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Parent(s): 5834385
docs: update README for expert tasks, dynamic max_steps, and reward tweaks
Browse files
README.md
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@@ -28,11 +28,12 @@ Every step produces a real HTTP call. The grader is fully deterministic: no LLM,
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| Property | Value |
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| **Framework** | OpenEnv (openenv-core 0.2.3) |
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| **Tasks** |
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| **Max Steps per Episode** | 5 |
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| **Reward Range** | 0.0 β 1.0 |
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| **Grader** | Fully deterministic (no LLM) |
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| **Mock API** | Internal FastAPI router, same container |
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| **Port** | 7860 (HF Spaces) |
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---
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@@ -103,6 +104,16 @@ Requires multi-step reasoning and handling stateful API behaviour.
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| `hard_rate_limit` | No backoff after 429 | After receiving 429, include `X-Retry-After: 2` header on next request |
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| `hard_pagination` | Never follows cursor | Call GET `/mock_api/logs?cursor=<value>` until `has_more` is `false` |
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---
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## Reward Function
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| 405 / 415 | 0.10 | Auth ok, wrong method or content-type |
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| 422 | 0.15 | Auth ok, body validation failed |
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| 429 | 0.20 | Hit endpoint, needs rate limit handling |
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| 200 (schema mismatch) | 0.
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| 200 (schema match) | 0.85β1.00 | Correct β higher reward for fewer attempts |
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---
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@@ -234,7 +245,8 @@ api_debug_env/
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βββ tasks/
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β βββ easy.py β 3 easy tasks
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β βββ medium.py β 3 medium tasks
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β βββ hard.py β 3 hard tasks
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β βββ registry.py β TASK_REGISTRY dict
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βββ graders/
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β βββ grader.py β Deterministic reward logic
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| Property | Value |
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| **Framework** | OpenEnv (openenv-core 0.2.3) |
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| **Tasks** | 4 difficulty levels β 12 tasks total |
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| **Max Steps per Episode** | Dynamic (5 for Easy/Medium, 10 for Hard/Expert) |
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| **Reward Range** | 0.0 β 1.0 |
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| **Grader** | Fully deterministic (no LLM), robust to negative reward hacking |
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| **Mock API** | Internal FastAPI router, same container |
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| **State Reset** | Secure `/_admin/reset` endpoint guarantees strict episode isolation |
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| **Port** | 7860 (HF Spaces) |
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---
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| `hard_rate_limit` | No backoff after 429 | After receiving 429, include `X-Retry-After: 2` header on next request |
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| `hard_pagination` | Never follows cursor | Call GET `/mock_api/logs?cursor=<value>` until `has_more` is `false` |
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### Expert β Sandbox & Undocumented APIs
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Advanced RL environment forcing pure systematic exploration and state tracking.
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| Task ID | Bug | What the Agent Needs to Fix |
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|---|---|---|
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| `expert_openapi_discovery` | Completely undocumented endpoint | Query `/mock_api/system/metrics` utilizing OPTIONS/Swagger to find correct schema |
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| `expert_stateful_chain` | UUIDs change every run | Create a user, extract the generated `user_id`, and immediately update their preferences |
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| `expert_transaction_rollback` | Multi-step transaction | Begin a transaction, fail it intentionally, and issue a rollback command cleanly |
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---
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## Reward Function
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| 405 / 415 | 0.10 | Auth ok, wrong method or content-type |
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| 422 | 0.15 | Auth ok, body validation failed |
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| 429 | 0.20 | Hit endpoint, needs rate limit handling |
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| 200 (schema mismatch) | 0.25 | Right status, wrong response structure |
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| 200 (schema match) | 0.85β1.00 | Correct β higher reward for fewer attempts |
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---
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βββ tasks/
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β βββ easy.py β 3 easy tasks
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β βββ medium.py β 3 medium tasks
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β βββ hard.py β 3 hard/multi-step tasks
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β βββ expert.py β 3 expert advanced RL tasks
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β βββ registry.py β TASK_REGISTRY dict
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βββ graders/
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β βββ grader.py β Deterministic reward logic
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