Add local Workshop trajectory evals - #361
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Posted 1 actionable inline finding. |
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@AshishKumar4 Bonk workflow failed. Check the logs for details. View workflow run · To retry, trigger Bonk again. |
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LGTM! |
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LGTM! |
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LGTM! |
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Posted 2 actionable inline findings. |
| CF_AI_GATEWAY_PROVIDERS: "cloudflare", | ||
| ...(access.apiToken === undefined ? {} : { CF_AI_GATEWAY_API_TOKEN: access.apiToken }), | ||
| }; | ||
| if (access.apiToken === undefined) { |
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To be honest this should probably also check for CF_AI_GATEWAY_USE_BINDING=false / not existing rather than just empty api token
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tbh my agent actually proposed that but why would we want that though? feels redundant state?
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Because we use this elsewhere in the repo, and what if you have an API token already in env vars but you want to opt out?
This PR adds
pnpm evalson top ofWorkshopAgentSession. An eval defines one or more prompts and deterministic checks against the Gadget the agent created. The runner starts an isolated Workshop under local workerd, runs each model and trial, calls the generated Gadget through its RPC API, and cleans up the workspace afterward.The report shows whether the task passed, which checks failed, and the evidence returned by each check. It also records the canonical conversation, timings, model turns, tool calls, tool errors, final-step tokens, observed chat cost, model, trial, Git commit, and prompt hash.
The first eval asks the agent to create a Project Doc. Only model inference leaves the machine. This PR does not add a production target, Braintrust, or an LLM quality judge.
Wall time: 0.45 seconds
Wall time: 2.19 seconds
Wall time: 0.48 seconds