FindInFiles

FindInFiles is a smart chatbot that helps you quickly retrieve, search, and summarize information from documents. Simply place your files in a folder (docs), ask your question, search for specific words, or request a summary, and the bot will process the content to provide precise responses. It's an efficient solution for professionals, students, and researchers to streamline document analysis and save time.

Features

• Intelligent Chat: Engage in a conversational manner to ask questions and get accurate answers based on document content.
• Quick Search: Rapidly locate specific words or phrases within documents.
• Document Summarization: Generate concise summaries of document content.
• Advanced Language Model: Utilizes state-of-the-art natural language processing to understand and process queries.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/FindInFiles.git
   cd FindInFiles
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Set up your environment variables:

   • Copy .env-example to .env
   • Fill in your API keys and other required information

Usage

1. Start the Flask server:

   python app.py
   

2. Send POST requests to http://localhost:5000/process with the following JSON structure:

   For chat mode:

   {
     "query": "Your question here",
     "mode": "chat"
   }

   For search mode:

   {
     "query": "search word",
     "mode": "search"
   }

   For summary mode:

   {
     "query": "Number of lines for summary",
     "mode": "summary"
   }

3. The server will respond with the answer, search results, or summary based on the documents in the docs folder.

Configuration

• Place your documents in the docs folder.
• Adjust the max_history_size in chains.py to control the chat history length.
• Modify the chunk_size and chunk_overlap in retrievers.py to fine-tune document processing.

Evaluation

To evaluate the performance of the chatbot, you can run the following command:

python evals.py

This will perform an experiment and evaluate the results based on the specified evaluators.

Evaluation Config

• The evaluators are in the eval_utils/evaluators.py file.You can add more evaluators to this file.
• Dataset is in the eval_utils/datasets.py file. Modify the dataset to add more examples.
• Experiment is in the eval_utils/experiments.py file.

Evaluation Results

• The evaluation results will be displayed in the langsmith console.
• Visit link that appears in the terminal to see the evaluation results.