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MCP: Fetch — deterministic MCP env with single fetch tool #540
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I screwed up the commit format, sorry. if you want me to close and create another pull request with the proper format i can, but all of the appropriate things have been done. The new and old test suite pass, I reviewed the code (i can remove the extra bits but they seemed helpful). Let me know what you want me to do formatting issue wont happen again, I'm new at this. |
ronaldnetawat
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Nov 13, 2025
* verifiers integration v0.0 * verifiers integration v0.0 * training finishes on reversetext * reverse_text trains 0.13 -> 0.70 * pin git branch in pyproject * removed ac in config * remove DataConfig * removed print debug * configurable masks * rm dataconfig instance * pinned vf commit, removed extra deps * registry cleanup, reworked gsm8k, removed default env * bumped verifiers commit, fixed training divergence vs refactor branch * vf simple-math * simple-math edits * debug * simple_math train matching reference * rename math tasks, port to verifiers * Update configs * Fix imports * Add back envs that were accidentically deleted during rebase * Fix sampling.n missing and unused vars * Remove redundant log * Update README with new task names * Fix hendrycks math config path in README * Update W&B project names * Fix wrong config key * Add missing import * Fix sampling.n not defined * Fix missing config key * Do not tokenize in eval * Fix typos * Add 1B and 7B hendryck's and intellect math * Remove comment * fix tests and configs (PrimeIntellect-ai#548) * add tests orch * fix configs * fix configs * fix tests * fix pydantic ofnig * fix tetstp * Dispatch subconfigs via tmp toml file * Add correct GPU placement for int math run * More consistent var names * Set project and model also in orchestrator * Update readme (PrimeIntellect-ai#550) * fix readme * fix scripts * Parse single-turn prompt and completions tokens/ logprobs from vLLM directly via mock process_env_results function * Update verifiers rev * Fix style * Do not filter if field is missing --------- Co-authored-by: Mika Senghaas <[email protected]> Co-authored-by: samsja <[email protected]>
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Summary:
environments/mcp_fetch/, an MCPEnv-based environment exposing thefetchMCP tool.large payloads, hash/truncation checks, pointer/workflow chains, and rubric-graded summaries.
ANSWER: <value>; host allow-list, timeouts, and max-bytes caps enforce safety.Design:
FetchEnv(MCPEnv)wiresload_environment(...), dataset builder, rubric, and simulator lifecycle management.fetchtool schema: inputs (url,method,headers,params,timeout_s,max_bytes); outputs (status,headers,body_text/body_json,hash,final_url,content_type,bytes,truncated, etc.). Host allow-list defaults to127.0.0.1:<fixture_port>withallow_onlineoverrides.Data:
tasks/qa.jsonlhas 84 tasks (≥20 enforced) spanning planner/workflow combos, pointer lookups, ledger math, headerchallenges, query summaries, truncation/hash probes, etc.
fixtures/html|json|text/*) plus helper scripts keep runs deterministic.Evaluation:
uv run pytest tests/environments/test_mcp_fetch.py -q
uv run ruff check environments/mcp_fetch
tasks/ judge_rubrics.yaml.Difficulty calibration:
Notes:
.gitignoreblocks nested.venv/directories; committed envs were removed.Run gh pr create --title "MCP: Fetch — deterministic MCP env with single fetch tool" --body-file --base
main --head aibozo:main --repo PrimeIntellect-ai/prime-environments once authenticated, or paste the text into the compare
page noted above.