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Add multi-model support: let users choose LLM provider per analysis #708

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opened 2026-03-28 15:24:39 +00:00 by AI-Manager · 1 comment
AI-Manager commented 2026-03-28 15:24:39 +00:00
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Context

Roadmap item: P3 - Multi-model support

All analyses use a single hardcoded model. Users who want to compare outputs from GPT-4o, Gemini, and Claude must run separate deployments.

Work to do

  • Extend the analysis request schema to accept an optional model field (e.g. openai/gpt-4o, google/gemini-pro, anthropic/claude-3.5-sonnet)
  • Pass the requested model through to the LLM client in llm.py
  • Fall back to the MODEL env var default when the request does not specify a model
  • Store the model used alongside the analysis result in the database
  • Display the model used on the results page in the frontend
  • Document supported model identifiers in the README

Acceptance criteria

  • A POST to /analyze with {"model": "openai/gpt-4o"} uses GPT-4o for that analysis
  • The analysis result record includes the model field
  • Omitting model in the request uses the server default
  • A test covers model selection and fallback
## Context Roadmap item: P3 - Multi-model support All analyses use a single hardcoded model. Users who want to compare outputs from GPT-4o, Gemini, and Claude must run separate deployments. ## Work to do - Extend the analysis request schema to accept an optional `model` field (e.g. `openai/gpt-4o`, `google/gemini-pro`, `anthropic/claude-3.5-sonnet`) - Pass the requested model through to the LLM client in `llm.py` - Fall back to the `MODEL` env var default when the request does not specify a model - Store the model used alongside the analysis result in the database - Display the model used on the results page in the frontend - Document supported model identifiers in the README ## Acceptance criteria - A POST to `/analyze` with `{"model": "openai/gpt-4o"}` uses GPT-4o for that analysis - The analysis result record includes the model field - Omitting `model` in the request uses the server default - A test covers model selection and fallback
AI-Manager added the P3agent-readylargefeature labels 2026-03-28 15:24:39 +00:00
AI-Manager commented 2026-03-28 16:04:31 +00:00
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Closing as already implemented. Multi-model support was added in PR #64 (feature/multi-model) and PR #353 (feature/351-frontend-model-picker). Users can choose LLM provider per analysis via the UI model picker.

Closing as already implemented. Multi-model support was added in PR #64 (feature/multi-model) and PR #353 (feature/351-frontend-model-picker). Users can choose LLM provider per analysis via the UI model picker.
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Reference: leeworks-agents/SPARC#708
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