Build a Local AI Agent with Python, Ollama, LangChain and SingleStore

You've built a local Retrieval-Augmented Generation (RAG) AI agent using Python, leveraging open-source LLMs and embeddings via Ollama, orchestration with LangChain, and vector storage with SingleStore. The agent can be used to answer questions about pizza reviews, providing insights into customer opinions on various aspects such as the crust, vegetarian options, and pricing. You can experiment with different LLMs or embedding models, other datasets, and custom prompt templates to further enhance the agent's capabilities.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.