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DRAFT: Miscellaneous updates to HTTP API. Tried to finish off Python API ref… (#2909)
…erence but failed. ### What problem does this PR solve? ### Type of change - [x] Documentation Update
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api/http_api.md
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api/http_api.md
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@ -380,7 +380,7 @@ The ID of the document to retrieve. Defaults to `None`.
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#### keywords: `str`
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The keywords to match document titles. Defaults to `None`.
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The keywords used to match document titles. Defaults to `None`.
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#### offset: `int`
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@ -419,7 +419,7 @@ A `Document` object contains the following attributes:
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- `created_by`: `str` The creator of the document. Defaults to `""`.
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- `size`: `int` The document size in bytes. Defaults to `0`.
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- `token_count`: `int` The number of tokens in the document. Defaults to `0`.
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- `chunk_count`: `int` The number of chunks that the document is split into. Defaults to `0`.
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- `chunk_count`: `int` The number of chunks in the document. Defaults to `0`.
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- `progress`: `float` The current processing progress as a percentage. Defaults to `0.0`.
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- `progress_msg`: `str` A message indicating the current progress status. Defaults to `""`.
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- `process_begin_at`: `datetime` The start time of document processing. Defaults to `None`.
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@ -432,8 +432,8 @@ A `Document` object contains the following attributes:
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```python
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from ragflow import RAGFlow
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rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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dataset = rag.create_dataset(name="kb_1")
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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="kb_1")
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filename1 = "~/ragflow.txt"
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blob = open(filename1 , "rb").read()
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@ -482,6 +482,8 @@ dataset.delete_documents(ids=["id_1","id_2"])
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DataSet.async_parse_documents(document_ids:list[str]) -> None
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```
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Parses documents in the current dataset.
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### Parameters
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#### document_ids: `list[str]`, *Required*
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@ -490,7 +492,7 @@ The IDs of the documents to parse.
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### Returns
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- Success: No value is returned.
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- Success: No value is returned.????????????????????
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- Failure: `Exception`
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### Examples
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@ -520,6 +522,8 @@ print("Async bulk parsing initiated.")
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DataSet.async_cancel_parse_documents(document_ids:list[str])-> None
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```
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Stops parsing specified documents.
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### Parameters
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#### document_ids: `list[str]`, *Required*
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@ -554,27 +558,80 @@ print("Async bulk parsing cancelled.")
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---
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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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```
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Adds a chunk to the current document.
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### Parameters
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#### content: `str`, *Required*
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The text content of the chunk.
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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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### Returns
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- Success: A `Chunk` object.
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- Failure: `Exception`.
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A `Chunk` object contains the following attributes:
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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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- `create_timestamp`: `float` The timestamp representing the creation time of the chunk, expressed in seconds since January 1, 1970.
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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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### Examples
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```python
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from ragflow import RAGFlow
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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.list_datasets(id="123")
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dtaset = dataset[0]
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doc = dataset.list_documents(id="wdfxb5t547d")
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doc = doc[0]
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chunk = doc.add_chunk(content="xxxxxxx")
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```
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---
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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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```
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Retrieves a list of document chunks.
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Retrieves a list of chunks from the current document.
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### Parameters
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#### keywords: `str`
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List chunks whose name has the given keywords. Defaults to `None`
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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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The maximum number of chunks to retrieve. Default: `30`
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The maximum number of chunks to retrieve. Default: `30`?????????
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#### id
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@ -598,42 +655,9 @@ for chunk in doc.list_chunks(keywords="rag", offset=0, limit=12):
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print(chunk)
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```
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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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```
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### Parameters
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#### content: *Required*
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The text content of the chunk.
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#### important_keywords :`list[str]`
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List the key terms or phrases that are significant or central to the chunk's content.
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### Returns
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chunk
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### Examples
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```python
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from ragflow import RAGFlow
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rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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dataset = rag.list_datasets(id="123")
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dtaset = dataset[0]
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doc = dataset.list_documents(id="wdfxb5t547d")
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doc = doc[0]
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chunk = doc.add_chunk(content="xxxxxxx")
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```
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---
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## Delete chunk
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## Delete chunks
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```python
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Document.delete_chunks(chunk_ids: list[str])
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@ -657,10 +681,10 @@ The IDs of the chunks to delete. Defaults to `None`. If not specified, all chunk
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```python
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from ragflow import RAGFlow
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rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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ds = rag.list_datasets(id="123")
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ds = ds[0]
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doc = ds.list_documents(id="wdfxb5t547d")
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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.list_datasets(id="123")
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dataset = dataset[0]
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doc = dataset.list_documents(id="wdfxb5t547d")
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doc = doc[0]
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chunk = doc.add_chunk(content="xxxxxxx")
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doc.delete_chunks(["id_1","id_2"])
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@ -683,7 +707,7 @@ Updates content or configurations for the current chunk.
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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 to attach to 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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@ -715,13 +739,15 @@ chunk.update({"content":"sdfx..."})
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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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```
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???????
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### Parameters
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#### question: `str` *Required*
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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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@ -735,7 +761,7 @@ The starting index for the documents to retrieve. Defaults to `0`??????.
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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 `6`.???????????????
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#### Similarity_threshold: `float`
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@ -749,18 +775,18 @@ The weight of vector cosine similarity. Defaults to `0.3`. If x represents the v
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The number of chunks engaged in vector cosine computaton. Defaults to `1024`.
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#### rerank_id
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#### rerank_id: `str`
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The ID of the rerank model. Defaults to `None`.
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The ID of the rerank model. Defaults to `None`.
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#### keyword
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#### keyword: `bool`
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Indicates whether keyword-based matching is enabled:
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- `True`: Enabled.
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- `False`: Disabled.
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- `False`: Disabled (default).
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#### highlight:`bool`
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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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@ -775,16 +801,16 @@ Specifying whether to enable highlighting of matched terms in the results (True)
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from ragflow import RAGFlow
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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ds = rag_object.list_datasets(name="ragflow")
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ds = ds[0]
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dataset = rag_object.list_datasets(name="ragflow")
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dataset = dataset[0]
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name = 'ragflow_test.txt'
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path = './test_data/ragflow_test.txt'
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rag_object.create_document(ds, name=name, blob=open(path, "rb").read())
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doc = ds.list_documents(name=name)
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rag_object.create_document(dataset, name=name, blob=open(path, "rb").read())
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doc = dataset.list_documents(name=name)
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doc = doc[0]
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ds.async_parse_documents([doc.id])
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dataset.async_parse_documents([doc.id])
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for c in rag_object.retrieve(question="What's ragflow?",
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datasets=[ds.id], documents=[doc.id],
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datasets=[dataset.id], documents=[doc.id],
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offset=1, limit=30, similarity_threshold=0.2,
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vector_similarity_weight=0.3,
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top_k=1024
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@ -818,11 +844,11 @@ Creates a chat assistant.
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The following shows the attributes of a `Chat` object:
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#### name: *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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#### avatar
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#### avatar: `str`
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Base64 encoding of the avatar. Defaults to `""`.
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@ -830,7 +856,7 @@ Base64 encoding of the avatar. Defaults to `""`.
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The IDs of the associated datasets. Defaults to `[""]`.
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#### llm
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#### llm: `Chat.LLM`
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The llm of the created chat. Defaults to `None`. When the value is `None`, a dictionary with the following values will be generated as the default.
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@ -849,7 +875,7 @@ An `LLM` object contains the following attributes:
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- `max_token`, `int`
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This sets the maximum length of the model’s output, measured in the number of tokens (words or pieces of words). Defaults to `512`.
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#### Prompt
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#### prompt: `Chat.Prompt`
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Instructions for the LLM to follow. A `Prompt` object contains the following attributes:
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@ -876,17 +902,17 @@ Instructions for the LLM to follow. A `Prompt` object contains the following at
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```python
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from ragflow import RAGFlow
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rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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kbs = rag.list_datasets(name="kb_1")
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list_kb=[]
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for kb in kbs:
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list_kb.append(kb.id)
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assi = rag.create_chat("Miss R", knowledgebases=list_kb)
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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datasets = rag_object.list_datasets(name="kb_1")
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dataset_ids = []
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for dataset in datasets:
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dataset_ids.append(dataset.id)
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assistant = rag_object.create_chat("Miss R", knowledgebases=dataset_ids)
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```
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---
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## Update chat
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## Update chat assistant
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```python
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Chat.update(update_message: dict)
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@ -934,15 +960,15 @@ A dictionary representing the attributes to update, with the following keys:
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```python
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from ragflow import RAGFlow
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rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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knowledge_base = rag.list_datasets(name="kb_1")
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assistant = rag.create_chat("Miss R", knowledgebases=knowledge_base)
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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datasets = rag_object.list_datasets(name="kb_1")
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assistant = rag_object.create_chat("Miss R", knowledgebases=datasets)
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assistant.update({"name": "Stefan", "llm": {"temperature": 0.8}, "prompt": {"top_n": 8}})
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```
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---
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## Delete chats
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## Delete chat assistants
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```python
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RAGFlow.delete_chats(ids: list[str] = None)
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@ -966,13 +992,13 @@ The IDs of the chat assistants to delete. Defaults to `None`. If not specified,
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```python
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from ragflow import RAGFlow
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rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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rag.delete_chats(ids=["id_1","id_2"])
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
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rag_object.delete_chats(ids=["id_1","id_2"])
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```
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---
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## List chats
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## List chat assistants
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```python
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RAGFlow.list_chats(
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@ -989,29 +1015,32 @@ Retrieves a list of chat assistants.
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### Parameters
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#### page
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#### page: `int`
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Specifies the page on which the chat assistants will be displayed. Defaults to `1`.
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#### page_size
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#### page_size: `int`
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The number of chat assistants on each page. Defaults to `1024`.
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#### order_by
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#### orderby: `str`
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The attribute by which the results are sorted. Defaults to `"create_time"`.
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The attribute by which the results are sorted. Available options:
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#### desc
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- `"create_time"` (default)
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- `"update_time"`
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#### desc: `bool`
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Indicates whether the retrieved chat assistants should be sorted in descending order. Defaults to `True`.
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#### id: `string`
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#### id: `str`
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The ID of the chat to retrieve. Defaults to `None`.
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The ID of the chat assistant to retrieve. Defaults to `None`.
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#### name: `string`
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#### name: `str`
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The name of the chat to retrieve. Defaults to `None`.
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The name of the chat assistant to retrieve. Defaults to `None`.
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### Returns
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@ -1031,7 +1060,7 @@ for assistant in rag_object.list_chats():
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---
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:::tip API GROUPING
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Chat-session APIs
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Chat Session APIs
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:::
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---
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@ -1046,7 +1075,7 @@ Creates a chat session.
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|
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### Parameters
|
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#### name
|
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#### name: `str`
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The name of the chat session to create.
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@ -1064,12 +1093,14 @@ The name of the chat session to create.
|
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```python
|
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from ragflow import RAGFlow
|
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|
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rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
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assistant = rag.list_chats(name="Miss R")
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
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assistant = rag_object.list_chats(name="Miss R")
|
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assistant = assistant[0]
|
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session = assistant.create_session()
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```
|
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|
||||
---
|
||||
|
||||
## Update session
|
||||
|
||||
```python
|
||||
@ -1096,8 +1127,8 @@ A dictionary representing the attributes to update, with only one key:
|
||||
```python
|
||||
from ragflow import RAGFlow
|
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|
||||
rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
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assistant = rag.list_chats(name="Miss R")
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rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
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assistant = rag_object.list_chats(name="Miss R")
|
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assistant = assistant[0]
|
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session = assistant.create_session("session_name")
|
||||
session.update({"name": "updated_name"})
|
||||
@ -1105,6 +1136,101 @@ session.update({"name": "updated_name"})
|
||||
|
||||
---
|
||||
|
||||
## List sessions
|
||||
|
||||
```python
|
||||
Chat.list_sessions(
|
||||
page: int = 1,
|
||||
page_size: int = 1024,
|
||||
orderby: str = "create_time",
|
||||
desc: bool = True,
|
||||
id: str = None,
|
||||
name: str = None
|
||||
) -> list[Session]
|
||||
```
|
||||
|
||||
Lists sessions associated with the current chat assistant.
|
||||
|
||||
### Parameters
|
||||
|
||||
#### page: `int`
|
||||
|
||||
Specifies the page on which the sessions will be displayed. Defaults to `1`.
|
||||
|
||||
#### page_size: `int`
|
||||
|
||||
The number of sessions on each page. Defaults to `1024`.
|
||||
|
||||
#### orderby: `str`
|
||||
|
||||
The field by which sessions should be sorted. Available options:
|
||||
|
||||
- `"create_time"` (default)
|
||||
- `"update_time"`
|
||||
|
||||
#### desc: `bool`
|
||||
|
||||
Indicates whether the retrieved sessions should be sorted in descending order. Defaults to `True`.
|
||||
|
||||
#### id: `str`
|
||||
|
||||
The ID of the chat session to retrieve. Defaults to `None`.
|
||||
|
||||
#### name: `str`
|
||||
|
||||
The name of the chat session to retrieve. Defaults to `None`.
|
||||
|
||||
### Returns
|
||||
|
||||
- Success: A list of `Session` objects associated with the current chat assistant.
|
||||
- Failure: `Exception`.
|
||||
|
||||
### Examples
|
||||
|
||||
```python
|
||||
from ragflow import RAGFlow
|
||||
|
||||
rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
||||
assistant = rag_object.list_chats(name="Miss R")
|
||||
assistant = assistant[0]
|
||||
for session in assistant.list_sessions():
|
||||
print(session)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Delete sessions
|
||||
|
||||
```python
|
||||
Chat.delete_sessions(ids:list[str] = None)
|
||||
```
|
||||
|
||||
Deletes sessions by ID.
|
||||
|
||||
### Parameters
|
||||
|
||||
#### ids: `list[str]`
|
||||
|
||||
The IDs of the sessions to delete. Defaults to `None`. If not specified, all sessions associated with the current chat assistant will be deleted.
|
||||
|
||||
### Returns
|
||||
|
||||
- Success: No value is returned.
|
||||
- Failure: `Exception`
|
||||
|
||||
### Examples
|
||||
|
||||
```python
|
||||
from ragflow import RAGFlow
|
||||
|
||||
rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
||||
assistant = rag_object.list_chats(name="Miss R")
|
||||
assistant = assistant[0]
|
||||
assistant.delete_sessions(ids=["id_1","id_2"])
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Chat
|
||||
|
||||
```python
|
||||
@ -1115,11 +1241,11 @@ Asks a question to start a conversation.
|
||||
|
||||
### Parameters
|
||||
|
||||
#### question *Required*
|
||||
#### question: `str` *Required*
|
||||
|
||||
The question to start an AI chat. Defaults to `None`.
|
||||
The question to start an AI chat.
|
||||
|
||||
#### stream
|
||||
#### stream: `str`
|
||||
|
||||
Indicates whether to output responses in a streaming way:
|
||||
|
||||
@ -1172,8 +1298,8 @@ A list of `Chunk` objects representing references to the message, each containin
|
||||
```python
|
||||
from ragflow import RAGFlow
|
||||
|
||||
rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
||||
assistant = rag.list_chats(name="Miss R")
|
||||
rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
||||
assistant = rag_object.list_chats(name="Miss R")
|
||||
assistant = assistant[0]
|
||||
session = assistant.create_session()
|
||||
|
||||
@ -1188,99 +1314,4 @@ while True:
|
||||
for ans in session.ask(question, stream=True):
|
||||
print(answer.content[len(cont):], end='', flush=True)
|
||||
cont = answer.content
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## List sessions
|
||||
|
||||
```python
|
||||
Chat.list_sessions(
|
||||
page: int = 1,
|
||||
page_size: int = 1024,
|
||||
orderby: str = "create_time",
|
||||
desc: bool = True,
|
||||
id: str = None,
|
||||
name: str = None
|
||||
) -> list[Session]
|
||||
```
|
||||
|
||||
Lists sessions associated with the current chat assistant.
|
||||
|
||||
### Parameters
|
||||
|
||||
#### page
|
||||
|
||||
Specifies the page on which the sessions will be displayed. Defaults to `1`.
|
||||
|
||||
#### page_size
|
||||
|
||||
The number of sessions on each page. Defaults to `1024`.
|
||||
|
||||
#### orderby
|
||||
|
||||
The field by which sessions should be sorted. Available options:
|
||||
|
||||
- `"create_time"` (default)
|
||||
- `"update_time"`
|
||||
|
||||
#### desc
|
||||
|
||||
Indicates whether the retrieved sessions should be sorted in descending order. Defaults to `True`.
|
||||
|
||||
#### id
|
||||
|
||||
The ID of the chat session to retrieve. Defaults to `None`.
|
||||
|
||||
#### name
|
||||
|
||||
The name of the chat to retrieve. Defaults to `None`.
|
||||
|
||||
### Returns
|
||||
|
||||
- Success: A list of `Session` objects associated with the current chat assistant.
|
||||
- Failure: `Exception`.
|
||||
|
||||
### Examples
|
||||
|
||||
```python
|
||||
from ragflow import RAGFlow
|
||||
|
||||
rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
||||
assistant = rag_object.list_chats(name="Miss R")
|
||||
assistant = assistant[0]
|
||||
for session in assistant.list_sessions():
|
||||
print(session)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Delete sessions
|
||||
|
||||
```python
|
||||
Chat.delete_sessions(ids:list[str] = None)
|
||||
```
|
||||
|
||||
Deletes sessions by ID.
|
||||
|
||||
### Parameters
|
||||
|
||||
#### ids: `list[str]`
|
||||
|
||||
The IDs of the sessions to delete. Defaults to `None`. If not specified, all sessions associated with the current chat assistant will be deleted.
|
||||
|
||||
### Returns
|
||||
|
||||
- Success: No value is returned.
|
||||
- Failure: `Exception`
|
||||
|
||||
### Examples
|
||||
|
||||
```python
|
||||
from ragflow import RAGFlow
|
||||
|
||||
rag = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
|
||||
assistant = rag.list_chats(name="Miss R")
|
||||
assistant = assistant[0]
|
||||
assistant.delete_sessions(ids=["id_1","id_2"])
|
||||
```
|
||||
Loading…
x
Reference in New Issue
Block a user