diff --git a/embedchain/embedchain.py b/embedchain/embedchain.py index 64a021fb..7dd5ab29 100644 --- a/embedchain/embedchain.py +++ b/embedchain/embedchain.py @@ -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]