potpie-graph

Graph-based project memory management allows AI agents to access and manipulate a project's codebase, structure, decisions, and history. It performs semantic operations like reading, writing, and validating the project memory graph to track changes and infrastructure plans.

Yes, performing semantic operations on a project memory graph requires the Potpie CLI and related Python libraries. These dependencies facilitate graph operations and data manipulation for accessing the project's codebase and history.

Graph-based project memory is a structured representation of a project's code, structure, decisions, and history. It helps AI agents understand code structure by enabling semantic operations to find bug patterns, read code scope preferences, and commit infrastructure plans.

To read the timeline of changes for the last 7 days, use the Potpie CLI to perform semantic operations on the project memory graph. This allows AI agents to access historical data and track recent codebase modifications effectively.

Yes, AI agents can use graph-based project memory to find all occurrences of a bug pattern in the project's history. By performing semantic operations on the memory graph, the agent queries historical decisions and code changes to identify patterns.

Graph-based project memory management requires YAML configuration and Python dependencies, meaning it needs specific environment setup. It is limited to semantic operations defined within the Potpie CLI framework for accessing codebase structure and history.