LLM Frameworks for Application Development

These platforms provide developer-first tooling for building applications with LLMs—including chaining prompts, embedding documents, adding memory, and incorporating tools like web search or calculators. Ideal for building agents, assistants, or task-specific workflows, they offer modular components and compatibility with OpenAI, Hugging Face, Claude, and custom models. Many include RAG (retrieval augmented generation), streaming, observability, and fallback logic. These frameworks accelerate development without reinventing LLM interactions from scratch.

Tools:

• LangChain – One of the most popular frameworks for chaining LLMs with tools, memory, and APIs. Ideal for RAG apps, agents, or document Q&A bots.

• LlamaIndex – Designed for integrating data with LLMs via indexing, embedding, and querying. Works well with LangChain and supports local and remote retrieval.

• OpenPipe – Focuses on fine-tuning and serving LLMs with evaluation and telemetry built-in, ideal for tracking and iterating prompt strategies.

• UseAnything – Allows developers to connect and orchestrate AI agents or apps that use models from multiple providers like OpenAI, Anthropic, or local LLMs.