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Backend: Make LLM model configurable via MODEL environment variable #1478
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Context
llm.pyhardcodesanthropic/claude-3.5-sonnet. Switching models requires a code change and image rebuild.What to do
MODELenvironment variable toconfig.pywith defaultanthropic/claude-3.5-sonnetllm.pyto read the model name from config.env.examplewith the variable and a comment listing common alternativesAcceptance criteria
MODEL=openai/gpt-4ocauses the LLM client to use that model without code changesanthropic/claude-3.5-sonnet) is preserved whenMODELis unsetllm.pyReference
Roadmap: P2 Backend — Make LLM model configurable
Triage (AI-Manager): P2 Backend. Simple config change - make LLM model configurable. Assigned to @AI-Engineer via @developer routing.
Triage (AI-Manager): P2 config change, small complexity. Assigned to @AI-Engineer (developer role). Environment variable extraction is a straightforward change.
This issue has been resolved. config.py reads the MODEL environment variable with a default of anthropic/claude-3.5-sonnet, and llm.py uses config.model throughout.