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ragflow/internal/development.md
Jin Hai 49714865c1 Go: rename ragflow_cli to ragflow-cli (#16270) 
### What problem does this PR solve?

rename ragflow cli binary

### Type of change

- [x] Refactoring

Signed-off-by: Jin Hai <haijin.chn@gmail.com>
2026-06-23 19:20:49 +08:00

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# RAGFlow Go Version - Startup Guide
## 1. Start Dependencies
```bash
docker compose -f docker/docker-compose-base.yml up -d
```
## 2. Build Go Version RAGFlow
- First build (includes C++ dependencies and office_oxide native library):
```bash
./build.sh --cpp
```
- Subsequent builds (Go only):
```bash
./build.sh --go
```
> **Note**: If you use IDEs like GoLand to run/debug directly (via Run/Debug buttons), or run `go build` / `go run` from command line, you must set the following two CGO environment variables in your run configuration or shell:
>
> ```bash
> export CGO_CFLAGS="-I${HOME}/.office_oxide/include/office_oxide_c"
> export CGO_LDFLAGS="-L${HOME}/.office_oxide/lib -loffice_oxide -Wl,-rpath,${HOME}/.office_oxide/lib"
> ```
## 3. Run Go Version RAGFlow
Note: admin_server must be started first; otherwise, ragflow_server will encounter errors when sending heartbeats.
```bash
# Start admin server
./bin/admin_server
```
```bash
# Start RAGFlow server
./bin/ragflow_server
```
```bash
# Run CLI
./bin/ragflow-cli
```
## 4. Start Frontend
```bash
cd web && export API_PROXY_SCHEME=hybrid && npm run dev
```
## 5. Service Ports & API Routing
- ragflow_server listens on port 9384
- admin_server listens on port 9383
After updating or implementing an API, update the frontend development environment routes in web/vite.config.ts under proxySchemes.
### Proxy Schemes
| Scheme | Description |
|--------|-------------|
| `python` | All API requests from the frontend are routed to the Python server |
| `hybrid` | API requests are partially routed to the Go server and partially to the Python server |
| `go` | All API requests from the frontend are routed to the Go server |
## 6. RAGFlow commands
You can use the following CLI commands to test the corresponding API implementations.
### 6.1. Run ragflow-cli, register user, login, and logout:
```
$ ./ragflow-cli
Welcome to RAGFlow CLI
Type \? for help, \q to quit
RAGFlow(api/default)> REGISTER USER 'aaa@aaa.com' AS 'aaa' PASSWORD 'aaa';
Register successfully
RAGFlow(api/default)> login user 'aaa@aaa.com';
password for aaa@aaa.com: Password:
Login user aaa@aaa.com successfully
RAGFlow(api/default)> logout;
SUCCESS
```
### 6.2. List currently supported providers
```
RAGFlow(api/default)> list available providers;
```
### 6.3. Add or delete a provider for the current tenant
```
RAGFlow(api/default)> add provider 'openai';
```
```
RAGFlow(api/default)> delete provider 'openai';
```
### 6.4. Create a model instance for a specific provider
```
RAGFlow(api/default)> create provider 'openai' instance 'instance_name' key 'api-key';
```
Note: The api-key is a valid API key that needs to be applied for. You can create multiple instances for the same model provider, each with a different API key.
For locally deployed models (e.g., ollama, vLLM), use the following command to add a model instance:
```
RAGFlow(api/default)> create provider 'vllm' instance 'instance_name' key '' url 'http://192.168.1.96:8123/v1';
```
### 6.5. List and delete an instance
```
RAGFlow(api/default)> list instances from 'openai';
```
```
RAGFlow(api/default)> drop instance 'instance_name' from 'openai';
```
### 6.6. List models supported by a model instance
```
RAGFlow(api/default)> list models from 'openai' 'instance_name';
```
### 6.7. Chat with LLM
- Chat
```
RAGFlow(api/default)> chat with 'glm-4.5-flash@test@zhipu-ai' message '20 words introduce LLM';
Answer: A large language model is an AI trained on vast text data to understand, generate, and refine human-like language.
Time: 1.052269
```
- Chat with Thinking (Reasoning)
```
RAGFlow(api/default)> think chat with 'glm-4.5-flash@test@zhipu-ai' message '20 words introduce LLM';
Thinking: I need to create a concise 20-word introduction to LLMs...
Answer: Large Language Models are AI systems trained on vast datasets, enabling human-like text generation, comprehension, and problem-solving across diverse applications.
Time: 11.592358
```
- Streaming Chat
```
RAGFlow(api/default)> stream chat with 'glm-4.5-flash@test@zhipu-ai' message '20 words introduce LLM';
Answer: Language Models are advanced AI systems. They process text to learn, generate human-like responses, and perform diverse tasks through machine learning.
Time: 2.615930
```
- Streaming Chat with Thinking
```
RAGFlow(api/default)> stream think chat with 'glm-4.5-flash@test@zhipu-ai' message '20 words introduce LLM';
Thinking: The user is asking for a very concise introduction to LLMs...
Answer: language models are AI systems trained on vast text datasets to understand and generate human-like text for diverse tasks.
Time: 11.958035
```
- Image Understanding
```
RAGFlow(api/default)> chat with 'glm-4.6v-flash@test@zhipu-ai' message 'What are the pics talk about?' image 'https://cdn.bigmodel.cn/static/logo/register.png' 'https://cdn.bigmodel.cn/static/logo/api-key.png'
Answer: The first picture shows a login/register modal... The second picture displays the API keys management page...
Time: 31.600545
```
- Video Understanding
```
RAGFlow(api/default)> chat with 'glm-4.6v-flash@test@zhipu-ai' message 'What are the video talk about?' video 'https://cdn.bigmodel.cn/agent-demos/lark/113123.mov'
Answer: Based on the sequence of frames provided, the video is a demonstration of a web search and navigation process...
Time: 76.582520
```
Note: Both image and video understanding support streaming and thinking modes as well.
### 6.8. Chat with OpenAI compatible API
```
RAGFlow(api/default)> openai_chat '<chat_id>' 'Hello, how are you?';
Answer: Hello! I'm just a virtual assistant, so I don't have feelings, but I'm here and ready to help you with anything you need. How can I assist you today? 😊
Time: 8.487349
```
```
RAGFlow(api/default)> openai_chat '<chat_id>' 'Great, now what about x^3?' \
system 'You are a math tutor. Always explain step by step.' \
history 'user:What is the derivative of x^2?;assistant:The derivative of x^2 is 2x.';
```
```
RAGFlow(api/default)> openai_chat '<chat_id>' 'Hello, how are you?' temperature 0.7 max_tokens 100;
```
```
RAGFlow(api/default)> openai_chat '<chat_id>' "what's in the doc?" stream true \
extra_body '{"reference":true,"reference_metadata":{"include":true,"fields":["author","title"]}}';
```
```
RAGFlow(api/default)> openai_chat '7b1d58f263ca11f18121ab54cc8673a7' 'Hello' \
extra_body '{"metadata_condition":{"logic":"and","conditions":[{"key":"doc_type","operator":"is","value":"faq"}]}}';
```
```
RAGFlow(api/default)> openai_chat '<chat_id>' 'Hello, how are you?' temp 100;
CLI error: OPENAI_CHAT: unknown option "temp" (valid: model, system, history, delimiter, temperature, max_tokens, stream, top_p, frequency_penalty, presence_penalty, extra_body)
```
```
RAGFlow(api/default)> openai_chat '<chat_id>' 'Hello, how are you?' extra_body '{"ref":true}';
CLI error: OPENAI_CHAT extra_body: unknown field "ref" (valid: reference, reference_metadata, metadata_condition)
```
### 6.9. Generate Embeddings
```
RAGFlow(api/default)> embed text 'what is rag' 'who are you' with 'embedding-3@test@zhipu-ai' dimension 16;
```
### 6.10. Document Reranking
```
RAGFlow(api/default)> rerank query 'what is rag' document 'rag is retrieval augment generation' 'rag need llm' 'famous rag project includes ragflow' with 'rerank@test@zhipu-ai' top 2;
```
### 6.11. Get supported models from provider API
```
RAGFlow(api/default)> list supported models from 'gitee' 'test';
+-----------+---------------------------+---------------+------------+-----------------------------------------------------------------+----------------------------------------------------------+---------------------------------------------+
| dimension | dimensions | max_dimension | max_tokens | model_types | name | thinking |
+-----------+---------------------------+---------------+------------+-----------------------------------------------------------------+----------------------------------------------------------+---------------------------------------------+
| | | | | | bce-embedding-base_v1@maidalun1020 | |
| | | | | | bce-embedding-base_v1@maidalun1020 | |
| | | | 8192 | [rerank] | jina-reranker-m0@jinaai | |
| | | | 8192 | [rerank] | jina-reranker-m0@jinaai | |
| | [64 128 256 512 768] | | 8192 | [embedding vision] | jina-clip-v1@jinaai | |
| | [64 128 256 512 768] | | 8192 | [embedding vision] | jina-clip-v1@jinaai | |
| | | | 32768 | [chat] | Qwen2.5-Coder-14B-Instruct@Qwen | |
| | | | 32768 | [chat] | Qwen2.5-Coder-14B-Instruct@Qwen | |
| | [64 128 256 512 768 1024] | | 8192 | [embedding vision] | jina-clip-v2@jinaai | |
| | | | 262144 | [chat image2text vision video_understanding] | Qwen3.6-27B@Qwen | map[clear_thinking:true default_value:true] |
| | | | 262144 | [chat image2text vision video_understanding] | Qwen3.6-27B@Qwen | map[clear_thinking:true default_value:true] |
| | | | 32768 | [rerank] | Qwen3-Reranker-0.6B@Qwen | |
+-----------+---------------------------+---------------+------------+-----------------------------------------------------------------+----------------------------------------------------------+---------------------------------------------+
```
### 6.12. Get preset models of a provider
```
RAGFlow(api/default)> list models from 'minimax';
+------------+-------------+------------------------+
| max_tokens | model_types | name |
+------------+-------------+------------------------+
| 204800 | [chat] | minimax-m2.7 |
| 204800 | [chat] | minimax-m2.7-highspeed |
| 204800 | [chat] | minimax-m2.5 |
| 204800 | [chat] | minimax-m2.5-highspeed |
| 204800 | [chat] | minimax-m2.1 |
| 204800 | [chat] | minimax-m2.1-highspeed |
| 204800 | [chat] | minimax-m2 |
| 65536 | [chat] | minimax-m2-her |
+------------+-------------+------------------------+
```
### 6.13. List instances of a provider
```
RAGFlow(api/default)> list instances from 'zhipu-ai';
+---------+----------------------+----------------------------------+--------------+----------------------------------+--------+
| apiKey | extra | id | instanceName | providerID | status |
+---------+----------------------+----------------------------------+--------------+----------------------------------+--------+
| api-key | {"region":"default"} | 19f620e73c7a11f1a51138a74640adcc | test | d21a3758398f11f1ab4838a74640adcc | enable |
+---------+----------------------+----------------------------------+--------------+----------------------------------+--------+
```
### 6.14. Show instance of a provider
```
RAGFlow(api/default)> show instance 'test' from 'zhipu-ai';
+----------------------------------+--------------+----------------------------------+---------+--------+
| id | instanceName | providerID | region | status |
+----------------------------------+--------------+----------------------------------+---------+--------+
| 19f620e73c7a11f1a51138a74640adcc | test | d21a3758398f11f1ab4838a74640adcc | default | enable |
+----------------------------------+--------------+----------------------------------+---------+--------+
```
### 6.15. List models of a specific instance
```
RAGFlow(api/default)> list models from 'minimax' 'test';
+------------+-------------+------------------------+--------+
| max_tokens | model_types | name | status |
+------------+-------------+------------------------+--------+
| 204800 | [chat] | minimax-m2.7 | active |
| 204800 | [chat] | minimax-m2.7-highspeed | active |
| 204800 | [chat] | minimax-m2.5 | active |
| 204800 | [chat] | minimax-m2.5-highspeed | active |
| 204800 | [chat] | minimax-m2.1 | active |
| 204800 | [chat] | minimax-m2.1-highspeed | active |
| 204800 | [chat] | minimax-m2 | active |
| 65536 | [chat] | minimax-m2-her | active |
+------------+-------------+------------------------+--------+
```
### 6.16. List added providers
```
RAGFlow(api/default)> list providers;
+--------------------------------------------------------------------------+-------------+--------------+
| base_url | name | total_models |
+--------------------------------------------------------------------------+-------------+--------------+
| map[default:https://ark.cn-beijing.volces.com/api/v3] | VolcEngine | 2 |
| map[default:https://api.minimaxi.com/ global:https://api.minimax.io/] | MiniMax | 8 |
| map[default:https://api.moark.com/v1] | Gitee | 5 |
+--------------------------------------------------------------------------+-------------+--------------+
```
### 6.17. Deactivate / activate a model
```
RAGFlow(api/default)> disable model 'deepseek-v4-pro' from 'deepseek' 'test';
SUCCESS
RAGFlow(api/default)> list models from 'deepseek' 'test';
+------------+-------------+-------------------+----------+
| max_tokens | model_types | name | status |
+------------+-------------+-------------------+----------+
| 1048576 | [chat] | deepseek-v4-flash | active |
| 1048576 | [chat] | deepseek-v4-pro | inactive |
+------------+-------------+-------------------+----------+
RAGFlow(api/default)> enable model 'deepseek-v4-pro' from 'deepseek' 'test';
SUCCESS
```
### 6.18. Set current model
```
RAGFlow(api/default)> use model 'glm-4.5-flash@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> chat message '20 words introduce LLM';
Answer: Large language models are advanced AI systems. They process text to understand, generate, and refine human-like language for countless tasks.
Time: 1.680416
```
### 6.19. Set, reset, and list default models
```
RAGFlow(api/default)> set default chat model 'glm-4.5-flash@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> set default vision model 'glm-4.5v@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> set default embedding model 'embedding-2@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> set default rerank model 'rerank@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> set default ocr model 'glm-ocr@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> set default tts model 'tts@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> set default asr model 'glm-asr-2512@test@zhipu-ai';
SUCCESS
RAGFlow(api/default)> list default models;
+--------+----------------+---------------+----------------+------------+
| enable | model_instance | model_name | model_provider | model_type |
+--------+----------------+---------------+----------------+------------+
| true | test | glm-4.5-flash | zhipu-ai | chat |
| true | test | embedding-2 | zhipu-ai | embedding |
| true | test | rerank | zhipu-ai | rerank |
| true | test | glm-asr-2512 | zhipu-ai | asr |
| true | test | glm-4.5v | zhipu-ai | vision |
| true | test | glm-ocr | zhipu-ai | ocr |
| true | test | glm-tts | zhipu-ai | tts |
+--------+----------------+---------------+----------------+------------+
RAGFlow(api/default)> reset default embedding model;
SUCCESS
RAGFlow(api/default)> reset default chat model;
SUCCESS
RAGFlow(api/default)> list default models;
+--------+----------------+--------------+----------------+------------+
| enable | model_instance | model_name | model_provider | model_type |
+--------+----------------+--------------+----------------+------------+
| true | test | rerank | zhipu-ai | rerank |
| true | test | glm-asr-2512 | zhipu-ai | asr |
| true | test | glm-4.5v | zhipu-ai | vision |
| true | test | glm-ocr | zhipu-ai | ocr |
| true | test | glm-tts | zhipu-ai | tts |
+--------+----------------+--------------+----------------+------------+
```
### 6.20. Show current balance of a provider instance
```
RAGFlow(api/default)> show balance from 'gitee' 'test';
+-------------+----------+
| balance | currency |
+-------------+----------+
| 82.49835029 | CNY |
+-------------+----------+
```
### 6.21. Check provider instance availability
```
RAGFlow(api/default)> check instance 'test' from 'zhipu-ai';
SUCCESS
```
### 6.22. Add local model to RAGFlow, only for local deployed inference server, such as ollama
```
RAGFlow(api/default)> add model 'Qwen/Qwen2.5-0.5B' to provider 'vllm' instance 'test' with tokens 131072 chat;
SUCCESS
RAGFlow(api/default)> list models from 'vllm' 'test';
+-------------------+--------+
| name | status |
+-------------------+--------+
| Qwen/Qwen2.5-0.5B | active |
+-------------------+--------+
RAGFlow(api/default)> drop model 'Qwen/Qwen2.5-0.5B' from 'vllm' 'test';
SUCCESS
```
### 6.23. List datasets
```
RAGFlow(api/default)> list datasets;
+-------------+--------------+----------------+----------------------+----------------------------------+----------+------+----------+------------+----------------------------------+-----------+---------------+
| chunk_count | chunk_method | document_count | embedding_model | id | language | name | nickname | permission | tenant_id | token_num | update_time |
+-------------+--------------+----------------+----------------------+----------------------------------+----------+------+----------+------------+----------------------------------+-----------+---------------+
| 492 | naive | 1 | embedding-2@ZHIPU-AI | e93ab2c04ad111f1b17438a74640adcc | English | aaa | aaa | me | 2ba4881420fa11f19e9c38a74640adcc | 74278 | 1778245825722 |
| 0 | naive | 1 | embedding-2@ZHIPU-AI | 0abe79f9423311f1ad8d38a74640adcc | English | ccc | aaa | me | 2ba4881420fa11f19e9c38a74640adcc | 0 | 1777375201933 |
+-------------+--------------+----------------+----------------------+----------------------------------+----------+------+----------+------------+----------------------------------+-----------+---------------+
```
### 6.24. Text to Speech
```
RAGFlow(api/default)> tts with 'speech-2.8-hd@test@minimax' text 'He who desires but acts not, breeds pestilence.' play format 'wav' save './internal' param '{"voice_setting": {"voice_id": "English_radiant_girl", "speed": 1, "vol": 1, "pitch": 0}, "audio_setting": {"sample_rate": 32000, "bitrate": 128000, "format": "wav", "channel": 1}, "output_format": "hex"}'
Saved to directory: /home/infiniflow/Documents/development/ragflow/internal/speech-2.8-hd_output.wav
SUCCESS
```
### 6.25. Audio to Speech
```
RAGFlow(api/default)> asr with 'FunAudioLLM/SenseVoiceSmall@test@siliconflow' audio './internal/test.wav' param ''
+----------------------------------------------------------------------------------------------------------------------+
| text |
+----------------------------------------------------------------------------------------------------------------------+
| The examination and testimony of the experts enabled the commission to conclude that five shots may have been fired. |
+----------------------------------------------------------------------------------------------------------------------+
```
### 6.26. Optical Character Recognition
```
RAGFlow(api/default)> ocr with 'paddleocr-vl-0.9b@test@baidu' file './internal/text.jpg'
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| text |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Parallel to these organizational innovations there were significant complementary technical innovations (e.g., improved methods of manufacturing cast-iron pipe and of coating interiors for pressure maintenance, and newer paving and construction material... |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
```
### 6.27. Chunk Management Commands
- Create a chunk store with vector size
```
RAGFlow(api/default)> CREATE CHUNK STORE FOR DATASET 'test' VECTOR SIZE 384
```
- Insert data from JSON files
```
RAGFlow(api/default)> INSERT CHUNKS FROM FILE 'insert_kb.json'
```
- Update a chunk's content
```
RAGFlow(api/default)> UPDATE CHUNK 'deb165dc6a732a64' OF DOCUMENT 'bbe55942535e11f1bc5184ba59049aa3' IN DATASET 'test' SET '{"content": "Updated chunk content here", "important_keywords": ["keyword1", "keyword2"], "questions": ["What is this about?", "Why is it important?"], "available": true, "tag_kwd": ["tag5", "tag2"]}'
```
- Remove tags from a dataset
```
RAGFlow(api/default)> REMOVE TAGS 'tag1', 'tag2' FROM DATASET 'test'
```
- Remove specific chunks from a document
```
RAGFlow(api/default)> REMOVE CHUNKS '29cc4f6d7a5c6e7c' '0360e3d8519eab12' FROM DOCUMENT 'bbe55942535e11f1bc5184ba59049aa3' IN DATASET 'test'
```
- Remove all chunks from a document
```
RAGFlow(api/default)> REMOVE ALL CHUNKS FROM DOCUMENT 'bbe55942535e11f1bc5184ba59049aa3' IN DATASET 'test'
```
- Drop chunk store
```
RAGFlow(api/default)> DROP CHUNK STORE FOR DATASET 'test'
```
- Search chunks
```
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test'
```
- Get chunks
```
RAGFlow(api/default)> GET CHUNK '29cc4f6d7a5c6e7c' OF DATASET 'test' DOCUMENT 'bbe55942535e11f1bc5184ba59049aa3' IN DATASET 'test'
```
### 6.28. Metadata Management Commands
- Create metadata store
```
RAGFlow(api/default)> CREATE METADATA STORE
```
- Insert metadata from JSON files
```
RAGFlow(api/default)> INSERT METADATA FROM FILE 'insert_metadata.json'
```
- Set metadata for a document
```
RAGFlow(api/default)> SET METADATA OF DOCUMENT 'bbe55942535e11f1bc5184ba59049aa3' TO '{"author": ["John", "Tom"], "category": "tech"}';
```
- Delete metadata of a document
```
RAGFlow(api/default)> DELETE METADATA OF DOCUMENT 'bbe55942535e11f1bc5184ba59049aa3'
```
- Delete metadata keys of a document
```
RAGFlow(api/default)> DELETE METADATA OF DOCUMENT 'bbe55942535e11f1bc5184ba59049aa3' KEYS '["key1", "key2"]'
```
- Drop metadata store
```
RAGFlow(api/default)> DROP METADATA STORE
```
- Get metadata
```
RAGFlow(api/default)> GET METADATA OF DATASET 'test' 'test2'
```
### 6.29. Search datasets
- Search datasets using SQL-like dataset search syntax:
```
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test';
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test1, test2';
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH top_k 1;
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH page 2 page_size 20;
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH similarity_threshold 0.5;
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH vector_similarity_weight 0.0;
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH keyword true;
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH use_kg true;
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH rerank_id 'BAAI/bge-reranker-v2-m3@CI@SILICONFLOW';
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH search_id 'abc123';
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH cross_languages ['Chinese'];
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH doc_ids ['doc_a', 'doc_b'];
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH meta_data_filter '{"method":"auto"}';
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH meta_data_filter '{"method":"manual","conditions":[{"key":"author","op":"eq","value":"Luo"}]}';
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH top_k 50 similarity_threshold 0.5 vector_similarity_weight 0.5 use_kg true;
```
- Search datasets using filesystem-style search syntax:
```
RAGFlow(api/default)> search "AI" # search all datasets
RAGFlow(api/default)> search "AI" datasets/test # search only dataset 'test'
RAGFlow(api/default)> search "AI" datasets/test -n 20 # return top 20 results
RAGFlow(api/default)> search "AI" datasets 'test1' 'test2' # search in datasets
```
> [!Note]
> - `search` is the simple filesystem search command and only accepts `query [path] [-n number]`.
> - `RETRIEVE` / `SEARCH ... ON DATASETS ...` is the SQL-like search command and supports full `WITH` option expansion.
> - `WITH` options include: `top_k`, `page_size`, `page`, `similarity_threshold`, `vector_similarity_weight`, `keyword`, `use_kg`, `rerank_id`, `search_id`, `cross_languages`, `doc_ids`, and `meta_data_filter`.
- Example with multiple options:
```
RAGFlow(api/default)> RETRIEVE 'AI' ON DATASETS 'test' WITH top_k 50 similarity_threshold 0.5 vector_similarity_weight 0.5 use_kg true;
```
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