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43 lines
1.8 KiB
YAML
43 lines
1.8 KiB
YAML
# LiteLLM proxy config for running the workflow benchmark on a FREE model.
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#
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# The proxy exposes an Anthropic-compatible /v1/messages endpoint that
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# headless Claude Code can use via ANTHROPIC_BASE_URL, routing to a model
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# that costs nothing:
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#
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# export LITELLM_MASTER_KEY="$(openssl rand -hex 16)"
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# uv run --with 'litellm[proxy]' litellm --config workflow_bench/free-model.litellm.yaml --port 4000
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#
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# uv run python -m workflow_bench.runner \
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# --tasks workflow_bench/tasks.scenarios.yaml \
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# --base-url http://localhost:4000 --anthropic-api-key "$LITELLM_MASTER_KEY" \
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# --model free-coder
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#
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# Keep the proxy on loopback (litellm's default host). Anyone who can reach
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# the port with the master key can spend the configured backend's quota.
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#
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# Pick ONE of the model routes below (or add your own — anything litellm
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# supports works):
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model_list:
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# Hosted free tier: needs only a free OpenRouter account key in
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# OPENROUTER_API_KEY (eval/.env). ":free" variants are rate-limited
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# (~50 requests/day on a fresh account, 1000/day with a $10 balance) —
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# fine for a few benchmark tasks, not for large sweeps.
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- model_name: free-coder
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litellm_params:
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model: openrouter/qwen/qwen3-coder:free
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api_key: os.environ/OPENROUTER_API_KEY
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# Fully local and free: any Ollama model, no API key, no rate limits.
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# Needs `ollama serve` running and the model pulled
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# (`ollama pull qwen2.5-coder:14b`). Prefer a coding-tuned model that
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# handles tool calls; small models follow skills less reliably.
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- model_name: local-coder
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litellm_params:
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model: ollama_chat/qwen2.5-coder:14b
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api_base: http://localhost:11434
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general_settings:
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# No static default — export LITELLM_MASTER_KEY before starting the proxy
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# and pass the same value as --anthropic-api-key (see header).
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master_key: os.environ/LITELLM_MASTER_KEY
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