### What problem does this PR solve?
_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Co-authored-by: Jason <ggbbddjm@gmail.com>
### What problem does this PR solve?
[Update LLM factory ranks in llm_factories.json]
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
#10056
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Added vendor ranking so that frequently used model providers appear
higher on the page for easier access.
Remove deprecated LLM configurations from llm_factories.json to
streamline model management
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
fix infinity "INSERT: Column raptor_kwd not found in table" error
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: remove unsupported models in siliconflow api
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Add kimi-k2-thinking and moonshot-v1-vision-preview.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
This commit removes the Youdao and BAAI entries from the LLM factories
configuration as they are no longer needed or supported.
### Type of change
- [x] Config update
### What problem does this PR solve?
This PR adds a new TCADP (Tencent Cloud Advanced Document Processing)
parser to RAGFlow, enabling users to leverage Tencent Cloud's document
parsing capabilities for more accurate and structured document
processing. The implementation includes:
New TCADP Parser: A complete implementation of Tencent Cloud's document
parsing API without SDK dependency
Configuration Support: Added configuration options in service_conf.yaml
for Tencent Cloud API credentials
Frontend Integration: Updated UI components to support the new TCADP
parser option
Error Handling: Comprehensive error handling and retry mechanisms for
API calls
Result Processing: Support for both SSE streaming and JSON response
formats from Tencent Cloud API
### 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?
Introduced gpu profile in .env
Added Dockerfile_tei
fix datrie
Removed LIGHTEN flag
### Type of change
- [x] Documentation Update
- [x] Refactoring
### What problem does this PR solve?
issue:
[#9004](https://github.com/infiniflow/ragflow/issues/9004)
change:
VolcEngine Model type add IMAGE2TEXT
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
- Added new field 'toc_kwd' to infinity_mapping.json for table of
contents keyword support
- Changed page_num_int from integer to array type in task_executor.py to
handle multiple page numbers
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
fix issues：https://github.com/infiniflow/ragflow/issues/10402
As the newly distributed embedding models support vector dimensions max
to 4096, while current OpenSearch's max dimension support is 1536.
As I tested, the 4096-dimensions vector will be treated as a float type
which is unacceptable in OpenSearch.
Besides, OpenSearch supports max to 16000 dimensions by defalut with the
vector engine(Faiss). According to:
https://docs.opensearch.org/2.19/field-types/supported-field-types/knn-methods-engines/
I added max to 10240 dimensions support for OpenSearch, as I think will
be sufficient in the future.
As I tested , it worked well on my own server (treated as knn_vector)by
using qwen3-embedding:8b as the embedding model:
<img width="1338" height="790" alt="image"
src="https://github.com/user-attachments/assets/a9b2d284-fcf6-4cea-859a-6aadccf36ace"
/>
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
By the way, I will still focus on the stuff about
Elasticsearch/Opensearch as search engines and vector databases.
Co-authored-by: 张雨豪 <zhangyh80@chinatelecom.cn>
### Related issues
#10078
### What problem does this PR solve?
Integrate DeerAPI provider.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
Co-authored-by: DeerAPI <tensor.null@gmail.com>
### What problem does this PR solve?
Add support for LongCat-Flash-Thinking and Claude Sonnet 4.5.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
fix: Wrong Qwen models's ID
[Bug]: ERROR: litellm.NotFoundError: DashscopeException - The model
Qwen/Qwen3-Omni-Flash does not exist or you do not have access to it.
change: delete wrong qwen model id
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Fix: resolve hash collisions by switching to UUID &correct logic for
always-true statements, solved: #10165
Feat: Update GPT api integration, solved: #10204
Feat: Support qianwen-deepresearch, solved: #10163
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Introduce new feature: RAGFlow system admin service and CLI
### Introduction
Admin Service is a dedicated management component designed to monitor,
maintain, and administrate the RAGFlow system. It provides comprehensive
tools for ensuring system stability, performing operational tasks, and
managing users and permissions efficiently.
The service offers monitoring of critical components, including the
RAGFlow server, Task Executor processes, and dependent services such as
MySQL, Infinity / Elasticsearch, Redis, and MinIO. It automatically
checks their health status, resource usage, and uptime, and performs
restarts in case of failures to minimize downtime.
For user and system management, it supports listing, creating,
modifying, and deleting users and their associated resources like
knowledge bases and Agents.
Built with scalability and reliability in mind, the Admin Service
ensures smooth system operation and simplifies maintenance workflows.
It consists of a server-side Service and a command-line client (CLI),
both implemented in Python. User commands are parsed using the Lark
parsing toolkit.
- **Admin Service**: A backend service that interfaces with the RAGFlow
system to execute administrative operations and monitor its status.
- **Admin CLI**: A command-line interface that allows users to connect
to the Admin Service and issue commands for system management.
### Starting the Admin Service
1. Before start Admin Service, please make sure RAGFlow system is
already started.
2. Run the service script:
```bash
python admin/admin_server.py
```
The service will start and listen for incoming connections from the CLI
on the configured port.
### Using the Admin CLI
1. Ensure the Admin Service is running.
2. Launch the CLI client:
```bash
python admin/admin_client.py -h 0.0.0.0 -p 9381
## Supported Commands
Commands are case-insensitive and must be terminated with a semicolon
(`;`).
### Service Management Commands
- [x] `LIST SERVICES;`
- Lists all available services within the RAGFlow system.
- [ ] `SHOW SERVICE <id>;`
- Shows detailed status information for the service identified by
`<id>`.
- [ ] `STARTUP SERVICE <id>;`
- Attempts to start the service identified by `<id>`.
- [ ] `SHUTDOWN SERVICE <id>;`
- Attempts to gracefully shut down the service identified by `<id>`.
- [ ] `RESTART SERVICE <id>;`
- Attempts to restart the service identified by `<id>`.
### User Management Commands
- [x] `LIST USERS;`
- Lists all users known to the system.
- [ ] `SHOW USER '<username>';`
- Shows details and permissions for the specified user. The username
must be enclosed in single or double quotes.
- [ ] `DROP USER '<username>';`
- Removes the specified user from the system. Use with caution.
- [ ] `ALTER USER PASSWORD '<username>' '<new_password>';`
- Changes the password for the specified user.
### Data and Agent Commands
- [ ] `LIST DATASETS OF '<username>';`
- Lists the datasets associated with the specified user.
- [ ] `LIST AGENTS OF '<username>';`
- Lists the agents associated with the specified user.
### Meta-Commands
Meta-commands are prefixed with a backslash (`\`).
- `\?` or `\help`
- Shows help information for the available commands.
- `\q` or `\quit`
- Exits the CLI application.
## Examples
```commandline
admin> list users;
+-------------------------------+------------------------+-----------+-------------+
| create_date | email | is_active | nickname |
+-------------------------------+------------------------+-----------+-------------+
| Fri, 22 Nov 2024 16:03:41 GMT | jeffery@infiniflow.org | 1 | Jeffery |
| Fri, 22 Nov 2024 16:10:55 GMT | aya@infiniflow.org | 1 | Waterdancer |
+-------------------------------+------------------------+-----------+-------------+
admin> list services;
+-------------------------------------------------------------------------------------------+-----------+----+---------------+-------+----------------+
| extra | host | id | name | port | service_type |
+-------------------------------------------------------------------------------------------+-----------+----+---------------+-------+----------------+
| {} | 0.0.0.0 | 0 | ragflow_0 | 9380 | ragflow_server |
| {'meta_type': 'mysql', 'password': 'infini_rag_flow', 'username': 'root'} | localhost | 1 | mysql | 5455 | meta_data |
| {'password': 'infini_rag_flow', 'store_type': 'minio', 'user': 'rag_flow'} | localhost | 2 | minio | 9000 | file_store |
| {'password': 'infini_rag_flow', 'retrieval_type': 'elasticsearch', 'username': 'elastic'} | localhost | 3 | elasticsearch | 1200 | retrieval |
| {'db_name': 'default_db', 'retrieval_type': 'infinity'} | localhost | 4 | infinity | 23817 | retrieval |
| {'database': 1, 'mq_type': 'redis', 'password': 'infini_rag_flow'} | localhost | 5 | redis | 6379 | message_queue |
+-------------------------------------------------------------------------------------------+-----------+----+---------------+-------+----------------+
```
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
Signed-off-by: jinhai <haijin.chn@gmail.com>
### Related issues
#10078
### What problem does this PR solve?
Integrate CometAPI provider.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Documentation Update
### 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?
Refine dataflow and initialize dataflow app.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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?
Add Zhipu GLM-4.5 model series. #9708.
### 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?
add ZhipuAI GLM-4.5 model series
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### 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 SMTP support for user invitation emails
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Allows set multiple types of default models in service config.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Add Claude Opus 4.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
- [x] Refactoring
### What problem does this PR solve?
Add a series of qwen3 latest SOTA models:
qwen3-coder-480b-a35b-instruct, qwen3-30b-a3b-instruct-2507,
qwen3-30b-a3b-thinking-2507, qwen3-235b-a22b-instruct-2507,
qwen3-235b-a22b-thinking-2507
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Fix kimi-latest is not authorized.
Add kimi-thinking-preview.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
add Kimi-K2-Instruct from Tongyi-Qianwen API
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Add model provider DeepInfra. This model list comes from our community.
NOTE: most endpoints haven't been tested, but they should work as OpenAI
does.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
### What problem does this PR solve?
Adds configurations for gemini-2.5-flash and Gemini 2.5-pro models,
including tags, maximum token limits, and model types.
### Type of change
- [x] Bug Fix (non-breaking change which fixes an issue)
### What problem does this PR solve?
Add Kimi model series support.
### Type of change
- [x] New Feature (non-breaking change which adds functionality)
