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304 lines
11 KiB
Markdown
304 lines
11 KiB
Markdown
# Lord of Large Language Models (LoLLMs)
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<div align="center">
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<img src="https://github.com/ParisNeo/lollms/blob/main/lollms/assets/logo.png" alt="Logo" width="200" height="200">
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</div>
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![GitHub license](https://img.shields.io/github/license/ParisNeo/lollms)
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[![Discord](https://img.shields.io/discord/1092918764925882418?color=7289da&label=Discord&logo=discord&logoColor=ffffff)](https://discord.gg/4rR282WJb6)
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[![Downloads](https://static.pepy.tech/badge/lollms)](https://pepy.tech/project/lollms)
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[![Downloads](https://static.pepy.tech/badge/lollms/month)](https://pepy.tech/project/lollms)
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Lord of Large Language Models (LoLLMs) Server is a text generation server based on large language models. It provides a Flask-based API for generating text using various pre-trained language models. This server is designed to be easy to install and use, allowing developers to integrate powerful text generation capabilities into their applications.
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## Features
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- Fully integrated library with access to bindings, personalities and helper tools.
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- Generate text using large language models.
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- Supports multiple personalities for generating text with different styles and tones.
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- Real-time text generation with WebSocket-based communication.
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- RESTful API for listing personalities and adding new personalities.
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- Easy integration with various applications and frameworks.
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- Possibility to send files to personalities
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- Possibility to run on multiple nodes and provide a generation service to many outputs at once.
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- Data stays local even in the remote version. Only generations are sent to the host node. The logs, data and discussion history are kept in your local disucssion folder.
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## Installation
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You can install LoLLMs using pip, the Python package manager. Open your terminal or command prompt and run the following command:
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```bash
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pip install --upgrade lollms
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```
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Or if you want to get the latest version from the git:
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```bash
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pip install --upgrade git+https://github.com/ParisNeo/lollms.git
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```
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## GPU support
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If you want to use cuda. Either install it directly or use conda to install everything:
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```bash
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conda create --name lollms python=3.10
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```
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Activate the environment
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```bash
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conda activate lollms
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```
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Install cudatoolkit
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```bash
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conda install -c anaconda cudatoolkit
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```
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Install lollms
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```bash
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pip install --upgrade lollms
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```
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Now you are ready.
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To simply configure your environment run the settings app:
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```bash
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lollms-settings
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```
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The tool is intuitive and will guide you through configuration process.
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The first time you will be prompted to select a binding.
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![image](https://github.com/ParisNeo/lollms/assets/827993/2d7f58fe-089d-4d3e-a21a-0609f8e27969)
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Once the binding is selected, you have to install at least a model. You have two options:
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1- install from internet. Just give the link to a model on hugging face. For example. if you select the default llamacpp python bindings (7), you can install this model:
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```bash
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https://huggingface.co/TheBloke/airoboros-7b-gpt4-GGML/resolve/main/airoboros-7b-gpt4.ggmlv3.q4_1.bin
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```
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2- install from local drive. Just give the path to a model on your pc. The model will not be copied. We only create a reference to the model. This is useful if you use multiple clients so that you can mutualize your models with other tools.
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Now you are ready to use the server.
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## Library example
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Here is the smallest possible example that allows you to use the full potential of the tool with nearly no code
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```python
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from lollms.console import Conversation
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cv = Conversation(None)
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cv.start_conversation()
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```
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Now you can reimplement the start_conversation method to do the things you want:
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```python
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from lollms.console import Conversation
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class MyConversation(Conversation):
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def __init__(self, cfg=None):
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super().__init__(cfg, show_welcome_message=False)
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def start_conversation(self):
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prompt = "Once apon a time"
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def callback(text, type=None):
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print(text, end="", flush=True)
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return True
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print(prompt, end="", flush=True)
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output = self.safe_generate(prompt, callback=callback)
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if __name__ == '__main__':
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cv = MyConversation()
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cv.start_conversation()
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```
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Or if you want here is a conversation tool written in few lines
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```python
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from lollms.console import Conversation
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class MyConversation(Conversation):
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def __init__(self, cfg=None):
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super().__init__(cfg, show_welcome_message=False)
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def start_conversation(self):
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full_discussion=""
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while True:
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prompt = input("You: ")
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if prompt=="exit":
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return
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if prompt=="menu":
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self.menu.main_menu()
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full_discussion += self.personality.user_message_prefix+prompt+self.personality.link_text
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full_discussion += self.personality.ai_message_prefix
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def callback(text, type=None):
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print(text, end="", flush=True)
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return True
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print(self.personality.name+": ",end="",flush=True)
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output = self.safe_generate(full_discussion, callback=callback)
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full_discussion += output.strip()+self.personality.link_text
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print()
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if __name__ == '__main__':
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cv = MyConversation()
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cv.start_conversation()
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```
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Here we use the safe_generate method that does all the cropping for you ,so you can chat forever and will never run out of context.
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## Socket IO Server Usage
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Once installed, you can start the LoLLMs Server using the `lollms-server` command followed by the desired parameters.
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```
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lollms-server --host <host> --port <port> --config <config_file> --bindings_path <bindings_path> --personalities_path <personalities_path> --models_path <models_path> --binding_name <binding_name> --model_name <model_name> --personality_full_name <personality_full_name>
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```
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### Parameters
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- `--host`: The hostname or IP address to bind the server (default: localhost).
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- `--port`: The port number to run the server (default: 9600).
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- `--config`: Path to the configuration file (default: None).
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- `--bindings_path`: The path to the Bindings folder (default: "./bindings_zoo").
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- `--personalities_path`: The path to the personalities folder (default: "./personalities_zoo").
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- `--models_path`: The path to the models folder (default: "./models").
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- `--binding_name`: The default binding to be used (default: "llama_cpp_official").
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- `--model_name`: The default model name (default: "Manticore-13B.ggmlv3.q4_0.bin").
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- `--personality_full_name`: The full name of the default personality (default: "personality").
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### Examples
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Start the server with default settings:
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```
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lollms-server
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```
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Start the server on a specific host and port:
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```
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lollms-server --host 0.0.0.0 --port 5000
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```
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## API Endpoints
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### WebSocket Events
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- `connect`: Triggered when a client connects to the server.
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- `disconnect`: Triggered when a client disconnects from the server.
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- `list_personalities`: List all available personalities.
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- `add_personality`: Add a new personality to the server.
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- `generate_text`: Generate text based on the provided prompt and selected personality.
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### RESTful API
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- `GET /personalities`: List all available personalities.
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- `POST /personalities`: Add a new personality to the server.
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Sure! Here are examples of how to communicate with the LoLLMs Server using JavaScript and Python.
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### JavaScript Example
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```javascript
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// Establish a WebSocket connection with the server
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const socket = io.connect('http://localhost:9600');
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// Event: When connected to the server
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socket.on('connect', () => {
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console.log('Connected to the server');
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// Request the list of available personalities
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socket.emit('list_personalities');
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});
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// Event: Receive the list of personalities from the server
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socket.on('personalities_list', (data) => {
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const personalities = data.personalities;
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console.log('Available Personalities:', personalities);
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// Select a personality and send a text generation request
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const selectedPersonality = personalities[0];
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const prompt = 'Once upon a time...';
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socket.emit('generate_text', { personality: selectedPersonality, prompt: prompt });
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});
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// Event: Receive the generated text from the server
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socket.on('text_generated', (data) => {
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const generatedText = data.text;
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console.log('Generated Text:', generatedText);
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// Do something with the generated text
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});
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// Event: When disconnected from the server
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socket.on('disconnect', () => {
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console.log('Disconnected from the server');
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});
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```
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### Python Example
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```python
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import socketio
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# Create a SocketIO client
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sio = socketio.Client()
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# Event: When connected to the server
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@sio.on('connect')
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def on_connect():
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print('Connected to the server')
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# Request the list of available personalities
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sio.emit('list_personalities')
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# Event: Receive the list of personalities from the server
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@sio.on('personalities_list')
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def on_personalities_list(data):
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personalities = data['personalities']
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print('Available Personalities:', personalities)
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# Select a personality and send a text generation request
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selected_personality = personalities[0]
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prompt = 'Once upon a time...'
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sio.emit('generate_text', {'personality': selected_personality, 'prompt': prompt})
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# Event: Receive the generated text from the server
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@sio.on('text_generated')
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def on_text_generated(data):
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generated_text = data['text']
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print('Generated Text:', generated_text)
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# Do something with the generated text
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# Event: When disconnected from the server
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@sio.on('disconnect')
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def on_disconnect():
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print('Disconnected from the server')
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# Connect to the server
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sio.connect('http://localhost:9600')
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# Keep the client running
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sio.wait()
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```
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Make sure to have the necessary dependencies installed for the JavaScript and Python examples. For JavaScript, you need the `socket.io-client` package, and for Python, you need the `python-socketio` package.
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## Contributing
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Contributions to the LoLLMs Server project are welcome and appreciated. If you would like to contribute, please follow the guidelines outlined in the [CONTRIBUTING.md](https://github.com/ParisNeo/lollms/blob/main/CONTRIBUTING.md) file.
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## License
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LoLLMs Server is licensed under the Apache 2.0 License. See the [LICENSE](https://github.com/ParisNeo/lollms/blob/main/LICENSE) file for more information.
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## Repository
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The source code for LoLLMs Server can be found on GitHub
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