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feat(config): Implement asymmetric model configuration for Orchestrator and Workers

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Yunxiao Xu
2026-02-23 14:37:15 -08:00
parent 9b97140fff
commit 11c14fb8a8
3 changed files with 4 additions and 2 deletions
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2
backend/src/ea_chatbot/config.py
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@@ -52,6 +52,8 @@ class Settings(BaseSettings):
coder_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0)) coder_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0))
summarizer_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0)) summarizer_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0))
researcher_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0)) researcher_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0))
reflector_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0))
synthesizer_llm: LLMConfig = Field(default_factory=lambda: LLMConfig(model="gpt-5-mini", temperature=0.0))
# Allow nested env vars like QUERY_ANALYZER_LLM__MODEL # Allow nested env vars like QUERY_ANALYZER_LLM__MODEL
model_config = SettingsConfigDict(env_nested_delimiter='__', env_prefix='') model_config = SettingsConfigDict(env_nested_delimiter='__', env_prefix='')

2
backend/src/ea_chatbot/graph/nodes/reflector.py
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@@ -22,7 +22,7 @@ def reflector_node(state: AgentState) -> dict:
logger.info(f"Evaluating worker output for task: {task_desc[:50]}...") logger.info(f"Evaluating worker output for task: {task_desc[:50]}...")
llm = get_llm_model( llm = get_llm_model(
settings.planner_llm, # Using planner model for evaluation settings.reflector_llm,
callbacks=[LangChainLoggingHandler(logger=logger)] callbacks=[LangChainLoggingHandler(logger=logger)]
) )
structured_llm = llm.with_structured_output(ReflectorResponse) structured_llm = llm.with_structured_output(ReflectorResponse)

2
backend/src/ea_chatbot/graph/nodes/synthesizer.py
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@@ -19,7 +19,7 @@ def synthesizer_node(state: AgentState) -> dict:
logger.info("Synthesizing final answer from worker results...") logger.info("Synthesizing final answer from worker results...")
llm = get_llm_model( llm = get_llm_model(
settings.summarizer_llm, settings.synthesizer_llm,
callbacks=[LangChainLoggingHandler(logger=logger)] callbacks=[LangChainLoggingHandler(logger=logger)]
) )