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Miscellaneous updates to HTTP and PYthon APIs (#3000)

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### What problem does this PR solve?


### Type of change


- [x] Documentation Update
This commit is contained in:
writinwaters
2024-10-24 16:14:07 +08:00
committed by GitHub
parent 765a114be7
commit 524699da7d
2 changed files with 233 additions and 219 deletions
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api/python_api_reference.md
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@@ -105,16 +105,16 @@ dataset = rag_object.create_dataset(name="kb_1")
## Delete datasets
```python
RAGFlow.delete_datasets(ids: list[str] = None)
RAGFlow.delete_datasets(ids: list[str])
```
Deletes specified datasets or all datasets in the system.
### Parameters
#### ids: `list[str]`
#### ids: `list[str]`, *Required*
The IDs of the datasets to delete. Defaults to `None`. If not specified, all datasets in the system will be deleted.
The IDs of the datasets to delete.
### Returns
@@ -410,7 +410,7 @@ A `Document` object contains the following attributes:
- `id`: The document ID. Defaults to `""`.
- `name`: The document name. Defaults to `""`.
- `thumbnail`: The thumbnail image of the document. Defaults to `None`.
- `knowledgebase_id`: The dataset ID associated with the document. Defaults to `None`.
- `dataset_id`: The dataset ID associated with the document. Defaults to `None`.
- `chunk_method` The chunk method name. Defaults to `"naive"`.
- `parser_config`: `ParserConfig` Configuration object for the parser. Defaults to `{"pages": [[1, 1000000]]}`.
- `source_type`: The source type of the document. Defaults to `"local"`.
@@ -592,7 +592,7 @@ A `Chunk` object contains the following attributes:
- `important_keywords`: `list[str]` A list of key terms or phrases tagged with the chunk.
- `create_time`: `str` The time when the chunk was created (added to the document).
- `create_timestamp`: `float` The timestamp representing the creation time of the chunk, expressed in seconds since January 1, 1970.
- `knowledgebase_id`: `str` The ID of the associated dataset.
- `dataset_id`: `str` The ID of the associated dataset.
- `document_name`: `str` The name of the associated document.
- `document_id`: `str` The ID of the associated document.
- `available`: `bool` The chunk's availability status in the dataset. Value options:
@@ -740,7 +740,7 @@ chunk.update({"content":"sdfx..."})
## Retrieve chunks
```python
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]
RAGFlow.retrieve(question:str="", dataset_ids:list[str]=None, document_ids=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]
```
Retrieves chunks from specified datasets.
@@ -751,11 +751,11 @@ Retrieves chunks from specified datasets.
The user query or query keywords. Defaults to `""`.
#### datasets: `list[str]`, *Required*
#### dataset_ids: `list[str]`, *Required*
The IDs of the datasets to search from.
#### document: `list[str]`
#### document_ids: `list[str]`
The IDs of the documents to search from. Defaults to `None`.
@@ -817,7 +817,7 @@ doc = dataset.list_documents(name=name)
doc = doc[0]
dataset.async_parse_documents([doc.id])
for c in rag_object.retrieve(question="What's ragflow?",
datasets=[dataset.id], documents=[doc.id],
dataset_ids=[dataset.id], document_ids=[doc.id],
offset=1, limit=30, similarity_threshold=0.2,
vector_similarity_weight=0.3,
top_k=1024
@@ -839,7 +839,7 @@ Chat Assistant Management
RAGFlow.create_chat(
name: str,
avatar: str = "",
knowledgebases: list[str] = [],
dataset_ids: list[str] = [],
llm: Chat.LLM = None,
prompt: Chat.Prompt = None
) -> Chat
@@ -857,7 +857,7 @@ The name of the chat assistant.
Base64 encoding of the avatar. Defaults to `""`.
#### knowledgebases: `list[str]`
#### dataset_ids: `list[str]`
The IDs of the associated datasets. Defaults to `[""]`.
@@ -914,7 +914,7 @@ datasets = rag_object.list_datasets(name="kb_1")
dataset_ids = []
for dataset in datasets:
dataset_ids.append(dataset.id)
assistant = rag_object.create_chat("Miss R", knowledgebases=dataset_ids)
assistant = rag_object.create_chat("Miss R", dataset_ids=dataset_ids)
```
---
@@ -935,7 +935,7 @@ A dictionary representing the attributes to update, with the following keys:
- `"name"`: `str` The name of the chat assistant to update.
- `"avatar"`: `str` Base64 encoding of the avatar. Defaults to `""`
- `"knowledgebases"`: `list[str]` The datasets to update.
- `"dataset_ids"`: `list[str]` The datasets to update.
- `"llm"`: `dict` The LLM settings:
- `"model_name"`, `str` The chat model name.
- `"temperature"`, `float` Controls the randomness of the model's predictions.
@@ -969,7 +969,8 @@ from ragflow import RAGFlow
rag_object = RAGFlow(api_key="<YOUR_API_KEY>", base_url="http://<YOUR_BASE_URL>:9380")
datasets = rag_object.list_datasets(name="kb_1")
assistant = rag_object.create_chat("Miss R", knowledgebases=datasets)
dataset_id = datasets[0].id
assistant = rag_object.create_chat("Miss R", dataset_ids=[dataset_id])
assistant.update({"name": "Stefan", "llm": {"temperature": 0.8}, "prompt": {"top_n": 8}})
```
@@ -1238,7 +1239,7 @@ assistant.delete_sessions(ids=["id_1","id_2"])
---
## Chat
## Converse
```python
Session.ask(question: str, stream: bool = False) -> Optional[Message, iter[Message]]
@@ -1290,7 +1291,7 @@ A list of `Chunk` objects representing references to the message, each containin
The name of the referenced document.
- `position` `list[str]`
The location information of the chunk within the referenced document.
- `knowledgebase_id` `str`
- `dataset_id` `str`
The ID of the dataset to which the referenced document belongs.
- `similarity` `float`
A composite similarity score of the chunk ranging from `0` to `1`, with a higher value indicating greater similarity.