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Integrating Text File Content into Your Chat Agent

Enhancing your chat agent with the inclusion of plain text (.txt) files broadens its knowledge base, enabling it to draw upon a diverse range of textual content. The txt_chat method facilitates the seamless integration of text files into your chat agent, making this wealth of information accessible for enhancing conversation quality and relevance.

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Function Overview

The txt_chat function is designed to ingest content from text files into your chat agent, employing a variety of parameters to ensure this process is both efficient and effective.

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Parameters

  • input_dir (Optional[str]): Directory path containing text files to be added. If specified, the function will search this directory for eligible files.
  • input_files (Optional[List]): A list of paths to specific text files to be added. When provided, input_dir is bypassed.
  • exclude_hidden (bool): If True, hidden files or those starting with a dot (.) within input_dir are excluded.
  • filename_as_id (bool): If True, the filename is used as the unique identifier for each text document.
  • recursive (bool): If True, the function will also search subdirectories within input_dir for text files.
  • required_exts (Optional[List[str]]): Specifies the file extensions to include. Defaults to text file extensions.
  • system_prompt (str): An optional prompt to guide the system in processing text file content.
  • query_wrapper_prompt (str): An optional prompt that can improve the relevance of search queries by providing context related to the text content.
  • embed_model (Union[str, EmbedType]): The embedding model used for extracting and embedding text from the files. Defaults to a general-purpose model.
  • llm_params (dict): Configuration parameters for integrating Large Language Models to enhance content comprehension and query processing.
  • vector_store_params (dict): Configuration for vector storage, specifying how and where extracted content embeddings are stored.
  • service_context_params (dict): Additional parameters to customize the service context for the text file content.
  • chat_engine_params (dict): Customization parameters for the chat engine, influencing how the chat agent utilizes text file content in conversations.
  • retriever_params (dict): Configuration for the document retriever component, determining how text file content is indexed and retrieved in response to user queries.

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Example Usage

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Adding Text Files from a Directory

chat_agent.txt_chat(
    input_dir="/path/to/text/files",
    recursive=True
)

This snippet configures the chat agent to ingest text files from the specified directory and its subdirectories.

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Adding Specific Text Files

chat_agent.txt_chat(
    input_files=["/path/to/file1.txt", "/path/to/file2.txt"],
)

Here, specific text files are directly added to the chat agent, allowing it to leverage their content in conversations.

​
Integrating Text File Content into Your Chat Agent

Enhancing your chat agent with the inclusion of plain text (.txt) files broadens its knowledge base, enabling it to draw upon a diverse range of textual content. The txt_chat method facilitates the seamless integration of text files into your chat agent, making this wealth of information accessible for enhancing conversation quality and relevance.

​
Function Overview

The txt_chat function is designed to ingest content from text files into your chat agent, employing a variety of parameters to ensure this process is both efficient and effective.

​
Parameters

  • input_dir (Optional[str]): Directory path containing text files to be added. If specified, the function will search this directory for eligible files.
  • input_files (Optional[List]): A list of paths to specific text files to be added. When provided, input_dir is bypassed.
  • exclude_hidden (bool): If True, hidden files or those starting with a dot (.) within input_dir are excluded.
  • filename_as_id (bool): If True, the filename is used as the unique identifier for each text document.
  • recursive (bool): If True, the function will also search subdirectories within input_dir for text files.
  • required_exts (Optional[List[str]]): Specifies the file extensions to include. Defaults to text file extensions.
  • system_prompt (str): An optional prompt to guide the system in processing text file content.
  • query_wrapper_prompt (str): An optional prompt that can improve the relevance of search queries by providing context related to the text content.
  • embed_model (Union[str, EmbedType]): The embedding model used for extracting and embedding text from the files. Defaults to a general-purpose model.
  • llm_params (dict): Configuration parameters for integrating Large Language Models to enhance content comprehension and query processing.
  • vector_store_params (dict): Configuration for vector storage, specifying how and where extracted content embeddings are stored.
  • service_context_params (dict): Additional parameters to customize the service context for the text file content.
  • chat_engine_params (dict): Customization parameters for the chat engine, influencing how the chat agent utilizes text file content in conversations.
  • retriever_params (dict): Configuration for the document retriever component, determining how text file content is indexed and retrieved in response to user queries.

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Example Usage

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Adding Text Files from a Directory

chat_agent.txt_chat(
    input_dir="/path/to/text/files",
    recursive=True
)

This snippet configures the chat agent to ingest text files from the specified directory and its subdirectories.

​
Adding Specific Text Files

chat_agent.txt_chat(
    input_files=["/path/to/file1.txt", "/path/to/file2.txt"],
)

Here, specific text files are directly added to the chat agent, allowing it to leverage their content in conversations.