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Replace the blocking Chat() call in process() with
chatStreamWithFallback: ChatStream first, accumulate chunks, fall back
to non-stream Chat on connect failure or empty-stream failure.
Why: the non-streaming path blocked for the ENTIRE LLM generation (up
to the 180s HTTP timeout). Reasoning models thinking 60-120s plus AUTO
chain failover regularly exceeded it -> context canceled -> full turn
wasted. With streaming the first chunk arrives in ~1-3s and any
flowing token keeps the connection alive; total generation time is no
longer bounded by an overall timeout.
Compatibility (external behavior unchanged):
- process() signature/return values unchanged
- Aggregated events (EventReasoning / EventAgentLLMChain) still fire
once per turn with full text after stream completion - existing
plugin subscribers see identical payloads as before
- New incremental events EventReasoningDelta / EventContentDelta are
additive; old subscribers ignore unknown event types
- Tool execution loop, memory pipeline, stage pipeline untouched
Streaming details:
- Tool call fragments accumulated per OpenAI streaming convention:
id/name arrive on the first fragment, arguments as raw JSON string
shards across fragments; merged and parsed once at stream end
- normalizeStreamToolCalls keeps nameless argument shards (the
non-stream normalizer drops them); ToolCall gains RawArguments to
carry shard text
- Interrupt mid-stream returns partial content instead of discarding
the whole generation
Verified end-to-end against llmsproxy: plain chat streams correctly;
curl confirms tool-call shard wire format ({" + command" + :"date"}
-> {"command":"date"}); unit tests cover shard merging and
content/reasoning accumulation.