Add POST /v1/runs to start async agent runs and GET /v1/runs/{run_id}/events
for SSE streaming of typed lifecycle events (tool.started, tool.completed,
message.delta, reasoning.available, run.completed, run.failed).
Changes the internal tool_progress_callback signature from positional
(tool_name, preview, args) to event-type-first
(event_type, tool_name, preview, args, **kwargs). Existing consumers
filter on event_type and remain backward-compatible.
Adds concurrency limit (_MAX_CONCURRENT_RUNS=10) and orphaned run sweep.
Fixes logic inversion in cli.py _on_tool_progress where the original PR
would have displayed internal tools instead of non-internal ones.
Co-authored-by: Mibayy <mibayy@users.noreply.github.com>
The gateway created a fresh AIAgent per message, rebuilding the system
prompt (including memory, skills, context files) every turn. This broke
prompt prefix caching — providers like Anthropic charge ~10x more for
uncached prefixes.
Now caches AIAgent instances per session_key with a config signature.
The cached agent is reused across messages in the same session,
preserving the frozen system prompt and tool schemas. Cache is
invalidated when:
- Config changes (model, provider, toolsets, reasoning, ephemeral
prompt) — detected via signature mismatch
- /new, /reset, /clear — explicit session reset
- /model — global model change clears all cached agents
- /reasoning — global reasoning change clears all cached agents
Per-message state (callbacks, stream consumers, progress queues) is
set on the agent instance before each run_conversation() call.
This matches CLI behavior where a single AIAgent lives across all turns
in a session, with _cached_system_prompt built once and reused.