### What problem does this PR solve?
Dataflow supports markdown.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Dataflow supports Spreadsheet and Word processor document
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Add LongCat-Flash-Chat from Meituan, deepseek v3.1 from SiliconFlow,
kimi-k2-09-05-preview and kimi-k2-turbo-preview from Moonshot.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
The total token was incorrectly accumulated when using the
OpenAI-API-Compatible api.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Refine dataflow and initialize dataflow app.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Moved `signature_version` and `addressing_style` parameters to a
`Config` object from `botocore.config`
`signature_version` is now passed as `Config(signature_version='v4')`
`addressing_style` is now passed as `Config(s3={'addressing_style':
'path'})`
The `Config` object is then passed to `boto3.client()` via the `config`
parameter
## Changes Made
- Modified `rag/utils/s3_conn.py` in the `__open__()` method
- Updated parameter handling logic to use `config_kwargs` dictionary
- Maintained backward compatibility for configurations without these
parameters
## Related Issue
Fixes#9910
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
Co-authored-by: Syed Shahmeer Ali <ashahmeer73@gmail.com>
### What problem does this PR solve?
This PR fixes a critical bug in the knowledge base isolation feature
where chat responses were referencing documents from incorrect knowledge
bases. The issue was in the `infinity_conn.py` file where the
`equivalent_condition_to_str()` function was incorrectly skipping
`kb_id` filtering, causing documents from unintended knowledge bases to
be included in search results.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Syed Shahmeer Ali <ashahmeer73@gmail.com>
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Add exponential back-off for Chat LiteLLM. #9858.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
The default value for OpenAI '/v1/embeddings' parameter
'encoding_format' is 'base64'. Use 'float' explicitly to avoid base64
encoding & decoding, larger data size.
https://github.com/openai/openai-python/blob/main/src/openai/resources/embeddings.py
if not is_given(encoding_format):
params["encoding_format"] = "base64"
### Type of change
- [x] Performance Improvement
### What problem does this PR solve?
This revision performed a comprehensive check on LightRAG to ensure the
correctness of its implementation. It **did not involve** Entity
Resolution and Community Reports Generation. There is an example using
default entity types and the General chunking method, which shows good
results in both time and effectiveness. Moreover, response caching is
enabled for resuming failed tasks.
[The-Necklace.pdf](https://github.com/user-attachments/files/22042432/The-Necklace.pdf)
After:
```bash
Begin at:
Fri, 29 Aug 2025 16:48:03 GMT
Duration:
222.31 s
Progress:
16:48:04 Task has been received.
16:48:06 Page(1~7): Start to parse.
16:48:06 Page(1~7): OCR started
16:48:08 Page(1~7): OCR finished (1.89s)
16:48:11 Page(1~7): Layout analysis (3.72s)
16:48:11 Page(1~7): Table analysis (0.00s)
16:48:11 Page(1~7): Text merged (0.00s)
16:48:11 Page(1~7): Finish parsing.
16:48:12 Page(1~7): Generate 7 chunks
16:48:12 Page(1~7): Embedding chunks (0.29s)
16:48:12 Page(1~7): Indexing done (0.04s). Task done (7.84s)
16:48:17 Start processing for f421fb06849e11f0bdd32724b93a52b2: She had no dresses, no je...
16:48:17 Start processing for f421fb06849e11f0bdd32724b93a52b2: Her husband, already half...
16:48:17 Start processing for f421fb06849e11f0bdd32724b93a52b2: And this life lasted ten ...
16:48:17 Start processing for f421fb06849e11f0bdd32724b93a52b2: Then she asked, hesitatin...
16:49:30 Completed processing for f421fb06849e11f0bdd32724b93a52b2: She had no dresses, no je... after 1 gleanings, 21985 tokens.
16:49:30 Entities extraction of chunk 3 1/7 done, 12 nodes, 13 edges, 21985 tokens.
16:49:40 Completed processing for f421fb06849e11f0bdd32724b93a52b2: Finally, she replied, hes... after 1 gleanings, 22584 tokens.
16:49:40 Entities extraction of chunk 5 2/7 done, 19 nodes, 19 edges, 22584 tokens.
16:50:02 Completed processing for f421fb06849e11f0bdd32724b93a52b2: Then she asked, hesitatin... after 1 gleanings, 24610 tokens.
16:50:02 Entities extraction of chunk 0 3/7 done, 16 nodes, 28 edges, 24610 tokens.
16:50:03 Completed processing for f421fb06849e11f0bdd32724b93a52b2: And this life lasted ten ... after 1 gleanings, 24031 tokens.
16:50:04 Entities extraction of chunk 1 4/7 done, 24 nodes, 22 edges, 24031 tokens.
16:50:14 Completed processing for f421fb06849e11f0bdd32724b93a52b2: So they begged the jewell... after 1 gleanings, 24635 tokens.
16:50:14 Entities extraction of chunk 6 5/7 done, 27 nodes, 26 edges, 24635 tokens.
16:50:29 Completed processing for f421fb06849e11f0bdd32724b93a52b2: Her husband, already half... after 1 gleanings, 25758 tokens.
16:50:29 Entities extraction of chunk 2 6/7 done, 25 nodes, 35 edges, 25758 tokens.
16:51:35 Completed processing for f421fb06849e11f0bdd32724b93a52b2: The Necklace By Guy de Ma... after 1 gleanings, 27491 tokens.
16:51:35 Entities extraction of chunk 4 7/7 done, 39 nodes, 37 edges, 27491 tokens.
16:51:35 Entities and relationships extraction done, 147 nodes, 177 edges, 171094 tokens, 198.58s.
16:51:35 Entities merging done, 0.01s.
16:51:35 Relationships merging done, 0.01s.
16:51:35 ignored 7 relations due to missing entities.
16:51:35 generated subgraph for doc f421fb06849e11f0bdd32724b93a52b2 in 198.68 seconds.
16:51:35 run_graphrag f421fb06849e11f0bdd32724b93a52b2 graphrag_task_lock acquired
16:51:35 set_graph removed 0 nodes and 0 edges from index in 0.00s.
16:51:35 Get embedding of nodes: 9/147
16:51:35 Get embedding of nodes: 109/147
16:51:37 Get embedding of edges: 9/170
16:51:37 Get embedding of edges: 109/170
16:51:40 set_graph converted graph change to 319 chunks in 4.21s.
16:51:40 Insert chunks: 4/319
16:51:40 Insert chunks: 104/319
16:51:40 Insert chunks: 204/319
16:51:40 Insert chunks: 304/319
16:51:40 set_graph added/updated 147 nodes and 170 edges from index in 0.53s.
16:51:40 merging subgraph for doc f421fb06849e11f0bdd32724b93a52b2 into the global graph done in 4.79 seconds.
16:51:40 Knowledge Graph done (204.29s)
```
Before:
```bash
Begin at:
Fri, 29 Aug 2025 17:00:47 GMT
processDuration:
173.38 s
Progress:
17:00:49 Task has been received.
17:00:51 Page(1~7): Start to parse.
17:00:51 Page(1~7): OCR started
17:00:53 Page(1~7): OCR finished (1.82s)
17:00:57 Page(1~7): Layout analysis (3.64s)
17:00:57 Page(1~7): Table analysis (0.00s)
17:00:57 Page(1~7): Text merged (0.00s)
17:00:57 Page(1~7): Finish parsing.
17:00:57 Page(1~7): Generate 7 chunks
17:00:57 Page(1~7): Embedding chunks (0.31s)
17:00:57 Page(1~7): Indexing done (0.03s). Task done (7.88s)
17:00:57 created task graphrag
17:01:00 Task has been received.
17:02:17 Entities extraction of chunk 1 1/7 done, 9 nodes, 9 edges, 10654 tokens.
17:02:31 Entities extraction of chunk 2 2/7 done, 12 nodes, 13 edges, 11066 tokens.
17:02:33 Entities extraction of chunk 4 3/7 done, 9 nodes, 10 edges, 10433 tokens.
17:02:42 Entities extraction of chunk 5 4/7 done, 11 nodes, 14 edges, 11290 tokens.
17:02:52 Entities extraction of chunk 6 5/7 done, 13 nodes, 15 edges, 11039 tokens.
17:02:55 Entities extraction of chunk 3 6/7 done, 14 nodes, 13 edges, 11466 tokens.
17:03:32 Entities extraction of chunk 0 7/7 done, 19 nodes, 18 edges, 13107 tokens.
17:03:32 Entities and relationships extraction done, 71 nodes, 89 edges, 79055 tokens, 149.66s.
17:03:32 Entities merging done, 0.01s.
17:03:32 Relationships merging done, 0.01s.
17:03:32 ignored 1 relations due to missing entities.
17:03:32 generated subgraph for doc b1d9d3b6848711f0aacd7ddc0714c4d3 in 149.69 seconds.
17:03:32 run_graphrag b1d9d3b6848711f0aacd7ddc0714c4d3 graphrag_task_lock acquired
17:03:32 set_graph removed 0 nodes and 0 edges from index in 0.00s.
17:03:32 Get embedding of nodes: 9/71
17:03:33 Get embedding of edges: 9/88
17:03:34 set_graph converted graph change to 161 chunks in 2.27s.
17:03:34 Insert chunks: 4/161
17:03:34 Insert chunks: 104/161
17:03:34 set_graph added/updated 71 nodes and 88 edges from index in 0.28s.
17:03:34 merging subgraph for doc b1d9d3b6848711f0aacd7ddc0714c4d3 into the global graph done in 2.60 seconds.
17:03:34 Knowledge Graph done (153.18s)
```
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
- [x] Performance Improvement
### What problem does this PR solve?
Fix Ollama chat can only access localhost instance. #9806.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
for total_token_count method use if to check first, to improve the
performance when we need to handle exception cases
### Type of change
- [x] Refactoring
### What problem does this PR solve?
based on async await to handle Redis when raptor
### Type of change
- [x] Refactoring
- [x] Performance Improvement
### What problem does this PR solve?
Refactor OpenAI to enable audio parsing.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring
### What problem does this PR solve?
Fix Gemini parameters error.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
---------
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
Add embedded search functionality.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
---------
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
### What problem does this PR solve?
1. Use input length to prepare res
2. Adjust torch_empty_cache code location
### Type of change
- [x] Refactoring
- [x] Performance Improvement
### What problem does this PR solve?
Handle unexpected truncated Excel files.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
fix: preserve correct MIME & unify data URL handling for vision inputs
(relates #9248)
- Updated image2base64() to return a full data URL
(data:image/<fmt>;base64,...) with accurate MIME
- Removed hardcoded image/jpeg in Base._image_prompt(); pass through
data URLs and default raw base64 to image/png
- Set AnthropicCV._image_prompt() raw base64 media_type default to
image/png
- Ensures MIME type matches actual image content, fixing “cannot process
base64 image” errors on vLLM/OpenAI-compatible backends
### What problem does this PR solve?
This PR fixes a compatibility issue where base64-encoded images sent to
vision models (e.g., vLLM/OpenAI-compatible backends) were rejected due
to mismatched MIME type or incorrect decoding.
Previously, the backend:
- Always converted raw base64 into data:image/jpeg;base64,... even if
the actual content was PNG.
- In some cases, base64 decoding was attempted on the full data URL
string instead of the pure base64 part.
This caused errors like:
```
cannot process base64 image
failed to decode base64 string: illegal base64 data at input byte 0
```
by strict validators such as vLLM.
With this fix, the MIME type in the request now matches the actual image
content, and data URLs are correctly handled or passed through, ensuring
vision models can decode and process images reliably.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
All models pass the mock response tests, which means that if a model can
return the correct response, everything should work as expected.
However, not all models have been fully tested in a real environment,
the real API_KEY. I suggest actively monitoring the refactored models
over the coming period to ensure they work correctly and fixing them
step by step, or waiting to merge until most have been tested in
practical environment.
### Type of change
- [x] Refactoring
### What problem does this PR solve?
fix "no `tc` element at grid_offset", just log warning and ignore.
stacktrace:
```
Traceback (most recent call last):
File "/ragflow/rag/svr/task_executor.py", line 620, in handle_task
await do_handle_task(task)
File "/ragflow/rag/svr/task_executor.py", line 553, in do_handle_task
chunks = await build_chunks(task, progress_callback)
File "/ragflow/rag/svr/task_executor.py", line 257, in build_chunks
cks = await trio.to_thread.run_sync(lambda: chunker.chunk(task["name"], binary=binary, from_page=task["from_page"],
File "/ragflow/.venv/lib/python3.10/site-packages/trio/_threads.py", line 447, in to_thread_run_sync
return msg_from_thread.unwrap()
File "/ragflow/.venv/lib/python3.10/site-packages/outcome/_impl.py", line 213, in unwrap
raise captured_error
File "/ragflow/.venv/lib/python3.10/site-packages/trio/_threads.py", line 373, in do_release_then_return_result
return result.unwrap()
File "/ragflow/.venv/lib/python3.10/site-packages/outcome/_impl.py", line 213, in unwrap
raise captured_error
File "/ragflow/.venv/lib/python3.10/site-packages/trio/_threads.py", line 392, in worker_fn
ret = context.run(sync_fn, *args)
File "/ragflow/rag/svr/task_executor.py", line 257, in <lambda>
cks = await trio.to_thread.run_sync(lambda: chunker.chunk(task["name"], binary=binary, from_page=task["from_page"],
File "/ragflow/rag/app/naive.py", line 384, in chunk
sections, tables = Docx()(filename, binary)
File "/ragflow/rag/app/naive.py", line 230, in __call__
while i < len(r.cells):
File "/ragflow/.venv/lib/python3.10/site-packages/docx/table.py", line 438, in cells
return tuple(_iter_row_cells())
File "/ragflow/.venv/lib/python3.10/site-packages/docx/table.py", line 436, in _iter_row_cells
yield from iter_tc_cells(tc)
File "/ragflow/.venv/lib/python3.10/site-packages/docx/table.py", line 424, in iter_tc_cells
yield from iter_tc_cells(tc._tc_above) # pyright: ignore[reportPrivateUsage]
File "/ragflow/.venv/lib/python3.10/site-packages/docx/oxml/table.py", line 741, in _tc_above
return self._tr_above.tc_at_grid_offset(self.grid_offset)
File "/ragflow/.venv/lib/python3.10/site-packages/docx/oxml/table.py", line 98, in tc_at_grid_offset
raise ValueError(f"no `tc` element at grid_offset={grid_offset}")
ValueError: no `tc` element at grid_offset=10
```
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
