Chatlab is an AI chat application framework that utilizes llama-stack-client, Ollama, and MCP to facilitate integration testing and deployment of AI chatbot solutions with multiple model support.
Added on:
Created by:
May 10 2025
Chatlab is an AI chat application framework that utilizes llama-stack-client, Ollama, and MCP to facilitate integration testing and deployment of AI chatbot solutions with multiple model support.
Added on:
Created by:
May 10 2025
Ricardo
Featured
What is Chatlab?
Chatlab is a comprehensive LLM chat application designed for testing and developing AI chatbots using llama-stack-client, Ollama, and MCP integrations. It supports various inference models and provides a flexible environment for deploying chatbots in different contexts. The platform enables developers to experiment with large language models, perform integration tests efficiently, and deploy robust AI chat solutions seamlessly. It offers a user-friendly interface, model management, and API integration, making it suitable for both testing and production environments for AI-powered communication tools.
Who will use Chatlab?
- AI developers
- Chatbot developers
- Research scientists
- AI product teams
How to use the Chatlab?
- Step 1: Clone the repository from GitHub.
- Step 2: Set up the virtual environment and dependencies.
- Step 3: Configure environment variables including API keys or use Ollama locally.
- Step 4: Start Ollama or set the environment to use Together.ai API in main.py.
- Step 5: Run the Gradio application to access the chat interface.
- Step 6: Use the interface to test and develop AI chatbots.
Chatlab's Core Features & Benefits
The Core Features
- Supports llama-stack-client for model management
- Integrates Ollama for inference services
- Allows testing of multiple AI models
- Provides an interactive chat interface via Gradio
- Supports API account integration for model access
The Benefits
- Facilitates seamless AI chatbot testing
- Supports multiple machine learning models
- Enables rapid prototyping of AI communication tools
- Provides an easy-to-use interface for developers
- Flexibility in deployment options — local Ollama or cloud APIs
Chatlab's Main Use Cases & Applications
- Testing AI chatbots with various models
- Developing and deploying conversational AI solutions
- Performing integration tests for large language models
- Prototyping new chatbot features in a controlled environment
FAQs of Chatlab
Developer
- ricardoborges
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Research And Data
A server implementation supporting Model Context Protocol, integrating CRIC's industrial AI capabilities.
Provides real-time traffic, air quality, weather, and bike-sharing data for Valencia city in a unified platform.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
A MCP client integrating Brave Search API for web searches, utilizing MCP protocol for efficient communication.
A protocol server enabling seamless communication between Umbraco CMS and external applications.
NOL integrates LangChain and Open Router to create a multi-client MCP server using Next.js
Connects LLMs to Firebolt Data Warehouse for autonomous querying, data access, and insight generation.
A client framework for connecting AI agents to MCP servers, enabling tool discovery and integration.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
An open-source client to interact with multiple MCP servers, enabling seamless tool access for Claude.
AI Chatbot
Integrates APIs, AI, and automation to enhance server and client functionalities dynamically.
Provides long-term memory for LLMs by storing and retrieving contextual information via MCP standards.
An advanced clinical evidence analysis server supporting precision medicine and oncology research with flexible search options.
A platform collecting A2A agents, tools, servers, and clients for effective agent communication and collaboration.
A Spring-based chatbot for Cloud Foundry that integrates with AI services, MCP, and memGPT for advanced capabilities.
An AI agent controlling macOS using OS-level tools, compatible with MCP, facilitating system management via AI.
PHP client library enabling interaction with MCP servers via SSE, StdIO, or external processes.
A platform for managing and deploying autonomous agents, tools, servers, and clients for automation tasks.
Enables interaction with powerful Text to Speech and video generation APIs for multimedia content creation.
An MCP server providing API access to RedNote (XiaoHongShu, xhs) for seamless integration.