{ "completed": 10, "succeeded": 10, "aggregates": [ { "role": "opus", "evaluated": 5, "succeeded": 5, "mean_score": 82.16275510204082, "mean_rubric": 91.57551020408164, "mean_dimension": 72.75 }, { "role": "astra", "evaluated": 5, "succeeded": 5, "mean_score": 84.07959183673469, "mean_rubric": 93.15918367346939, "mean_dimension": 75.0 } ], "runs": [ { "role": "opus", "task_id": "bw_0003", "generation": { "role": "opus", "model": "claude-opus-5-5", "task_id": "bw_0003", "pid": 1002993, "status": "completed", "started_at": 1793240596.1523275, "returncode": 0, "seconds": 3990.11683511734, "blend_exists": true, "terminal": { "duration_api_ms": 1170290, "stop_reason": "end_turn", "session_id": "8cf589c3-dfb5-42e9-9043-ee67f22dd1a4", "total_cost_usd": 3.4967074, "usage": { "input_tokens": 124, "cache_creation_input_tokens": 308057, "cache_read_input_tokens": 3784932, "output_tokens": 59947, "output_tokens_details": { "thinking_tokens": 27488 }, "server_tool_use": { "web_search_requests": 0, "web_fetch_requests": 0 }, "service_tier": "standard", "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 308057 }, "inference_geo": "", "iterations": [], "speed": "standard", "fallback_credit": null }, "modelUsage": { "claude-opus-5-5": { "inputTokens": 124, "outputTokens": 59947, "cacheReadInputTokens": 3784932, "cacheCreationInputTokens": 308057, "webSearchRequests": 0, "costUSD": 3.4967074, "contextWindow": 1000000, "maxOutputTokens": 128000, "thinkingTokens": 27488, "cacheCreationEphemeral5mInputTokens": 308057, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "claude-opus-5-5", "provider": "firstParty", "costBasis": "list" } }, "permission_denials": [], "terminal_reason": "completed", "fast_mode_state": "off", "fast_mode_disabled_reason": "sdk_opt_in_required", "subagent_stats": { "spawned": 0, "requested": { "background": 0, "foreground": 0, "unset": 0 }, "started_in_background": 0, "max_depth": 0, "spawned_by_subagents": 0, "completed": 0, "failed": 0, "killed": { "parent": 0, "user": 0, "system": 0 }, "refused": { "depth_limit": 0, "concurrency_limit": 0, "budget": 0 }, "by_type": {} }, "safety_stops": 0, "is_error": false, "num_turns": 67, "subtype": "success", "api_error_status": null, "result": "I've rendered the final image and saved the editable Blender project. Both are in `/workspace/exports/`. I checked the final render at full size and in close-up crops, and nothing was still rendering when I finished.\n\n- **Image:** `membrane_schematic.png`, 3840×2160, 16-bit RGB, rendered in Cycles on the CPU with 8 threads at 384 samples and denoising. The render took about 19 minutes.\n- **Project:** `final.blend`. All materials are built in Blender's node editor, so there are no external texture files to keep track of.\n\n**One change from the reference:** I used a 16:9 frame instead of the reference's wide banner shape. The wide shape left too little height to show the top of the membrane and its cut edge together.\n\n**What's in the scene:**\n- **Bilayer:** an upward-bulging membrane made of rows of olive/yellow-green glossy heads with mild subsurface scattering, top and bottom. Paired orange-brown tails point inward, one tail of each pair slightly bent. The front edge is cut away so you can see heads, tails and heads stacked from top to bottom, which is the clearest spot for a bilayer callout.\n- **Membrane protein:** one blue, semi-transparent glass-like complex sitting right at that cut edge. It spans the full membrane and sticks out on both sides, with seven faint helices visible inside.\n- **Glycoprotein clusters:** seven on the outer surface. Each is a purple protein core sunk into the outer layer, with branched chains of pink sugar beads on the outside only, as in standard textbooks.\n- **Background:** one matte DNA double helix entering diagonally from the lower left (cream backbones, orange-pink base pairs, with major and minor grooves), six translucent light-blue ball-and-stick small molecules, and one gold nanoparticle with a subtly pitted, grainy surface. I added nothing else, including the small floating dots in the reference.\n- **Look:** a light-blue gradient background, a large soft key light from the upper left, a subtle rim light from behind, a weak fill, and a 45 mm camera at f/2.4 focused on the protein. The background is slightly soft but still readable.\n\n**Adjusting it later:**\n- Objects are sorted into clearly named groups (bilayer, protein, glycoproteins, DNA, small molecules, nanoparticle, camera and lights), so they're easy to select for annotations.\n- The camera is `MacroCamera`. Depth of field follows an empty object called `DOF_FocusTarget`; move it to change what's in focus.\n- The background is a gradient panel attached to the camera, so it stays behind the scene when you move the camera.\n- The lipids are generated by a node setup (`GN_LipidInstancer`) from two hidden template objects, one head and one tail pair. Editing either template changes every lipid at once.\n- Sizes and counts were chosen for a clear, balanced picture and are not measured biological values. Please keep that in mind when you write the figure caption.", "ttft_ms": 9767, "type": "result", "duration_ms": 3989559, "uuid": "a7b09e82-d9b5-4531-9f43-9d989840c71f", "ttft_stream_ms": 9741, "time_to_request_ms": 119, "first_content_frame_ms": 9742, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "claude-opus-5-5": { "inputTokens": 124, "outputTokens": 59947, "cacheReadInputTokens": 3784932, "cacheCreationInputTokens": 308057, "webSearchRequests": 0, "costUSD": 3.4967074, "contextWindow": 1000000, "maxOutputTokens": 128000, "thinkingTokens": 27488, "cacheCreationEphemeral5mInputTokens": 308057, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "claude-opus-5-5", "provider": "firstParty", "costBasis": "list" } } } }, "evaluation": { "task_id": "bw_0003", "modality": "image", "ok": true, "score": 89.375, "rubric_score": 100.0, "dimension_score": 78.75, "error": "" } }, { "role": "astra", "task_id": "bw_0003", "generation": { "role": "astra", "model": "gpt-6-astra", "task_id": "bw_0003", "pid": 1003791, "status": "completed", "started_at": 1793240757.732598, "returncode": 0, "seconds": 1742.373886346817, "blend_exists": true, "terminal": { "duration_api_ms": 1229657, "stop_reason": "end_turn", "session_id": "299b5d36-500f-4635-91b9-8aa20cdf4043", "total_cost_usd": 7.700716, "usage": { "input_tokens": 1799149, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "output_tokens": 25206, "output_tokens_details": { "thinking_tokens": 0 }, "server_tool_use": { "web_search_requests": 0, "web_fetch_requests": 0 }, "service_tier": "standard", "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 0 }, "inference_geo": "", "iterations": [], "speed": "standard", "fallback_credit": null }, "modelUsage": { "gpt-6-astra": { "inputTokens": 1799149, "outputTokens": 25206, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 7.700716, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } }, "permission_denials": [], "terminal_reason": "completed", "fast_mode_state": "off", "fast_mode_disabled_reason": "sdk_opt_in_required", "subagent_stats": { "spawned": 0, "requested": { "background": 0, "foreground": 0, "unset": 0 }, "started_in_background": 0, "max_depth": 0, "spawned_by_subagents": 0, "completed": 0, "failed": 0, "killed": { "parent": 0, "user": 0, "system": 0 }, "refused": { "depth_limit": 0, "concurrency_limit": 0, "budget": 0 }, "by_type": {} }, "safety_stops": 0, "is_error": false, "num_turns": 72, "subtype": "success", "api_error_status": null, "result": "Completed and verified:\n\n- [High-resolution illustration](exports/membrane_schematic.png) — 3840 × 2400, 16-bit PNG, rendered in Cycles.\n- [Editable Blender project](exports/final.blend) — organized collections, adjustable camera, and procedural materials.\n- [Scope and editing notes](exports/README.txt)\n\nThe image is unlabeled for later callouts and presented as a qualitative educational schematic, not a measured molecular model.", "ttft_ms": 8050, "type": "result", "duration_ms": 1741860, "uuid": "1dc32f28-83dd-4894-91e7-a96de1ecda1f", "ttft_stream_ms": 99, "time_to_request_ms": 93, "first_content_frame_ms": 8049, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "gpt-6-astra": { "inputTokens": 1799149, "outputTokens": 25206, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 7.700716, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } } } }, "evaluation": { "task_id": "bw_0003", "modality": "image", "ok": true, 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"api_error_status": null, "result": "I've built the booth scene and rendered it in Cycles at 3600×2400 (256 adaptive samples, denoised). I checked the final render at full size: it's clean, the hull paneling and hatch read clearly, and the lighting doesn't wash them out.\n\n**What's in the scene** (left to right, as in the photo)\n- **Red pillar:** 0.74 × 0.54 × 3.5 m, satin red lacquer. It has a white maple leaf, two four-point stars and a \"Canada\" wordmark with a small flag over the last \"a\".\n- **TV wall:** 2.55 m wide × 3.0 m high, brushed light-gray metal panels with recessed seams and raised bands top and bottom. It has rivets, a vertical stiffener rib and a vent plate with small indicator lights. A 75″ screen at 1.8 m centre height shows a CSA logo image I made, and the screen lights the wall around it.\n- **Hull wall:** 3.4 m wide × 3.4 m high, stepped 16 cm forward of the TV wall, in a darker metallic gray. It has panel seams with rivet rows, vertical stiffener ribs, raised outline lines around the hatch and angled vent plates.\n- **Hatch:** about 1.64 × 2.14 m, with a deep white frame, a recessed opening and double doors. Each door has two eight-sided windows with bolt rings, a centre bar, hinges and a latch.\n- **Lunar view:** the windows look into a real 3D scene behind the wall, not a flat picture. It has a cratered surface, a horizon, a starfield, Earth and a six-wheeled rover. Its sunlight is restricted to that scene, so it doesn't spill into the booth.\n- **Right side wall:** I added a 1.6 m wall in the same hull paneling to close off the right side of the booth. It isn't in your photo, so delete it in Blender if you'd rather not have it.\n- **Ceiling and floor:** a dark suspended ceiling at 4.05 m with LED strips along its edges and five ceiling-mounted floodlights. The floor is a raised white tiled platform (1 m tiles) with an aluminium edge.\n- **Lighting:** a cool-toned mix of soft overhead light, light washing down the walls, the floodlights, the screen glow and a faint blue-white LED line at the base of the walls.\n\nDimensions not given in the photo are my estimates based on typical booth sizes.\n\n**Camera:** 24 mm, eye height 1.62 m, placed left of the booth centre about 5.6 m back, so the hatch faces the camera almost head-on. The camera is kept level so vertical lines stay straight. To change the angle, move or rotate `Booth_Camera` or adjust its lens and vertical shift.\n\nThe .blend is organized by element, so each part is easy to select and adjust. The scene was generated by `/workspace/work/build.py` if you ever want to rebuild it.\n\nFiles are in `/workspace/exports`:\n- `final.blend` (screen image, starfield and font are packed inside)\n- `booth_render.png`\n- `textures/` (the screen and starfield images)", "ttft_ms": 3715, "type": "result", "duration_ms": 4436800, "uuid": "db02cd3d-c2c0-4b5a-a329-a2549838837f", "ttft_stream_ms": 2563, "time_to_request_ms": 120, "first_content_frame_ms": 2563, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "claude-opus-5-5": { "inputTokens": 72, "outputTokens": 73328, "cacheReadInputTokens": 1859781, "cacheCreationInputTokens": 449115, "webSearchRequests": 0, "costUSD": 4.266524399999999, "contextWindow": 1000000, "maxOutputTokens": 128000, "thinkingTokens": 29362, "cacheCreationEphemeral5mInputTokens": 449115, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "claude-opus-5-5", "provider": "firstParty", "costBasis": "list" } } } }, "evaluation": { "task_id": "bw_0006", "modality": "image", "ok": true, "score": 87.5, "rubric_score": 100.0, "dimension_score": 75.0, "error": "" } }, { "role": "astra", "task_id": "bw_0006", "generation": { "role": "astra", "model": "gpt-6-astra", "task_id": "bw_0006", "pid": 1003793, "status": "completed", "started_at": 1793240757.7437882, "returncode": 0, "seconds": 3758.8534133434296, "blend_exists": true, "terminal": { "duration_api_ms": 1945951, "stop_reason": "end_turn", "session_id": "404ff286-701d-4842-92cc-9a5874fcc1f8", "total_cost_usd": 15.769663999999997, "usage": { "input_tokens": 3726216, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "output_tokens": 43240, "output_tokens_details": { "thinking_tokens": 0 }, "server_tool_use": { "web_search_requests": 0, "web_fetch_requests": 0 }, "service_tier": "standard", "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 0 }, "inference_geo": "", "iterations": [], "speed": "standard", "fallback_credit": null }, "modelUsage": { "gpt-6-astra": { "inputTokens": 3726216, "outputTokens": 43240, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 15.769663999999997, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } }, "permission_denials": [], "terminal_reason": "completed", "fast_mode_state": "off", "fast_mode_disabled_reason": "sdk_opt_in_required", "subagent_stats": { "spawned": 0, "requested": { "background": 0, "foreground": 0, "unset": 0 }, "started_in_background": 0, "max_depth": 0, "spawned_by_subagents": 0, "completed": 0, "failed": 0, "killed": { "parent": 0, "user": 0, "system": 0 }, "refused": { "depth_limit": 0, "concurrency_limit": 0, "budget": 0 }, "by_type": {} }, "safety_stops": 0, "is_error": false, "num_turns": 77, "subtype": "success", "api_error_status": null, "result": "Completed and verified.\n\n- [Editable Blender project](exports/final.blend)\n- [Main Cycles render — 3600 × 2700](exports/booth_perspective.png)\n- [Hatch detail — 2800 × 2800](exports/hatch_detail.png)\n- [Dimensioned circulation plan](exports/layout_plan.png)\n- [Editing notes](exports/README.md)\n\nThe project includes packed textures and fonts, editable cameras, and a separate modeled lunar-rover scene. Estimated overall footprint: **6.40 × 3.96 m**. All rendering is finished, and both final renders were visually inspected.", "ttft_ms": 4959, "type": "result", "duration_ms": 3758093, "uuid": "4f8b1b5e-3239-4cf6-a53e-04513f8e94b2", "ttft_stream_ms": 97, "time_to_request_ms": 91, "first_content_frame_ms": 4957, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "gpt-6-astra": { "inputTokens": 3726216, "outputTokens": 43240, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 15.769663999999997, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } } } }, "evaluation": { "task_id": "bw_0006", "modality": "image", "ok": true, "score": 93.125, "rubric_score": 100.0, "dimension_score": 86.25, "error": "" } }, { "role": "opus", "task_id": "bw_0100", "generation": { "role": "opus", "model": "claude-opus-5-5", "task_id": "bw_0100", "pid": 1022232, "status": "completed", "started_at": 1793244587.9109678, "returncode": 0, "seconds": 3427.3369603157043, "blend_exists": true, "terminal": { "duration_api_ms": 1760483, "stop_reason": "end_turn", "session_id": "baccb469-796a-4796-9e24-f2fccc9cd8e9", "total_cost_usd": 4.8264742, "usage": { "input_tokens": 120, "cache_creation_input_tokens": 444707, "cache_read_input_tokens": 4868196, "output_tokens": 81441, "output_tokens_details": { "thinking_tokens": 42006 }, "server_tool_use": { "web_search_requests": 0, "web_fetch_requests": 0 }, "service_tier": "standard", "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 444707 }, "inference_geo": "global", "iterations": [], "speed": "standard", "fallback_credit": null }, "modelUsage": { "claude-opus-5-5": { "inputTokens": 120, "outputTokens": 81441, "cacheReadInputTokens": 4868196, "cacheCreationInputTokens": 444707, "webSearchRequests": 0, "costUSD": 4.8264742, "contextWindow": 1000000, "maxOutputTokens": 128000, "thinkingTokens": 42006, "cacheCreationEphemeral5mInputTokens": 444707, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "claude-opus-5-5", "provider": "firstParty", "costBasis": "list" } }, "permission_denials": [], "terminal_reason": "completed", "fast_mode_state": "off", "fast_mode_disabled_reason": "sdk_opt_in_required", "subagent_stats": { "spawned": 0, "requested": { "background": 0, "foreground": 0, "unset": 0 }, "started_in_background": 0, "max_depth": 0, "spawned_by_subagents": 0, "completed": 0, "failed": 0, "killed": { "parent": 0, "user": 0, "system": 0 }, "refused": { "depth_limit": 0, "concurrency_limit": 0, "budget": 0 }, "by_type": {} }, "safety_stops": 0, "is_error": false, "num_turns": 64, "subtype": "success", "api_error_status": null, "result": "I've rendered the figure as a 3840×2160 16-bit PNG at 512 samples and saved the editable project. I checked the full render and close-up crops before finishing, and none of my render jobs are still running.\n\n**Deliverables** (all in `/workspace/exports/`)\n- `ahmed_body_flow_schematic.png` — 16-bit RGB PNG, 3840×2160, Cycles, AgX\n- `final.blend` — the editable project. Textures and fonts are linked with relative paths from `textures/` and `fonts/`; Blender reports no missing files.\n\n**What's in the figure**\n- **Body and floor:** a 1044 × 389 × 288 mm body with R100 rounded front edges and a 25° rear slant 222 mm long. It sits 50 mm off the floor on four Ø30 mm dark-grey matte stilts. The floor has a light grid at 100 mm spacing that fades into a neutral grey gradient background.\n- **Camera:** three-quarter rear view from slightly above, 50 mm lens, f/11 for a mild depth of field. The body, all four stilts, the rear slant and the wake are visible.\n- **Flow:** ribbons are released upstream and coloured viridis, and some of them roll up into the trailing vortices at the slant's side edges. The y=0 wake slice shows a small separation bubble at the top of the slant and two counter-rotating recirculation zones behind the base, marked with white direction arrows.\n- **Surface pressure:** a blue–white–red tendency map over a dark-grey paint base, so the suction at the front edges, slant and base shows as blue.\n- **Labels:** the caption \"Illustrative flow visualization — not simulation data.\" and \"U∞ = 40 m/s, Re ≈ 2.8×10⁶\" stated as nominal reference conditions, not computed values. The legend says \"schematic / illustrative\" and is marked only low / high, with no numbers anywhere. A U∞ arrow on the floor shows the flow direction, and there's open space left for your callouts.\n\n**Things to be aware of**\n- **The flow is hand-built, not computed.** I made a simple model of the flow by hand so the ribbons and slice look plausible. It is not a CFD solution or experimental data, as the caption says.\n- **GPU/OptiX wasn't available.** This machine only has a CPU, so I rendered on CPU with Blender's standard denoiser (Intel OpenImageDenoise) instead.\n- **Stilt positions are my assumption.** The spec only gives their diameter, so I placed them 470 mm apart lengthwise and 243 mm apart across, which is a common layout for this model.\n- **The HDRI is Blender's bundled \"studio\" map** (CC0 licence), used at low strength for reflections only, because none was supplied.\n- **The labels are composited from a second scene.** The text and legend are real Blender text objects in a separate \"Annotations_Overlay\" scene, layered on in the compositor so the depth of field doesn't blur them. You can edit them directly in `final.blend`.\n- **Another process was competing for the CPU.** While I was rendering, a Blender job I didn't start (`last_annotation_fix.py`, from a different session) was using about 7–8 cores. It didn't appear to touch my files, so I left it running; it only slowed my render.\n\nThe scripts that rebuild the scene are in `/workspace/work/`: `build_scene.py`, `flowfield.py`, `slice_tex.py` and `overlay.py`.", "ttft_ms": 10841, "type": "result", "duration_ms": 3426788, "uuid": "48b51582-48db-4f64-9765-714c4a57d92c", "ttft_stream_ms": 10687, "time_to_request_ms": 92, "first_content_frame_ms": 10687, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "claude-opus-5-5": { "inputTokens": 120, "outputTokens": 81441, "cacheReadInputTokens": 4868196, "cacheCreationInputTokens": 444707, "webSearchRequests": 0, "costUSD": 4.8264742, "contextWindow": 1000000, "maxOutputTokens": 128000, "thinkingTokens": 42006, "cacheCreationEphemeral5mInputTokens": 444707, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "claude-opus-5-5", "provider": "firstParty", "costBasis": "list" } } } }, "evaluation": { "task_id": "bw_0100", "modality": "text", "ok": true, "score": 70.75, "rubric_score": 64.0, "dimension_score": 77.5, "error": "" } }, { "role": "astra", "task_id": "bw_0100", "generation": { "role": "astra", "model": "gpt-6-astra", "task_id": "bw_0100", "pid": 1015735, "status": "completed", "started_at": 1793242501.295004, "returncode": 0, "seconds": 6072.398525476456, "blend_exists": true, "terminal": { "duration_api_ms": 1349565, "stop_reason": "end_turn", "session_id": "35e9ef08-5ed2-44b3-91ef-658606e96df1", "total_cost_usd": 8.749952000000002, "usage": { "input_tokens": 2017738, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "output_tokens": 33950, "output_tokens_details": { "thinking_tokens": 0 }, "server_tool_use": { "web_search_requests": 0, "web_fetch_requests": 0 }, "service_tier": "standard", "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 0 }, "inference_geo": "", "iterations": [], "speed": "standard", "fallback_credit": null }, "modelUsage": { "gpt-6-astra": { "inputTokens": 2017738, "outputTokens": 33950, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 8.749952000000002, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } }, "permission_denials": [], "terminal_reason": "completed", "fast_mode_state": "off", "fast_mode_disabled_reason": "sdk_opt_in_required", "subagent_stats": { "spawned": 0, "requested": { "background": 0, "foreground": 0, "unset": 0 }, "started_in_background": 0, "max_depth": 0, "spawned_by_subagents": 0, "completed": 0, "failed": 0, "killed": { "parent": 0, "user": 0, "system": 0 }, "refused": { "depth_limit": 0, "concurrency_limit": 0, "budget": 0 }, "by_type": {} }, "safety_stops": 0, "is_error": false, "num_turns": 55, "subtype": "success", "api_error_status": null, "result": "Completed and visually inspected the final figure.\n\n- [16-bit PNG — 3840 × 2160](exports/Ahmed_body_illustrative_flow.png)\n- [Editable Blender project](exports/final.blend)\n\nThe project includes packed assets, editable labels, and the required illustrative-data disclaimer. Rendered with CPU Cycles, 8 threads, 512 samples, and OpenImageDenoise.", "ttft_ms": 3684, "type": "result", "duration_ms": 6071851, "uuid": "d9003e44-6a5f-4746-958f-2362415e1f58", "ttft_stream_ms": 98, "time_to_request_ms": 92, "first_content_frame_ms": 3682, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "gpt-6-astra": { "inputTokens": 2017738, "outputTokens": 33950, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 8.749952000000002, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } } } }, "evaluation": { "task_id": "bw_0100", "modality": "text", "ok": true, "score": 82.375, "rubric_score": 76.0, "dimension_score": 88.75, "error": "" } }, { "role": "opus", "task_id": "bw_0111", "generation": { "role": "opus", "model": 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"刚才被系统停掉的是我自己写的一个等待脚本，它只负责循环检查渲染进程有没有退出，本身不渲染任何东西。它停不下来，是因为检查条件写错了：它会把自己的命令行当成渲染进程，所以永远等不到结束。\n\n渲染本身早就完成了。`/workspace/exports/lumi_hero_2000x2500.png`（2000×2500）已经写入并检查过，`final.blend` 也重新打开验证过，贴图是打包的。现在没有任何渲染任务在跑，交付文件不受影响，不需要重新启动。", "ttft_ms": 14972, "type": "result", "duration_ms": 16866, "uuid": "eee21fa9-3310-4d6a-b931-441316f3aee1", "ttft_stream_ms": 14451, "time_to_request_ms": 107, "first_content_frame_ms": 14451, "queued_turn_count": 0, "result_index": 1, "model_usage_since_last_result": { "claude-opus-5-5": { "inputTokens": 4, "outputTokens": 248, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 131161, "webSearchRequests": 0, "costUSD": 0.660781, "contextWindow": 1000000, "maxOutputTokens": 128000, "thinkingTokens": 40, "cacheCreationEphemeral5mInputTokens": 131161, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "claude-opus-5-5", "provider": "firstParty", "costBasis": "list" } } } }, "evaluation": { "task_id": "bw_0111", "modality": "text", "ok": true, "score": 90.0, "rubric_score": 100.0, "dimension_score": 80.0, "error": "" } }, { "role": "astra", "task_id": "bw_0111", "generation": { "role": "astra", "model": "gpt-6-astra", "task_id": "bw_0111", "pid": 1021915, "status": "completed", "started_at": 1793244518.1127045, "returncode": 0, "seconds": 9554.035770654678, "blend_exists": true, "terminal": { "duration_api_ms": 2375663, "stop_reason": "end_turn", "session_id": "d7047f8e-6a09-44a2-8e58-c78e16d3f978", "total_cost_usd": 13.512671999999998, "usage": { "input_tokens": 3123793, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "output_tokens": 50875, "output_tokens_details": { "thinking_tokens": 0 }, "server_tool_use": { "web_search_requests": 0, "web_fetch_requests": 0 }, "service_tier": "standard", "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 0 }, "inference_geo": "", "iterations": [], "speed": "standard", "fallback_credit": null }, "modelUsage": { "gpt-6-astra": { "inputTokens": 3123793, "outputTokens": 50875, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 13.512671999999998, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } }, "permission_denials": [], "terminal_reason": "completed", "fast_mode_state": "off", "fast_mode_disabled_reason": "sdk_opt_in_required", "subagent_stats": { "spawned": 0, "requested": { "background": 0, "foreground": 0, "unset": 0 }, "started_in_background": 0, "max_depth": 0, "spawned_by_subagents": 0, "completed": 0, "failed": 0, "killed": { "parent": 0, "user": 0, "system": 0 }, "refused": { "depth_limit": 0, "concurrency_limit": 0, "budget": 0 }, "by_type": {} }, "safety_stops": 0, "is_error": false, "num_turns": 77, "subtype": "success", "api_error_status": null, "result": "已完成，并检查了最终渲染与工程尺寸。\n\n- [主图 PNG｜2000 × 2500](/workspace/exports/final.png)\n- [可编辑 Blender 工程](/workspace/exports/final.blend)\n- [编辑说明](/workspace/exports/README.txt)\n\n采用 Cycles 渲染并开启降噪，全部贴图已打包。画面上下保留了文案空间，瓶标、材质、灯光和各模型组件均可继续调整。", "ttft_ms": 6594, "type": "result", "duration_ms": 9553516, "uuid": "a85fef0d-d11b-4421-8ba6-2b3492d38f67", "ttft_stream_ms": 96, "time_to_request_ms": 91, "first_content_frame_ms": 6592, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "gpt-6-astra": { "inputTokens": 3123793, "outputTokens": 50875, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 13.512671999999998, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } } } }, "evaluation": { "task_id": "bw_0111", "modality": "text", "ok": true, "score": 86.875, "rubric_score": 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"is_error": false, "num_turns": 2, "subtype": "success", "api_error_status": null, "result": "That notice is the broken wait loop I mentioned being shut down when it hit its time limit. It never finished on its own because its `pgrep` check matched its own command line. Nothing is lost: all 78 frames had already rendered, and `final.mp4` and `final.blend` in `/workspace/exports` are complete and checked. No other jobs are running.\n\nI added a note to memory: wait on the last output frame file instead of `pgrep`, so this doesn't happen again.", "ttft_ms": 82103, "type": "result", "duration_ms": 123848, "uuid": "e7430e74-fa11-4223-b1c4-6c0849a5c127", "ttft_stream_ms": 80981, "time_to_request_ms": 117, "first_content_frame_ms": 80981, "queued_turn_count": 0, "result_index": 1, "model_usage_since_last_result": { "claude-opus-5-5": { "inputTokens": 6, "outputTokens": 518, "cacheReadInputTokens": 237133, "cacheCreationInputTokens": 237598, "webSearchRequests": 0, "costUSD": 1.2458006, "contextWindow": 1000000, "maxOutputTokens": 128000, "thinkingTokens": 70, "cacheCreationEphemeral5mInputTokens": 237598, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "claude-opus-5-5", "provider": "firstParty", "costBasis": "list" } } } }, "evaluation": { "task_id": "bw_0214", "modality": "video", "ok": true, "score": 73.18877551020408, "rubric_score": 93.87755102040816, "dimension_score": 52.5, "error": "" } }, { "role": "astra", "task_id": "bw_0214", "generation": { "role": "astra", "model": "gpt-6-astra", "task_id": "bw_0214", "pid": 1038641, "status": "completed", "started_at": 1793248575.0108213, "returncode": 0, "seconds": 24978.948877334595, "blend_exists": true, "terminal": { "duration_api_ms": 3411429, "stop_reason": "end_turn", "session_id": "7a30ce14-1627-48ba-8ef4-0f8a6991f42f", "total_cost_usd": 27.507243999999993, "usage": { "input_tokens": 6624916, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0, "output_tokens": 50379, "output_tokens_details": { "thinking_tokens": 0 }, "server_tool_use": { "web_search_requests": 0, "web_fetch_requests": 0 }, "service_tier": "standard", "cache_creation": { "ephemeral_1h_input_tokens": 0, "ephemeral_5m_input_tokens": 0 }, "inference_geo": "", "iterations": [], "speed": "standard", "fallback_credit": null }, "modelUsage": { "gpt-6-astra": { "inputTokens": 6624916, "outputTokens": 50379, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 27.507243999999993, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } }, "permission_denials": [], "terminal_reason": "completed", "fast_mode_state": "off", "fast_mode_disabled_reason": "sdk_opt_in_required", "subagent_stats": { "spawned": 0, "requested": { "background": 0, "foreground": 0, "unset": 0 }, "started_in_background": 0, "max_depth": 0, "spawned_by_subagents": 0, "completed": 0, "failed": 0, "killed": { "parent": 0, "user": 0, "system": 0 }, "refused": { "depth_limit": 0, "concurrency_limit": 0, "budget": 0 }, "by_type": {} }, "safety_stops": 0, "is_error": false, "num_turns": 122, "subtype": "success", "api_error_status": null, "result": "Completed and verified:\n\n- [4K animation](/workspace/exports/aquarium.mp4) — H.264, 3840×2160, 30 fps, exactly 2.6 seconds.\n- [Editable Blender project](/workspace/exports/final.blend) — eight poseable fish rigs, animated tails and fins, camera movement, and packed textures.\n- [Editing notes](/workspace/exports/README.md)\n\nAll 78 frames finished rendering. The encoded video was visually inspected and decoded without errors.", "ttft_ms": 6965, "type": "result", "duration_ms": 24978146, "uuid": "b68d34a8-ffae-404b-a83c-7fd61c248e0d", "ttft_stream_ms": 97, "time_to_request_ms": 92, "first_content_frame_ms": 6963, "queued_turn_count": 0, "result_index": 0, "model_usage_since_last_result": { "gpt-6-astra": { "inputTokens": 6624916, "outputTokens": 50379, "cacheReadInputTokens": 0, "cacheCreationInputTokens": 0, "webSearchRequests": 0, "costUSD": 27.507243999999993, "contextWindow": 200000, "maxOutputTokens": 32000, "thinkingTokens": 0, "cacheCreationEphemeral5mInputTokens": 0, "cacheCreationEphemeral1hInputTokens": 0, "canonicalModel": "gpt-6-astra", "provider": "firstParty", "costBasis": "unknown" } } } }, "evaluation": { "task_id": "bw_0214", "modality": "video", "ok": true, "score": 71.77295918367346, "rubric_score": 89.79591836734694, "dimension_score": 53.75, "error": "" } } ] }