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DRAFT: Updated python and http api references (#2973)
### What problem does this PR solve? ### Type of change - [x] Documentation Update
This commit is contained in:
writinwaters
@ -17,10 +17,9 @@ RAGFlow.create_dataset(
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name: str,
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avatar: str = "",
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description: str = "",
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embedding_model: str = "BAAI/bge-zh-v1.5",
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language: str = "English",
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permission: str = "me",
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document_count: int = 0,
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chunk_count: int = 0,
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chunk_method: str = "naive",
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parser_config: DataSet.ParserConfig = None
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) -> DataSet
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@ -143,7 +142,7 @@ RAGFlow.list_datasets(
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) -> list[DataSet]
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```
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Retrieves a list of datasets.
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Lists datasets.
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### Parameters
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@ -296,7 +295,7 @@ Updates configurations for the current document.
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A dictionary representing the attributes to update, with the following keys:
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- `"name"`: `str` The name of the document to update.
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- `"display_name"`: `str` The name of the document to update.
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- `"parser_config"`: `dict[str, Any]` The parsing configuration for the document:
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- `"chunk_token_count"`: Defaults to `128`.
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- `"layout_recognize"`: Defaults to `True`.
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@ -370,7 +369,7 @@ print(doc)
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Dataset.list_documents(id:str =None, keywords: str=None, offset: int=0, limit:int = 1024,order_by:str = "create_time", desc: bool = True) -> list[Document]
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```
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Retrieves a list of documents from the current dataset.
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Lists documents in the current dataset.
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### Parameters
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@ -388,7 +387,7 @@ The starting index for the documents to retrieve. Typically used in confunction
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#### limit: `int`
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The maximum number of documents to retrieve. Defaults to `1024`. A value of `-1` indicates that all documents should be returned.
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The maximum number of documents to retrieve. Defaults to `1024`.
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#### orderby: `str`
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@ -412,7 +411,7 @@ A `Document` object contains the following attributes:
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- `name`: The document name. Defaults to `""`.
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- `thumbnail`: The thumbnail image of the document. Defaults to `None`.
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- `knowledgebase_id`: The dataset ID associated with the document. Defaults to `None`.
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- `chunk_method` The chunk method name. Defaults to `""`. ?????naive??????
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- `chunk_method` The chunk method name. Defaults to `"naive"`.
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- `parser_config`: `ParserConfig` Configuration object for the parser. Defaults to `{"pages": [[1, 1000000]]}`.
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- `source_type`: The source type of the document. Defaults to `"local"`.
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- `type`: Type or category of the document. Defaults to `""`. Reserved for future use.
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@ -425,7 +424,7 @@ A `Document` object contains the following attributes:
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- `process_begin_at`: `datetime` The start time of document processing. Defaults to `None`.
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- `process_duation`: `float` Duration of the processing in seconds. Defaults to `0.0`.
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- `run`: `str` The document's processing status:
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- `"0"`: UNSTART (default)
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- `"0"`: UNSTART (default) ?????????
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- `"1"`: RUNNING
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- `"2"`: CANCEL
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- `"3"`: DONE
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@ -506,9 +505,9 @@ The IDs of the documents to parse.
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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dataset = rag_object.create_dataset(name="dataset_name")
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documents = [
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{'name': 'test1.txt', 'blob': open('./test_data/test1.txt',"rb").read()},
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{'name': 'test2.txt', 'blob': open('./test_data/test2.txt',"rb").read()},
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{'name': 'test3.txt', 'blob': open('./test_data/test3.txt',"rb").read()}
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{'display_name': 'test1.txt', 'blob': open('./test_data/test1.txt',"rb").read()},
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{'display_name': 'test2.txt', 'blob': open('./test_data/test2.txt',"rb").read()},
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{'display_name': 'test3.txt', 'blob': open('./test_data/test3.txt',"rb").read()}
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]
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dataset.upload_documents(documents)
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documents = dataset.list_documents(keywords="test")
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@ -546,9 +545,9 @@ The IDs of the documents for which parsing should be stopped.
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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dataset = rag_object.create_dataset(name="dataset_name")
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documents = [
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{'name': 'test1.txt', 'blob': open('./test_data/test1.txt',"rb").read()},
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{'name': 'test2.txt', 'blob': open('./test_data/test2.txt',"rb").read()},
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{'name': 'test3.txt', 'blob': open('./test_data/test3.txt',"rb").read()}
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{'display_name': 'test1.txt', 'blob': open('./test_data/test1.txt',"rb").read()},
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{'display_name': 'test2.txt', 'blob': open('./test_data/test2.txt',"rb").read()},
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{'display_name': 'test3.txt', 'blob': open('./test_data/test3.txt',"rb").read()}
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]
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dataset.upload_documents(documents)
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documents = dataset.list_documents(keywords="test")
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@ -566,7 +565,7 @@ print("Async bulk parsing cancelled.")
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## Add chunk
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```python
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Document.add_chunk(content:str) -> Chunk ?????????????????????
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Document.add_chunk(content:str, important_keywords:list[str] = []) -> Chunk
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```
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Adds a chunk to the current document.
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@ -577,7 +576,7 @@ Adds a chunk to the current document.
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The text content of the chunk.
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#### important_keywords: `list[str]` ??????????????????????
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#### important_keywords: `list[str]`
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The key terms or phrases to tag with the chunk.
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@ -588,7 +587,7 @@ The key terms or phrases to tag with the chunk.
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A `Chunk` object contains the following attributes:
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- `id`: `str`
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- `id`: `str`
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- `content`: `str` Content of the chunk.
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- `important_keywords`: `list[str]` A list of key terms or phrases to tag with the chunk.
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- `create_time`: `str` The time when the chunk was created (added to the document).
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@ -596,9 +595,9 @@ A `Chunk` object contains the following attributes:
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- `knowledgebase_id`: `str` The ID of the associated dataset.
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- `document_name`: `str` The name of the associated document.
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- `document_id`: `str` The ID of the associated document.
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- `available`: `int`???? The chunk's availability status in the dataset. Value options:
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- `0`: Unavailable
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- `1`: Available
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- `available`: `bool` The chunk's availability status in the dataset. Value options:
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- `False`: Unavailable
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- `True`: Available
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### Examples
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@ -619,26 +618,26 @@ chunk = doc.add_chunk(content="xxxxxxx")
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## List chunks
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```python
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Document.list_chunks(keywords: str = None, offset: int = 0, limit: int = -1, id : str = None) -> list[Chunk]
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Document.list_chunks(keywords: str = None, offset: int = 1, limit: int = 1024, id : str = None) -> list[Chunk]
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```
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Retrieves a list of chunks from the current document.
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Lists chunks in the current document.
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### Parameters
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#### keywords: `str`
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#### keywords: `str`
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The keywords used to match chunk content. Defaults to `None`
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#### offset: `int`
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The starting index for the chunks to retrieve. Defaults to `1`??????
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The starting index for the chunks to retrieve. Defaults to `1`.
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#### limit
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#### limit: `int`
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The maximum number of chunks to retrieve. Default: `30`?????????
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The maximum number of chunks to retrieve. Default: `1024`
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#### id
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#### id: `str`
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The ID of the chunk to retrieve. Default: `None`
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@ -713,9 +712,9 @@ A dictionary representing the attributes to update, with the following keys:
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- `"content"`: `str` Content of the chunk.
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- `"important_keywords"`: `list[str]` A list of key terms or phrases to tag with the chunk.
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- `"available"`: `int` The chunk's availability status in the dataset. Value options:
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- `0`: Unavailable
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- `1`: Available
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- `"available"`: `bool` The chunk's availability status in the dataset. Value options:
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- `False`: Unavailable
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- `True`: Available
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### Returns
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@ -741,10 +740,10 @@ chunk.update({"content":"sdfx..."})
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## Retrieve chunks
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```python
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RAGFlow.retrieve(question:str="", datasets:list[str]=None, document=list[str]=None, offset:int=1, limit:int=30, similarity_threshold:float=0.2, vector_similarity_weight:float=0.3, top_k:int=1024,rerank_id:str=None,keyword:bool=False,higlight:bool=False) -> list[Chunk]
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RAGFlow.retrieve(question:str="", datasets:list[str]=None, document=list[str]=None, offset:int=1, limit:int=1024, similarity_threshold:float=0.2, vector_similarity_weight:float=0.3, top_k:int=1024,rerank_id:str=None,keyword:bool=False,higlight:bool=False) -> list[Chunk]
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```
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???????
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Retrieves chunks from specified datasets.
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### Parameters
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@ -752,21 +751,21 @@ RAGFlow.retrieve(question:str="", datasets:list[str]=None, document=list[str]=No
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The user query or query keywords. Defaults to `""`.
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#### datasets: `list[str]`, *Required*?????
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#### datasets: `list[str]`, *Required*
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The datasets to search from.
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#### document: `list[str]`
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The documents to search from. `None` means no limitation. Defaults to `None`.
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The documents to search from. Defaults to `None`.
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#### offset: `int`
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The starting index for the documents to retrieve. Defaults to `0`??????.
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The starting index for the documents to retrieve. Defaults to `1`.
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#### limit: `int`
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The maximum number of chunks to retrieve. Defaults to `6`.???????????????
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The maximum number of chunks to retrieve. Defaults to `1024`.
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#### Similarity_threshold: `float`
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@ -786,14 +785,17 @@ The ID of the rerank model. Defaults to `None`.
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#### keyword: `bool`
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Indicates whether keyword-based matching is enabled:
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Indicates whether to enable keyword-based matching:
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- `True`: Enabled.
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- `False`: Disabled (default).
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- `True`: Enable keyword-based matching.
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- `False`: Disable keyword-based matching (default).
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#### highlight: `bool`
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Specifying whether to enable highlighting of matched terms in the results (True) or not (False).
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Specifying whether to enable highlighting of matched terms in the results:
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- `True`: Enable highlighting of matched terms.
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- `False`: Disable highlighting of matched terms (default).
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### Returns
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@ -849,15 +851,15 @@ Creates a chat assistant.
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The following shows the attributes of a `Chat` object:
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#### name: `str`, *Required*????????
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#### name: `str`, *Required*
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The name of the chat assistant. Defaults to `"assistant"`.
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The name of the chat assistant..
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#### avatar: `str`
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Base64 encoding of the avatar. Defaults to `""`.
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#### knowledgebases: `list[str]`
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#### knowledgebases: `list[str]`
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The IDs of the associated datasets. Defaults to `[""]`.
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@ -1016,7 +1018,7 @@ RAGFlow.list_chats(
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) -> list[Chat]
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```
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Retrieves a list of chat assistants.
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Lists chat assistants.
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### Parameters
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