Block a user
78459c974e
tau2 via OFFICIAL engine: self-running env plugin (run_task hook + needs_adapter generic dispatch, no name hardcoding), deep generate() patch, official ToolCall shape, data plugin keeps verbatim Task json, official reward scoring; checkpoint plugin (per-sample resume) + summary csv with time/categories
85dd193bcf
Execution-bench fixes verified on real model: BCB standalone-module + unittest semantics (100%), LCB base64+zlib+pickle private cases + line-normalized runner (100%), code_any def-start heuristic, general_fc should-call-tool semantics (80%), bfcl real-model 51 samples/17 categories (45.1%, multi_turn needs stateful env - known)
1da665fec4
Add --limit-per-task (per-subset cap, evalscope --limit semantics; composable with --limit as intersection); execution-bench parity verified: official human-eval core 5/5 == our docker sandbox on same completions
89e721414f
Simplify install: light deps (datasets/pyarrow/sympy/pylatexenc/numpy/scipy) are DEFAULT; single [bfcl] extra for the heavy official checker
99c9df5412
Unify on-demand install hints to extras names ([all]/[bfcl]); native bfcl fallback carries upgrade hint
32b7276142
Extras: add [all] (conflict-free bundle) and [bfcl] (official checker, heavy deps isolated)
d830e08923
Drop logprob scoring path entirely; MCQ = strict-letter generation (evalscope parity 'ANSWER: X'), few-shot defaults stay; fix output.py duplication
a8d3400ed5
Paper-faithful eval: P1 logprob scoring (completions_echo + chat_first_token fallback, sglang top_logprobs parser), few_shot_num dataset defaults (mmlu5/cmmlu5/mmlu_pro5/gsm8k4/math4/drop3), official BBH 3-shot CoT vendored, strict_letter default prompt (evalscope parity), official simpleqa grader prompt
a32d902e94
Comparison-driven fixes: MCQ choices in prompt + letter contract, Answer: suffix for QA, markdown answer cleaning, trivia_qa answer_phrase priority, DROP gold-as-alternatives (OR) official semantics, retry on 5xx, numpy/scipy compat
3d16ab9103
Add SWE-bench single-turn harness (patch apply + FAIL_TO_PASS in official sweb image, sh entries in docker sandbox), bigcodebench official all-libs image, docker default for humaneval/LCB, input truncation (max_input_chars) + context assembly (passage/context), API retry with backoff, judge thread-safe bridge, parquet blob integrity check, summary.csv in out-dir, sandbox prefetch CLI
b2e7133b20
Add sandbox layer (docker exec hard-isolation + serve envs, refcounted acquire/release, atexit teardown, bind-mount sharing) and agent evaluation driver (message pump drive(), Trajectory, bfcl_mock env with official call-sequence scoring, mock:fc oracle); Deployer delegates to sandbox.serve_env; code_any extractor fixes indentation-stripping; CLI --env
6b3bb330c7
Add model layer: async ModelAdapter (openai_compatible + mock) returning structured ModelOutput(text,tool_calls,usage), Deployer registry (vllm/sglang docker-pinned via models.yaml, external), async run_eval generate->score, CLI --model, agent-ready SampleResult.trajectory/env_state, tests
4a15f80897
Add evaluation layer + visualization: extract/score/aggregate plugins, 28 recipes, official-aligned scorers (PRM800K math, DROP Hungarian EM/F1, SimpleQA A/B/C judge), report artifacts, console renderers, CLI eval/viz, regression tests
414a89216c
Unify cache root override: loader.get/set_cache_root as single source, fixes --cache-dir not relocating .raw blobs
f8cd15fea1
EvalHarness data layer: 28 dataset plugins, lazy materialize cache (raw/ + samples.jsonl + meta.json), ModelScope native loader, CLI list/fetch/unload/stats/show
