Chat-Based Mail Agent with Vector Retrieval
Chat-driven AI agent that retrieves context from a vector database and can compose and send emails based on stored mail-related data.
This workflow exposes an AI agent through a chat interface and combines conversational input with vector-based retrieval. Incoming chat messages are processed by the agent, which can query a Pinecone-backed vector store containing embedded mail-related content.
User queries are embedded and matched against stored vectors, allowing the agent to retrieve relevant context before generating a response. The retrieved information is incorporated into the agent’s reasoning step, providing grounded responses rather than relying solely on the chat model.
Depending on the interaction, the agent can use an email-sending tool to compose and send messages. Chat handling, retrieval, and tool execution are kept clearly separated, making the workflow easy to follow and adjust.
The setup is designed to support experimentation with retrieval-based email assistants while keeping the overall structure explicit and controlled.
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