Add LlamaCpp to readme and documentation

README.md

@@ -45,7 +45,9 @@ In a nutshell, ConfiChat caters to users who value transparent control over thei
 
 - **Cross-Platform Compatibility**: Developed in Flutter, ConfiChat runs on Windows, Linux, Android, MacOS, and iOS
 
-- **Local Model (Ollama) Support**: [Ollama](https://ollama.com) offers a range of lightweight, open-source local models, such as [Llama by Meta](https://ai.meta.com/llama/), [Gemma by Google](https://ai.google.dev/gemma), and [Llava](https://github.com/haotian-liu/LLaVA) for multimodal/image support. These models are designed to run efficiently even on machines with limited resources. By focusing on local processing, Ollama enables the use of powerful LLMs without relying on cloud services, enhancing both privacy and offline capabilities. For an up-to-date list of available models, refer to the [Ollama library](https://ollama.com/library).
+- **Local Model Support (Ollama and LlamaCpp)**: [Ollama](https://ollama.com) & [LlamaCpp](https://github.com/ggerganov/llama.cpp) both offer a range of lightweight, open-source local models, such as [Llama by Meta](https://ai.meta.com/llama/), [Gemma by Google](https://ai.google.dev/gemma), and [Llava](https://github.com/haotian-liu/LLaVA) for multimodal/image support. These models are designed to run efficiently even on machines with limited resources. By focusing on local processing, Ollama enables the use of powerful LLMs without relying on cloud services, enhancing both privacy and offline capabilities. 
+
+For an up-to-date list of available models, refer to the [Ollama library](https://ollama.com/library) or [Hugging Face](https://huggingface.co/) for gguf model files for LlamaCpp.
 
 - **OpenAI Integration**: Seamlessly integrates with [OpenAI](https://openai.com) to provide advanced language model capabilities using your [own API key](https://platform.openai.com/docs/quickstart). Please note that while the API does not store conversations like ChatGPT does, OpenAI retains input data for abuse monitoring purposes. You can review their latest [data retention and security policies](https://openai.com/enterprise-privacy/). In particular, check the "How does OpenAI handle data retention and monitoring for API usage?" in their FAQ (https://openai.com/enterprise-privacy/).
 

docs/quickstart.md

@@ -21,6 +21,11 @@ Get up and running with **ConfiChat** by following this guide. Whether you're us
    - [4. Get Your OpenAI API Key](#4-get-your-openai-api-key)
    - [5. Configure ConfiChat with Your API Key](#5-configure-confichat-with-your-api-key)
    - [Additional Resources](#additional-resources-2)
+4. [Using ConfiChat with LlamaCpp](#using-confichat-with-llamacpp)
+   - [1. Install LlamaCpp](#1-install-llamacpp)
+   - [2. Run LlamaCpp Server](#2-run-llamacpp-server)
+   - [3. Set Up ConfiChat](#3-set-up-confichat)
+   - [Additional Resources](#additional-resources-3)
 
 ---
 
@@ -162,3 +167,41 @@ Follow the instructions in the [Configure ConfiChat with Your API Key](#3-config
 ### Additional Resources
 
 For more detailed instructions and troubleshooting, please visit the [Ollama documentation](https://ollama.com/docs), the [OpenAI documentation](https://platform.openai.com/docs), and the [ConfiChat repository](https://github.com/your-repository/ConfiChat).
+
+
+## Using ConfiChat with LlamaCp
+
+Set up **LlamaCpp** with **ConfiChat** by following these steps. This section will guide you through installing LlamaCpp, running the server, and configuring ConfiChat.
+
+### 1. Install LlamaCpp
+
+To use LlamaCpp, you first need to install it:
+
+- **macOS**:
+  ```bash
+  brew install llamacpp
+  ```
+
+- **Windows**:
+  Download the binaries from the [LlamaCpp GitHub releases page](https://github.com/ggerganov/llama.cpp/releases) and follow the installation instructions.
+
+- **Linux**:
+  ```bash
+  sudo apt-get install llamacpp
+  ```
+
+### 2. Run LlamaCpp Server
+After installing LlamaCpp, you'll need to run the LlamaCpp server with your desired model:
+```
+llama-server -m /path/to/your/model --port 8080
+```
+
+This command will start the LlamaCpp server, which ConfiChat can connect to for processing language model queries.
+
+### 3. Set Up ConfiChat
+
+Follow the instructions in the [Set Up ConfiChat](#3-set-up-confichat) section above.
+
+### Additional Resources
+
+For more detailed instructions and troubleshooting, please visit the [LlamaCpp documentation](https://github.com/ggerganov/llama.cpp) and the [ConfiChat repository](https://github.com/your-repository/ConfiChat).