This project is a Q&A chatbot powered by Streamlit and Ollama models, allowing users to ask questions and receive helpful responses. The chatbot provides an interactive interface and allows for model selection and response customization.
- User-friendly Interface: A simple web interface where users can ask any question.
- Model Selection: Choose between open-source models such as
llama3.1
andgemma2:2b
. - Response Customization: Adjust parameters like
temperature
andmax tokens
to fine-tune responses. - Langsmith Tracking: Integrated Langsmith API for project tracking.
- Python 3.x
- Streamlit
- Langchain
- Ollama
- dotenv
Ollama supports a variety of models available at ollama.com/library.
Here are some example models that can be downloaded:
Model | Parameters | Size | Download |
---|---|---|---|
Llama 3.2 | 3B | 2.0GB | ollama run llama3.2 |
Llama 3.2 | 1B | 1.3GB | ollama run llama3.2:1b |
Llama 3.1 | 8B | 4.7GB | ollama run llama3.1 |
Llama 3.1 | 70B | 40GB | ollama run llama3.1:70b |
Llama 3.1 | 405B | 231GB | ollama run llama3.1:405b |
Phi 3 Mini | 3.8B | 2.3GB | ollama run phi3 |
Phi 3 Medium | 14B | 7.9GB | ollama run phi3:medium |
Gemma 2 | 2B | 1.6GB | ollama run gemma2:2b |
Gemma 2 | 9B | 5.5GB | ollama run gemma2 |
Gemma 2 | 27B | 16GB | ollama run gemma2:27b |
Mistral | 7B | 4.1GB | ollama run mistral |
Moondream 2 | 1.4B | 829MB | ollama run moondream |
Neural Chat | 7B | 4.1GB | ollama run neural-chat |
Starling | 7B | 4.1GB | ollama run starling-lm |
Code Llama | 7B | 3.8GB | ollama run codellama |
Llama 2 Uncensored | 7B | 3.8GB | ollama run llama2-uncensored |
LLaVA | 7B | 4.5GB | ollama run llava |
Solar | 10.7B | 6.1GB | ollama run solar |
Note: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.