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https://github.com/shitan198u/anychat
Chat with your Documents(PDF, TXT, DOCX, ODT, PPTX etc), Websites and Youtube Chat too!, CSV files. Uses langchain, Ollama, Groq, Gemini, Streamlit. Llama3 available
https://github.com/shitan198u/anychat
gemini genai groq groqapi langchain llama3 ollama streamlit website youtube
Last synced: 3 months ago
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Chat with your Documents(PDF, TXT, DOCX, ODT, PPTX etc), Websites and Youtube Chat too!, CSV files. Uses langchain, Ollama, Groq, Gemini, Streamlit. Llama3 available
- Host: GitHub
- URL: https://github.com/shitan198u/anychat
- Owner: shitan198u
- License: mit
- Created: 2024-03-13T17:39:34.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-04-24T04:39:31.000Z (9 months ago)
- Last Synced: 2024-09-23T11:31:59.798Z (4 months ago)
- Topics: gemini, genai, groq, groqapi, langchain, llama3, ollama, streamlit, website, youtube
- Language: Python
- Homepage:
- Size: 57.6 KB
- Stars: 42
- Watchers: 4
- Forks: 12
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# AnyChat: Chat with Your Documents
AnyChat is a powerful chatbot that allows you to interact with your documents (PDF, TXT, DOCX, ODT, PPTX, CSV, etc.) in a natural and conversational way. It leverages the capabilities of LangChain, Ollama, Groq, Gemini, and Streamlit to provide an intuitive and informative experience.
[Video Demo](https://github.com/shitan198u/AnyChat/assets/74671269/6cdaf9ef-1b52-4ddc-bb45-721b3886f826)
## Features
- **Conversational Interaction:** Ask questions about your documents and receive human-like responses from the chatbot.
- **Multi-Document Support:** Upload and process various document formats, including PDFs, text files, Word documents, spreadsheets, and presentations.
- **Website-Chat Support:** Chat with any valid website.
- **Advanced Language Models:** Choose from different language models (LLMs) like Ollama, Groq, and Gemini to power the chatbot's responses.
- **Embedding Models:** Select from Ollama Embeddings or GooglePalm Embeddings to enhance the chatbot's understanding of your documents.
- **User-Friendly Interface:** Streamlit provides a clean and intuitive interface for interacting with the chatbot.
## Installation
### Prerequisites
- Python 3.10 or higher
- A virtual environment (recommended)
### Clone the Repository
Clone the AnyChat repository from GitHub:
```bash
git clone https://github.com/shitan198u/AnyChat.git
```
### Navigate to the working directory
```bash
cd Anychat
```
### Using `Rye` (Recommended)
1. Install the Rye package manager: [Installation Guide](https://rye-up.com/guide/installation/)
2. Sync the project:
```bash
rye sync
```
### Using `venv`
1. Create a virtual environment:
```bash
python -m venv anychat-env
```
2. Activate the virtual environment:
```bash
source anychat-env/bin/activate
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
### Using `conda`
1. Create a conda environment:
```bash
conda create -n anychat-env python=3.12
```
2. Activate the conda environment:
```bash
conda activate anychat-env
```
3. Install the required dependencies:
```bash
conda install --file requirements.txt
```
## Configuration
- Rename the `secrets_example.toml` file to `secrets.toml` in the `src/anychat/.streamlit/` directory.
## Ollama Installation
To use Ollama for AnyChat, you need to install Ollama and download the necessary models. Follow the instructions below:
1. **Install Ollama:**
Visit the official Ollama website for installation instructions: [Ollama Download](https://ollama.com/download)
2. **Download Ollama Models:**
Open your terminal and run the following commands to download the required models:
```bash
ollama pull nomic-embed-text
```
This command downloads the `nomic-embed-text` model, which is necessary for running Ollama embeddings.
```bash
ollama pull openchat
```
This command downloads the `openchat` model, which you can use as a language model in AnyChat.
## Usage
1. **Set API Keys:**
- 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.
2. **Run the Application:**
```bash
cd src/anychat
streamlit run chatbot.py
```
3. **Using Rye**
```bash
cd src/anychat
rye run streamlit run chatbot.py
```
4. **Upload Documents:**
- In the Streamlit interface, upload the documents you want to chat with.
- Click the "Process" button to process the documents.
5. **Start Chatting:**
- Once the documents are processed, you can start asking questions in the chat input field.
- The chatbot will analyze your documents and provide relevant answers based on their content.
## License
This project is licensed under the MIT License. See the `LICENSE` file for details.
## Additional Notes
- For optimal performance, ensure you have the necessary resources (CPU, RAM) to handle the document processing and LLM computations.
- The chatbot's accuracy and responsiveness may vary depending on the complexity of your documents and the chosen LLM.
- Consider using a GPU-enabled environment if you have access to one, as it can significantly speed up the processing.