{"id":14964721,"url":"https://github.com/shitan198u/anychat","last_synced_at":"2025-10-25T08:30:20.385Z","repository":{"id":227519324,"uuid":"771653321","full_name":"shitan198u/AnyChat","owner":"shitan198u","description":"Chat with your Documents(PDF, TXT, DOCX, ODT, PPTX etc), Websites and Youtube Chat too!, CSV files. Uses langchain, Ollama, Groq, Gemini, Streamlit. 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It leverages the capabilities of LangChain, Ollama, Groq, Gemini, and Streamlit to provide an intuitive and informative experience.\n\n[Video Demo](https://github.com/shitan198u/AnyChat/assets/74671269/6cdaf9ef-1b52-4ddc-bb45-721b3886f826)\n\n\n## Features\n\n- **Conversational Interaction:** Ask questions about your documents and receive human-like responses from the chatbot.\n- **Multi-Document Support:** Upload and process various document formats, including PDFs, text files, Word documents, spreadsheets, and presentations.\n- **Website-Chat Support:** Chat with any valid website.\n- **Advanced Language Models:** Choose from different language models (LLMs) like Ollama, Groq, and Gemini to power the chatbot's responses.\n- **Embedding Models:** Select from Ollama Embeddings or GooglePalm Embeddings to enhance the chatbot's understanding of your documents.\n- **User-Friendly Interface:** Streamlit provides a clean and intuitive interface for interacting with the chatbot.\n\n## Installation\n\n### Prerequisites\n\n- Python 3.10 or higher\n- A virtual environment (recommended)\n\n### Clone the Repository\n\nClone the AnyChat repository from GitHub:\n\n```bash\ngit clone https://github.com/shitan198u/AnyChat.git\n```\n### Navigate to the working directory\n\n```bash\ncd Anychat\n```\n\n### Using `Rye` (Recommended)\n\n1. Install the Rye package manager: [Installation Guide](https://rye-up.com/guide/installation/)\n\n2. Sync the project:\n\n```bash\nrye sync\n```\n\n### Using `venv`\n\n1. Create a virtual environment:\n\n```bash\npython -m venv anychat-env\n```\n\n2. Activate the virtual environment:\n\n```bash\nsource anychat-env/bin/activate\n```\n\n3. Install the required dependencies:\n\n```bash\npip install -r requirements.txt\n```\n\n### Using `conda`\n\n1. Create a conda environment:\n\n```bash\nconda create -n anychat-env python=3.12\n```\n\n2. Activate the conda environment:\n\n```bash\nconda activate anychat-env\n```\n\n3. Install the required dependencies:\n\n```bash\nconda install --file requirements.txt\n```\n\n## Configuration\n\n- Rename the `secrets_example.toml` file to `secrets.toml` in the `src/anychat/.streamlit/` directory.\n\n## Ollama Installation\n\nTo use Ollama for AnyChat, you need to install Ollama and download the necessary models. Follow the instructions below:\n\n1. **Install Ollama:**\n\nVisit the official Ollama website for installation instructions: [Ollama Download](https://ollama.com/download)\n\n2. **Download Ollama Models:**\n\nOpen your terminal and run the following commands to download the required models:\n\n```bash\nollama pull nomic-embed-text\n```\n\nThis command downloads the `nomic-embed-text` model, which is necessary for running Ollama embeddings.\n\n```bash\nollama pull openchat\n```\n\nThis command downloads the `openchat` model, which you can use as a language model in AnyChat.\n\n## Usage\n\n1. **Set API Keys:**\n- If you're using Google Gemini or Groq, obtain the necessary API keys and store them securely in the `src/anychat/.streamlit/secrets.toml` file or Upload them in the chatbot interface.\n\n2. **Run the Application:**\n\n```bash\ncd src/anychat\nstreamlit run chatbot.py\n```\n3. **Using Rye**\n\n```bash\ncd src/anychat\nrye run streamlit run chatbot.py\n```\n\n4. **Upload Documents:**\n- In the Streamlit interface, upload the documents you want to chat with.\n- Click the \"Process\" button to process the documents.\n\n5. **Start Chatting:**\n- Once the documents are processed, you can start asking questions in the chat input field.\n- The chatbot will analyze your documents and provide relevant answers based on their content.\n\n## License\n\nThis project is licensed under the MIT License. See the `LICENSE` file for details.\n\n## Additional Notes\n\n- For optimal performance, ensure you have the necessary resources (CPU, RAM) to handle the document processing and LLM computations.\n- The chatbot's accuracy and responsiveness may vary depending on the complexity of your documents and the chosen LLM.\n- Consider using a GPU-enabled environment if you have access to one, as it can significantly speed up the processing.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshitan198u%2Fanychat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshitan198u%2Fanychat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshitan198u%2Fanychat/lists"}