errors.invoke import InvokeBadRequestError
|
||||
from core.moderation.input_moderation import InputModeration
|
||||
from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
|
||||
@ -29,6 +31,106 @@ if TYPE_CHECKING:
|
||||
|
||||
|
||||
class AppRunner:
|
||||
def get_pre_calculate_rest_tokens(
|
||||
self,
|
||||
app_record: App,
|
||||
model_config: ModelConfigWithCredentialsEntity,
|
||||
prompt_template_entity: PromptTemplateEntity,
|
||||
inputs: Mapping[str, str],
|
||||
files: Sequence["File"],
|
||||
query: Optional[str] = None,
|
||||
) -> int:
|
||||
"""
|
||||
Get pre calculate rest tokens
|
||||
:param app_record: app record
|
||||
:param model_config: model config entity
|
||||
:param prompt_template_entity: prompt template entity
|
||||
:param inputs: inputs
|
||||
:param files: files
|
||||
:param query: query
|
||||
:return:
|
||||
"""
|
||||
# Invoke model
|
||||
model_instance = ModelInstance(
|
||||
provider_model_bundle=model_config.provider_model_bundle, model=model_config.model
|
||||
)
|
||||
|
||||
model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)
|
||||
|
||||
max_tokens = 0
|
||||
for parameter_rule in model_config.model_schema.parameter_rules:
|
||||
if parameter_rule.name == "max_tokens" or (
|
||||
parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
|
||||
):
|
||||
max_tokens = (
|
||||
model_config.parameters.get(parameter_rule.name)
|
||||
or model_config.parameters.get(parameter_rule.use_template or "")
|
||||
) or 0
|
||||
|
||||
if model_context_tokens is None:
|
||||
return -1
|
||||
|
||||
if max_tokens is None:
|
||||
max_tokens = 0
|
||||
|
||||
# get prompt messages without memory and context
|
||||
prompt_messages, stop = self.organize_prompt_messages(
|
||||
app_record=app_record,
|
||||
model_config=model_config,
|
||||
prompt_template_entity=prompt_template_entity,
|
||||
inputs=inputs,
|
||||
files=files,
|
||||
query=query,
|
||||
)
|
||||
|
||||
prompt_tokens = model_instance.get_llm_num_tokens(prompt_messages)
|
||||
|
||||
rest_tokens: int = model_context_tokens - max_tokens - prompt_tokens
|
||||
if rest_tokens < 0:
|
||||
raise InvokeBadRequestError(
|
||||
"Query or prefix prompt is too long, you can reduce the prefix prompt, "
|
||||
"or shrink the max token, or switch to a llm with a larger token limit size."
|
||||
)
|
||||
|
||||
return rest_tokens
|
||||
|
||||
def recalc_llm_max_tokens(
|
||||
self, model_config: ModelConfigWithCredentialsEntity, prompt_messages: list[PromptMessage]
|
||||
):
|
||||
# recalc max_tokens if sum(prompt_token + max_tokens) over model token limit
|
||||
model_instance = ModelInstance(
|
||||
provider_model_bundle=model_config.provider_model_bundle, model=model_config.model
|
||||
)
|
||||
|
||||
model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)
|
||||
|
||||
max_tokens = 0
|
||||
for parameter_rule in model_config.model_schema.parameter_rules:
|
||||
if parameter_rule.name == "max_tokens" or (
|
||||
parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
|
||||
):
|
||||
max_tokens = (
|
||||
model_config.parameters.get(parameter_rule.name)
|
||||
or model_config.parameters.get(parameter_rule.use_template or "")
|
||||
) or 0
|
||||
|
||||
if model_context_tokens is None:
|
||||
return -1
|
||||
|
||||
if max_tokens is None:
|
||||
max_tokens = 0
|
||||
|
||||
prompt_tokens = model_instance.get_llm_num_tokens(prompt_messages)
|
||||
|
||||
if prompt_tokens + max_tokens > model_context_tokens:
|
||||
max_tokens = max(model_context_tokens - prompt_tokens, 16)
|
||||
|
||||
for parameter_rule in model_config.model_schema.parameter_rules:
|
||||
if parameter_rule.name == "max_tokens" or (
|
||||
parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
|
||||
):
|
||||
model_config.parameters[parameter_rule.name] = max_tokens
|
||||
|
||||
def organize_prompt_messages(
|
||||
self,
|
||||
app_record: App,
|
||||
|
||||
@ -18,7 +18,7 @@ from core.app.apps.chat.generate_response_converter import ChatAppGenerateRespon
|
||||
from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
|
||||
from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
|
||||
from core.app.entities.app_invoke_entities import ChatAppGenerateEntity, InvokeFrom
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
|
||||
from core.ops.ops_trace_manager import TraceQueueManager
|
||||
from extensions.ext_database import db
|
||||
from factories import file_factory
|
||||
@ -237,7 +237,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
|
||||
except ValidationError as e:
|
||||
logger.exception("Validation Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
except ValueError as e:
|
||||
except (ValueError, InvokeError) as e:
|
||||
if dify_config.DEBUG:
|
||||
logger.exception("Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
|
||||
@ -50,6 +50,20 @@ class ChatAppRunner(AppRunner):
|
||||
query = application_generate_entity.query
|
||||
files = application_generate_entity.files
|
||||
|
||||
# Pre-calculate the number of tokens of the prompt messages,
|
||||
# and return the rest number of tokens by model context token size limit and max token size limit.
|
||||
# If the rest number of tokens is not enough, raise exception.
|
||||
# Include: prompt template, inputs, query(optional), files(optional)
|
||||
# Not Include: memory, external data, dataset context
|
||||
self.get_pre_calculate_rest_tokens(
|
||||
app_record=app_record,
|
||||
model_config=application_generate_entity.model_conf,
|
||||
prompt_template_entity=app_config.prompt_template,
|
||||
inputs=inputs,
|
||||
files=files,
|
||||
query=query,
|
||||
)
|
||||
|
||||
memory = None
|
||||
if application_generate_entity.conversation_id:
|
||||
# get memory of conversation (read-only)
|
||||
@ -180,6 +194,9 @@ class ChatAppRunner(AppRunner):
|
||||
if hosting_moderation_result:
|
||||
return
|
||||
|
||||
# Re-calculate the max tokens if sum(prompt_token + max_tokens) over model token limit
|
||||
self.recalc_llm_max_tokens(model_config=application_generate_entity.model_conf, prompt_messages=prompt_messages)
|
||||
|
||||
# Invoke model
|
||||
model_instance = ModelInstance(
|
||||
provider_model_bundle=application_generate_entity.model_conf.provider_model_bundle,
|
||||
|
||||
@ -17,7 +17,7 @@ from core.app.apps.completion.generate_response_converter import CompletionAppGe
|
||||
from core.app.apps.message_based_app_generator import MessageBasedAppGenerator
|
||||
from core.app.apps.message_based_app_queue_manager import MessageBasedAppQueueManager
|
||||
from core.app.entities.app_invoke_entities import CompletionAppGenerateEntity, InvokeFrom
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
|
||||
from core.ops.ops_trace_manager import TraceQueueManager
|
||||
from extensions.ext_database import db
|
||||
from factories import file_factory
|
||||
@ -214,7 +214,7 @@ class CompletionAppGenerator(MessageBasedAppGenerator):
|
||||
except ValidationError as e:
|
||||
logger.exception("Validation Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
except ValueError as e:
|
||||
except (ValueError, InvokeError) as e:
|
||||
if dify_config.DEBUG:
|
||||
logger.exception("Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
|
||||
@ -43,6 +43,20 @@ class CompletionAppRunner(AppRunner):
|
||||
query = application_generate_entity.query
|
||||
files = application_generate_entity.files
|
||||
|
||||
# Pre-calculate the number of tokens of the prompt messages,
|
||||
# and return the rest number of tokens by model context token size limit and max token size limit.
|
||||
# If the rest number of tokens is not enough, raise exception.
|
||||
# Include: prompt template, inputs, query(optional), files(optional)
|
||||
# Not Include: memory, external data, dataset context
|
||||
self.get_pre_calculate_rest_tokens(
|
||||
app_record=app_record,
|
||||
model_config=application_generate_entity.model_conf,
|
||||
prompt_template_entity=app_config.prompt_template,
|
||||
inputs=inputs,
|
||||
files=files,
|
||||
query=query,
|
||||
)
|
||||
|
||||
# organize all inputs and template to prompt messages
|
||||
# Include: prompt template, inputs, query(optional), files(optional)
|
||||
prompt_messages, stop = self.organize_prompt_messages(
|
||||
@ -138,6 +152,9 @@ class CompletionAppRunner(AppRunner):
|
||||
if hosting_moderation_result:
|
||||
return
|
||||
|
||||
# Re-calculate the max tokens if sum(prompt_token + max_tokens) over model token limit
|
||||
self.recalc_llm_max_tokens(model_config=application_generate_entity.model_conf, prompt_messages=prompt_messages)
|
||||
|
||||
# Invoke model
|
||||
model_instance = ModelInstance(
|
||||
provider_model_bundle=application_generate_entity.model_conf.provider_model_bundle,
|
||||
|
||||
@ -89,7 +89,6 @@ class MessageBasedAppGenerator(BaseAppGenerator):
|
||||
Conversation.id == conversation_id,
|
||||
Conversation.app_id == app_model.id,
|
||||
Conversation.status == "normal",
|
||||
Conversation.is_deleted.is_(False),
|
||||
]
|
||||
|
||||
if isinstance(user, Account):
|
||||
|
||||
@ -20,7 +20,7 @@ from core.app.apps.workflow.generate_response_converter import WorkflowAppGenera
|
||||
from core.app.apps.workflow.generate_task_pipeline import WorkflowAppGenerateTaskPipeline
|
||||
from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerateEntity
|
||||
from core.app.entities.task_entities import WorkflowAppBlockingResponse, WorkflowAppStreamResponse
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
|
||||
from core.ops.ops_trace_manager import TraceQueueManager
|
||||
from extensions.ext_database import db
|
||||
from factories import file_factory
|
||||
@ -221,7 +221,6 @@ class WorkflowAppGenerator(BaseAppGenerator):
|
||||
single_iteration_run=WorkflowAppGenerateEntity.SingleIterationRunEntity(
|
||||
node_id=node_id, inputs=args["inputs"]
|
||||
),
|
||||
workflow_run_id=str(uuid.uuid4()),
|
||||
)
|
||||
contexts.tenant_id.set(application_generate_entity.app_config.tenant_id)
|
||||
|
||||
@ -271,7 +270,7 @@ class WorkflowAppGenerator(BaseAppGenerator):
|
||||
except ValidationError as e:
|
||||
logger.exception("Validation Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
except ValueError as e:
|
||||
except (ValueError, InvokeError) as e:
|
||||
if dify_config.DEBUG:
|
||||
logger.exception("Error when generating")
|
||||
queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
import logging
|
||||
import time
|
||||
from collections.abc import Generator
|
||||
from typing import Optional, Union
|
||||
from typing import Any, Optional, Union
|
||||
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
@ -58,6 +58,7 @@ from models.workflow import (
|
||||
Workflow,
|
||||
WorkflowAppLog,
|
||||
WorkflowAppLogCreatedFrom,
|
||||
WorkflowNodeExecution,
|
||||
WorkflowRun,
|
||||
WorkflowRunStatus,
|
||||
)
|
||||
@ -65,11 +66,16 @@ from models.workflow import (
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class WorkflowAppGenerateTaskPipeline:
|
||||
class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleManage):
|
||||
"""
|
||||
WorkflowAppGenerateTaskPipeline is a class that generate stream output and state management for Application.
|
||||
"""
|
||||
|
||||
_task_state: WorkflowTaskState
|
||||
_application_generate_entity: WorkflowAppGenerateEntity
|
||||
_workflow_system_variables: dict[SystemVariableKey, Any]
|
||||
_wip_workflow_node_executions: dict[str, WorkflowNodeExecution]
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
application_generate_entity: WorkflowAppGenerateEntity,
|
||||
@ -78,7 +84,7 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
user: Union[Account, EndUser],
|
||||
stream: bool,
|
||||
) -> None:
|
||||
self._base_task_pipeline = BasedGenerateTaskPipeline(
|
||||
super().__init__(
|
||||
application_generate_entity=application_generate_entity,
|
||||
queue_manager=queue_manager,
|
||||
stream=stream,
|
||||
@ -95,21 +101,19 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
else:
|
||||
raise ValueError(f"Invalid user type: {type(user)}")
|
||||
|
||||
self._workflow_cycle_manager = WorkflowCycleManage(
|
||||
application_generate_entity=application_generate_entity,
|
||||
workflow_system_variables={
|
||||
SystemVariableKey.FILES: application_generate_entity.files,
|
||||
SystemVariableKey.USER_ID: user_session_id,
|
||||
SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
|
||||
SystemVariableKey.WORKFLOW_ID: workflow.id,
|
||||
SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
|
||||
},
|
||||
)
|
||||
|
||||
self._application_generate_entity = application_generate_entity
|
||||
self._workflow_id = workflow.id
|
||||
self._workflow_features_dict = workflow.features_dict
|
||||
|
||||
self._workflow_system_variables = {
|
||||
SystemVariableKey.FILES: application_generate_entity.files,
|
||||
SystemVariableKey.USER_ID: user_session_id,
|
||||
SystemVariableKey.APP_ID: application_generate_entity.app_config.app_id,
|
||||
SystemVariableKey.WORKFLOW_ID: workflow.id,
|
||||
SystemVariableKey.WORKFLOW_RUN_ID: application_generate_entity.workflow_run_id,
|
||||
}
|
||||
|
||||
self._task_state = WorkflowTaskState()
|
||||
self._wip_workflow_node_executions = {}
|
||||
self._workflow_run_id = ""
|
||||
|
||||
def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStreamResponse, None, None]]:
|
||||
@ -118,7 +122,7 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
:return:
|
||||
"""
|
||||
generator = self._wrapper_process_stream_response(trace_manager=self._application_generate_entity.trace_manager)
|
||||
if self._base_task_pipeline._stream:
|
||||
if self._stream:
|
||||
return self._to_stream_response(generator)
|
||||
else:
|
||||
return self._to_blocking_response(generator)
|
||||
@ -233,29 +237,29 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
"""
|
||||
graph_runtime_state = None
|
||||
|
||||
for queue_message in self._base_task_pipeline._queue_manager.listen():
|
||||
for queue_message in self._queue_manager.listen():
|
||||
event = queue_message.event
|
||||
|
||||
if isinstance(event, QueuePingEvent):
|
||||
yield self._base_task_pipeline._ping_stream_response()
|
||||
yield self._ping_stream_response()
|
||||
elif isinstance(event, QueueErrorEvent):
|
||||
err = self._base_task_pipeline._handle_error(event=event)
|
||||
yield self._base_task_pipeline._error_to_stream_response(err)
|
||||
err = self._handle_error(event=event)
|
||||
yield self._error_to_stream_response(err)
|
||||
break
|
||||
elif isinstance(event, QueueWorkflowStartedEvent):
|
||||
# override graph runtime state
|
||||
graph_runtime_state = event.graph_runtime_state
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
with Session(db.engine) as session:
|
||||
# init workflow run
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_start(
|
||||
workflow_run = self._handle_workflow_run_start(
|
||||
session=session,
|
||||
workflow_id=self._workflow_id,
|
||||
user_id=self._user_id,
|
||||
created_by_role=self._created_by_role,
|
||||
)
|
||||
self._workflow_run_id = workflow_run.id
|
||||
start_resp = self._workflow_cycle_manager._workflow_start_to_stream_response(
|
||||
start_resp = self._workflow_start_to_stream_response(
|
||||
session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
|
||||
)
|
||||
session.commit()
|
||||
@ -267,14 +271,12 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
):
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_retried(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
workflow_node_execution = self._handle_workflow_node_execution_retried(
|
||||
session=session, workflow_run=workflow_run, event=event
|
||||
)
|
||||
response = self._workflow_cycle_manager._workflow_node_retry_to_stream_response(
|
||||
response = self._workflow_node_retry_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -288,14 +290,12 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_node_execution_start(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
workflow_node_execution = self._handle_node_execution_start(
|
||||
session=session, workflow_run=workflow_run, event=event
|
||||
)
|
||||
node_start_response = self._workflow_cycle_manager._workflow_node_start_to_stream_response(
|
||||
node_start_response = self._workflow_node_start_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -306,11 +306,9 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if node_start_response:
|
||||
yield node_start_response
|
||||
elif isinstance(event, QueueNodeSucceededEvent):
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_success(
|
||||
session=session, event=event
|
||||
)
|
||||
node_success_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
|
||||
with Session(db.engine) as session:
|
||||
workflow_node_execution = self._handle_workflow_node_execution_success(session=session, event=event)
|
||||
node_success_response = self._workflow_node_finish_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -321,12 +319,12 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if node_success_response:
|
||||
yield node_success_response
|
||||
elif isinstance(event, QueueNodeFailedEvent | QueueNodeInIterationFailedEvent | QueueNodeExceptionEvent):
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_node_execution = self._workflow_cycle_manager._handle_workflow_node_execution_failed(
|
||||
with Session(db.engine) as session:
|
||||
workflow_node_execution = self._handle_workflow_node_execution_failed(
|
||||
session=session,
|
||||
event=event,
|
||||
)
|
||||
node_failed_response = self._workflow_cycle_manager._workflow_node_finish_to_stream_response(
|
||||
node_failed_response = self._workflow_node_finish_to_stream_response(
|
||||
session=session,
|
||||
event=event,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
@ -341,17 +339,13 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
parallel_start_resp = (
|
||||
self._workflow_cycle_manager._workflow_parallel_branch_start_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
parallel_start_resp = self._workflow_parallel_branch_start_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
|
||||
yield parallel_start_resp
|
||||
@ -360,17 +354,13 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
parallel_finish_resp = (
|
||||
self._workflow_cycle_manager._workflow_parallel_branch_finished_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
parallel_finish_resp = self._workflow_parallel_branch_finished_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
event=event,
|
||||
)
|
||||
|
||||
yield parallel_finish_resp
|
||||
@ -379,11 +369,9 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
iter_start_resp = self._workflow_cycle_manager._workflow_iteration_start_to_stream_response(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
iter_start_resp = self._workflow_iteration_start_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -396,11 +384,9 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
iter_next_resp = self._workflow_cycle_manager._workflow_iteration_next_to_stream_response(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
iter_next_resp = self._workflow_iteration_next_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -413,11 +399,9 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not self._workflow_run_id:
|
||||
raise ValueError("workflow run not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._get_workflow_run(
|
||||
session=session, workflow_run_id=self._workflow_run_id
|
||||
)
|
||||
iter_finish_resp = self._workflow_cycle_manager._workflow_iteration_completed_to_stream_response(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._get_workflow_run(session=session, workflow_run_id=self._workflow_run_id)
|
||||
iter_finish_resp = self._workflow_iteration_completed_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -432,8 +416,8 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not graph_runtime_state:
|
||||
raise ValueError("graph runtime state not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_success(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._handle_workflow_run_success(
|
||||
session=session,
|
||||
workflow_run_id=self._workflow_run_id,
|
||||
start_at=graph_runtime_state.start_at,
|
||||
@ -447,7 +431,7 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
# save workflow app log
|
||||
self._save_workflow_app_log(session=session, workflow_run=workflow_run)
|
||||
|
||||
workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
|
||||
workflow_finish_resp = self._workflow_finish_to_stream_response(
|
||||
session=session,
|
||||
task_id=self._application_generate_entity.task_id,
|
||||
workflow_run=workflow_run,
|
||||
@ -461,8 +445,8 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not graph_runtime_state:
|
||||
raise ValueError("graph runtime state not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_partial_success(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._handle_workflow_run_partial_success(
|
||||
session=session,
|
||||
workflow_run_id=self._workflow_run_id,
|
||||
start_at=graph_runtime_state.start_at,
|
||||
@ -477,7 +461,7 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
# save workflow app log
|
||||
self._save_workflow_app_log(session=session, workflow_run=workflow_run)
|
||||
|
||||
workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
|
||||
workflow_finish_resp = self._workflow_finish_to_stream_response(
|
||||
session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
|
||||
)
|
||||
session.commit()
|
||||
@ -489,8 +473,8 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
if not graph_runtime_state:
|
||||
raise ValueError("graph runtime state not initialized.")
|
||||
|
||||
with Session(db.engine, expire_on_commit=False) as session:
|
||||
workflow_run = self._workflow_cycle_manager._handle_workflow_run_failed(
|
||||
with Session(db.engine) as session:
|
||||
workflow_run = self._handle_workflow_run_failed(
|
||||
session=session,
|
||||
workflow_run_id=self._workflow_run_id,
|
||||
start_at=graph_runtime_state.start_at,
|
||||
@ -508,7 +492,7 @@ class WorkflowAppGenerateTaskPipeline:
|
||||
# save workflow app log
|
||||
self._save_workflow_app_log(session=session, workflow_run=workflow_run)
|
||||
|
||||
workflow_finish_resp = self._workflow_cycle_manager._workflow_finish_to_stream_response(
|
||||
workflow_finish_resp = self._workflow_finish_to_stream_response(
|
||||
session=session, task_id=self._application_generate_entity.task_id, workflow_run=workflow_run
|
||||
)
|
||||
session.commit()
|
||||
|
||||
@ -195,7 +195,7 @@ class WorkflowAppGenerateEntity(AppGenerateEntity):
|
||||
|
||||
# app config
|
||||
app_config: WorkflowUIBasedAppConfig
|
||||
workflow_run_id: str
|
||||
workflow_run_id: Optional[str] = None
|
||||
|
||||
class SingleIterationRunEntity(BaseModel):
|
||||
"""
|
||||
|
||||
@ -15,6 +15,7 @@ from core.app.entities.queue_entities import (
|
||||
from core.app.entities.task_entities import (
|
||||
ErrorStreamResponse,
|
||||
PingStreamResponse,
|
||||
TaskState,
|
||||
)
|
||||
from core.errors.error import QuotaExceededError
|
||||
from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
|
||||
@ -29,12 +30,22 @@ class BasedGenerateTaskPipeline:
|
||||
BasedGenerateTaskPipeline is a class that generate stream output and state management for Application.
|
||||
"""
|
||||
|
||||
_task_state: TaskState
|
||||
_application_generate_entity: AppGenerateEntity
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
application_generate_entity: AppGenerateEntity,
|
||||
queue_manager: AppQueueManager,
|
||||
stream: bool,
|
||||
) -> None:
|
||||
"""
|
||||
Initialize GenerateTaskPipeline.
|
||||
:param application_generate_entity: application generate entity
|
||||
:param queue_manager: queue manager
|
||||
:param user: user
|
||||
:param stream: stream
|
||||
"""
|
||||
self._application_generate_entity = application_generate_entity
|
||||
self._queue_manager = queue_manager
|
||||
self._start_at = time.perf_counter()
|
||||
|
||||
@ -31,19 +31,10 @@ from services.annotation_service import AppAnnotationService
|
||||
|
||||
|
||||
class MessageCycleManage:
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
application_generate_entity: Union[
|
||||
ChatAppGenerateEntity,
|
||||
CompletionAppGenerateEntity,
|
||||
AgentChatAppGenerateEntity,
|
||||
AdvancedChatAppGenerateEntity,
|
||||
],
|
||||
task_state: Union[EasyUITaskState, WorkflowTaskState],
|
||||
) -> None:
|
||||
self._application_generate_entity = application_generate_entity
|
||||
self._task_state = task_state
|
||||
_application_generate_entity: Union[
|
||||
ChatAppGenerateEntity, CompletionAppGenerateEntity, AgentChatAppGenerateEntity, AdvancedChatAppGenerateEntity
|
||||
]
|
||||
_task_state: Union[EasyUITaskState, WorkflowTaskState]
|
||||
|
||||
def _generate_conversation_name(self, *, conversation_id: str, query: str) -> Optional[Thread]:
|
||||
"""
|
||||
@ -145,7 +136,7 @@ class MessageCycleManage:
|
||||
|
||||
# get extension
|
||||
if "." in message_file.url:
|
||||
extension = f".{message_file.url.split('.')[-1]}"
|
||||
extension = f'.{message_file.url.split(".")[-1]}'
|
||||
if len(extension) > 10:
|
||||
extension = ".bin"
|
||||
else:
|
||||
|
||||
@ -34,6 +34,7 @@ from core.app.entities.task_entities import (
|
||||
ParallelBranchStartStreamResponse,
|
||||
WorkflowFinishStreamResponse,
|
||||
WorkflowStartStreamResponse,
|
||||
WorkflowTaskState,
|
||||
)
|
||||
from core.file import FILE_MODEL_IDENTITY, File
|
||||
from core.model_runtime.utils.encoders import jsonable_encoder
|
||||
@ -57,20 +58,13 @@ from models.workflow import (
|
||||
WorkflowRunStatus,
|
||||
)
|
||||
|
||||
from .exc import WorkflowRunNotFoundError
|
||||
from .exc import WorkflowNodeExecutionNotFoundError, WorkflowRunNotFoundError
|
||||
|
||||
|
||||
class WorkflowCycleManage:
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity],
|
||||
workflow_system_variables: dict[SystemVariableKey, Any],
|
||||
) -> None:
|
||||
self._workflow_run: WorkflowRun | None = None
|
||||
self._workflow_node_executions: dict[str, WorkflowNodeExecution] = {}
|
||||
self._application_generate_entity = application_generate_entity
|
||||
self._workflow_system_variables = workflow_system_variables
|
||||
_application_generate_entity: Union[AdvancedChatAppGenerateEntity, WorkflowAppGenerateEntity]
|
||||
_task_state: WorkflowTaskState
|
||||
_workflow_system_variables: dict[SystemVariableKey, Any]
|
||||
|
||||
def _handle_workflow_run_start(
|
||||
self,
|
||||
@ -108,8 +102,7 @@ class WorkflowCycleManage:
|
||||
inputs = dict(WorkflowEntry.handle_special_values(inputs) or {})
|
||||
|
||||
# init workflow run
|
||||
# TODO: This workflow_run_id should always not be None, maybe we can use a more elegant way to handle this
|
||||
workflow_run_id = str(self._workflow_system_variables.get(SystemVariableKey.WORKFLOW_RUN_ID) or uuid4())
|
||||
workflow_run_id = str(self._workflow_system_variables.get(SystemVariableKey.WORKFLOW_RUN_ID, uuid4()))
|
||||
|
||||
workflow_run = WorkflowRun()
|
||||
workflow_run.id = workflow_run_id
|
||||
@ -246,7 +239,7 @@ class WorkflowCycleManage:
|
||||
workflow_run.finished_at = datetime.now(UTC).replace(tzinfo=None)
|
||||
workflow_run.exceptions_count = exceptions_count
|
||||
|
||||
stmt = select(WorkflowNodeExecution.node_execution_id).where(
|
||||
stmt = select(WorkflowNodeExecution).where(
|
||||
WorkflowNodeExecution.tenant_id == workflow_run.tenant_id,
|
||||
WorkflowNodeExecution.app_id == workflow_run.app_id,
|
||||
WorkflowNodeExecution.workflow_id == workflow_run.workflow_id,
|
||||
@ -254,18 +247,16 @@ class WorkflowCycleManage:
|
||||
WorkflowNodeExecution.workflow_run_id == workflow_run.id,
|
||||
WorkflowNodeExecution.status == WorkflowNodeExecutionStatus.RUNNING.value,
|
||||
)
|
||||
ids = session.scalars(stmt).all()
|
||||
# Use self._get_workflow_node_execution here to make sure the cache is updated
|
||||
running_workflow_node_executions = [
|
||||
self._get_workflow_node_execution(session=session, node_execution_id=id) for id in ids if id
|
||||
]
|
||||
|
||||
running_workflow_node_executions = session.scalars(stmt).all()
|
||||
|
||||
for workflow_node_execution in running_workflow_node_executions:
|
||||
now = datetime.now(UTC).replace(tzinfo=None)
|
||||
workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value
|
||||
workflow_node_execution.error = error
|
||||
workflow_node_execution.finished_at = now
|
||||
workflow_node_execution.elapsed_time = (now - workflow_node_execution.created_at).total_seconds()
|
||||
workflow_node_execution.finished_at = datetime.now(UTC).replace(tzinfo=None)
|
||||
workflow_node_execution.elapsed_time = (
|
||||
workflow_node_execution.finished_at - workflow_node_execution.created_at
|
||||
).total_seconds()
|
||||
|
||||
if trace_manager:
|
||||
trace_manager.add_trace_task(
|
||||
@ -283,7 +274,7 @@ class WorkflowCycleManage:
|
||||
self, *, session: Session, workflow_run: WorkflowRun, event: QueueNodeStartedEvent
|
||||
) -> WorkflowNodeExecution:
|
||||
workflow_node_execution = WorkflowNodeExecution()
|
||||
workflow_node_execution.id = str(uuid4())
|
||||
workflow_node_execution.id = event.node_execution_id
|
||||
workflow_node_execution.tenant_id = workflow_run.tenant_id
|
||||
workflow_node_execution.app_id = workflow_run.app_id
|
||||
workflow_node_execution.workflow_id = workflow_run.workflow_id
|
||||
@ -307,8 +298,6 @@ class WorkflowCycleManage:
|
||||
workflow_node_execution.created_at = datetime.now(UTC).replace(tzinfo=None)
|
||||
|
||||
session.add(workflow_node_execution)
|
||||
|
||||
self._workflow_node_executions[event.node_execution_id] = workflow_node_execution
|
||||
return workflow_node_execution
|
||||
|
||||
def _handle_workflow_node_execution_success(
|
||||
@ -336,7 +325,6 @@ class WorkflowCycleManage:
|
||||
workflow_node_execution.finished_at = finished_at
|
||||
workflow_node_execution.elapsed_time = elapsed_time
|
||||
|
||||
workflow_node_execution = session.merge(workflow_node_execution)
|
||||
return workflow_node_execution
|
||||
|
||||
def _handle_workflow_node_execution_failed(
|
||||
@ -376,7 +364,6 @@ class WorkflowCycleManage:
|
||||
workflow_node_execution.elapsed_time = elapsed_time
|
||||
workflow_node_execution.execution_metadata = execution_metadata
|
||||
|
||||
workflow_node_execution = session.merge(workflow_node_execution)
|
||||
return workflow_node_execution
|
||||
|
||||
def _handle_workflow_node_execution_retried(
|
||||
@ -404,7 +391,7 @@ class WorkflowCycleManage:
|
||||
execution_metadata = json.dumps(merged_metadata)
|
||||
|
||||
workflow_node_execution = WorkflowNodeExecution()
|
||||
workflow_node_execution.id = str(uuid4())
|
||||
workflow_node_execution.id = event.node_execution_id
|
||||
workflow_node_execution.tenant_id = workflow_run.tenant_id
|
||||
workflow_node_execution.app_id = workflow_run.app_id
|
||||
workflow_node_execution.workflow_id = workflow_run.workflow_id
|
||||
@ -428,8 +415,6 @@ class WorkflowCycleManage:
|
||||
workflow_node_execution.index = event.node_run_index
|
||||
|
||||
session.add(workflow_node_execution)
|
||||
|
||||
self._workflow_node_executions[event.node_execution_id] = workflow_node_execution
|
||||
return workflow_node_execution
|
||||
|
||||
#################################################
|
||||
@ -826,20 +811,22 @@ class WorkflowCycleManage:
|
||||
return None
|
||||
|
||||
def _get_workflow_run(self, *, session: Session, workflow_run_id: str) -> WorkflowRun:
|
||||
if self._workflow_run and self._workflow_run.id == workflow_run_id:
|
||||
cached_workflow_run = self._workflow_run
|
||||
cached_workflow_run = session.merge(cached_workflow_run)
|
||||
return cached_workflow_run
|
||||
"""
|
||||
Refetch workflow run
|
||||
:param workflow_run_id: workflow run id
|
||||
:return:
|
||||
"""
|
||||
stmt = select(WorkflowRun).where(WorkflowRun.id == workflow_run_id)
|
||||
workflow_run = session.scalar(stmt)
|
||||
if not workflow_run:
|
||||
raise WorkflowRunNotFoundError(workflow_run_id)
|
||||
self._workflow_run = workflow_run
|
||||
|
||||
return workflow_run
|
||||
|
||||
def _get_workflow_node_execution(self, session: Session, node_execution_id: str) -> WorkflowNodeExecution:
|
||||
if node_execution_id not in self._workflow_node_executions:
|
||||
raise ValueError(f"Workflow node execution not found: {node_execution_id}")
|
||||
cached_workflow_node_execution = self._workflow_node_executions[node_execution_id]
|
||||
return cached_workflow_node_execution
|
||||
stmt = select(WorkflowNodeExecution).where(WorkflowNodeExecution.id == node_execution_id)
|
||||
workflow_node_execution = session.scalar(stmt)
|
||||
if not workflow_node_execution:
|
||||
raise WorkflowNodeExecutionNotFoundError(node_execution_id)
|
||||
|
||||
return workflow_node_execution
|
||||
|
||||
@ -62,9 +62,8 @@ class ApiExternalDataTool(ExternalDataTool):
|
||||
|
||||
if not api_based_extension:
|
||||
raise ValueError(
|
||||
"[External data tool] API query failed, variable: {}, error: api_based_extension_id is invalid".format(
|
||||
self.variable
|
||||
)
|
||||
"[External data tool] API query failed, variable: {}, "
|
||||
"error: api_based_extension_id is invalid".format(self.variable)
|
||||
)
|
||||
|
||||
# decrypt api_key
|
||||
|
||||
@ -90,7 +90,7 @@ class File(BaseModel):
|
||||
def markdown(self) -> str:
|
||||
url = self.generate_url()
|
||||
if self.type == FileType.IMAGE:
|
||||
text = f""
|
||||
text = f''
|
||||
else:
|
||||
text = f"[{self.filename or url}]({url})"
|
||||
|
||||
|
||||
@ -11,6 +11,15 @@ from configs import dify_config
|
||||
|
||||
SSRF_DEFAULT_MAX_RETRIES = dify_config.SSRF_DEFAULT_MAX_RETRIES
|
||||
|
||||
proxy_mounts = (
|
||||
{
|
||||
"http://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTP_URL),
|
||||
"https://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTPS_URL),
|
||||
}
|
||||
if dify_config.SSRF_PROXY_HTTP_URL and dify_config.SSRF_PROXY_HTTPS_URL
|
||||
else None
|
||||
)
|
||||
|
||||
BACKOFF_FACTOR = 0.5
|
||||
STATUS_FORCELIST = [429, 500, 502, 503, 504]
|
||||
|
||||
@ -42,11 +51,7 @@ def make_request(method, url, max_retries=SSRF_DEFAULT_MAX_RETRIES, **kwargs):
|
||||
if dify_config.SSRF_PROXY_ALL_URL:
|
||||
with httpx.Client(proxy=dify_config.SSRF_PROXY_ALL_URL) as client:
|
||||
response = client.request(method=method, url=url, **kwargs)
|
||||
elif dify_config.SSRF_PROXY_HTTP_URL and dify_config.SSRF_PROXY_HTTPS_URL:
|
||||
proxy_mounts = {
|
||||
"http://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTP_URL),
|
||||
"https://": httpx.HTTPTransport(proxy=dify_config.SSRF_PROXY_HTTPS_URL),
|
||||
}
|
||||
elif proxy_mounts:
|
||||
with httpx.Client(mounts=proxy_mounts) as client:
|
||||
response = client.request(method=method, url=url, **kwargs)
|
||||
else:
|
||||
|
||||
@ -530,6 +530,7 @@ class IndexingRunner:
|
||||
# chunk nodes by chunk size
|
||||
indexing_start_at = time.perf_counter()
|
||||
tokens = 0
|
||||
chunk_size = 10
|
||||
if dataset_document.doc_form != IndexType.PARENT_CHILD_INDEX:
|
||||
# create keyword index
|
||||
create_keyword_thread = threading.Thread(
|
||||
@ -538,22 +539,11 @@ class IndexingRunner:
|
||||
)
|
||||
create_keyword_thread.start()
|
||||
|
||||
max_workers = 10
|
||||
if dataset.indexing_technique == "high_quality":
|
||||
with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
|
||||
with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
|
||||
futures = []
|
||||
|
||||
# Distribute documents into multiple groups based on the hash values of page_content
|
||||
# This is done to prevent multiple threads from processing the same document,
|
||||
# Thereby avoiding potential database insertion deadlocks
|
||||
document_groups: list[list[Document]] = [[] for _ in range(max_workers)]
|
||||
for document in documents:
|
||||
hash = helper.generate_text_hash(document.page_content)
|
||||
group_index = int(hash, 16) % max_workers
|
||||
document_groups[group_index].append(document)
|
||||
for chunk_documents in document_groups:
|
||||
if len(chunk_documents) == 0:
|
||||
continue
|
||||
for i in range(0, len(documents), chunk_size):
|
||||
chunk_documents = documents[i : i + chunk_size]
|
||||
futures.append(
|
||||
executor.submit(
|
||||
self._process_chunk,
|
||||
|
||||
@ -131,7 +131,7 @@ JAVASCRIPT_CODE_GENERATOR_PROMPT_TEMPLATE = (
|
||||
SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
|
||||
"Please help me predict the three most likely questions that human would ask, "
|
||||
"and keeping each question under 20 characters.\n"
|
||||
"MAKE SURE your output is the SAME language as the Assistant's latest response. "
|
||||
"MAKE SURE your output is the SAME language as the Assistant's latest response"
|
||||
"The output must be an array in JSON format following the specified schema:\n"
|
||||
'["question1","question2","question3"]\n'
|
||||
)
|
||||
|
||||
@ -26,7 +26,7 @@ class TokenBufferMemory:
|
||||
self.model_instance = model_instance
|
||||
|
||||
def get_history_prompt_messages(
|
||||
self, max_token_limit: int = 100000, message_limit: Optional[int] = None
|
||||
self, max_token_limit: int = 2000, message_limit: Optional[int] = None
|
||||
) -> Sequence[PromptMessage]:
|
||||
"""
|
||||
Get history prompt messages.
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
from .llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
|
||||
from .llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
|
||||
from .message_entities import (
|
||||
AssistantPromptMessage,
|
||||
AudioPromptMessageContent,
|
||||
@ -23,7 +23,6 @@ __all__ = [
|
||||
"AudioPromptMessageContent",
|
||||
"DocumentPromptMessageContent",
|
||||
"ImagePromptMessageContent",
|
||||
"LLMMode",
|
||||
"LLMResult",
|
||||
"LLMResultChunk",
|
||||
"LLMResultChunkDelta",
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
from decimal import Decimal
|
||||
from enum import StrEnum
|
||||
from enum import Enum
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import BaseModel
|
||||
@ -8,7 +8,7 @@ from core.model_runtime.entities.message_entities import AssistantPromptMessage,
|
||||
from core.model_runtime.entities.model_entities import ModelUsage, PriceInfo
|
||||
|
||||
|
||||
class LLMMode(StrEnum):
|
||||
class LLMMode(Enum):
|
||||
"""
|
||||
Enum class for large language model mode.
|
||||
"""
|
||||
|
||||
@ -221,12 +221,13 @@ class AIModel(ABC):
|
||||
:param credentials: model credentials
|
||||
:return: model schema
|
||||
"""
|
||||
# Try to get model schema from predefined models
|
||||
for predefined_model in self.predefined_models():
|
||||
if model == predefined_model.model:
|
||||
return predefined_model
|
||||
# get predefined models (predefined_models)
|
||||
models = self.predefined_models()
|
||||
|
||||
model_map = {model.model: model for model in models}
|
||||
if model in model_map:
|
||||
return model_map[model]
|
||||
|
||||
# Try to get model schema from credentials
|
||||
if credentials:
|
||||
model_schema = self.get_customizable_model_schema_from_credentials(model, credentials)
|
||||
if model_schema:
|
||||
|
||||
@ -30,11 +30,6 @@ from core.model_runtime.model_providers.__base.ai_model import AIModel
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
HTML_THINKING_TAG = (
|
||||
'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> '
|
||||
"<summary> Thinking... </summary>"
|
||||
)
|
||||
|
||||
|
||||
class LargeLanguageModel(AIModel):
|
||||
"""
|
||||
@ -405,40 +400,6 @@ if you are not sure about the structure.
|
||||
),
|
||||
)
|
||||
|
||||
def _wrap_thinking_by_reasoning_content(self, delta: dict, is_reasoning: bool) -> tuple[str, bool]:
|
||||
"""
|
||||
If the reasoning response is from delta.get("reasoning_content"), we wrap
|
||||
it with HTML details tag.
|
||||
|
||||
:param delta: delta dictionary from LLM streaming response
|
||||
:param is_reasoning: is reasoning
|
||||
:return: tuple of (processed_content, is_reasoning)
|
||||
"""
|
||||
|
||||
content = delta.get("content") or ""
|
||||
reasoning_content = delta.get("reasoning_content")
|
||||
|
||||
if reasoning_content:
|
||||
if not is_reasoning:
|
||||
content = HTML_THINKING_TAG + reasoning_content
|
||||
is_reasoning = True
|
||||
else:
|
||||
content = reasoning_content
|
||||
elif is_reasoning:
|
||||
content = "</details>" + content
|
||||
is_reasoning = False
|
||||
return content, is_reasoning
|
||||
|
||||
def _wrap_thinking_by_tag(self, content: str) -> str:
|
||||
"""
|
||||
if the reasoning response is a <think>...</think> block from delta.get("content"),
|
||||
we replace <think> to <detail>.
|
||||
|
||||
:param content: delta.get("content")
|
||||
:return: processed_content
|
||||
"""
|
||||
return content.replace("<think>", HTML_THINKING_TAG).replace("</think>", "</details>")
|
||||
|
||||
def _invoke_result_generator(
|
||||
self,
|
||||
model: str,
|
||||
|
||||
@ -1,8 +1,8 @@
|
||||
import logging
|
||||
from os.path import abspath, dirname, join
|
||||
from threading import Lock
|
||||
from typing import Any
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
from transformers import GPT2Tokenizer as TransformerGPT2Tokenizer # type: ignore
|
||||
|
||||
_tokenizer: Any = None
|
||||
_lock = Lock()
|
||||
@ -15,16 +15,11 @@ class GPT2Tokenizer:
|
||||
use gpt2 tokenizer to get num tokens
|
||||
"""
|
||||
_tokenizer = GPT2Tokenizer.get_encoder()
|
||||
tokens = _tokenizer.encode(text)
|
||||
tokens = _tokenizer.encode(text, verbose=False)
|
||||
return len(tokens)
|
||||
|
||||
@staticmethod
|
||||
def get_num_tokens(text: str) -> int:
|
||||
# Because this process needs more cpu resource, we turn this back before we find a better way to handle it.
|
||||
#
|
||||
# future = _executor.submit(GPT2Tokenizer._get_num_tokens_by_gpt2, text)
|
||||
# result = future.result()
|
||||
# return cast(int, result)
|
||||
return GPT2Tokenizer._get_num_tokens_by_gpt2(text)
|
||||
|
||||
@staticmethod
|
||||
@ -32,20 +27,8 @@ class GPT2Tokenizer:
|
||||
global _tokenizer, _lock
|
||||
with _lock:
|
||||
if _tokenizer is None:
|
||||
# Try to use tiktoken to get the tokenizer because it is faster
|
||||
#
|
||||
try:
|
||||
import tiktoken
|
||||
|
||||
_tokenizer = tiktoken.get_encoding("gpt2")
|
||||
except Exception:
|
||||
from os.path import abspath, dirname, join
|
||||
|
||||
from transformers import GPT2Tokenizer as TransformerGPT2Tokenizer # type: ignore
|
||||
|
||||
base_path = abspath(__file__)
|
||||
gpt2_tokenizer_path = join(dirname(base_path), "gpt2")
|
||||
_tokenizer = TransformerGPT2Tokenizer.from_pretrained(gpt2_tokenizer_path)
|
||||
logger.info("Fallback to Transformers' GPT-2 tokenizer from tiktoken")
|
||||
base_path = abspath(__file__)
|
||||
gpt2_tokenizer_path = join(dirname(base_path), "gpt2")
|
||||
_tokenizer = TransformerGPT2Tokenizer.from_pretrained(gpt2_tokenizer_path)
|
||||
|
||||
return _tokenizer
|
||||
|
||||
@ -1,5 +1,4 @@
|
||||
- openai
|
||||
- deepseek
|
||||
- anthropic
|
||||
- azure_openai
|
||||
- google
|
||||
@ -33,6 +32,7 @@
|
||||
- localai
|
||||
- volcengine_maas
|
||||
- openai_api_compatible
|
||||
- deepseek
|
||||
- hunyuan
|
||||
- siliconflow
|
||||
- perfxcloud
|
||||
|
||||
@ -51,40 +51,6 @@ model_credential_schema:
|
||||
show_on:
|
||||
- variable: __model_type
|
||||
value: llm
|
||||
- variable: mode
|
||||
show_on:
|
||||
- variable: __model_type
|
||||
value: llm
|
||||
label:
|
||||
en_US: Completion mode
|
||||
type: select
|
||||
required: false
|
||||
default: chat
|
||||
placeholder:
|
||||
zh_Hans: 选择对话类型
|
||||
en_US: Select completion mode
|
||||
options:
|
||||
- value: completion
|
||||
label:
|
||||
en_US: Completion
|
||||
zh_Hans: 补全
|
||||
- value: chat
|
||||
label:
|
||||
en_US: Chat
|
||||
zh_Hans: 对话
|
||||
- variable: context_size
|
||||
label:
|
||||
zh_Hans: 模型上下文长度
|
||||
en_US: Model context size
|
||||
required: true
|
||||
show_on:
|
||||
- variable: __model_type
|
||||
value: llm
|
||||
type: text-input
|
||||
default: "4096"
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的模型上下文长度
|
||||
en_US: Enter your Model context size
|
||||
- variable: jwt_token
|
||||
required: true
|
||||
label:
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user