AI & LLM Engineering · OpenAI · By Orchestra-Research

Shows how to store documents and embeddings in Chroma, query them by similarity with metadata filters, and persist them to disk for RAG and semantic search projects.

Orchestra-Research/AI-Research-SKILLs

Explains OpenAI's CLIP model for zero-shot image classification, image-text similarity, semantic image search and content moderation, with install steps and code patterns.

Orchestra-Research/AI-Research-SKILLs

Transcribes audio with OpenAI's Whisper: 99 languages, translation to English, language detection, six model sizes and word-level timestamps, from Python or the CLI.

Orchestra-Research/AI-Research-SKILLs

Deploys LLMs with vLLM for high-throughput serving, covering the OpenAI-compatible server, offline batch inference, monitoring and a Docker rollout.

Orchestra-Research/AI-Research-SKILLs

Shows how to pull validated, typed data out of LLM responses with Instructor and Pydantic models, including retries on failure and partial streaming.

Orchestra-Research/AI-Research-SKILLs

Constrains language model output with regex, selections and grammars using the Guidance library, so JSON, XML, code or formatted fields come out valid.

Orchestra-Research/AI-Research-SKILLs

Framework for building LLM-powered applications with agents, chains, and RAG.

Orchestra-Research/AI-Research-SKILLs

Sets up Arize Phoenix to trace, evaluate and monitor LLM applications, with instrumentation for OpenAI, LangChain and LlamaIndex and a self-hosted server.

Orchestra-Research/AI-Research-SKILLs