🚀 New @LiteLLM Integration 🚀 Track & log all your LiteLLM calls with @literalai in just 2 lines of code! LiteLLM allows you to interact with 100+ LLMs (@OpenAI, @AnthropicAI, @MistralAI, etc.) seamlessly using a consistent OpenAI-compatible format, either use their python

Build your own Reflection Playground with @chainlit_io, serving @mattshumer_ new Reflection-70b model! 🤗 @huggingface for the weights 🔧 @basetenco for inference 🖥️ @nvidia TensorRT 🌐 @chainlit_io for app deployment

🎉 Introducing @literalai 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

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. 🧵

Build a Blazing-Fast RAG Chatbot with Llama3 on @GroqInc, @chainlit_io, and @llama_index ⚡️ 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

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

Great example by @HoloMarkeD on how GenAI can improve learning with personalized lessons tailored to your abilities and experiences. Delivered via an interactive user interface using @chainlit_io @LangChainAI @AnthropicAI 🔥

Announcing Chainlit 🔗💡- Build & share Python LLM apps in minutes⚡️ Chainlit is an open-source 🐍 Python package that lets you create ChatGPT-like UIs on top of your existing code effortlessly! `pip install chainlit` https://t.co/4V2xkTH3As 🧵👇