PaperOps.ai - a DeepResearch Agent

A professional-grade, autonomous research agent powered by LangChain and Groq LLMs. This tool intelligently searches the web, analyzes academic sources, and compiles structured research reports on any given topic.

Features

• Autonomous Agentic Workflow: Uses the ReAct (Reason + Act) pattern to dynamically plan and execute research.
• Smart Web Search: Integrates with DuckDuckGo to find high-quality, relevant sources.
• Intelligent Summarization: Reads and distills complex web pages using Llama 3 models.
• Rate-Limit Resilient: detailed "Mellow Mode" architecture ensures stability even on free API tiers.
• Zero Cost: Built entirely on free tools (Groq API + DuckDuckGo).

Tech Stack

• Python 3.11+
• LangChain: For agent orchestration and tool management.
• Groq: For ultra-fast Llama 3 inference.
• BeautifulSoup4: For robust web scraping.

Installation

1. Clone the Repository (if applicable)
2. Create a Virtual Environment (Recommended):

   python -m venv venv
   # Windows
   venv\Scripts\activate
   # Mac/Linux
   source venv/bin/activate

3. Install Dependencies:

   pip install -r requirements.txt

Configuration

1. Obtain a free API Key from Groq Console.
2. Create a .env file in the project root:

   cp .env.example .env

3. Add your API key to the .env file:

   GROQ_API_KEY=gsk_your_actual_api_key_here

Usage

Run the agent via the command line:

# Ensure your virtual environment is active
python main.py

Follow the prompts to enter your research topic (e.g., "Quantum Computing applications in Finance"). The agent will:

1. Think: Formulate a search strategy.
2. Search & Read: Gather information from multiple sources.
3. Write: Generate a comprehensive markdown report (report.md) in the current directory.

Next Stpes : Build LateX code output, and also its direct export agentically, rather than being tied to markdown