Building an Operational Knowledge Base
Purpose
[stub: building-an-operational-knowledge-base]
Metadata
| Author | Amit Singh |
| Scope | agentic-ai-projects-and-mastery |
Local graph
Related notes
7.1 Connecting Agents to Grafana
Wiring an agent's tool layer to Grafana's HTTP API and Prometheus datasource — authentication, the metrics query surface, and the error handling an agent needs when a query fails mid-investigation.
3. Build an Agent with Memory
Hand-rolling short-term and long-term memory for an agent — SQLite-backed storage for conversation history and investigation history across sessions.
4.2 Retrieval-Augmented Generation (RAG)
Why RAG exists, document processing and chunking strategy, embeddings, vector database choice, and the retrieval pipeline that feeds relevant context into an agent's prompt.
1.1 Setting Up the Development Environment
Python project setup, virtual environments, and installing the OpenAI SDK, LangChain, and LangGraph so the rest of the book's code samples run without friction.