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A full-stack Webui implementation of Large Language model, such as ChatGPT or LLaMA.
| Date | Stars |
|---|---|
| 2026-07-24 | 291 |
| 2026-07-25 | 291 |
| 2026-07-28 | 291 |
| 2026-07-30 | 290 |
| 2026-08-08 | 290 |
| 2026-09-06 | 290 |
| 2026-09-20 | 290 |
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# LLMChat 🎉
👋 Welcome to the LLMChat repository, a full-stack implementation of an API server built with Python FastAPI, and a beautiful frontend powered by Flutter.
💬 This project is designed to deliver a seamless chat experience with the advanced ChatGPT and other LLM models.
🔝 Offering a modern infrastructure that can be easily extended when GPT-4's Multimodal and Plugin features become available.
🚀 Enjoy your stay!
## **Demo**
---
### **Enjoy the beautiful UI and rich set of customizable widgets provided by Flutter.**
- It supports both `mobile` and `PC` environments.
- `Markdown` is also supported, so you can use it to format your messages.
---
### Web Browsing
+ #### **Duckduckgo**
You can use the Duckduckgo search engine to find relevant information on the web. Just activate the 'Browse' toggle button!
Watch the demo video for full-browsing: https://www.youtube.com/watch?v=mj_CVrWrS08
> 
---
### Vector Embedding
+ #### **Embed Any Text**
With the `/embed` command, you can store the text indefinitely in your own private vector database and query it later, anytime. If you use the `/share` command, the text is stored in a public vector database that everyone can share. Enabling `Query` toggle button or `/query` command helps the AI generate contextualized answers by searching for text similarities in the public and private databases. This solves one of the biggest limitations of language models: **memory**.
+ #### **Upload Your PDF File**
You can embed PDF file by clicking `Embed Document` on the bottom left. In a few seconds, text contents of PDF will be converted to vectors and embedded to Redis cache.
> 
---
+ ### Change your chat model
You can change your chat model by dropdown menu. You can define whatever model you want to use in `LLMModels` which is located in `app/models/llms.py`.
> 
---
+ ### Change your chat title
You can change your chat title by clicking the title of the chat. This will be stored until you change or delete it!
> 
---
### 🦙 Local LLMs
> 
For the local Llalam LLMs, it is assumed to work only in the local environment and uses the `http://localhost:8002/v1/completions` endpoint. It continuously checks the status of the llama API server by connecting to `http://localhost:8002/health` once a second to see if a 200 OK response is returned, and if not, it automatically runs a separate process to create a the API server.
#### **Llama.cpp**
The main goal of llama.cpp is to run the LLaMA model using `GGML` 4-bit quantization with plain C/C++ implementation without dependencies. You have to download GGML `bin` file from huggingface and put it in the `llama_models/ggml` folder, and define LLMModel in `app/models/llms.py`. There are few examples, so you can easily define your own model.
Refer to the `llama.cpp` repository for more information: https://github.com/ggerganov/llama.cpp
#### **Exllama**
A standalone Python/C++/CUDA implementation of Llama for use with 4-bit `GPTQ` weights, designed to be fast and memory-efficient on modern GPUs. It uses `pytorch` and `sentencepiece` to run the model. It is assumed to work only in the local environment and at least one `NVIDIA CUDA GPU` is required. You have to download tokenizer, config, and GPTQ files from huggingface and put it in the `llama_models/gptq/YOUR_MODEL_FOLDER` folder, and define LLMModel in `app/models/llms.py`. There are few examples, so you can easily define your own model. Refer to the `exllama` repository for more detailed information: https://github.com/turboderp/exllama
---
## Key Features
- **FastAPI** - High-performance `web framework` for building APIs with Python.
- **Flutter** - `Webapp` frontend with beautExcerpt of 33,812 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:24cbc86bd046f136, topic:chatbot, topic:chatgpt, topic:webui