https://github.com/alphasecio/groq
A Streamlit chatbot with memory for running open-source text models on Groq.
https://github.com/alphasecio/groq
gemma groq llama mem0ai mistral python streamlit
Last synced: 11 months ago
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A Streamlit chatbot with memory for running open-source text models on Groq.
- Host: GitHub
- URL: https://github.com/alphasecio/groq
- Owner: alphasecio
- License: mit
- Created: 2024-03-31T02:09:12.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-07-12T04:54:04.000Z (12 months ago)
- Last Synced: 2025-07-19T21:16:58.082Z (11 months ago)
- Topics: gemma, groq, llama, mem0ai, mistral, python, streamlit
- Language: Python
- Homepage: https://groqqi.streamlit.app
- Size: 907 KB
- Stars: 2
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
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README
# Groq Chatbot with Memory
[Groq](https://groq.com) is a platform for running large language models (LLMs) with token-based pricing and no infrastructure management. Groq uses LPU Inference Engines, a new type of end-to-end processing unit system that provides fast inference for computationally intensive systems. This project showcases a Streamlit app using Groq-hosted models combined with [Mem0](https://github.com/mem0ai/mem0) for persistent conversational memory.
Sign up for an account at [GroqCloud](https://console.groq.com/keys) and get an API key, which you'll need for this project. You'll also need an [OpenAI API key](https://platform.openai.com/account/api-keys) for the embeddings model used by Mem0.
### Supported Models
* Groq (for chat response)
* `llama-3.3-70b-versatile`
* `meta-llama/llama-4-scout-17b-16e-instruct`
* `gemma2-9b-it`
* `mistral-saba-24b`
* `qwen-qwq-32b`
* `deepseek-r1-distill-llama-70b`
* Mem0 (for memory backend)
* `mixtral-8x7b-32768`: for semantic memory retrieval
* `text-embedding-3-small`: for embeddings
### Usage
1. Clone the repository. Alternatively, deploy to [Railway](https://railway.app/?referralCode=alphasec), Render, or Google Cloud Run.
```bash
git clone https://github.com/alphasecio/groq.git
cd groq
```
2. Set your API keys either as environment variables or via the Streamlit sidebar inputs.
3. Run the app.
```bash
streamlit run streamlit_app.py
````