Two goals: 1. Centralize system_instruction vs context system message resolution into the LLM adapters. This eliminates duplication between in-pipeline and out-of-band (run_inference) code paths across ~16 locations in service llm.py files. 2. Add support for "developer" role messages in conversation context, which is facilitated by the above centralization. Shared helpers on BaseLLMAdapter: - _extract_initial_system_or_developer: extracts/converts messages[0] based on role and whether system_instruction is provided - _resolve_system_instruction: warns on conflicts between system_instruction and context system messages, returns the effective instruction Developer message handling (new): - Non-OpenAI adapters: an initial "developer" message is promoted to the system instruction when no system_instruction is provided; otherwise it is converted to "user". Subsequent "developer" messages are always converted to "user". No conflict warning is emitted for developer messages (unlike "system" messages). - OpenAI adapter: "developer" messages pass through in conversation history without triggering conflict warnings. - OpenAI Responses adapter: "developer" messages are kept as "developer" role (same as "system", which is also converted to "developer" for the Responses API). Other behavior changes: - Gemini: "initial" system message detection now checks messages[0] only (previously searched anywhere in the list) - Bedrock: a lone system message is now converted to "user" instead of being extracted to an empty message list (matches existing Anthropic behavior)
55 KiB
55 KiB