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Integrating DOCX Content into Your Chat Agent

Incorporating DOCX (Microsoft Word) documents into your chat agent significantly enriches its conversational abilities by tapping into the wealth of information stored in these widely used document formats. The docx_chat method facilitates the addition of DOCX content, enabling your chat agent to access and leverage the detailed information contained within DOCX files for more informed and accurate interactions.

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Function Overview

The docx_chat function is specifically tailored to ingest DOCX content into your chat agent, using a variety of parameters to control how this content is processed, indexed, and utilized during conversations.

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Parameters

  • input_dir (Optional[str]): Directory path containing DOCX files to be added. If specified, the function scans this directory for eligible DOCX files.
  • input_files (Optional[List]): A list of specific DOCX file paths to be added. This parameter takes precedence over input_dir if provided.
  • exclude_hidden (bool): If True, hidden files or files starting with a dot (.) in input_dir are excluded from processing.
  • filename_as_id (bool): Uses the filename as the unique identifier for each DOCX document if set to True.
  • recursive (bool): If True, includes files from subdirectories within input_dir.
  • required_exts (Optional[List[str]]): Specifies file extensions to include, typically set to [".docx"] to target DOCX files.
  • system_prompt (str): An optional prompt guiding the system in processing DOCX content.
  • query_wrapper_prompt (str): An optional prompt to enhance the relevance of user queries by providing specific context related to the DOCX content.
  • embed_model (Union[str, EmbedType]): The embedding model used for text extraction and embedding from DOCX documents. Defaults to a standard model optimized for document content.
  • llm_params (dict): Parameters for integrating Large Language Models to enhance content understanding and query processing.
  • vector_store_params (dict): Configuration for vector storage, detailing how and where the content embeddings are stored.
  • service_context_params (dict): Additional parameters to customize the service context for DOCX content.
  • chat_engine_params (dict): Customization parameters for the chat engine, influencing how the chat agent utilizes the DOCX content in conversations.
  • retriever_params (dict): Configuration for the document retriever component, determining how DOCX content is indexed and retrieved in response to user queries.

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Example Usage

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Adding DOCX Files from a Directory

chat_agent.docx_chat(
    input_dir="/path/to/docx/documents",
    recursive=True
)

This code snippet adds DOCX documents from the specified directory (and its subdirectories, if recursive is True) to the chat agent’s database.

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Adding Specific DOCX Files

chat_agent.docx_chat(
    input_files=["/path/to/document1.docx", "/path/to/document2.docx"],
 )

Here, specific DOCX files are directly added to the chat agent, enabling it to draw upon their content in conversation.

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