## Summary
- When an agent workflow has multiple `UserFillUp` pause points,
`canvas.run()` calls `reset(True)` on **all** components at the start of
each run. This clears outputs from components that completed in prior
runs, so downstream references like `{Agent:XXX@content}` resolve to
`None`.
- This fix only resets components on the **current execution path**
(`self.path`), preserving outputs from previously completed components.
## Problem
In a multi-step agent (e.g. draft email → user confirms → send email):
1. First `run()`: Agent drafts content, UserFillUp pauses for user input
→ Agent output is saved
2. Second `run()`: User submits input, but `reset(True)` clears **all**
components including the Agent that already completed
3. Email component references `{Agent:XXX@content}` → gets `None`
instead of the draft
This affects **all** agents that reference upstream component outputs
after a UserFillUp pause point.
## Fix
```python
# Before: reset ALL components
for k, cpn in self.components.items():
self.components[k]["obj"].reset(True)
# After: only reset components on current execution path
path_set = set(self.path)
for k, cpn in self.components.items():
if k in path_set:
self.components[k]["obj"].reset(True)
```
`self.path` already tracks the current execution path. For agents
without UserFillUp (single run), `path` contains all components, so
behavior is unchanged.
## Test plan
- [x] Agent with single UserFillUp: outputs from prior components are
preserved after resume
- [x] Agent with multiple UserFillUp: each resume preserves all
previously completed outputs
- [x] Agent without UserFillUp: behavior unchanged (all components in
path, all reset)
- [x] Webhook-triggered agents: unaffected (path includes all components
on first run)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: wanghualoong <wanghualoong@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
### What problem does this PR solve?
Fixes#14412.
`common.metadata_utils.meta_filter` evaluates user-defined metadata
conditions in Python after `DocMetadataService.get_flatted_meta_by_kbs`
loads the entire `meta_fields` table into memory. Past a few thousand
documents per knowledge base this becomes a memory bottleneck and a
wasted ES round-trip — every filter request currently fetches up to
10000 metadata rows even when the resulting `doc_ids` list is tiny.
This PR adds an ES push-down path that translates the same filter
language into a `bool` query and returns just the matching document IDs.
**Changes**
- `common/metadata_es_filter.py` *(new)*: pure-Python translator from
the RAGflow filter list to ES DSL. Covers every operator the in-memory
path supports (`=`, `≠`, `>`, `<`, `≥`, `≤`, `in`, `not in`, `contains`,
`not contains`, `start with`, `end with`, `empty`, `not empty`) with
`case_insensitive: true` on `prefix` and `wildcard` for parity with the
existing lower-cased Python comparisons. User wildcard metacharacters
are escaped before being injected into `wildcard` patterns. Negative
operators (`≠`, `not in`, `not contains`, ranges) are wrapped with an
`exists` guard so they do not accidentally match documents missing the
key, matching the legacy `if k not in metas` behaviour.
- `api/db/services/doc_metadata_service.py`: new
`DocMetadataService.filter_doc_ids_by_meta_pushdown(kb_ids, filters,
logic)` that returns the doc IDs ES matched, or `None` to signal the
caller should fall back to the in-memory path. Returns `None` when the
active doc store is Infinity (`meta_fields` is a JSON column, not a
dotted-object mapping), when any filter cannot be expressed in DSL
(`UnsupportedMetaFilter`), or when the ES request or metadata index
lookup errors.
- `common/metadata_utils.py`: `apply_meta_data_filter` accepts an
optional `kb_ids` argument. When supplied, conditions go through
push-down first via a new `_try_meta_pushdown` helper; on `None` the
function falls back to the original `meta_filter` call. Default
behaviour is unchanged for callers that don't pass `kb_ids`.
- Updated all four callers (`agent/tools/retrieval.py`,
`api/db/services/dialog_service.py` ×2,
`api/apps/services/dataset_api_service.py`, `api/apps/sdk/session.py`)
to forward `kb_ids` so the push-down path is exercised in production.
- `test/unit_test/common/test_metadata_es_filter.py` *(new)*: 35 unit
tests covering every operator's DSL shape, value coercion
(`ast.literal_eval`, lowercasing, ISO-date pass-through), wildcard
escaping, OR-logic wrapping that protects negative clauses, and the
doc-ID extractor.
**Behaviour preserved**
- The in-memory `meta_filter` is untouched and still services every
fallback case (Infinity backend, unknown operators, ES outages).
- The eligibility / credibility / issue-multiplier semantics described
in the LLM-driven `auto` and `semi_auto` modes still hand the LLM the
full in-memory `metas` dict to choose conditions from. Only the
*evaluation* of those generated conditions is pushed down.
- Existing tests in
`test/unit_test/common/test_metadata_filter_operators.py` continue to
pass (14/14).
**Test plan**
- `pytest test/unit_test/common/test_metadata_es_filter.py` — 35 passed.
- `pytest test/unit_test/common/test_metadata_filter_operators.py` — 14
passed.
- `ruff check` clean on every modified file.
- Reviewer please validate the ES query shapes against a live cluster —
particularly `case_insensitive` on `wildcard` and `prefix` (requires ES
7.10+) and the `exists` + `must_not` pairing for `≠`.
**Notes**
- The first cut caps each push-down request at 10000 results, matching
the existing `get_flatted_meta_by_kbs` limit, and logs a warning when
the cap is hit. A `search_after` follow-up would let us drop the cap
entirely once the push-down path is validated.
- Operator parity with the in-memory path is exact for the canonical
unicode operators (`≥`, `≤`, `≠`) used internally; the ASCII aliases
(`>=`, `<=`, `!=`) are normalised by `convert_conditions` before they
reach the translator.
### Type of change
- [x] Performance Improvement
---------
Co-authored-by: sxxtony <sxxtony@users.noreply.github.com>
### What problem does this PR solve?
Feat: support local provider for code exec component & remove some
outdated models
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
preserve doc generator download metadata
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
agent toolcall null response & schema validation & DeepSeek think
history
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
prioritize explore session ID and reset default conversation variables
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Before migration: GET /v1/document/artifact/<filename>
After migration: GET /api/v1/documents/artifact/<filename>
### Type of change
- [x] Refactoring
### What problem does this PR solve?
The POST /upload_info?url=<url> endpoint accepted a user-supplied URL
and passed it directly to AsyncWebCrawler without any validation. There
were no restrictions on URL scheme, destination hostname, or resolved IP
address. This allowed any authenticated user to instruct the server to
make outbound HTTP requests to internal infrastructure — including RFC
1918 private networks, loopback addresses, and cloud metadata services
such as http://169.254.169.254 — effectively using the server as a proxy
for internal network reconnaissance or credential theft.
This PR adds an SSRF guard (_validate_url_for_crawl) that runs before
any crawl is initiated. It enforces an allowlist of safe schemes
(http/https), resolves the hostname at validation time, and rejects any
URL whose resolved IP falls within a private or reserved network range.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Add tips for installing Chinse fonts under code sandbox. Otherwise,
`matplotlib `won't render Chinese correctly.
<img width="2082" height="1186" alt="sales_analysis"
src="https://github.com/user-attachments/assets/57e675ab-1e92-4662-9aeb-ad72a6121eb5"
/>
### Type of change
- [x] Documentation Update
### What problem does this PR solve?
Add a new agent template that demonstrates how to leverage the
`CodeExec` component to do the data analysis.
### Type of change
- [x] Other (please describe): Agent template
### What problem does this PR solve?
Updated ingestion pipeline template descriptions for better technical
accuracy and readability.
### Type of change
- [x] Refactoring
### What problem does this PR solve?
Sandbox don't attach attachment metadata
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Feat: update templates && add resume template
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
- Implemented a helper function to convert markdown cell text to native
numeric types for Excel output.
- Ensured that leading zeros are preserved and handled various numeric
formats, including those with thousand separators and scientific
notation.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Closes#13907
The template catalog had duplicate files (e.g. `*_r.json`) only to place
the same template into multiple sidebar groups.
This increases maintenance cost and makes template updates error-prone.
This PR adds first-class support for multiple template categories in a
single file via `canvas_types`, then removes duplicate template files.
What changed:
- Added `canvas_types` to `CanvasTemplate` model and DB migration.
- Added normalization logic when loading templates:
- accepts legacy `canvas_type`
- accepts new `canvas_types`
- merges/deduplicates values
- preserves backward compatibility by keeping `canvas_type` as first
normalized value.
- Updated template import flow to load only `.json` files and in stable
sorted order.
- Updated frontend template filtering to match on `canvas_types` first,
with fallback to legacy `canvas_type`.
- Consolidated duplicated template pairs into single files and removed:
- `deep_search_r.json`
- `reflective_academic_paper_generator_r.json`
- `seo_article_writer_r.json`
- Added regression/edge-case tests for category normalization and route
serialization expectations.
### Type of change
- [ ] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [ ] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):
### What problem does this PR solve?
Sandbox cannot accept large args list.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Close#14018
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### Problem
In Agent applications, even with the cite option enabled, only inline
[ID: x] citation markers are visible (showing chunk content on hover).
The Agent does not display the referenced file cards below the response,
unlike Chat applications.
### Root Cause
The Agent's Retrieval tool (agent/tools/retrieval.py) calls
retriever.retrieval() with aggs=False, which means the retrieval results
do not include doc_aggs (document aggregation) data. Without doc_aggs,
the frontend ReferenceDocumentList component has no data to render the
file cards.
In contrast, the Chat application (api/db/services/dialog_service.py)
calls the same retriever.retrieval() method with aggs=True.
### Fix
Changed aggs=False to aggs=True in agent/tools/retrieval.py so that
document aggregation data is returned along with the retrieved chunks.
### What problem does this PR solve?
Fix import error in sandbox provider.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Chores**
* Updated internal configuration import mechanism for sandbox provider
initialization. No end-user impact.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
### What problem does this PR solve?
Fix: The agent selected a knowledge base, but the API returned the
error: "No dataset is selected".
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: balibabu <assassin_cike@163.com>
### What problem does this PR solve?
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
---------
Co-authored-by: Zhichang Yu <yuzhichang@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
### What problem does this PR solve?
Update the customer feedback dispatcher template and introduce a new
operator `Variable Aggregator`.
### Type of change
- [x] Other (please describe): Template change
---------
Co-authored-by: Jin Hai <haijin.chn@gmail.com>
\`switch.py\` line 137 concatenates the operator directly after the text
without separator:
\`'Not supported operator' + operator\` → produces \`"Not supported
operatorXXX"\`
Changed to: \`f'Not supported operator: {operator}'\`
Two small fixes:
1. **iterationitem.py line 72**: Typo "interationitem" → "iterationitem"
(missing 't'). The component name check never matched IterationItem
components.
2. **raptor.py line 94**: Error message "Embedding error: " had a
trailing colon with no details. Changed to "Embedding error: empty
embeddings returned".
## Summary
Add a complete Turkish translation of the README and include a Turkish
language badge across all existing README files.
## Changes
- **New file**: `README_tr.md` - Full Turkish translation of README.md,
covering all sections (What is RAGFlow, Demo, Latest Updates, Key
Features, System Architecture, Get Started, Configurations, Docker
Image, Development from Source, Documentation, Roadmap, Community,
Contributing)
- **Updated 9 existing README files** (README.md, README_zh.md,
README_tzh.md, README_ja.md, README_ko.md, README_id.md,
README_pt_br.md, README_fr.md, README_ar.md) to include the Turkish
language badge in the language selector
## Impact
- 10 files changed, 417 insertions
- Follows the same structure and conventions as other language-specific
README files (README_ja.md, README_ko.md, etc.)
- Turkish badge uses the same styling pattern (highlighted with DBEDFA
in README_tr.md, standard DFE0E5 in others)
---------
Co-authored-by: bakiburakogun <bakiburakogun@users.noreply.github.com>
### What problem does this PR solve?
Get user_id from canvas variable when input a {} pattern value.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Closes#13277
### What problem does this PR solve?
Adds `{variable_name}` (and `{component@variable}`) interpolation
support to HTTP header values in the `Invoke` component, matching the
existing URL interpolation behavior.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
<img width="1280" height="867" alt="image"
src="https://github.com/user-attachments/assets/8ab7b4e9-7cc0-4a7f-8a5f-f838a15a5fda"
/>
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
### What problem does this PR solve?
Get user_id from canvas and record it.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
## Summary
This PR fixes two runtime bugs in agent components:
**Bug 1: `agent/component/invoke.py` — `NameError` in POST +
`clean_html` path**
The POST method's `clean_html` branch uses the variable `sections`
without ever defining it. Both the GET and PUT branches correctly call
`sections = HtmlParser()(None, response.content)` before referencing
`sections`, but this line was missing from the POST branch (copy-paste
omission). This causes a `NameError` whenever a user configures an
Invoke component with `method="post"` and `clean_html=True`.
**Bug 2: `agent/component/data_operations.py` — `AttributeError` in
`_recursive_eval`**
The `_recursive_eval` method recursively calls `self.recursive_eval()`
(without the leading underscore) instead of `self._recursive_eval()`.
Since the method is defined as `_recursive_eval`, this causes an
`AttributeError` at runtime when the `literal_eval` operation processes
nested dicts or lists.
## Test plan
- [ ] Configure an Invoke node with `method=post` and `clean_html=True`,
verify HTML is parsed correctly without `NameError`
- [ ] Configure a DataOperations node with `operations=literal_eval` on
nested data, verify no `AttributeError`
---------
Signed-off-by: JiangNan <1394485448@qq.com>
## Summary
Fix a database connection and cursor resource leak in the ExeSQL agent
tool.
When SQL execution raises an exception (for example syntax error or
missing table),
the existing code path skips `cursor.close()` and `db.close()`, causing
database
connections to accumulate over time.
This can eventually lead to connection exhaustion in long-running agent
workflows.
## Root Cause
The cleanup logic for database cursors and connections is placed after
the SQL
execution loop without `try/finally` protection. If an exception occurs
during
`cursor.execute()`, `fetchmany()`, or result processing, the cleanup
code is not
reached and the connection remains open.
The same issue also exists in the IBM DB2 execution path where
`ibm_db.close(conn)`
may be skipped when exceptions occur.
## Fix
- Wrap SQL execution logic in `try/finally` blocks to guarantee resource
cleanup.
- Ensure `cursor.close()` and `db.close()` are always executed.
- Add explicit `db.close()` when `db.cursor()` creation fails.
- Remove redundant close calls in early-return branches since `finally`
now handles cleanup.
## Impact
- No change to normal execution behavior.
- Ensures database resources are always released when errors occur.
- Prevents connection leaks in long-running workflows.
- Only affects `agent/tools/exesql.py`.
## Testing
Manual test scenarios:
1. Valid SQL execution
2. SQL syntax error
3. Query against a non-existing table
4. Execution cancellation during query
In all scenarios the database cursor and connection are properly closed.
Code quality checks:
- `ruff check` passed
- No new warnings introduced
### What problem does this PR solve?
Fix update_cnt add error in init_data.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
