AutoResearchBot

A multi-agent system that automates research and generates concise reports on given topics using Langchain and Streamlit, with data stored in SQLite.

Features

• Automated Research: Gathers information on a given topic using various APIs.
• Summarization: Generates concise summaries using a language model.
• Interactive Interface: User-friendly Streamlit interface to input topics and view/edit summaries.
• Database Integration: Stores edited summaries in an SQLite database.

Requirements

• Python 3.10+
• Docker (for containerized setup)

Setup

Local Setup

1. Clone the Repository:

   git clone https://github.com/your-username/AutoResearchBot.git
   cd AutoResearchBot

2. Create a Virtual Environment:

   poetry install
   poetry shell

3. Set Up Environment Variables: Create a .env file in the root directory and add the following:

   OPENAI_API_KEY=your_openai_api_key

4. Run the Application:

   streamlit run app.py

Docker Setup

1. Build the Docker Image:

   docker build -t autoresearchbot .

2. Run the Docker Container:

   docker run -d -p 8501:8501 --env OPENAI_API_KEY=your_openai_api_key autoresearchbot

Usage

1. Input a Topic: Enter a topic in the input field on the Streamlit interface.

2. Generate Report: Click the "Generate Report" button to fetch data and generate a summary.

3. Edit and Save Summary: Edit the summary if needed and click the "Save Summary" button to store it in the database.