Feature: Persistent cross-project memory via Dakera — agents recall prior related work

ChatDev 2.0 is an excellent multi-agent platform, but agents re-derive the same architectural decisions from scratch on every new task. This proposes Dakera (https://dakera.ai) as a persistent memory layer so agents can recall patterns from prior related projects.

Problem: When users give ChatDev similar tasks repeatedly, agents re-derive the same architectural decisions every time. A PM agent doesn't remember that last month's REST API project used FastAPI; an engineer doesn't recall the testing patterns used in a similar project.

Proposed Integration: At ChatChain start, recall(task_description) retrieves memories from similar prior projects. At ChatChain end, store_memory(project_summary) persists key decisions.

In chat_chain.py:

• Before chain execution: inject recalled memories into initial system context
• After chain execution: store a summary of decisions made

Setup: docker run -d -p 3300:3300 -e DAKERA_API_KEY=demo ghcr.io/dakera-ai/dakera:latest / pip install dakera

Why Dakera fits ChatDev's philosophy: Both are fully self-hosted. Dakera's decay weighting means more recent successful project patterns surface preferentially — exactly what a simulated software company would want.

Happy to open a PR.