Agentic AI Multilang Research

🌍🤖 AI-powered multilingual research assistant for instant web search and summaries ✨

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Overview

agentic-ai-multilang-research is an advanced, agentic research assistant that empowers you to ask questions in any language and receive concise, insightful answers—instantly.
It leverages state-of-the-art language models, agentic workflows, and real-time web search to deliver up-to-date, multilingual research summaries.

• Ask in any language: The assistant detects your language and responds accordingly.
• Always up-to-date: Integrates with Google Search for the latest information.
• Powered by LLMs: Uses Ollama and LangChain for local, private, and fast LLM inference.
• Agentic reasoning: Employs graph-based agent workflows for multi-step synthesis.

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Features

• 🌐 Multilingual Input & Output: Seamlessly handles questions and answers in any language.
• 🔍 Automated Web Search: Retrieves and summarizes relevant web content in your language.
• 🧠 Agentic Reasoning: Uses graph-based workflows for advanced, multi-step synthesis.
• 📝 Concise Summaries: Delivers clear, actionable answers using LLM-powered summarization.
• 🛠️ Customizable & Modular: Easily swap models, search providers, or summarization logic.
• 🏃 Runs Locally: All LLM inference is performed locally via Ollama for privacy and speed.

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Quick Start

1. Clone the repository:

   git clone [email protected]:josego85/agentic-ai-multilang-research.git
   cd agentic-ai-multilang-research

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate

3. Install dependencies:

   pip install --upgrade pip
   pip install -r requirements.txt

4. Download an LLM model with Ollama:

   ollama pull gemma3:1b

   (Or use another supported model, e.g., llama2)

5. Configure API keys:
   This project requires a SerpAPI key for Google Search integration.
   Visit SerpAPI to create an account and obtain your API key.
   Add your credentials to a .env file in the project root:

   SERPAPI_API_KEY=your_api_key_here
   

6. Run the assistant:

   python main.py

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Example Usage

python main.py

Sample interaction:

AI Agent: Ask your question in any language and get a summarized answer.
Your question:

--> Was ist der Einfluss von KI-Agenten auf die Arbeitswelt?

🔍 Searching the web for: Was ist der Einfluss von KI-Agenten auf die Arbeitswelt? (lang=de)

⏱ Model response time: 3.92 seconds
⏱ Model response time: 5.96 seconds

Final Response: 

Laut der Zusammenfassung hat der Einfluss von KI-Agenten auf die Arbeitswelt folgende Auswirkungen:

*   **Aufgabeübernahme:** KI-Agenten übernehmen Aufgaben, die bisher menschliche Mitarbeiter erledigten.
*   **Einstiegshürden senken:** Sie machen es einfacher, neue Berufe zu erlernen und zu ergreifen.

Kurz gesagt, KI-Agenten verändern die Arbeitswelt, indem sie Aufgaben automatisieren und so neue Möglichkeiten für Menschen schaffen.

Try questions in any language:

• English:
  How will AI agents impact the future of education?
• Español:
  ¿Qué impacto tendrán los agentes de IA en la medicina moderna?
• Français:
  Quel est l'effet des agents IA sur la productivité des entreprises ?

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Project Structure

• main.py — Entry point; handles user queries and displays responses.
• agent/graph.py — Defines the agentic workflow and orchestration logic.
• service/llm_agent.py — LLM interface using LangChain and Ollama.
• service/summarize.py — Summarization service for multilingual output.
• .env — (Optional) API keys and environment variables.

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Configuration

• Model Selection:
  Change the model name in service/llm_agent.py to use a different LLM with Ollama.

• Environment Variables:
  Place your .env file in the project root with any required API keys or configuration.

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Requirements

• Python 3.11+
• Ollama installed and running for local LLM inference

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Contributing

Contributions, issues, and feature requests are welcome!
Feel free to open an issue or submit a pull request.

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License

GNU General Public License v3.0

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Acknowledgements

• LangChain
• Ollama
• Google Search Results API

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Contact

For questions or support, open an issue on GitHub.