[checkpoint] Restore conversational tool-use simulation trajectories
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- Dominant language
- Python
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Description
Parent
Child of #3219 and #3024.
Problem and state owner
resources_servers/conversational_tool_use_simulation/app.py owns the evolving conversation, current actor, pending tool calls, artifacts, failures, terminal state, and judge results in ConversationSessionState.
Proposed adapter
Version and serialize the complete logical trajectory, including phase/actor and pending-call disposition; do not re-run simulator generations already represented in the snapshot.
Implement explicit checkpoint opt-in, route classification, export/restore/retire hooks, execution-to-session binding, revision reporting, atomic replacement under attempt N+1, and stale-attempt fencing.
Acceptance criteria
- Restore after user, assistant, and pending-tool boundaries selects the exact next actor and never repeats a committed simulator/model operation.
- Checkpoint after multiple mutations, replace the server process, restore, and compare the next operation with an uninterrupted execution.
- Corrupt or incomplete bulk state activates no sessions.
- Attempt N cannot mutate or retire restored attempt N+1.
- Terminal cleanup is idempotent and releases restored state exactly once.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with resources_servers/conversational_tool_use_simulation/app.py and inspect ConversationSessionState and the existing conversation execution flow. Trace how actors, pending tool calls, artifacts, failures, terminal state, and judge results are mutated; done means the acceptance scenarios pass, including exact next-actor recovery, corrupt-state rejection, stale-attempt fencing, and idempotent cleanup.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100