Apple MLX: Build Your Own Private AI Server 📱100% Local to your Network 🌐 Access AI on Any Device 🖥️ Run Locally 🔧 Using MLX Server 👩‍💻 Create a UI Chatbot using Chainlit 📚 Step-by-Step Guide Subscribe: youtube.com/@MervinPraison YT: youtube.com/watch?v=mStqWk… Awni Hannun

Chainlit is built for multi modality but was not supporting voice use cases … until today! Chainlit developers can now access user audio streams and build voice-based LLM applications 🔥 🧵

LM Studio CLI 1.0: Speed Up Your AI App Development 🚀 LM Studio CLI Overview LM Studio 🔧 Install and Setup 🤖 Integrate Chatbot UI Chainlit 🐍 Python Application Integration 📊 Log Monitoring Subscribe: youtube.com/@MervinPraison YT: youtube.com/watch?v=QL9CfG…

Secrets to Self-Hosting Ollama on a Remote Server 🔧 Create Server - Google Cloud 📦 Install Llama 3 🤖 Develop Chatbot UI - Chainlit 💻 GPU Setup 🚀 Install NVIDIA Drivers 🌐 Enable Remote Access 📲 App Integration & Testing - ollama Subscribe: youtube.com/@MervinPraison

🚨 New Github repo: OpenAI Assistant x Chainlit 🚨 Distribute your OpenAI Assistant as a Chainlit app, copilot or Slack bot in just a few minutes 🔥

Llama Index AI Agents: How to Get Started for Beginners? 🤖 100% Local - ollama ➕ Creating Custom Tools 🛠️ Building AI Agent 🖥️ User Interface Creation - Chainlit Subscribe: youtube.com/@MervinPraison YT: youtube.com/watch?v=jnWaUt… Jerry Liu LlamaIndex 🦙

Build a Blazing-Fast RAG Chatbot with Llama3 on Groq Inc, Chainlit, and LlamaIndex 🦙 ⚡️ This is a neat resource by Jayita B. on teaching you how to not only build an advanced RAG indexing/query pipeline, but also turn it into a full-stack application with rapid response

Impressed by OpenAI Assistant with code interpreter! A 5-lines prompt is enough to make it run data analysis on CSV files with dynamic charts. Had fun building this demo with Chainlit. Try it -> chainlit-data-analyst.onrender.com Source code -> github.com/willydouhard/d…

Simple RAG with Crawl4AI: Banish hallucinations in a Groq Inc-powered chat app built by Chainlit LLMs often hallucinate when the answer isn't in their training data. Programmers need a RAG-like solution specially for updated library docs. This demo shows a simple approach

Literal AI is now in public beta 🎉 Literal AI is the multimodal LLM app observability and evaluation solution for developers and product owners. Supports uses cases from simple LLM calls to complex agentic systems across various modalities: text, image and audio. 🧵

A Beginner’s Guide to Building a Full-Stack Agent 🤖 We love this tutorial by Mervin Praison that gives a step-by-step overview on how to build the core components of an agent to build a simple application, using local models (ollama) and Chainlit. Define the tools, plug

Praison AI User Interface 🚀 Use crewAI and AutoGen 🧠 Automatically Generate AI Agents ✏️ Edit Agents 🔧 Add Custom Tools 🌐 Integrate Groq Inc ollama LM Studio 🗂️ Save Chat History Chainlit Subscribe: youtube.com/@MervinPraison pip install "praison[ui]" YT:

Florence-2: Open Source Vision Foundation Model by Microsoft 🌟 Lightweight 💪 Strong zero-shot capabilities 🖼️ 126 million images dataset - FLD-5B 📊 5.4 billion visual annotations 🗺️ Create a Chatbot with this Model - Chainlit 🚀 Competitive with larger models 🤖 DaViT

Checkout the newest Chainlit & Mistral AI cookbook! Thanks Chainlit for contributing to our cookbook 🙏

RouteLLM Hands-on Tutorial - Anyscale lmsys.org 💡 Cost-effective LLM routing 🌐 Performance nearly GPT-4o 🔧 Integrate with Python App ⚙️ Integrate ollama Groq Inc 🖥️ User interface Chainlit Subscribe: youtube.com/@MervinPraison

🚀 Exciting update! Introducing UI integration with Chainlit by community contributor Kaushal Solanki. Now visualize MetaGPT in action with ease. Check it out here: github.com/geekan/MetaGPT…

How to Publish @Ollama to the Cloud? 🚀 Deploy Local AI to the Cloud - Gemma 2 🛠️ Using Cloud Run Google Cloud 🔐 Authenticate & Secure Access 🔗 Integrate with App 🎨 Create User Interface Chainlit Sub: youtube.com/@MervinPraison @googlecloudtech Google for Developers @google

🎉 Introducing Literal AI Prompt and LLM A/B Testing 📈 Gradually roll out new prompts or LLMs in production and compare performance metrics, reducing risk 🚀 Product teams can independently deploy prompt or LLM updates, speeding up iteration and freeing engineering resources

Build your own Reflection Playground with Chainlit, serving Matt Shumer new Reflection-70b model! 🤗 Hugging Face for the weights 🔧 Baseten for inference 🖥️ NVIDIA TensorRT 🌐 Chainlit for app deployment