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Doc string fix for embedchain.py (#1381)

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This commit is contained in:
Anu
2024-06-05 11:44:09 -06:00
committed by GitHub
parent 622ed4a7c9
commit 26c771503b
1 changed files with 26 additions and 8 deletions
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34
embedchain/embedchain.py
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@@ -132,7 +132,14 @@ class EmbedChain(JSONSerializable):
:type config: Optional[AddConfig], optional
:raises ValueError: Invalid data type
:param dry_run: Optional. A dry run displays the chunks to ensure that the loader and chunker work as intended.
deafaults to False
defaults to False
:type dry_run: bool
:param loader: The loader to use to load the data, defaults to None
:type loader: BaseLoader, optional
:param chunker: The chunker to use to chunk the data, defaults to None
:type chunker: BaseChunker, optional
:param kwargs: To read more params for the query function
:type kwargs: dict[str, Any]
:return: source_hash, a md5-hash of the source, in hexadecimal representation.
:rtype: str
"""
@@ -293,12 +300,19 @@ class EmbedChain(JSONSerializable):
Loads the data from the given URL, chunks it, and adds it to database.
:param loader: The loader to use to load the data.
:type loader: BaseLoader
:param chunker: The chunker to use to chunk the data.
:type chunker: BaseChunker
:param src: The data to be handled by the loader. Can be a URL for
remote sources or local content for local loaders.
:param metadata: Optional. Metadata associated with the data source.
:type src: Any
:param metadata: Metadata associated with the data source.
:type metadata: dict[str, Any], optional
:param source_hash: Hexadecimal hash of the source.
:param dry_run: Optional. A dry run returns chunks and doesn't update DB.
:type source_hash: str, optional
:param add_config: The `AddConfig` instance to use as configuration options.
:type add_config: AddConfig, optional
:param dry_run: A dry run returns chunks and doesn't update DB.
:type dry_run: bool, defaults to False
:return: (list) documents (embedded text), (list) metadata, (list) ids, (int) number of chunks
"""
@@ -474,12 +488,14 @@ class EmbedChain(JSONSerializable):
:type input_query: str
:param config: The `BaseLlmConfig` instance to use as configuration options. This is used for one method call.
To persistently use a config, declare it during app init., defaults to None
:type config: Optional[BaseLlmConfig], optional
:type config: BaseLlmConfig, optional
:param dry_run: A dry run does everything except send the resulting prompt to
the LLM. The purpose is to test the prompt, not the response., defaults to False
:type dry_run: bool, optional
:param where: A dictionary of key-value pairs to filter the database results., defaults to None
:type where: Optional[dict[str, str]], optional
:type where: dict[str, str], optional
:param citations: A boolean to indicate if db should fetch citation source
:type citations: bool
:param kwargs: To read more params for the query function. Ex. we use citations boolean
param to return context along with the answer
:type kwargs: dict[str, Any]
@@ -541,14 +557,16 @@ class EmbedChain(JSONSerializable):
:type input_query: str
:param config: The `BaseLlmConfig` instance to use as configuration options. This is used for one method call.
To persistently use a config, declare it during app init., defaults to None
:type config: Optional[BaseLlmConfig], optional
:type config: BaseLlmConfig, optional
:param dry_run: A dry run does everything except send the resulting prompt to
the LLM. The purpose is to test the prompt, not the response., defaults to False
:type dry_run: bool, optional
:param session_id: The session id to use for chat history, defaults to 'default'.
:type session_id: Optional[str], optional
:type session_id: str, optional
:param where: A dictionary of key-value pairs to filter the database results., defaults to None
:type where: Optional[dict[str, str]], optional
:type where: dict[str, str], optional
:param citations: A boolean to indicate if db should fetch citation source
:type citations: bool
:param kwargs: To read more params for the query function. Ex. we use citations boolean
param to return context along with the answer
:type kwargs: dict[str, Any]