This project involves the development of an intelligent chatbot using LlamaIndex, designed to assist users by answering queries related to specific topics provided through documents. Additionally, the chatbot can solve mathematical questions pertinent to these topics. This solution is ideal for companies looking to provide a responsive and informative digital assistant on their website.
- Topic-Specific Query Handling: The chatbot is trained on specific documents provided by the company, enabling it to answer questions accurately and contextually based on the content of these documents.
- Mathematical Query Resolution: Beyond textual information, the chatbot can handle and solve mathematical problems related to the topics it covers, offering a well-rounded user experience.
- Seamless Integration with Websites: The chatbot can be easily embedded into your company's website, providing real-time assistance to visitors.
- Powered by LlamaIndex: Utilizing LlamaIndex allows the chatbot to efficiently index and query large volumes of data, ensuring quick and relevant responses.
git clone https://github.com/your-repo/llamaindex-chatbot.git cd llamaindex-chatbot
Install Dependencies Ensure you have Python installed (preferably version 3.8 or higher). Then, install the required packages:
bash Copy code pip install -r requirements.txt Set Up Environment Variables Create a .env file in the root directory and add your API keys:
makefile Copy code OPENAI_API_KEY=your_openai_api_key Load the Documents Place the documents containing the topics the chatbot will cover into the data/documents/ directory. The chatbot will use these documents to build its knowledge base.
Run the Application Start the chatbot server by running:
bash Copy code python main.py Integration with FastAPI (Optional) If you wish to deploy the chatbot as part of a FastAPI application, follow these additional steps:
Install FastAPI:
bash Copy code pip install fastapi Modify the main.py file to include FastAPI routes for the chatbot.
Usage Once the chatbot is running, visitors to your website can interact with it by asking questions related to the topics you've provided. The chatbot will retrieve information from the indexed documents and provide accurate responses. It will also handle mathematical queries efficiently, leveraging LlamaIndex's capabilities.
Customization Document Updates: To update the topics, simply replace or add new documents in the data/documents/ directory and restart the application. Mathematical Query Handling: Customize the mathematical problem-solving capabilities by extending the relevant functions in the math_solver.py module. Contribution Contributions are welcome! Please fork this repository, make your changes, and submit a pull request. Ensure your code is well-documented and tested.
Contact For any inquiries or support, please reach out to [Hardik Singh] at [hardiksingh5864@gmai.com]
I've been working on an intelligent chatbot for my company, leveraging the power of LlamaIndex to create a dynamic, topic-specific assistant. This chatbot not only answers questions based on documents we provide but also handles mathematical queries related to those topics.
🔍 Key Features:
Contextual answers based on specific documents. Capable of solving related mathematical problems. Easily integrated into our company’s website for real-time user assistance. This project showcases how LlamaIndex can be a game-changer in creating interactive and intelligent web services. Can't wait to see how it enhances user engagement on our platform!
Feel free to check out the project or reach out if you're interested in learning more! 🌟