Multi-Agent AI Researcher Powered by DeepSeek-R1 LLM Model 🔍🤖

Overview

The Multi-Agent AI Researcher is a Streamlit application that leverages GroqChat and HackerNews tools to provide in-depth research and analysis of HackerNews stories and user profiles. Designed for researchers, analysts, and enthusiasts, this app offers a collaborative AI-driven team that generates insights, trends, and content based on HackerNews data.

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Key Features

• Multi-Agent Collaboration: Includes specialized AI assistants for story and user analysis.
• GroqChat Integration: Powered by the deepseek-r1-distill-llama-70b model for detailed, insightful responses.
• HackerNews Tools: Analyzes HackerNews stories, profiles, and trends.
• Customizable System Prompt: Ensures responses are detailed, insightful, and actionable.
• Streamlit Interface: Simple, user-friendly design for seamless interaction.

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Installation

Prerequisites

Ensure Python 3.8 or higher is installed.

Steps

1. Clone the repository:

   git clone https://github.com/your-username/multi-agent-researcher.git
   cd multi-agent-researcher

2. Install dependencies:

   pip install phi streamlit

3. Set up your Groq API key:

   • Enter the key in the app's input field after launching.

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Usage

1. Run the Application:

   streamlit run app.py

2. Interface:

   • Enter your Groq API Key.
   • Input your research query related to HackerNews stories or users.
   • Click Generate Insights to receive a detailed response.

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Technical Details

AI Assistants

• HackerNews Story Researcher:
  • Analyzes top stories on HackerNews.
  • Provides trends, context, and significance of stories.
• HackerNews User Researcher:
  • Examines user profiles, contributions, and influence within the community.
• HackerNews Insights Team:
  • A collaborative assistant leveraging GroqChat for combined story and user analysis.

System Prompt Highlights

The system prompt ensures:

• Responses are context-rich and data-supported.
• Insights are framed in the broader context of technology and society.
• Suggestions for further exploration are provided.

Example Workflow

1. Query: "What are the emerging trends in AI from HackerNews stories?"
2. Response:
   • Analysis of top stories tagged with AI.
   • Insights into the frequency and themes of AI-related discussions.
   • Broader implications for the tech industry.

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Screenshots

• Homepage: Input fields for API key and research query.
• Insights: Detailed responses displayed in markdown.

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Future Enhancements

• Add visualization tools to display trends (charts, graphs).
• Expand tool capabilities to include other data sources like Reddit or Medium.
• Enable multi-query sessions with saved history.

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License

This project is licensed under the MIT License.

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Contact

For queries or contributions, feel free to reach out:

• Author: Stanley Ekene Uzum
• Email: [email protected]
• GitHub: uzumstanley