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"task_ref": "sha256:6aab6511a5344ce87698293bb1ce4cc51d9a45f1ad9f0c075d2a83197b36727d", + "trial": "merge-diff-arc-agi-task__ZkfGvPf", + "reward": 1.0, + "baseline_reward": 1.0, + "same_task_ref": true, + "exception_type": null, + "terminal_outcome": "completed", + "terminal_error_type": null, + "failure_category": "passed", + "phase_seconds": { + "environment_setup": 1.008, + "agent_setup": 45.998, + "agent_execution": 327.054, + "verifier": 16.319 + }, + "model_calls_started": 17, + "model_calls_completed": 17, + "model_http_request_count": 17, + "tool_calls": 19, + "pre_connection_timeout_count": 0, + "generation_request_count": 17, + "max_reply_output_tokens": 5518, + "last_stop_reason": "end_turn", + "usage_complete": true, + "cost_complete": true, + "known_completed_reply_tokens": { + "total_prompt_tokens": 247339, + "total_cached_tokens": 219904, + "total_completion_tokens": 14890 + }, + "supplemental_billing_receipts": [], + "final_metrics": { + "total_steps": 18, + "total_prompt_tokens": 247339, + "total_completion_tokens": 14890, + "total_cached_tokens": 219904, + "total_cost_usd": 0.004524624 + }, + "billing_known_cost_usd": 0.004524624, + "billing_total_cost_usd": 0.004524624, + "billing_cost_complete": true, + "argument_error_count": 0, + "argument_error_tools": {}, + "malformed_json_rejections": 0, + "argument_errors_followed_by_model_call": 0, + "argument_errors_followed_by_successful_same_tool": 0, + "clean_pass": true, + "atif_valid": true, + "native_journal_projection_matches": true, + "journal_truncated_entries": 0, + "verifier_timed_out": false, + "all_requests_use_65536": true, + "complete_model_streams": 17, + "local_trajectory": "jobs/tb21-tool-input-recovery-pilot20-20260914/merge-diff-arc-agi-task__ZkfGvPf/agent/trajectory.json", + "trajectory_source": "native", + "runtime_packages": { + "nanopycodeagent": "0.8.1.dev25+g27a950315", + "anthropic": "1.5.0", + "httpx": "0.28.1", + "httpx2": "2.12.0", + "pydantic": "2.13.5" + }, + "execution_control": { + "execution_limit_seconds": 3600, + "finalization_grace_seconds": 120, + "deadline_reached": false, + "forced_kill": false, + "exit_code": 0, + "elapsed_seconds": 326.532, + "started_at": "2026-09-14T17:52:33.416588+00:00", + "finished_at": "2026-09-14T17:57:59.948543+00:00" + }, + "official_test_summary": { + "tests": 5, + "passed": 5, + "failed": 0, + "skipped": 0, + "pending": 0, + "other": 0, + "start": 1789408696.8872302, + "stop": 1789408696.9054453 + } + } + ] + } + ], + "comparisons": { + "original_8192_pilot": { + "attempts": 20, + "passed": 8, + "passed_without_harbor_exception": 7 + }, + "previous_65536_initial18": { + "attempts": 18, + "passed": 5, + "scored_zero": 8, + "unscored": 5 + }, + "fresh20": { + "planned": 20, + "finished": 20, + "passed": 10, + "clean_passed": 9, + "failed": 9, + "unscored": 1, + "argument_errors": 0, + "argument_errors_followed_by_model_call": 0, + "argument_errors_followed_by_successful_same_tool": 0, + "model_calls_started": 491, + "model_calls_completed": 487 + }, + "fresh_matching18": { + "attempts": 18, + "passed": 8, + "clean_passed": 7, + "scored_zero": 9, + "unscored": 1 + }, + "fresh_vs_8192": { + "reward_gains": [ + "terminal-bench/write-compressor", + "terminal-bench/regex-log", + "terminal-bench/circuit-fibsqrt" + ], + "reward_regressions": [ + "terminal-bench/llm-inference-batching-scheduler" + ], + "previous_passes_now_unscored": [] + } + }, + "billing_known_lower_bound_usd": 0.705181383, + "billing_total_usd": 0.705181383 +} diff --git a/docs/changelogs/0.8.x.md b/docs/changelogs/0.8.x.md index 51b034b..e3fdea8 100644 --- a/docs/changelogs/0.8.x.md +++ b/docs/changelogs/0.8.x.md @@ -11,6 +11,10 @@ All notable changes in the **0.8.x** release series are documented here. trajectories while retaining compatibility with older journals. ### Fixed +- Return correctable tool errors for missing or incorrectly typed arguments and + unknown tool names, allowing the model to retry within the existing turn + budget. Keep previews safe, reject incomplete argument JSON yielded by the + SDK, and preserve rejected inputs and error results in Journals and ATIF. - Stop explicitly when a model response reaches `max_tokens`, reporting `response_truncated` in Event Journals and ATIF trajectories instead of task completion. Preserve partial output, usage, and cost accounting; skip tools diff --git a/docs/dev_notes/en/0.8.x.md b/docs/dev_notes/en/0.8.x.md index 716673a..5363167 100644 --- a/docs/dev_notes/en/0.8.x.md +++ b/docs/dev_notes/en/0.8.x.md @@ -438,7 +438,7 @@ This pilot costs about 0.12 USD. Multiplying mechanically by 89/20 gives about 0 ### Fixing problems found in batch Terminal-Bench runs -The following notes explain the problems, implementations, and proposed fixes. Truncation handling and configurable model generation budgets are implemented. The remaining sections describe problems and proposed work whose code has not yet been implemented. +The following notes explain the problems, implementations, and proposed fixes. Truncation handling, configurable model generation budgets, and recovery from missing tool arguments are implemented. The remaining sections describe problems and proposed work whose code has not yet been implemented. #### Truncation handling @@ -765,6 +765,157 @@ Missing required argument: path. Provide the file path and retry. The model can then supply the missing value in a later turn and continue within the remaining budget. Both display and execution must tolerate incomplete input; otherwise the crash is merely deferred to the next stage. The principle is to return model-correctable argument errors as tool results so the task can continue, rather than ending the entire task. Other tools should follow the same principle. +**Implementation on 2026-09-13: tool argument validation and error feedback.** The implementation commit is `27a9503`. Before preview or execution, `read`, `write`, `edit`, and `bash` share validation of required fields, the string/integer/boolean types declared in their schemas, and NUL characters in paths and commands. Unknown tool names also return errors. Arguments are not coerced: for example, `replace_all="false"` is not treated as true, and booleans cannot substitute for read line numbers. Extra fields permitted by the schema, empty file contents, and empty replacement text remain supported. + +Invalid calls do not reach tool implementations. Instead, they receive a `tool_result` matching the original call ID, with `is_error=True` and correction guidance. The preview indicates that the call did not execute. Other valid calls in the same reply still run in order, and recovery does not repeat successful tools. The next model reply retains the task, history, and remaining turns, without a separate retry budget. Unexpected programming exceptions inside tools still propagate, avoiding misclassification of every `KeyError` as a model input error. + +The agent also checks the argument JSON actually received in the response stream. The SDK parses partial JSON during streaming; a dictionary containing required fields does not justify executing a command if its closing brace is missing. When a stream finishes with `tool_use` but incomplete argument JSON, the call is rejected with a request for a complete object. Journals and ATIF retain the error, raw argument JSON, and SDK-parsed input. Non-object inputs are saved separately as `raw_input` while preserving existing object field constraints. Follow-up requests use sendable objects instead of replaying partial JSON. Existing `max_tokens` handling remains unchanged: all tools in a truncated reply are skipped and the run ends as `response_truncated`. Automatic continuation is not implemented here. + +**Automated validation and independent review.** All 276 core tests pass with locked dependencies. The same 276 tests also pass in a temporary environment pinned to the preceding experiment's reported Anthropic SDK 1.5.0, HTTPX 0.28.1, HTTPX2 2.12.0, and Pydantic 2.13.5. All 22 Harbor adapter tests pass. New coverage checks that invalid arguments have no side effects, incomplete JSON through the real SDK, corrected calls after error feedback, valid sibling calls, interactive/headless behavior, turn limits, and trajectory evidence. An independent reviewer inspected the complete change in a new Herdr split using the `review-agent` skill and reported **No findings**, additionally verifying mixed-call recovery through the real SDK and Harbor compatibility. + +The four actual failed response streams from circuit, QEMU, scheduler, and DNA were also replayed unchanged through SDK 1.5.0 offline. Each rejected the invalid call, returned an error, and then completed one valid call from a scripted follow-up reply before finishing normally. Tool execution was stubbed and there were no paid model calls. This demonstrates changed handling of identical failed inputs; it does not establish that those four real tasks pass. + +**Known boundary.** Recovery depends on the SDK delivering the response successfully. Some JSON syntax errors, including invalid escapes and trailing commas, raise inside the SDK before recovery can run; independent review confirmed that this limitation also exists on the main branch. Interrupted streams, algorithm errors, exhausted turns, and evaluation environment failures require separate handling. + +**Real-task rerun settings.** The reruns use the same reviewed wheel from `27a9503`, with `deepseek/deepseek-v4-flash-0731` through OpenRouter. Task refs and cached image digests for all original 20 tasks match the 09-06 baseline. Every reply explicitly uses `max_tokens=65536`, with 50 turns per task and at most two simultaneous trials; the project default remains 32768. Agent execution has 3600 seconds, finalization 120 seconds, and the Harbor outer allowance 3780 seconds. Verifiers retain their native task deadlines. Each task runs once per job with no automatic Harbor retries; additional reruns have separate job names and preserve earlier failures. + +In the first targeted5 group on 09-13, QEMU encountered APT 404 errors and DNA exceeded the 1080-second installation limit, both before any model call. PyTorch was paused by the user during installation, and circuit had not started. Subsequent groups increase only the **installation deadline** to 3600 seconds and retry system dependency installation at most three times on HTTP 404. The scheduler agent in that first group had already finished normally before the pause. After resumption, its unchanged artifacts in the preserved container passed all six official tests, yielding reward 1 with **no additional model calls**. This resumed verification is recorded separately from an uninterrupted Harbor trial. + +QEMU installation in the 09-14 targeted4 group still encountered intermittent 404 errors, so a separate retry uses the same 20 packages selected by the original APT index, downloaded from official URLs and checked against their SHA256 hashes and sizes. They enter the cache after `apt-get update`, before the original dependency installation. Preloading them earlier allowed the image's APT cleanup hook to remove them; correcting that order made installation succeed in the original image. Package versions and repositories remain the same. + +In the same targeted4 group, the PyTorch agent finished normally, but the official verifier exceeded its native 900-second deadline downloading Torch/CUDA dependencies, leaving the task unscored. A uv 0.9.5 cache was prepared for a separate retry and the subsequent full20 run, using the official script's unchanged requirements: `pytest==8.4.1`, `torch==2.7.1`, and `pytest-json-ctrf==0.3.5`. After relocation into the original image, all 31 packages installed offline and Torch imported successfully. Preparation ran no task tests. Only `pytorch-model-recovery` receives this cache; its official verification script and 900-second deadline stay unchanged. This changes cache conditions and must be distinguished from the tool argument fix's effect. + +The original 8192 baseline also used another source revision and agent deadlines. The preceding 65536 initial18 group passed five tasks; later supplements and compressor were separate attempts, while `regex-log` had only been rerun at 32768. Comparisons therefore keep the original 20 tasks and the matching 18-task subset separate, without combining different settings into one pass rate. Sampling, routing, cache, and backend state remain uncontrolled. Identical-response offline replays, observed recovery events in real runs, and final task scores are three distinct forms of evidence. + +**Targeted rerun results (2026-09-14).** The table preserves each historical argument failure and its observed rerun result. Installation failures, verifier timeouts, and supplements remain separate; these different conditions are not combined into one formal five-task score. + +| Task | Historical argument crash | Rerun result | Observed argument feedback | +| --- | --- | --- | --- | +| `dna-assembly` | `bash` missing `command`, with an unterminated JSON string | Reward **0**, **0/1** official tests; `max_turns_exhausted` after 50 replies and 3533.7 seconds of agent execution | None | +| `qemu-alpine-ssh` | `bash` missing `command`, with raw JSON `{` | Installation failures retained separately; cached retry reward **1**, **1/1** tests, normal completion after 48 replies | None | +| `llm-inference-batching-scheduler` | `write` missing `content`, with raw JSON `{` | Normal completion after 47 replies before the pause; resumed official verification reward **1**, **6/6** tests, no additional model calls | **One** incomplete `bash` JSON rejection, followed by another model call and a successful `bash` call | +| `pytorch-model-recovery` | The 8192 baseline omitted `edit.path` after timeout | First agent run completed normally but verifier downloads timed out; cached retry reward **1**, **5/5** tests, normal completion after eight replies | None in either run | +| `circuit-fibsqrt` | `bash` missing `command`, with raw JSON `{}` | Reached the 3600-second execution deadline after 49 replies; stopped artifacts passed **3/3** tests with reward **1**; **not a normally completed pass** | None | + +The experimental supervisor interrupted circuit, which ended with `KeyboardInterrupt` and exit 130; Harbor recorded `NonZeroAgentExitCodeError`. Finalization retained a native trajectory without a forced kill, and verification began only after the agent stopped. Both the passing artifact and the exhausted execution budget must therefore remain visible; reward 1 alone does not establish normal completion. + +Scheduler is the only real run in this group that directly demonstrates argument error feedback followed by continued execution and passing verification. Its new error concerns `bash` JSON, rather than the historical `write.content` failure. The other newly sampled attempts produced no argument validation errors, so their passes cannot independently be attributed to this feature. The preceding offline replays provide identical-input evidence for the four historical failed responses. + +Including scheduler, the first PyTorch verifier timeout, and both cached supplements, the group retains **six native ATIF files**. All validate against Harbor, match their full Journal projections, and contain no truncated Journal strings. These six runs account for 222 model replies, 12,183,309 input tokens including 10,021,376 cached tokens, 427,835 output tokens, and **$0.243005564** in model costs, with complete usage and billing. Pure installation failures, model execution that had not started at the pause, and offline replays incurred no model charges. The cached PyTorch retry spent 432.8 seconds installing, 140.0 seconds executing the agent, and 23.2 seconds verifying. This reflects the changed cache preparation; it does not show that agent code accelerated the preceding 900-second verifier download. + +**Full 20-task rerun (2026-09-14–15).** The independent full group finished with +**10/20 passes (50%), nine zeros, and one unscored task**. **Nine tasks completed +normally and passed (45%)**. The original 8192 pilot passed 8/20 (40%), with seven +passing trials without a Harbor exception. Circuit's artifacts passed here, but +cost reconciliation reached the execution deadline, so it is not a normally +completed pass. “No Harbor exception” is also not identical to the new definition, +which requires a native `completed` outcome, no error, and no execution deadline. +[Structured results](../../../benchmarks/harbor/results/tb21-tool-input-recovery-20260914.json) +preserve separate attempts, configuration, billing completeness, and validation evidence. + +| Experiment | Tasks | Reward 1 | Reward 0 | Unscored | +| --- | --- | --- | --- | --- | +| Original 8192 pilot | 20 | 8 | 12 | 0 | +| Previous 65536 initial18 | 18 | 5 | 8 | 5 | +| Fresh matching18 subset | 18 | 8 | 9 | 1 | +| Fresh independent full group | 20 | 10 | 9 | 1 | + +Seven of the matching18 subset's eight passes completed normally. Table values are +rewards. “Outside this group” means the previous initial18 did not include the task, +rather than an unscored attempt. Compressor already passed a separate previous +65536 supplement, while regex-log passed a 32768 supplement; neither belongs in +the old initial18 score. + +| Task | Original 8192 | Previous 65536 initial18 | Fresh 65536 | Fresh result details | +| --- | --- | --- | --- | --- | +| `write-compressor` | 0 | Outside this group | 1 | Normal completion; 3/3 | +| `torch-tensor-parallelism` | 0 | Unscored | 0 | Normal completion; 1/3 | +| `schemelike-metacircular-eval` | 0 | 0 | 0 | Response stream interrupted in request 18 | +| `kv-store-grpc` | 1 | 0 | 1 | Normal completion; 7/7 | +| `pypi-server` | 1 | 1 | 1 | Normal completion; 1/1 | +| `dna-assembly` | 0 | Unscored | 0 | Provider unavailable in request 2 | +| `torch-pipeline-parallelism` | 0 | Unscored | 0 | 50 turns exhausted; 2/3 | +| `qemu-alpine-ssh` | 1 | Unscored | 1 | Normal completion; 1/1 | +| `openssl-selfsigned-cert` | 1 | 1 | 1 | Normal completion; 6/6 | +| `regex-chess` | 0 | 0 | 0 | 50 turns exhausted; 1/4 | +| `log-summary-date-ranges` | 1 | 1 | 1 | Normal completion; 2/2 | +| `model-extraction-relu-logits` | 0 | Unscored | Unscored | Agent completed; verifier exceeded 900 seconds | +| `path-tracing` | 0 | 0 | 0 | Provider unavailable in request 32 | +| `regex-log` | 0 | Outside this group | 1 | Normal completion; 1/1 | +| `caffe-cifar-10` | 0 | 0 | 0 | Normal completion; 2/6 | +| `mteb-leaderboard` | 0 | 0 | 0 | 50 turns exhausted; 0/2 | +| `llm-inference-batching-scheduler` | 1 | 0 | 0 | Response stream interrupted in request 3 | +| `pytorch-model-recovery` | 1 | 1 | 1 | Normal completion; 5/5 | +| `circuit-fibsqrt` | 0 | 0 | 1 | 3/3; cost reconciliation interrupted, trajectory reconstructed | +| `merge-diff-arc-agi-task` | 1 | 1 | 1 | Normal completion; 5/5 | + +Relative to the original pilot, compressor, regex-log, and circuit gained passes, +while scheduler changed from a pass to zero: a net gain of two tasks. Relative to +the previous 65536 initial18, KV-store changed from zero to a pass, QEMU from +unscored to a pass, and circuit from zero to passing artifacts with a finalization +failure. KV-store and QEMU already passed the original 8192 pilot, and compressor +and regex-log passed their earlier budget supplements. These score changes +therefore do not establish an independent benefit from argument validation. + +The fresh full group recorded **no `ToolInputError` events**. The four offline +replays still provide identical-input evidence, while the targeted scheduler +provides observed live error feedback followed by continued execution and passing +verification. The fresh scheduler failed with `RemoteProtocolError` in request +three, after two completed replies. Its targeted success must not replace this +separate failed attempt. + +Four requests did not return complete responses: Scheme and scheduler lost their +response streams; DNA and path-tracing received `provider_unavailable` errors +referring to SIGTERM and a graceful shutdown timeout. These are transport or +upstream availability failures. Pipeline, regex-chess, and MTEB exhausted fifty +turns; tensor and Caffe completed normally without passing all functional tests. +Model extraction completed twenty-seven replies, installed dependencies, and +entered its single pytest test before exceeding the native 900-second verifier +limit. It remains unscored. This was not a dependency download timeout, and its +deadline was not extended to replace the result. + +**Circuit finalization failure.** Reply fifty finished with `end_turn` at +18:46:26.965 UTC, followed by provider cost reconciliation. The supervisor enforced +the 3600-second execution deadline at 18:47:05.171, interrupting reconciliation +before either `run.completed` or `run.failed` had been written. Native ATIF export +raised `AtifProjectionError: Event Journal has no terminal event`. The experiment +wrapper preserved the original Journal and reconstructed a trajectory with an +explicitly marked synthetic terminal event; it does not claim native export. +Official verification began after the agent stopped and passed all three tests. +This cost-finalization control block is unchanged from the implementation commit's +parent and was not modified here. A follow-up needs to ensure that interrupted +billing reconciliation still records a terminal state and exports a trajectory. +A separate `Gate`-object `KeyError` appeared in model-generated program output and +was returned as a tool result; it was not an agent crash from missing tool arguments. + +Late in circuit, three detailed monitoring probes each exceeded twenty-five +seconds. A read-only check found the container still running at about 1.983/2 GiB +of memory, with Docker not reporting an OOM. Detailed in-container probes were +then stopped in favor of host result files and container state. Agent, verifier, +and resource limits stayed unchanged; no orphaned probe was found. The earlier +probes' contribution to memory pressure is unknown, so this monitoring change +remains an experimental limitation. + +**Trajectories and costs.** All twenty ATIF files validate against Harbor: nineteen +are native exports matching their full Journal projections, and one is the +explicit reconstruction above. No Journal strings were truncated. There were +491 model calls started and 487 complete replies. Fully recorded replies account +for **21,991,162 input tokens**, including **18,119,936 cached tokens**, and +**724,013 output tokens**. Native usage for four interrupted responses remains +incomplete; missing values must not be treated as zero. Per-reply output maxima +also cover completed replies only and do not describe an interrupted response's +actual output. QEMU additionally had one pre-connection `ConnectTimeout` followed +by an SDK retry: forty-one model replies and forty-two HTTP attempts. + +All model costs are covered by native records or separate provider receipts. +Supplemental accounting distinguishes completed replies from interrupted requests +and subtracts costs already recorded in the Journal, avoiding double-counting +when a reconstructed trajectory lacks the native terminal event. The full twenty +tasks cost **$0.462175819**. Including targeted attempts, cached supplements, and +the scheduler whose verification resumed after the pause, total experiment model +cost is **$0.705181383**. Complete billing does not imply complete native responses +or usage. + #### Stopping execution on timeout Timeout handling must ensure that the agent inside the container actually stops before verification begins. In this pilot, Harbor had already classified the task as timed out while the agent continued calling the model. diff --git a/docs/dev_notes/zh-CN/0.8.x.md b/docs/dev_notes/zh-CN/0.8.x.md index 15fc5a7..9669e42 100644 --- a/docs/dev_notes/zh-CN/0.8.x.md +++ b/docs/dev_notes/zh-CN/0.8.x.md @@ -508,8 +508,9 @@ API 凭据，原件权限已设为 0600，归档副本已脱敏；原件与脱 ### 修复批量运行 Terminal-Bench 时遇到的问题 -以下记录本轮问题的含义、实现与修复方向。“截断处理”和“增加模型生成预算”已实现； -其余小节仍描述问题与拟议方向，不表示对应代码已修复。 +以下记录本轮问题的含义、实现与修复方向。“截断处理”“增加模型生成预算”和 +“缺失工具参数导致的崩溃”已实现修复；其余小节仍描述问题与拟议方向，不表示 +对应代码已修复。 #### 截断处理 @@ -1099,6 +1100,193 @@ Missing required argument: path. Provide the file path and retry. 是把模型可纠正的参数错误反馈为工具结果，让任务继续，而不是直接结束整个任务； 其他工具也应遵循这一原则。 +**2026-09-13 实现：工具参数校验与错误反馈。** 实现提交为 `27a9503`。 +`read`、`write`、`edit`、`bash` 在预览和执行前共用参数校验，检查必填字段、 +schema 中声明的字符串／整数／布尔类型，以及路径和命令中的 NUL；未知工具名 +也返回错误。参数不做隐式类型转换，例如 `replace_all="false"` 不会被当作真值， +布尔值也不能充当读取行号。schema 允许的额外字段、空文件内容和空替换文本仍可使用。 + +无效调用不进入工具实现，而是返回匹配原调用 ID 的 `tool_result`，设置 +`is_error=True` 并说明如何纠正。预览显示该调用未执行；同轮其他有效调用仍按顺序 +处理，已经成功的工具不会因为恢复而重新执行。下一次模型回复沿用原任务、历史 +和剩余轮数，不新增独立重试预算。工具内部意外抛出的编程错误仍向外传播，避免 +把所有 `KeyError` 都误报为模型参数错误。 + +同时检查响应流中实际收到的参数 JSON。SDK 会在流式接收期间解析部分 JSON；即使 +缺少结束括号时已经得到包含必填字段的字典，也不能据此执行命令。流完整结束于 +`tool_use`、但参数 JSON 不完整时，本次调用被拒绝并要求重发完整对象。Journal／ +ATIF 保留错误、原始参数 JSON，以及 SDK 已解析的输入；非对象输入在兼容现有 +object 字段约束的同时，另存为 `raw_input`。后续请求使用可发送的对象形式， +不会把半截 JSON 重放给接口。`max_tokens` 的原有处理保持不变：整条截断回复中的 +工具仍全部跳过，运行记录为 `response_truncated`，本次没有实现自动续写。 + +**自动化与独立审查。** 锁定依赖下的 276 项核心测试全部通过；临时环境固定为 +上一轮实跑报告的 Anthropic SDK 1.5.0、HTTPX 0.28.1、HTTPX2 2.12.0 和 +Pydantic 2.13.5，再跑同一核心套件也为 276 项通过。Harbor adapter 的 22 项 +测试通过。新测试覆盖错误参数不产生副作用、真实 SDK 接收不完整 JSON、错误 +反馈后纠正调用、同轮有效调用、交互／headless 模式、轮数上限与轨迹证据。 +通过 Herdr 新建 split，独立 reviewer 按 `review-agent` 技能审查完整差异， +结论为 **No findings**，并额外验证了真实 SDK 中混合调用的恢复和 Harbor 兼容性。 + +此外，将上一轮 circuit、QEMU、scheduler、DNA 的四份实际失败响应流原样交给 +SDK 1.5.0 离线重放，四次都把坏调用转为错误反馈，并在脚本提供的后续回复中 +完成一次有效调用、正常结束。该验证的工具执行被替身替代，没有付费模型调用， +证明同一失败输入的处理行为已经改变，不能当作四题真实解答通过。 + +**已知边界。** 本次恢复依赖 SDK 成功交付响应。非法转义和尾随逗号等部分 JSON +语法错误会先在 SDK 内部抛出异常，尚不能进入恢复流程；独立审查已确认主分支也 +存在这一限制。流中断、任务算法错误、轮数耗尽和评测环境故障也需要分别处理。 + +**实题复测设置。** 复测使用同一份已审查的 `27a9503` wheel，模型仍为 OpenRouter +上的 `deepseek/deepseek-v4-flash-0731`；原始 20 题的 task ref 和缓存镜像摘要 +均与 09-06 基线一致。每次回复显式设置 `max_tokens=65536`，每题最多 50 轮， +同时运行最多 2 题；项目默认值仍为 32768。agent 执行限时 3600 秒，收尾宽限 +120 秒，Harbor 外层限时 3780 秒，验证器保留各题原始时限。每题在每个 job 中 +只尝试一次，Harbor 自动重试为 0；额外补测使用独立 job，保留原失败记录。 + +09-13 首组 targeted5 中，QEMU 安装依赖遇到 APT 404，DNA 安装超过 1080 秒， +均未调用模型；PyTorch 在安装期间被用户暂停，circuit 尚未启动。后续仅将 +**安装时限**增加到 3600 秒，并对 HTTP 404 最多重试三次系统依赖安装。 +同组 scheduler 的 agent 已在暂停前正常结束，恢复任务后使用保留容器中的原始 +产物补跑官方验证：6/6 通过、reward 为 1，**没有新增模型调用**。这是暂停后 +补验证的结果，单独记录，不当作一次完整、不中断的 Harbor 运行。 + +09-14 targeted4 的 QEMU 安装仍遇到间歇性 404，因此另建补测：从原 APT 索引 +选中的官方地址下载同版本 20 个包，核对 SHA256 和大小，在 `apt-get update` +之后放入缓存，再执行原依赖安装。提前放入会被镜像的 APT 清理钩子删除；修正 +顺序后，原始镜像中的安装验证成功。包版本和软件源保持一致。 + +同一 targeted4 中，PyTorch 的 agent 正常结束，但官方验证器下载 Torch／CUDA +依赖超过原始 900 秒，未得到评分。为独立补测和后续完整 20 题准备了 uv 0.9.5 +缓存，依赖仍为官方脚本指定的 `pytest==8.4.1`、`torch==2.7.1` 和 +`pytest-json-ctrf==0.3.5`。缓存迁移到原始镜像后，31 个包离线安装成功，Torch +可正常导入；准备阶段没有运行题目测试。后续仅为 `pytorch-model-recovery` +预置这份缓存，官方验证脚本和 900 秒时限不变。这改变了缓存条件，不能与工具 +参数修复的效果混为一谈。 + +原始 8192 基线还使用不同源码和 agent 时限；上一轮 65536 的首批 18 题为 +5 题通过，之后的补测及 compressor 是独立尝试，`regex-log` 则仅在 32768 下 +复测过。因此分别比较原始 20 题和相同 18 题子集，不拼接不同设置生成通过率。 +采样、路由、缓存和服务端状态未受控；相同失败响应的离线重放、实跑中的错误 +恢复事件、最终题目评分，应作为三类不同证据解读。 + +**针对性复测结果（2026-09-14）。** 下表保留每题的历史报错来源和实际复测结果； +安装失败、验证超时及补测不相互覆盖，也不将这些不同条件合成一次正式的 5 题评分。 + +| 题目 | 历史参数崩溃 | 本次结果 | 本次观察到的参数反馈 | +| --- | --- | --- | --- | +| `dna-assembly` | `bash` 缺 `command`，原始 JSON 为未闭合字符串 | reward **0**，官方测试 **0/1**；50 次模型回复后 `max_turns_exhausted`，agent 执行 3533.7 秒 | 0 次 | +| `qemu-alpine-ssh` | `bash` 缺 `command`，原始 JSON 为 `{` | 安装失败单独保留；缓存补测 reward **1**、**1/1** 通过，48 次回复后正常结束 | 0 次 | +| `llm-inference-batching-scheduler` | `write` 缺 `content`，原始 JSON 为 `{` | 暂停前 47 次回复后正常结束；恢复后官方验证 reward **1**、**6/6** 通过，无新增模型调用 | **1 次**不完整 `bash` JSON 被拒绝，随后继续调用模型，并出现成功的 `bash` 调用 | +| `pytorch-model-recovery` | 8192 基线在超时后发生 `edit` 缺 `path` | 首次 agent 正常结束，验证下载超时未评分；缓存补测 reward **1**、**5/5** 通过，8 次回复后正常结束 | 两次均为 0 次 | +| `circuit-fibsqrt` | `bash` 缺 `command`，原始 JSON 为 `{}` | 49 次回复后达到 3600 秒执行时限，停止后产物通过 **3/3** 测试、reward **1**；**不计为正常结束的通过** | 0 次 | + +circuit 的中断由实验 supervisor 发出，最终为 `KeyboardInterrupt`／退出码 130， +Harbor 记录 `NonZeroAgentExitCodeError`。收尾完成且保留原生轨迹，没有强制杀进程； +验证在 agent 停止之后才开始。因此应同时保留“产物通过”和“执行预算耗尽”， +不能仅凭 reward 1 就把该运行记为正常完成。 + +本组实跑中，直接观察到参数错误反馈后继续并通过验证的只有 scheduler，且本次 +错误是 `bash` JSON，不是历史上的 `write.content`。其他题目的新采样没有产生 +参数校验错误；它们的通过不能单独归因于本功能。四份历史坏输入能否恢复，由 +前述原始响应离线重放提供同输入证据。 + +含 scheduler、首次 PyTorch 验证超时和两次缓存补测在内，共保留 **6 份原生 ATIF**， +全部通过 Harbor 校验、与完整 Journal 投影一致，且没有 Journal 字符串截断。 +这 6 次实跑共 222 次模型回复，输入 12,183,309 tokens（含缓存命中 10,021,376）， +输出 427,835 tokens，模型费用 **$0.243005564**，用量与费用均完整；纯安装失败、 +暂停时尚未启动的模型及离线重放没有模型费用。PyTorch 缓存补测的安装、agent、 +验证分别耗时 432.8、140.0、23.2 秒；这反映了缓存准备条件，不能解释为 agent +代码使原先 900 秒的验证下载变快。 + +**完整 20 题复测（2026-09-14～15）。** 独立完整组最终为 **10/20 通过（50%）、 +9 题零分、1 题未评分**；其中 **9 题正常完成并通过（45%）**。原始 8192 基线 +为 8/20 通过（40%），其中 7 次没有 Harbor 异常。本次 circuit 的产物通过了 +验证，但费用对账阶段达到执行上限，不能计为正常结束的通过。“无 Harbor 异常” +与本次要求原生 `completed`、无异常、未触及执行上限的定义也不完全相同。 +[结构化结果](../../../benchmarks/harbor/results/tb21-tool-input-recovery-20260914.json) +保留各次尝试、配置、计费完整性与验证证据。 + +| 实验组 | 题数 | reward 1 | reward 0 | 未评分 | +| --- | --- | --- | --- | --- | +| 原始 8192 基线 | 20 | 8 | 12 | 0 | +| 上一轮 65536 首批 18 题 | 18 | 5 | 8 | 5 | +| 本次相同 18 题子集 | 18 | 8 | 9 | 1 | +| 本次独立完整组 | 20 | 10 | 9 | 1 | + +相同 18 题子集的 8 次通过中，7 次正常结束。下表的数字为 reward；“不在此组” +表示上一轮首批 18 题没有包含该题，并不表示未评分。compressor 上一轮在独立 +65536 补测中已经通过，regex-log 则在 32768 补测中通过，均不能混入旧首批 18 题。 + +| 题目 | 原始 8192 | 上轮 65536 首批 18 | 本次 65536 | 本次结果说明 | +| --- | --- | --- | --- | --- | +| `write-compressor` | 0 | 不在此组 | 1 | 正常结束；3/3 | +| `torch-tensor-parallelism` | 0 | 未评分 | 0 | 正常结束；1/3 | +| `schemelike-metacircular-eval` | 0 | 0 | 0 | 第 18 次请求响应流中断 | +| `kv-store-grpc` | 1 | 0 | 1 | 正常结束；7/7 | +| `pypi-server` | 1 | 1 | 1 | 正常结束；1/1 | +| `dna-assembly` | 0 | 未评分 | 0 | 第 2 次请求服务商不可用 | +| `torch-pipeline-parallelism` | 0 | 未评分 | 0 | 50 轮耗尽；2/3 | +| `qemu-alpine-ssh` | 1 | 未评分 | 1 | 正常结束；1/1 | +| `openssl-selfsigned-cert` | 1 | 1 | 1 | 正常结束；6/6 | +| `regex-chess` | 0 | 0 | 0 | 50 轮耗尽；1/4 | +| `log-summary-date-ranges` | 1 | 1 | 1 | 正常结束；2/2 | +| `model-extraction-relu-logits` | 0 | 未评分 | 未评分 | agent 正常结束；验证 900 秒超时 | +| `path-tracing` | 0 | 0 | 0 | 第 32 次请求服务商不可用 | +| `regex-log` | 0 | 不在此组 | 1 | 正常结束；1/1 | +| `caffe-cifar-10` | 0 | 0 | 0 | 正常结束；2/6 | +| `mteb-leaderboard` | 0 | 0 | 0 | 50 轮耗尽；0/2 | +| `llm-inference-batching-scheduler` | 1 | 0 | 0 | 第 3 次请求响应流中断 | +| `pytorch-model-recovery` | 1 | 1 | 1 | 正常结束；5/5 | +| `circuit-fibsqrt` | 0 | 0 | 1 | 3/3；费用对账中断，轨迹重建 | +| `merge-diff-arc-agi-task` | 1 | 1 | 1 | 正常结束；5/5 | + +与原始基线相比，新增通过 compressor、regex-log、circuit，scheduler 从通过 +变为零分；净增加 2 题。与上一轮 65536 首批 18 题相比，KV-store 从零分变为通过， +QEMU 从未评分变为通过，circuit 从零分变为产物通过但收尾异常。前两题在原始 +8192 基线中本就通过，compressor 和 regex-log 在此前各自的预算补测中也已通过， +因此不能把这些分数变化当作参数校验的独立收益。 + +本次完整组 **没有触发 `ToolInputError`**。同一历史坏输入能否恢复，仍由四份 +原始响应的离线重放证明；实跑中观察到错误反馈后继续并通过的证据，来自前述 +定向 scheduler。本次完整组的 scheduler 在第 3 次请求发生 `RemoteProtocolError`， +只完成 2 次回复、得到零分；不能用定向组的成功覆盖这次独立失败。 + +完整组共有 4 次请求未完整返回：Scheme 和 scheduler 的响应流中断，DNA 和 +path-tracing 则收到 `provider_unavailable`，提示上游收到 SIGTERM、停止服务超时。 +这些属于传输或服务可用性问题。pipeline、regex-chess、MTEB 耗尽 50 轮；tensor +和 Caffe 正常结束但功能测试未全通过。模型提取完成 27 次回复，依赖已安装， +pytest 已收集并开始执行单个测试，但超过原始 900 秒验证时限，因此保留未评分； +这次不能归因于依赖下载，也没有延长时限来替换结果。 + +**circuit 的收尾问题。** 第 50 次回复在 UTC 18:46:26.965 以 `end_turn` 结束， +之后继续查询费用。supervisor 在 18:47:05.171 触发 3600 秒执行上限，打断费用 +对账；此时尚未写入 `run.completed` 或 `run.failed`，原生 ATIF 导出抛出 +`AtifProjectionError: Event Journal has no terminal event`。实验包装器保留原始 +Journal，另加明确标注的合成终止事件后重建轨迹；没有把重建文件冒充原生导出。 +agent 停止后官方测试 3/3 通过。这个费用收尾控制分支与实现提交的父提交相同， +本次没有修改它；后续需要处理“对账中断仍能记录终止状态并导出轨迹”的问题。 +工具输出中另有模型生成程序的 `Gate` 对象 `KeyError`，它作为工具结果返回， +不是 agent 因缺失工具参数而崩溃。 + +circuit 后段的三次详细监控探针各自超过 25 秒。只读检查时，容器仍在运行， +内存约 1.983/2 GiB，Docker 未报告 OOM；随后停用容器内详细探针，改读宿主机 +结果文件和容器状态，没有修改 agent、验证器或资源上限，也没有发现遗留探针。 +先前探针对内存压力的影响无法量化，因此把这次监控变化列为实验限制。 + +**轨迹与费用。** 20 份 ATIF 均通过 Harbor 校验，其中 19 份是原生导出且与完整 +Journal 投影一致，1 份是上述明确标注的重建文件；全部 Journal 均无字符串截断。 +共启动 491 次模型调用，487 次完整返回。已完整记录的回复合计输入 +**21,991,162 tokens**（含缓存命中 **18,119,936**）、输出 **724,013 tokens**； +4 次中断响应的原生用量仍不完整，不能把缺失值当零。逐回复输出最大值也只统计 +完整回复，不能用它代表中断响应的实际输出。QEMU 另有 1 次建连阶段 +`ConnectTimeout`，SDK 重试后正常通过：41 次模型回复、42 次 HTTP 尝试。 + +所有模型费用已由原生记录或独立账单回执补齐。补查区分已完整返回的调用与中断 +请求，并扣除 Journal 中已经记录的费用，避免重建轨迹缺少终止事件时重复计费。 +完整 20 题费用为 **$0.462175819**；连同定向组、缓存补测和恢复验证的 scheduler， +本次实验模型费用合计 **$0.705181383**。费用完整不等于原生响应或用量完整。 + #### 超时停止 “超时停止”指的是：任务达到规定的运行时间后，要确保容器里的 agent 真正停止 diff --git a/src/nanopycodeagent/agent.py b/src/nanopycodeagent/agent.py index 111f51e..799172b 100644 --- a/src/nanopycodeagent/agent.py +++ b/src/nanopycodeagent/agent.py @@ -19,10 +19,12 @@ and turns them into an exit code. """ +import json import os import sys import time import uuid +from copy import copy from importlib.metadata import PackageNotFoundError, version from pathlib import Path @@ -41,13 +43,13 @@ from anthropic.types import MessageParam, ToolResultBlockParam, ToolUseBlock from .atif import project_atif, write_atif -from .bash_tool import BASH_TOOL, run_bash +from .bash_tool import run_bash from .cost import ( pending_cost, resolve_generation_cost, usage_cost, ) -from .edit_tool import EDIT_TOOL, edit_preview, run_edit +from .edit_tool import edit_preview, run_edit from .event_journal import ( EventEmitter, EventJournal, @@ -57,10 +59,11 @@ RunOutcome, utc_now, ) -from .read_tool import READ_TOOL, run_read +from .read_tool import run_read from .settings import DEFAULT_MAX_TOKENS, load_settings_env, resolve_max_tokens from .terminal import Spinner, print_tool_output, print_tool_use -from .write_tool import WRITE_TOOL, content_preview, run_write +from .tool_validation import TOOLS, tool_input_error +from .write_tool import content_preview, run_write # The model used when ANTHROPIC_MODEL is set in neither the environment nor # the config file. @@ -106,10 +109,6 @@ "run. " ) + _TOOL_GUIDANCE -# Every tool offered to the model on each request. -TOOLS = [READ_TOOL, WRITE_TOOL, EDIT_TOOL, BASH_TOOL] - - def _json_value(value: object) -> JsonValue: """Convert an SDK value into the provider-neutral event representation.""" if value is None or isinstance(value, bool | int | float | str): @@ -144,12 +143,19 @@ def _native_content_blocks(value: object) -> list[JsonValue]: if source_type == "text": content.append({"type": "text", "text": source_block.get("text", "")}) elif source_type == "tool_use": + arguments = source_block.get("input") content.append( { "type": "tool_call", "tool_call_id": source_block.get("id"), "tool_name": source_block.get("name"), - "input": source_block.get("input"), + # Journal/ATIF require object arguments. Keep rejected + # non-object input separately instead of discarding it. + "input": arguments if isinstance(arguments, dict) else {}, + **( + {"raw_input": arguments} + if not isinstance(arguments, dict) else {} + ), } ) else: @@ -202,9 +208,12 @@ def __call__(self, event: NativeEvent) -> None: elif event.type == "tool.started": tool_name = str(event.payload["tool_name"]) arguments = event.payload["input"] - if not isinstance(arguments, dict): - raise TypeError("tool input event payload must be an object") - if tool_name == "read": + error = event.payload.get("input_error") or tool_input_error( + tool_name, arguments + ) + if error: + print_tool_use(f"[{tool_name}] (invalid arguments; not executed)") + elif tool_name == "read": print_tool_use(f"[read] {arguments['path']}") elif tool_name == "write": content = str(arguments["content"]) @@ -218,7 +227,7 @@ def __call__(self, event: NativeEvent) -> None: f"[edit] {arguments['path']}\n" f"{edit_preview(old_text, new_text)}" ) - else: + elif tool_name == "bash": print_tool_use(f"[bash]$ {arguments['command']}") elif event.type == "tool.completed": result = event.payload["result"] @@ -244,24 +253,28 @@ def _run_one_tool( block: ToolUseBlock, emitter: EventEmitter, model_call_id: str, + *, + input_error: str | None = None, ) -> ToolResultBlockParam: """Execute one ``tool_use`` block and emit its runtime facts.""" tool_input = _json_value(block.input) - if not isinstance(tool_input, dict): - raise TypeError("tool input must be an object") + input_error = input_error or tool_input_error(block.name, tool_input) emitter.emit( "tool.started", { "model_call_id": model_call_id, "tool_call_id": block.id, "tool_name": block.name, - "input": tool_input, + "input": tool_input if isinstance(tool_input, dict) else {}, + **({"input_error": input_error} if input_error else {}), "source_timestamp": utc_now(), }, ) tool_started_ns = time.perf_counter_ns() try: - if block.name == "read": + if input_error: + output, is_error = input_error, True + elif block.name == "read": path = block.input["path"] output, is_error = run_read( path, @@ -282,7 +295,7 @@ def _run_one_tool( new_text, replace_all=block.input.get("replace_all", False), ) - else: # bash — the only other tool offered + else: # bash; unknown names have already been rejected command = block.input["command"] with Spinner("Running..."): output, is_error = run_bash(command) @@ -310,6 +323,10 @@ def _run_one_tool( "tool_name": block.name, "result": output, "is_error": is_error, + **( + {"error": {"type": "ToolInputError", "message": input_error}} + if input_error else {} + ), "duration_ms": (time.perf_counter_ns() - tool_started_ns) / 1_000_000, "source_timestamp": utc_now(), }, @@ -486,21 +503,53 @@ def _run_model_loop( tools=TOOLS, messages=messages, ) as stream: - for text in stream.text_stream: - spinner.stop() - emitter.emit( - "model.output_delta", - { - "model_call_id": model_call_id, - "delta": text, - "source_timestamp": utc_now(), - }, - ) + input_json: dict[int, list[str]] = {} + for event in stream: + if event.type == "text": + spinner.stop() + emitter.emit( + "model.output_delta", + { + "model_call_id": model_call_id, + "delta": event.text, + "source_timestamp": utc_now(), + }, + ) + elif ( + event.type == "content_block_delta" + and event.delta.type == "input_json_delta" + ): + input_json.setdefault(event.index, []).append( + event.delta.partial_json + ) message = stream.get_final_message() generation_id = _response_header(stream, "x-generation-id") model_completed_ns = time.perf_counter_ns() content = _native_content_blocks(message.content) + input_errors: dict[str, str] = {} + invalid_json_ids: set[str] = set() + for index, block in enumerate(message.content): + if block.type != "tool_use": + continue + error = tool_input_error(block.name, block.input) + if index in input_json: + raw_json = "".join(input_json[index]) + try: + json.loads(raw_json) + except json.JSONDecodeError: + # The SDK parses partial JSON while streaming. Even a + # complete-looking dict is not permission to execute an + # unfinished call after a provider reports tool_use. + error = ( + "Invalid tool argument JSON: incomplete or malformed. " + "Resend a complete JSON object." + ) + invalid_json_ids.add(block.id) + content[index]["input_json"] = raw_json + if error: + input_errors[block.id] = error + content[index]["input_error"] = error tool_calls = [ item for item in content @@ -542,7 +591,15 @@ def _run_model_loop( } ) return "response_truncated" - messages.append({"role": "assistant", "content": message.content}) + request_content = [] + for block in message.content: + if block.type == "tool_use" and ( + block.id in invalid_json_ids or not isinstance(block.input, dict) + ): + block = copy(block) + block.input = {} + request_content.append(block) + messages.append({"role": "assistant", "content": request_content}) if message.stop_reason != "tool_use": return "completed" if max_turns is not None and turns >= max_turns: @@ -552,7 +609,10 @@ def _run_model_loop( # Every tool_use block needs a matching tool_result in the next # user message, or the API rejects the request. results = [ - _run_one_tool(block, emitter, model_call_id) + _run_one_tool( + block, emitter, model_call_id, + input_error=input_errors.get(block.id), + ) for block in message.content if block.type == "tool_use" ] diff --git a/src/nanopycodeagent/atif.py b/src/nanopycodeagent/atif.py index ca1a5b5..a3b7ab1 100644 --- a/src/nanopycodeagent/atif.py +++ b/src/nanopycodeagent/atif.py @@ -190,10 +190,13 @@ def _tool_calls_and_observation( } tool_call_extra = tool_call.setdefault("extra", {}) assert isinstance(tool_call_extra, dict) + for field in ("input_error", "input_json", "raw_input"): + if field in native_tool_call: + tool_call_extra[field] = native_tool_call[field] _add_journal_truncation( tool_call_extra, entry, - f"/tool_calls/{tool_call_index}/input", + f"/tool_calls/{tool_call_index}", ) if not tool_call_extra: tool_call.pop("extra") diff --git a/src/nanopycodeagent/tool_validation.py b/src/nanopycodeagent/tool_validation.py new file mode 100644 index 0000000..521b68b --- /dev/null +++ b/src/nanopycodeagent/tool_validation.py @@ -0,0 +1,40 @@ +"""Validate model-supplied arguments before previewing or executing tools.""" + +from .bash_tool import BASH_TOOL +from .edit_tool import EDIT_TOOL +from .read_tool import READ_TOOL +from .write_tool import WRITE_TOOL + +TOOLS = [READ_TOOL, WRITE_TOOL, EDIT_TOOL, BASH_TOOL] + + +def tool_input_error(name: str, arguments: object) -> str | None: + """Check the flat schemas of the offered tools without coercing values. + + Additional properties remain allowed, as in the published schemas. Tool + implementations still handle domain errors such as an out-of-range offset + or an edit whose old text does not match the file. + """ + tool = next((tool for tool in TOOLS if tool["name"] == name), None) + if tool is None: + return f"Unknown tool: {name}. Use one of: read, write, edit, bash." + if not isinstance(arguments, dict): + return "Invalid tool arguments: expected a JSON object. Provide it and retry." + schema = tool["input_schema"] + missing = [key for key in schema["required"] if key not in arguments] + if missing: + return ( + f"Missing required argument(s): {', '.join(missing)}. " + "Provide the missing arguments and retry." + ) + types = {"string": str, "integer": int, "boolean": bool} + for key, definition in schema["properties"].items(): + if key not in arguments: + continue + expected = definition["type"] + # bool is an int subclass in Python, but not a JSON integer. + if type(arguments[key]) is not types[expected]: + return f"Invalid argument: {key} must be {expected}. Correct it and retry." + if key in {"path", "command"} and "\x00" in arguments[key]: + return f"Invalid argument: {key} contains a NUL character. Remove it and retry." + return None diff --git a/tests/helpers.py b/tests/helpers.py index 31572a4..9e07a4b 100644 --- a/tests/helpers.py +++ b/tests/helpers.py @@ -10,6 +10,15 @@ from types import SimpleNamespace import anthropic +import anthropic._base_client + + +def sdk_http_module(): + """Use the SDK's transport family when mocking its real streaming client.""" + return ( + getattr(anthropic._base_client, "httpx", None) + or anthropic._base_client.httpx2 + ) def text_block(text): @@ -80,6 +89,10 @@ def __enter__(self): def __exit__(self, *exc_info): return False + def __iter__(self): + for text in self.text_stream: + yield SimpleNamespace(type="text", text=text) + @property def text_stream(self): def _gen(): diff --git a/tests/test_tool_validation.py b/tests/test_tool_validation.py new file mode 100644 index 0000000..49b855a --- /dev/null +++ b/tests/test_tool_validation.py @@ -0,0 +1,228 @@ +"""Invalid model calls must yield recoverable results without side effects.""" + +import json +from types import SimpleNamespace + +import anthropic +import pytest + +from nanopycodeagent import agent, settings +from nanopycodeagent.event_journal import EventJournal + +from helpers import ( + FakeClient, + FakeMessages, + FakeStream, + edit_tool_use_block, + patch_client, + patch_client_and_input, + sdk_http_module, + text_block, + write_tool_use_block, +) + + +def journal_entries(): + path, = (settings.SETTINGS_PATH.parent / "journals").glob("*.jsonl") + return EventJournal.replay(path) + + +@pytest.mark.parametrize(("name", "arguments", "diagnostic"), [ + ("read", {}, "path"), + ("write", {"path": "file"}, "content"), + ("write", {"content": "text"}, "path"), + ("edit", {"old_text": "old", "new_text": "new"}, "path"), + ("edit", {"path": "file", "new_text": "new"}, "old_text"), + ("edit", {"path": "file", "old_text": "old"}, "new_text"), + ("bash", {}, "command"), + ("read", {"path": None}, "path must be string"), + ("read", {"path": [], "offset": 1}, "path must be string"), + ("read", {"path": "file", "offset": True}, "offset must be integer"), + ("read", {"path": "file", "limit": 1.5}, "limit must be integer"), + ("read", {"path": "file", "limit": None}, "limit must be integer"), + ("write", {"path": "file", "content": 3}, "content must be string"), + ("edit", {"path": "file", "old_text": None, "new_text": ""}, "old_text must be string"), + ("edit", {"path": "file", "old_text": "old", "new_text": []}, "new_text must be string"), + ("edit", {"path": "file", "old_text": "old", "new_text": "new", "replace_all": "false"}, "replace_all must be boolean"), + ("bash", {"command": ["echo", "hello"]}, "command must be string"), + ("read", {"path": "a\x00b"}, "NUL"), + ("bash", {"command": "echo\x00hello"}, "NUL"), + ("unoffered", {"command": "echo must-not-run"}, "Unknown tool"), + ("write", [], "expected a JSON object"), + ("bash", "echo must-not-run", "expected a JSON object"), + ("read", None, "expected a JSON object"), +]) +def test_invalid_calls_are_reported_without_executing( + monkeypatch, tmp_path, capsys, name, arguments, diagnostic +): + def must_not_run(*args, **kwargs): + pytest.fail("Invalid input reached a tool implementation") + + for tool in ("read", "write", "edit", "bash"): + monkeypatch.setattr(agent, "run_" + tool, must_not_run) + block = SimpleNamespace(type="tool_use", id="bad", name=name, input=arguments) + messages = FakeMessages([ + FakeStream([block], stop_reason="tool_use"), [text_block("done")], + ]) + patch_client(monkeypatch, FakeClient(messages)) + trajectory_path = tmp_path / "trajectory.json" + + assert agent.run_headless("work", trajectory_path=trajectory_path) == 0 + + result, = messages.calls[1][-1]["content"] + assert result["tool_use_id"] == "bad" and result["is_error"] is True + assert diagnostic in result["content"] + assert "not executed" in capsys.readouterr().out + entries = journal_entries() + completed = next(e for e in entries if e.type == "tool.completed") + assert completed.payload["result"] == result["content"] + assert completed.payload["error"]["type"] == "ToolInputError" + assert entries[-1].payload["outcome"] == "completed" + trajectory = json.loads(trajectory_path.read_text()) + step = trajectory["steps"][1] + observation, = step["observation"]["results"] + assert observation["source_call_id"] == "bad" + assert observation["extra"]["is_error"] is True + if not isinstance(arguments, dict): + assert step["tool_calls"][0]["extra"]["raw_input"] == arguments + assert messages.calls[1][-2]["content"][0].input == {} + + +@pytest.mark.parametrize("interactive", [False, True]) +def test_model_corrects_bad_call_and_keeps_successful_sibling( + monkeypatch, tmp_path, interactive +): + target = tmp_path / "result.txt" + good = write_tool_use_block("good", path=str(target), content="original") + bad = edit_tool_use_block("bad", old_text="original", new_text="corrected") + correction = edit_tool_use_block( + "fixed", path=str(target), old_text="original", new_text="corrected" + ) + messages = FakeMessages([ + FakeStream([good, bad], stop_reason="tool_use"), + FakeStream([correction], stop_reason="tool_use"), + [text_block("done")], + ]) + client = FakeClient(messages) + if interactive: + prompts = patch_client_and_input(monkeypatch, client=client, inputs=["work", "/exit"]) + assert agent.run() == 0 + assert len(prompts) == 2 + else: + patch_client(monkeypatch, client) + assert agent.run_headless("work", max_turns=3) == 0 + + assert target.read_text() == "corrected" + results = messages.calls[1][-1]["content"] + assert [r["tool_use_id"] for r in results] == ["good", "bad"] + assert [r["is_error"] for r in results] == [False, True] + assert messages.calls[2][-1]["content"][0]["is_error"] is False + starts = [e.payload["tool_call_id"] for e in journal_entries() if e.type == "tool.started"] + assert starts == ["good", "bad", "fixed"] + + +def test_repeated_invalid_calls_do_not_reset_turn_budget(monkeypatch): + messages = FakeMessages([ + FakeStream([write_tool_use_block(str(i))], stop_reason="tool_use") + for i in range(3) + ]) + patch_client(monkeypatch, FakeClient(messages)) + assert agent.run_headless("work", max_turns=3) == 0 + assert len(messages.calls) == 3 + entries = journal_entries() + assert len([e for e in entries if e.type == "tool.completed"]) == 2 + assert entries[-1].payload["outcome"] == "max_turns_exhausted" + + +def test_valid_empty_strings_and_extra_fields_remain_allowed(monkeypatch, tmp_path): + target = tmp_path / "empty.txt" + messages = FakeMessages([ + FakeStream([write_tool_use_block("empty", path=str(target), content="", extra=1)], stop_reason="tool_use"), + [text_block("done")], + ]) + patch_client(monkeypatch, FakeClient(messages)) + assert agent.run_headless("work") == 0 + assert target.read_bytes() == b"" + assert messages.calls[1][-1]["content"][0]["is_error"] is False + + +def test_programming_keyerror_is_not_converted_to_argument_feedback(monkeypatch): + def broken(*args): + raise KeyError("internal bug") + + monkeypatch.setattr(agent, "run_write", broken) + messages = FakeMessages([ + FakeStream([write_tool_use_block("valid", path="file", content="text")], stop_reason="tool_use"), + ]) + patch_client(monkeypatch, FakeClient(messages)) + with pytest.raises(KeyError, match="internal bug"): + agent.run_headless("work") + assert journal_entries()[-1].type == "run.failed" + + +@pytest.mark.parametrize("bad_json", [ + "{}", "{", '{"command":"unfinished', + # The SDK can already expose the complete value despite the missing brace. + '{"command":"echo must-not-run"', "[]", "null", +]) +def test_real_sdk_bad_input_is_rejected_and_corrected( + monkeypatch, tmp_path, bad_json +): + httpx = sdk_http_module() + requests = [] + executions = [] + + def run_bash(command): + executions.append(command) + return "ok", False + + monkeypatch.setattr(agent, "run_bash", run_bash) + + def respond(request): + requests.append(json.loads(request.content)) + turn = len(requests) + events = [{"type": "message_start", "message": { + "id": f"msg-{turn}", "type": "message", "role": "assistant", + "model": "test-model", "content": [], "stop_reason": None, + "stop_sequence": None, "usage": {"input_tokens": 10, "output_tokens": 0}, + }}] + if turn < 3: + events += [ + {"type": "content_block_start", "index": 0, "content_block": { + "type": "tool_use", "id": f"call-{turn}", "name": "bash", "input": {}, + }}, + {"type": "content_block_delta", "index": 0, "delta": { + "type": "input_json_delta", "partial_json": bad_json if turn == 1 else '{"command":"echo corrected"}', + }}, + {"type": "content_block_stop", "index": 0}, + ] + events += [ + {"type": "message_delta", "delta": { + "stop_reason": "tool_use" if turn < 3 else "end_turn", "stop_sequence": None, + }, "usage": {"output_tokens": 20}}, + {"type": "message_stop"}, + ] + wire = "".join(f"event: {e['type']}\ndata: {json.dumps(e)}\n\n" for e in events) + return httpx.Response(200, headers={"content-type": "text/event-stream"}, content=wire) + + trajectory_path = tmp_path / "trajectory.json" + with anthropic.Anthropic( + api_key="test-key", base_url="https://example.test", + http_client=httpx.Client(transport=httpx.MockTransport(respond)), + ) as client: + patch_client(monkeypatch, client) + assert agent.run_headless("work", max_turns=3, trajectory_path=trajectory_path) == 0 + + assert executions == ["echo corrected"] + assert len(requests) == 3 + rejected = requests[1]["messages"][-1]["content"][0] + assert rejected["is_error"] is True and rejected["tool_use_id"] == "call-1" + assert requests[1]["messages"][-2]["content"][0]["input"] == {} + assert requests[2]["messages"][-1]["content"][0]["is_error"] is False + trajectory = json.loads(trajectory_path.read_text()) + call = trajectory["steps"][1]["tool_calls"][0] + if bad_json.startswith("{") and bad_json != "{}": + assert call["extra"]["input_json"] == bad_json + assert "JSON" in rejected["content"] + assert trajectory["final_metrics"]["total_completion_tokens"] == 60 + assert trajectory["extra"]["terminal"]["outcome"] == "completed" diff --git a/tests/test_truncation.py b/tests/test_truncation.py index 4da9f48..68e0a74 100644 --- a/tests/test_truncation.py +++ b/tests/test_truncation.py @@ -4,7 +4,6 @@ from types import SimpleNamespace import anthropic -import httpx import pytest from anthropic.types import ThinkingBlock @@ -17,6 +16,7 @@ FakeStream, patch_client, patch_client_and_input, + sdk_http_module, text_block, write_tool_use_block, ) @@ -132,6 +132,7 @@ def test_sdk_stream_with_partial_tool_json_preserves_truncation( monkeypatch, tmp_path, capsys ): """Use the real SDK accumulator with an input JSON delta cut mid-string.""" + httpx = sdk_http_module() events = [ {"type": "message_start", "message": { "id": "msg-truncated", "type": "message", "role": "assistant",