[System]
You are participating in Blender-Bench, a public benchmark where AI models complete the same Blender task.

Your result will be compared head-to-head with another model. Anyone on the internet can vote based on two equally important published views: a 2D rendered presentation and an interactive 3D scene exported to GLB. Treat neither view as optional; make the result clear and compelling in both.

Complete the request as well as you can. The benchmark does not prescribe a workflow or visual style; use whichever Blender techniques you consider appropriate. Make the important requirements evident in the published result, save a complete scene, and present the work clearly in every requested output.

The 2D presentation is rendered by the benchmark from your saved scene using Cycles at 1536 x 1536, 64 samples, denoising enabled, and GPU acceleration when available with a CPU fallback. It is the native-fidelity view of the Blender scene, so you may use Blender's full feature set. Preview and validate your materials, lighting, color management, and camera composition in Cycles, and do not rely on EEVEE-only effects for the final appearance.

The interactive 3D view is a best-effort GLB export containing geometry, compatible materials, the contestant camera, and supported lights. Because glTF cannot represent every Blender feature, native effects such as particles, hair or curves, volumes, simulations, and some procedural geometry may appear only in the 2D render. The benchmark may also generate a separate preview GLB by baking supported procedural material inputs to textures; this does not convert unsupported geometry or guarantee exact parity with Blender. When practical, keep the core form and scene readable in the 3D view while using the 2D presentation to show native Blender features faithfully.

## Harness Instructions

You are writing a single Python script for Blender 5.1 using the bpy API. The scene starts empty. Your script must build everything the user's prompt asks for.

You are building a real three-dimensional scene, and evaluators judge the whole scene and your final render side by side — an interactive 3D view and a benchmark-generated 360° camera orbit rendered in Cycles from your saved scene appear next to your presentation render, so forms that only read correctly from one angle will show. Build genuine 3D first, then present it well: before you finish, set up a camera and lighting to frame a single, well-composed presentation image of your result — a good scene that happens to have a well-placed camera and lights. The final benchmark capture overrides the scene render settings and renders in Cycles at 1536x1536, 64 samples, with denoising and GPU acceleration (CPU fallback). Preview and validate materials, lighting, color management, and composition in Cycles; do not rely on EEVEE-only effects. Use whatever Blender features best serve the result; a best-effort GLB export is also provided for interactive inspection, and features glTF cannot represent are not expected to survive it.

You get one attempt: the script runs once, headless, with no feedback and no chance to iterate, so write robust code. Reply with exactly one fenced Python code block containing the complete script and nothing else.

[User]
## Task

Complete the following Blender task:

<task>

An abandoned village slowly reclaimed by nature. Weathered houses with rusted, corroded metal roofs; overgrown foliage creeping up the walls and through broken windows; moss, grass, and vines spreading across the ground and over the rooftops. Convey age, decay, and the quiet return of the wild.

</task>

[System]
You are participating in Blender-Bench, a public benchmark where AI models complete the same Blender task.

Your result will be compared head-to-head with another model. Anyone on the internet can vote based on two equally important published views: a 2D rendered presentation and an interactive 3D scene exported to GLB. Treat neither view as optional; make the result clear and compelling in both.

Complete the request as well as you can. The benchmark does not prescribe a workflow or visual style; use whichever Blender techniques you consider appropriate. Make the important requirements evident in the published result, save a complete scene, and present the work clearly in every requested output.

The 2D presentation is rendered by the benchmark from your saved scene using Cycles at 1536 x 1536, 64 samples, denoising enabled, and GPU acceleration when available with a CPU fallback. It is the native-fidelity view of the Blender scene, so you may use Blender's full feature set. Preview and validate your materials, lighting, color management, and camera composition in Cycles, and do not rely on EEVEE-only effects for the final appearance.

The interactive 3D view is a best-effort GLB export containing geometry, compatible materials, the contestant camera, and supported lights. Because glTF cannot represent every Blender feature, native effects such as particles, hair or curves, volumes, simulations, and some procedural geometry may appear only in the 2D render. The benchmark may also generate a separate preview GLB by baking supported procedural material inputs to textures; this does not convert unsupported geometry or guarantee exact parity with Blender. When practical, keep the core form and scene readable in the 3D view while using the 2D presentation to show native Blender features faithfully.

## Harness Instructions

You are writing a single Python script for Blender 5.1 using the bpy API. The scene starts empty. Your script must build everything the user's prompt asks for.

You are building a real three-dimensional scene, and evaluators judge the whole scene and your final render side by side — an interactive 3D view and a benchmark-generated 360° camera orbit rendered in Cycles from your saved scene appear next to your presentation render, so forms that only read correctly from one angle will show. Build genuine 3D first, then present it well: before you finish, set up a camera and lighting to frame a single, well-composed presentation image of your result — a good scene that happens to have a well-placed camera and lights. The final benchmark capture overrides the scene render settings and renders in Cycles at 1536x1536, 64 samples, with denoising and GPU acceleration (CPU fallback). Preview and validate materials, lighting, color management, and composition in Cycles; do not rely on EEVEE-only effects. Use whatever Blender features best serve the result; a best-effort GLB export is also provided for interactive inspection, and features glTF cannot represent are not expected to survive it.

You get one attempt: the script runs once, headless, with no feedback and no chance to iterate, so write robust code. Reply with exactly one fenced Python code block containing the complete script and nothing else.

[User]
## Task

Complete the following Blender task:

<task>

An abandoned village slowly reclaimed by nature. Weathered houses with rusted, corroded metal roofs; overgrown foliage creeping up the walls and through broken windows; moss, grass, and vines spreading across the ground and over the rooftops. Convey age, decay, and the quiet return of the wild.

</task>

payment=(self "https://checkout.stripe.com" "https://connect-js.stripe.com" "https://js.stripe.com" "https://*.js.stripe.com" "https://hooks.stripe.com")

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":" parts","reasoning_details":[{"type":"reasoning.summary","summary":" parts","format":"openai-responses-v1","index":16}]},"finish_reason":null,"native_finish_reason":null}]}

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data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":" all","reasoning_details":[{"type":"reasoning.summary","summary":" all","format":"openai-responses-v1","index":16}]},"finish_reason":null,"native_finish_reason":null}]}

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":" about","reasoning_details":[{"type":"reasoning.summary","summary":" about","format":"openai-responses-v1","index":16}]},"finish_reason":null,"native_finish_reason":null}]}

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":" getting","reasoning_details":[{"type":"reasoning.summary","summary":" getting","format":"openai-responses-v1","index":16}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":" just","reasoning_details":[{"type":"reasoning.summary","summary":" just","format":"openai-responses-v1","index":16}]},"finish_reason":null,"native_finish_reason":null}]}

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":" right","reasoning_details":[{"type":"reasoning.summary","summary":" right","format":"openai-responses-v1","index":16}]},"finish_reason":null,"native_finish_reason":null}]}

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":"!","reasoning_details":[{"type":"reasoning.summary","summary":"!","format":"openai-responses-v1","index":16}]},"finish_reason":null,"native_finish_reason":null}]}

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQoOWtON2dgpOO-JQOKiEHvs5YCismQCi0-D3SFd-fLy59-1M1Sp6rbz421VR7wgNc0B5D_toMP89J8vmcLhU3Z9EN9gY_ObPsMpocjleuDapJDHM3q-YUYK0n8mTuPSWiXx2Z36bDVt8qCP13Rz6I9CaVnODDyPorqHa4kzA82ivAlpPoZvajd-eZozJLc84YMyr24e2Q_iOloaS63M2eFzjcgdnk5ASRhs52nqKKYy2RhM1lqOQ0RU_ecb8PAaZyMOQbkE_1uJSMhyM6YXb_taqzkh_zdjekEY5pWlO1Nm6Rqw-Wt--HZlAr5owcLisV2KfE4_i5vDaet0CxcDZ5f37btv1nzE-vvHyUVlpg1m6LYYHhOZ7jpqrLbW_5QnqndlnhZIdqGKpDQr7ls5wjfC7qS1MYZSi3HJcGSbc-HaXRmAGrKeBVmyGeU6KljwljHo5qPggiACk0izQFDZublmZla0R8SmIQk5ve8L0Ks9PWJQy05VhMX7LzUZJsteTFYg9ixGVZbvDrvdzfwPK_BmAvhy0h2zkC7wmrjEy6amzSISCDFzLjbDKCjFf6A-KPwwFwiEJaEdSIceQicMqV4xyxlELarT19VQRZjlct-nnMuXZVEc6om_DTPLrtrR6N5srkScpnDfTSgVeRW9GVg2Qqr6wz4N3yQXbjVLt72WMq4bezGzVa7ajdZEXF8TqGaVBZ5OfbFoEQVqAehIVwSBw_9ZL-NyXeG2XOLqKbWKETRXmB9-l1DzoPjIx6-Is2HqPX6VHZVNyqr2lkieyL-BqLhJfW2MPAwjHlmGdCVKu4d3hYQAaDO_2RoVM200cFvyZUcP59rQsxbf2rOpN1oVQPRNrH2CuM_Ga0hTbtMS02CV28akj6dmAc84oQbzyQvL8JiB3wd0PBrkOrDSErmaQKC12fROy3ORw5vchZcLu_fDbP-j-hQx64YpF1kBg3Oo75po7URDQWPN6apq9GWM330ZFXM73ERGpDH2swbLlAksKVo1OnyAJv8jowQVE3e4Cq8f6PnOqBz0VtJSZRFwHe8iphJ1XpkpFW-fyphsKeO0eAJLBUAn2pSO0KZ2Ces_Hb7hYoTYokByUoCq5QahdgfcMddg89kQKuvK_JoUnydm87hQHSeSTuow_HwE4O27vY6Vn9Eg_M1Eud-R0d4nZt7CppqLUrLZHx8yI5jNk3naTyGyfQE63Kq4076XZNq5u-IFYnYcA3Hsqk4pRmlKKvJ5_HkvaqJkMqh2KaMLZokTHhvuTZsN-eWFqDJkuAgqOtF3a_5Ws8Ual6rkDKHFbGymEpD4tLaL3f1kKx0bK-cKstvCJEmITGnlL2Woav0_bAt9blvNvBtCvRimw58LydeHkKX53ZHu4YrbapbjTqKiC1VvG8NERBPDslQZZ2vZav95Z6Ji5mhX5oUHtmGP3iU6smlbGAlHc0a-uhpd_Z4NrZezmHvtPkmHWC4JVYhERCKgtp_uAK4SsCRrJDxJG_vhwfQnjnkk_lIX7fVJ5P0DP9e7X4qTS0LXMG6XsfCrBel9y5UYRe-0LCgyesfHRzqAwu5GBZpqlZ_EFdvSKOBxYLZY04aBzABxlBDJwyHNdECNNBiBT4aotxn07l3l3TPMvvL6dFq7W-FskWSSvKSgD1B9XtIgvNmoDPc1hThUjL7UcJ8CYhByUtWvKG5qDFfce-0Kdgq1AgrnIWZv2A5teMfLjmyIeKw9AdH0H-TMzm67zfgHrjf6cum5eC5O6xOuuxUUV-uhDIWWxPDU5g-R1mV5fG7bR-sA8cuTnFevOlsUutItoxjj2vkrgxlnZzBtJm0Pmiv5m8ZyEkEeoQ8ZJ4VCf6g-C_BL_5zCz83SS2MNiO2tIS9v7N5YAo98qcdjcbP4fveMVQJjcSLn8oHDqsRQfrMZ4x8oJdDOFa7hSK6AP7G_7nfAYCUvmjI2yAqvpaDgEahMsFWPcdXwbjzMdmb8U3IB2WtzVfZCEORYH8uFHSyulbSxPwr9eApI_3h_DghC5DMsLXogIkyxx-hVMi6bIj5LXDQ-YgQghnLWbabhp7ctX1i8JIEwsH1agAYEUGWN2zBJBCF06i0r5nGEhxKBcCQk1BLh-aWJ8E4ZL2f-xnoPe5yk-l9LPF8H0gr6ajVuaM1QZgNr-W_BQHNoqFRiXv0nrUIUZPhclOKlcsTv_RkOpA4Yx4Jb0lUjEeEVJ5HtP9t3ka94g2xrps3QpvRrpkV3Pg5dvJo4PGDDT8JI3zJon1YM8_V-GTPP5LsHspYilO3ybiowa66tVCIXdN243SSSjXnR9e7GZx9jldY12xPEiMDk_XQNJLKJu2BLblDDbRYdwTbCD6SMRdefHBB9xcX9hh6BxVuGvDcCdtUDOQRjba5nW3QIbL8T4RGo1yUptReuDf1zib-_JZZtPk9iDObWXUZNwkyUO60gSLoyxc_FOSwp4B3xpjfLFVi2ntFR9bNaCR9dHVuj5Zgu-Px22Piv5oUVSlljJeeAoO2EjV0-BniSd4tBNNkzNg57IpwS-SIloR8654_PbXI5qfftJIaPmKxSL2x5GkvH1CoNIMHt5_q2VkFVZCewswjBYTscKjTc3wT6ijXPVY8Z_OymYITO7vB34r1U7E8jKnup4xRCq6JckAkPbh23h-31P2SrnaWl4tSDkb3mBN2sk39DflcCYssjjTBQEVPqOi2BIMObtd938oL7_VQn-3-4mNzydlRqMO6N5fSJmDtEUdG5K80cuKokXA7XQBznZW244QHNjhTE8YDKNXnChhG0-3XQzxi_txM8pTbIbV5UfORcVfHrWlEwj0gx-_oJYgERQmqz5SCIWNRcU28W6utVDTSXyhfF1-1StJd10iL51TGrge06Ia1Twfl5Bv6poOcy7rGuIzPxnCjetW-7_CDUt00AQ095yYvxfdddn_jgCYxXSpN9os_bfVFeGAOHlXuQXr3Ymi-hjmlh7ZRxPTak8OB5rVMeKdBAjQemz7cK2eABYMGAYTIydXVzV7HiayEMWU7JKCzHKKwrhQNyAk0FrxCssXtz-gG-JlJU0SpjNHt4VwS-4cx6sZZv9hmE6dXSKwEs7IGq7NFUYE9A3NQmezsoVfFNejxf7hluTupYHlX7_tIQxMinYBdfefg5Ro5olprICgfTIyBEmheFerWxB5sxnESB0ZuxqCiF0-LS6eGiGW9boidmk99BIqHz-WJlpJZRfciJOpejG1k_m5hs5_ljBopdze513jXkBtm7o5_TSBPBp62jqwN1TEAz3hHBtNTZuFbLjtNZDV_I1O72UNEHtNd0dEjVffk1EKw7iTcRFBA_oCOesbhhWeBsDVHbsdiZTcMSuixbza6MKGltPRG_CgqqCEpHOx_-fJ2N-KUve-qSE463FSwkqB8-iQk6ZqEjPfLHsGCDRWNNQFmiKbS8UObtb5hkaX8AHoUpzYCZ0naV_lvJ5NJ35V2K6USBppKP3siIE_zrnaybOZLmKtIxKsmUCbqkAzkIrDcQ45tHjyfCJ78aVu0IEMxvCwDrPzk-fDpZdkC09cMK64WTkvWHEbYq4AAiBJeUo-x1_ndwKxQmwGp-l-u2x0Wyw_kgo6YBr0kefWeAFBpWWNWbh3V-5jcRCO1w8AUoAqsNA52UbKPpoy3tangAY6dfI72iJHh_6bvCd-3FiQMFtxlxu0aY1dOH840_0DHovF_UjxW98TA1_iCico8lQfvQW_0E9sqI5advKperM76x72SKx5JzPas9Mxp3n_NOcIJVfp1oxuSea5a3z7PE-whr25jbkVU4QOytPpVk6udRqepa0TJAS7yTjHQJwtfaz9u-L7gyDmh8-0fcAhrfpo9VaowJfhv4A9sVx1011AEQlJs4E7lmcOv_oNlCq7XAP4U=","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0a000758819f9e63db545133b63a","index":17}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQoxukYDrRttUNXLnv9GqwizwL9Ouyfw1oQ1wDOXi_pGLaipgS_kGTkhH629_F2XXoT1hEO15ZxBJBktY4FA4VOs-AqhkMKbeK19tHWjh4u57JcYFjscrb0NIt6xyKEUNCIWCindR9d5htoQKDDik7uSFE9pB3usfBpV3B3_jt7G-lC4u-og1obSn8518PsXBZENhy9vJOm8IJsIFZivDAyI87UH5H2ccOX-Lk6gYVigs86A-QVSQpSH98PQGLtx6MhhLZH4z1Wxx2sf0RY1TWth_ToLyoaJd1x5T8-8MgTXIjxqG-zTJGpAeIjP0x2CC2wldkY5AmjzUoss8wH-3G1Mj0ksxEYBKvGg0byRdpzAW6phBaaqy4Jo4k9PcMOvO7TULfMQPeuveZClZVbm9RLXCmA7u0DBilGbHWdfo2l2RQj7yDXgRXyOvMzXJL66asXi8k7TkaUPdhlgKSVbtChwnJRbCs4-T8wNlFePzD3R3xeG3KSEcM9tSAm6gL8mRGVY6j5ewJB2Oo7Wq0i2eBgyp_oHUNnQi3BUISDmRr-lp4B56au9r5Fds8qGasiLrGObKoQTY21i96zCSjvcs_YrULd392AkWdc743XwOhP7YJzdgfoUbpZUGXiy1HnGi1xJWJs7yu-O28qDEhihef_NyhhjJjVIyx9Jl9SP_ln8F6cmj9JbQ0ZSkFYPZmNM4UHrZOT5aDmyXl1ziMMs7CxQE17hIGQEgY43aO4ItHwHhCc5Odk61j08YHXOfb4ADF5TOpctZajGSR8YLhKdZvBUf0i6VM_llXDm0JNhnk4o2yMv8cCshvtz046gSyUwALC2FKpen1kJXcrU5XcAhO1Ex3YFrrg2hYtiQIkRbU2crJNQGaLWtljarEjRiq6hhX0TOrA9r0QI-iKJ4ZC39A3RPyuhOOhKayk_oTyRVLUCwtXK5E5NKbFlIzcCSalPvizm4PsZJRg_D5_6EWJVJx_HnMwl-azvelvJT1etPHqCziovSw8ff_mlo8_6iIJS8UajG-moSyCJydpZ5ddjN_o3w9HKFpT3lSQyxyCeY3QTDo7Ur2QUqbKGW0wi4WuGar7vZPGHy2viuHjy_xqZoBy4feZ0mms0JjZ1HNUaYhqD-Lj6GvZBuOGu8SQNQRRAsNXzzVlQ7WK8H8ma7XvT_v9fdjRLoBCTlVmG9ivKHh5cU-ZUbcWjmEz69eaKL7__aFm2Zx1A50cyL3Fl4NhbLzFUlJYprHPd0m6tt0FrhvMwGHjZ9SSlRvbAykZe1ehoRquoZ6eWcclclbM1rZOT8gyYoT8tv0Ku5KhB6onWBZLA5LWyDrF0CauUXTz4SFcnIWxdYRXqu9i9pg3Sk-fzkDM6lo0EZid8iH5JxAzstscCgsWL59EP6ux6wTS3r9eJMNbm9ZGCQnPWK7zJnc5EtgBBkyND1SMe8_rgvnChXRFSncRNKWnaLhFSAmeeRNc38nrKM3h0R9VDAGhQQqw0_zb44SDzmvX6pYLraKpWcC4R4ih3TFSPT7O5mtSZDYsHBedmbRctSX4BrhEMnLi3JPAoq1gwAwi0hKYQ2BQw5jYyNRuv0ACCXAqnp0ULykDKJ2_Unh34zoUmEY2MR2qVG1zatBA3AuiF0osB03n8_m2HxfMilWS_zBEqppPAJ0T3zk2svTbWRjt1k-MAm9fcghgwsEIqBlYh2z2Iw1JXacSMuS3tAQ3oht-QBxtm2Y3khKdT1OlSmWkYZYlzpasZKCd0JPyttDRxzahtKhyqhnWJ8lvc8kKFCNdOBQGKF84OYC_C-9Bwk33wveoRu5SCepc9x9YhQl5vLJ8ygNpaEUpCIobanQtM8X7AivPXjVvK-krnD03xIdrgfsK5IxlMZsNCknwRvq-zj1m_L_6EreG_jOqlGAb_03F7mW7n0A3ZZuorx2FBSWGJlIyxAgRX1xtRR278f0QRTCZvZh6S9bxr13cS9pL7o7pMvTJ5fE0zyNcmh01YK-aKACagcVfuGJOCGwNGlMhVxNxgU1MStRySUepSmIsWskQuAfi-FXvZcfc-aOLn-XX92uhL-GG6biQis459reyAa0gskY_E3IkoREAP-QV1O5xTEri8zd7pNSpahwwGP9v4Oae3YVgGQWiNXykVn0ZUscnqVJmCieiVFPAT55DJ7WQqwjCLaqwthK8FTo9h0PkVXgnvksZB7rGe3g5eQ4UNypMblxgQ-tsUcsqMmZk5j9drnMnp1ENShQKXiXINGJPAZcArybGezK9HVszmLYao8T_gK3Vp2Nk4gPsQhm_eBSbDp7K5uRkg58zeKUPrAgbymL3tqwy2JSMjbgjgufk50AyZx_taxjM0gAVwneGGh2zGakS3HVu0bg3gOIvhsGnlQYHLc9bNzFD1Wk86v6eQRc4rJNzWrMFjUjonM3-iOzP4H6CGDTe9mU0YsNVnVQieAK7hbFga4VhQio3__vGQevMjrOWSdlk5NtOM4LqgJ156jxLNHntSVSvisoDH7BUfKtvUG6TujOFW2zZE8YRjMb-umDHn-pWizPU_tQ2Qj2mn066dNorpk79vnMrIld3kUp2K-ltAC4yHoxq_8NJL4wXnAbLy7kOIgLGP7uQGASA-9zLTYiLdDMNGLeWirJ3PHO5VIWR8G5CY_-Qhseb5drBGyKCkABrmoqrBaOBK7zA5vrc6Cf2BFBzw-NvsJ8J3s0nTDkUzw0XKsNW7e3N7Yie5gT3sVczO1dunNiDzP-4lacWYc8NHCi4sl7QlCbJxDwAC_G7_hqeQKXQRxOmY3yhZUOy155u1tY3CznDI5e__oEIjo_lr60KpJAPb3H8Pjwv4DQUvfXpHRMgWRl_Nwr_-Ppe7fhwmZqyn6i7IWT6ABfQN3xfY_LrYUGXe_UN_f76_byo3Ko8E8Mep7JPiLZE01zSRHI4z3krZspS1gK5BbKUk4ZqliFfcKhSurGe9fQt6dxc_beEfVFpjocZ-58PdVAQX0ZbcxsNPcZBLzAwtc7jjmQu4nSHsXxk1K8ndS8TLTZ9LOcbooiGqmYsZZwHZhc4_UYeo5nM3M3QvFbLSOB6SirDPXMVsFwPfBcy2lWQ0lFqlQBdt-NVr8pydi34WkuFGPBpR1HoFBoyNN47L76fb1pT5Bsgmdzxfxt0Gbono1eQ6wReBIug82Nb1wEmnaXNmOxwdsu-iuPXjWLYoidtqdi28KzAk2jG9qvb5pOgPEqNsfHkOr_IZkTKHuQjfaAvjo67L7AYlx_4EbhR2GbrneDWwn7umFwnKX7102Hh10fdVuZ9L4qDIt_tPMUBMcwoA0IJATWlm4GCdHFuW-28YdQm_m6ah2uyTzDUjeqmdIxjPX2vvfwSMl0QNRimZi36i_GY7E3QJVFWer7u3DHAFL3LV9SMRPqyXbIEe-L34yimsCXriJExlu1yMsA6917xO3lXJLrEygSprvE66iU0vEMyim_td11wlV3_cLf8mPMV3hKsx2jVDDzDbvm55QBPEI9uRTmKoUlQIAyW5lHFqbuvnYooiSoIbFRQXXKCqW2Q2IxQXugIv6DGy3uSwMO4dh5lisrxawJv5-MAE-YuGKEAYM6grdV-HvUcJp1erHUKwETO46INKkzRXQvx3ngJNxMq5PuAnx8IXPbbC3vwvyljHdSe_19ERUPNni6loSbwukHPMQrYwv2GLfFDwinXvN9ChnO0RW6kGYUSW0XfRliDgGf-OYtagKiExWfa_B64eusMjYYfzgmobIBnWzsZBsfalm_72k_93JIKD1iurKBJ2592yoRW8pkxwE_mH_0xwHaFVRUVk263GBxMyalEAViE4mFSbaihV3aL21EpKWv_xMXJgpBTO6FkVibTWUOGI1WQEeIGHekI45Fwlk5ZwLu_1IGetqeszX-ZBHivsAi8mj0-1","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0a2ac870819fb84fc8345280f7b8","index":23}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQtMLIo-4Fgi-4RfCwmU2mnsNHsDoqkQeqex2gonwbedGdcWEXdQ9E3fgZjaceEnd31HFDRITbt5tv4a4W3dyIxaFSs1PIdgCqNGJLBbWmcFJBzobP_66vx6xszR6c2ip9rtFDASavB58VDUAtnXIZB3bALm4Oc2_uj-kjW3utI3PnFVVcIwt5h-xYr2nGb6r0pmzUqV1Yu8TUY7XV2OHQWyAZe0TKP5dJH5KbVx1nYEzZs5oObn6FmGuiMEqAEHNwNPnu2-MU-QO1lOMI3MCkNHxXNxve2PieTKI4oOk-F6NmMsJrjjX3sRujC6LcEmgWVNMAr9eOWf3z8hZ11U7lDZXRvGZWHdJ9OU_4cZR8ZZ9W-_G5jhu2IQDE6cRU-MR3z263Nerspbk86sTNGjvEtyL9okb2DJm7dw8yNu9_1x0zkcwNF_l1Hp5txN693E8ozxxXHYbjUcmviHWbNfGMLK_ap-otfeYxzV7YYhKwLqZFRGTNAA7U7cYzQ4EiJiDhHGKZ1UTepOiF2fhKz3f2gT1VRR51cW8yvGawaFWJWkVgDvYXdEp2lNAMrKMg-jQPbiNJPF1Fxo9MX7LV1v9qeEHNqnoGuXLH-IsaNzZRQQoRq07eFLQfqC2fpqJAwRg8Gw_rxgK1kErWbH3vmfb8NAMW7d7CGZxnurQ9HNIQgQIuZz-4oWMgSNi-zLfWt2XrFlE9L7IbSIAgvVHYm3NYa26te5Uned85glmYQnEyHkXaaTCXC3P5QdHyN9u39H8O3u0usRPHYoA-4mhPVsNNwV0AxuRKt3OGNOafv_NX46M4QscPT5_V4SdlBj-Hj-NCumAzo5lvLiTBIyaMZpCpWJdf3-es47FL6MkBPzGTwwJd82zEEzxo6zvgN5Tbb17NZIWzQP-u9XjSTOG28_iefbqHf4OnPG-3gacDQOVHik4tJYSBpyQNzPMMccbQHpmjsXy_H0QObz9QXjtgKifvhL367fmlEfKQ16bZ35MzJGlMyM3hxidapsA0GWa3-qqUBonAIwWJlDEkICoQpJgDAZhxxxJGV-6nPsGAV9YhE_V8TuA6QlybfppZKux51A3jZsb3v2-6Wgd_es7LDVbDMbMHubSU-LSOEdnk648KuK54ioXJAusn_zRofjwSm2oHgzPhGEn7vaEd5rFmL3OutHfj3z1bwi9LKyaZwJSGzdxFikiAhaSuenmgHnXpRzhgDeKHj15RheCbgfdGgU59sCAuacs27swR2lwiMcZouzt_RoioU4NfowICgpzXQQie0iS5WJK5AD9Mg4I28cInwdapgHBr7KsYS4tfCLgCAUPL1YTeeczLjWOXi1pwMW4SLkmSHY3cAyaM0ZCcRAOxs5vvpgh4RQ8aHW1Q0mXWcZ8zehxSLqgwXQ2PZAcJkPhqtHJcUBp0nuo6hEbvS4BhrIYwcTRCVAOKGLjAobkpDIBah_RZA8ED-TDn4l6EBRSGqamTMvngWgRJWPer48z-eMwMvWygbHlfpqmSBsrTIzLFr1fewPIuP5O8BhRqyWmP6huCTTQ-AhWFyFNaBhZh9m7ynif-8yk2LvCV8cZMaHsJLklF5a_DJZF9Kd_Owi76xzgtxdCugNa0KZIkX-D4zAKfK18CO4rvH9GqwPqAi9Yrwx8MeNH4Pb-C0kacimd3CiovQmySD9BopFzYqxfKeYd2dW3uVDVK1JRMGJ7gmRz-Spq2v8roc6VI9QxOSjzlpm4D1vRHpnThXg309DrpelV5y5M9LzFCsugmtmS3nw0l_IheFDRRmlMk2DCd4Ygzck4EUNlKbh_9Gkpp6U6xJpAPtI-gZeWbd-tFsB3YGFAfpWVPePVdzPnH3TQA5n37h4nbk_l1Vfbcr-elm8ZQI7u3cdDUfyJEnwcJglsIJnSJWMW9avUDesELvOKBiamMlNokVYeDnvp2DZfbIPPgPDytK37UrR_KBrlQQgCnJtYBUo0c5tR_ow7zfaVMNfSx9N1x6O6GO3HXW4waW2Cqw5YurPALK9AD8LFogPvEgYBhLKpdVQtevxg4zhml14ScVkXafCtcILiQX-298W_yninTfjn01HkF-v_Y1a_bX6drP9AwZMRU0JSmH8ElMz48CGE56d81cM2icElm1ddYXJa2sxfA9_r2YBrIFZeMnqER1ZS6Hybut0QHpycGIjt6dizALbklAIiZu6fR-9gBXDA6f8XMTvm4ns8KyCexQgU084p8tqLl4YFVaEacWTepGb46PuXFKAXbkbiU79DzAKoBvE45w5Rj2E3Ws8wM7yUSDEKIkdVgYCBOFJA3FNtbqrokDcttK1NtFixossnc_oHaSVaW2ra4PNTRDgoDqdWQam6EgnJHIpXJk3OOfjckjBkjyr6JKrF0GkHr6PzglvfedKjaFplZz8_uugN7VOTeuLFfn6YnTkPM9WQ47VszilfddA-xSJc6Rw5zoJBQJZS56TJ3egs6tU7w_X23Of7ir-oKj7JMSPDCuCv577CmQzxU5k7LB4tyBprU56BrZPTnl3WQumdTD2PyHwGHjxwHTIs4Ifoqz4ZJT8fti0jBXZPsQ7ft4leE41HM9ls7SbLrfIaLz6iWRFo0EX0BUc-ok9_Ds-lz3HCCFxuc8SWQaihhhYMnMGBu-_Bs7VMo_Kv48rLdLHN19ALxbojTJ87iGSG-NcG1XPwjOO0MCAgebkexkXxQ9aS7N_nICxRoQID0TkCsuTopLFhGKYH6gjR66doW7KFyOFwg4Q2hzFlQcJ7cyjkwY5zKELEvGJHwVVGjEDwsnetmiN6VlWdsdZV-MsdHPOCGCjYDM1TJ8Kc93eiyFtAkATHC-m4uYc6cB6Rz29kGIozyQsjjJMPL6SRXjToMrOs7MEuVEqTm5-ep_9JHciW6bI35z0V9oc_MAv4tekEJxoRwrE5h6NGwKjiYyZcB8jBEQbayFR52g9ER8a6d-DxXNCAEYjumNtYTY9-C4J6acoTSrMEMP-nYa9tY2IX69x4mISh-soqDTer2ugx2560gnIYlv0SZYx8DTkPn1E2AcyLtbZVQKn7nd6o1Y2tYKZajWCoVuCR70YPWgqIFVZwHfnt0oREfaSVEZi9FjageYcm6cZGa_cjROcQfr_KkGDNS5x2YgfTf04mOIDI_bysBT0adw_9K6XoQP8vDzKLVLXjyPNIMATJYLbi3zWO72dQeJ5geGoi6X4jb_X7LQyxCo82CBAukjhcVX-cc130MYwEiUBIqbBe8dgGc3gACVxFamrCvwMTRHWXpF02PmURaBWOMTLdOqPBCEVH94dCRWHtO_eUhpFpJgmD39RL_u0sBPsMDaS942HhxaPFuZC8i6twGEDAf1jo2v43w-uSQV-3v68TtHmD1tNS98j5_Tru81FHNpd16iHo09xmHlyItY-HGhv1iE6oaEqL1G4fFaTn4UaGUTflIRoLgaVJLtf_hVQgX3ifPhHINNkU0xMvckn4FyGdMkG-sgwtwSPhhjHn5WLpHnSADpJN_RFC3Qvqn6PFwWSh2I76E7ufXS8p7pM3hCqH8jY91H-C9e4MXQRZ30ukOUGNDetV7NGC8WOR7Mk3sltuYEs40vu7ALiX4T_I62ZjSHulgCSa_sERK-RmwHeGa-9OJYBN2hm1xe0a_g_mQ2GQc1eXy9fCtEbX1P4ZIqTjxophw_7_ev4d7K96Cd0t7ov-sioepdhZo90i_LUr7FZBIh5XYD_pXbtWJOR0iZqewY9t1x3OjjEN3q3oFQgCSM6jmHhSXYmfaNX0aMhgmnDspaqOuXR0yRUnQEbCkwKW844pDStPfmQgmmImisVZL3TR0RjbjE8a3rC5BrVL-YDbEiIbGcuDYPKqr0o8FoqOwHtYx6tMH9_k2JMcWSlIKja0nYcc73XYis4nF5zrKF3Wu1cpMa1RwGyafa9wGEQovUD0_0t1Y5dv_KhCxyoieG2oBtwehAeSPk16_nGnCkzhHJ2ZAU7R-6cQtCs3WJXL9fb0vWRNTn0fqaorOI7GeMUN_usI8_9NaVONFziRh3xVdyZLJGhPHKsxoGxyEnNiqHHAkF2Xx1u06zRZJMTFSRkcFgljLS5JPmwYXqkR8r5TTLr6Kq3MBDKIdA9zmB6rUDhhfINoRw7gTy7etbRKkKaz1p5Zp7P0fjM-Vz3AZOxk0JNU4QE","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0b432f28819fafa035129d88896d","index":64}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQtfXpGpWlOSG5WAJR7XyaVAGxPH4pcBVTgR8uK1ZH2Mju7PR3Pk4eo1-zzI8-Q9Yg1tchxQru31SCZsgjxwqEYt8gDnGYZ730N6NBA3rx00059ULZ9hKCDnx-9R6s9zwSkoVeEss4R7tXzDqKTTBET8-jKt8Fiv4RNR0zB71aewnd98MCKnsKZPN8nXdvk8Eelcf4StZQfJ97QLtUzCaa-HhvuzMguJAJQ-yaAKIM9A36vmML84P6lf40mHZ76ALuzNpij6JhbuMyDUrcKHfkuymeyxGYhBggKuv82QRzwSMOGeSQ190kZRhrlpKMN2zCEHA9IRlDHc4DlMhie3C2DThnN28DYmIeWeaYcRe5hToV-sj_wlxE8A93u4KkzlczPcZaCgGNLBqWzGjWTNyKPC3LHxSfd93wvjVPPVcQ92qveQpfPqeYOCeDWglSpOT3ZN98bwBgpaYHa5IROlHJtlqyOiSfC4pT8fJiDBfm8y7zEAxHZpdh-Eby2SKWpK_YaleQkcc8DSEJsYyK9V1IhrGukgrzBSXaMK44TRPa6L8cFiCX2fSBVoQ1TjeeTBqqf0eMFVr50t86yP4yL5lD3Wva0YBrzgVzl3K_ybLd5s9oHlpI9A8YAnmYA_tjC_1ZvkF9QPmArn7DhNSDUj-ud0M9IlIBhjJtSVXHeeYbKW7neEExP5quLsrMFjVptd0ri9kSBLjVKlxC9WBDFQS43LgFNLMx-LHvw31irYCImM6bVulFW-lu5PV3PiqQUDJdJc4rh40nj5Zdrtleb5APmK7rf0kjXtHeYAPD2cJz9gy6lmchAltpNhCSES3tP7k7pzx4dlPnU56FFIF0r_E-a_NaevkOx9UUJ8kvgx7jTaYUOdK9RHrKLT3CkEoyiVvXT99LhuTYG_wQacdFE0qKdYWhQJuWuukTewnEi55PmmlyUox_SGNbrHWlKpZupmSBU39UJ3JLlO7uyxOucJ8TRdT95JY0uHE8acED5jpJCQhX5x0x-q4AMtLsENZ4RcgrcJ1agDNc88v6mw9ewIb4d-uAwx6EEgk8Kt7U3d6Q6iQQUIUNuT9eZCBOM0w-rkqqeqW9aAvxbi6U-o6Tz4iMSa1i06y4wnXtTAWGY4fl040R1JAAlOoLb9-EFDM8sGWQa3dI9LJZ4sgJRkoimbr2zG4_jMDpwIqIPoco-fquqa3jtUR5yox55M1q9dg4rIS7qvo6mMnlm6mzoYnvkVc6uDQuKcxkE0pLnzMdvfY6cn0dv8Be8GFFiKWT_lBTZcScDrFmg6BebBP7lO9jsVo6Pmx_eYwLKcQSAa-5tPmi9rOu5b2_d7Rq_5jBsCPK_t0iTdMtzY2qEHK3FxdpXx0XybI7GN_oox1QO5KINwY3RS7MmDLi7RRyeHzxSAlzeU7M7_qC_300nctScfxOc0FsqeG241K_8U7ulqBYe6aVuL3mYwY90iMIsy1tCDJtLhCFt_ey85m1DaQ_HyLNnpUkVfYo9nAEuMPZUXk4xqCqnbhCtWtL10tjN0GSKjphv0qoaeMYtcaDPxavNrOdqsxVloMGOqTKc-7d5PSjdokwMQmir65GQYaej1OChJ9vN4zt3lT9RlIWTCh4VceWFJz1I1334koi2CjKClbAPNXI3BQkdMmocv871BOH9s8qR-6KJaxTtbmtiLAjr9hRkphI5nZKGzmuO16l4MfKQ43OCB-AbW0jXMMPPOf2JO1HGwVDg-xp3AuJBZ7Z4NBIVJb2qXtsoocB0lf5i6Xss6Fj_3Os_bA1St3VqjwTyJMmljrClQKgCUBUwwNS2hQ0GrNy2W_Lpwid6RkTemovT1DVKavqXuinc-lojYdtOJtt9ijdnd3cajoOSeXWVN7iZQMJZ_QXgSjLz5wjNgs0VgFAK-LPT1e6CZisGcUUPUBE3ymtn7X7B4aRY3yLH-f4_T8q9aGA0ncKY7_TFPxO5DkFX8VUlI7iSbbOIURNeFI7XCvnoo0CgjpG69k2EGs9N9ZN3F7K2S5sEjzWtUGDExbO9ZFzeCTdUZnsSj3zjBm4t7LT_NPSPwEIuQWJ8L4Fww9Sw9t7b6WAr6GfQ0YocF3t8bJPLa9-YI0Mx5dt6o0KJFhGxnn1hk8_6hIUm9OqPqCSqXWfymRT7Aliloh049QGZitlu1ZfCdS1uYAO4FFi41NC6feGGiR4Oj1V7JQf1FwPG60HDLyyPyvGibpEDVi99rKGakMW2eFfcFuSgaBjgQKm1qqel_ch89mb18O3qF1tBoawU5k_nCPR2tcjm7JvnbOganOSPifBx3Lznd8nccuUFGKiG9m7WH2VX0eWXKtgcMZNmFzYbPW_vgs7rUzHDKIXLguxJtnC086olJEkIaoqTLgD3iGr97HWAZOsRzv_wsaapDZg-Nkp_7cJf0_Mkn_OGzGXrFC9IxkX_NS0av0uW9VbJmEfbOaI9CTcWFonSg1ityyB27ONlqTtKVdct3xJn7FpSd4znM2aGy1ZXT3rW8XsWeTQzE4I3VIeMjfi_1tS3s2I8YHr_FHW77R-vFMR0U4IbVQZdDf6b6SOoPd-hEqkl9bZDmA-dofqCSZfcdaXhCKEFYR5tWSsHy5myvDVTsbCtyUzUt9sH4pl-6waw-ePU706l32jOfNHK8p8tdhX2HOLeU0UauwkyL87wie04F950hu4egrcAkqCsYWKmdCoeZEaxd3mYblfc6yRmDgWIyS_ptt_N7uCjIz0ozOUhntHD-fFdAcFmmp5COzvQO1KAOSWdMmNm73Igwvxoss1qRZYxSw6o3AmD4NvsJUheEaAxObD0_CCM9zWiEVRrw2jpA9TXeGbi0V2IecS_li96LY44Ga3dxkUCb3DTEFt7YNbxkLYyV5JdbyJd7R25FRBIgLaMH3q89X9y9TYVZxuqzQ58Ty1n_1mjBHTd02kgUmVgCDLBo_icV2Ku865yHYYnubeTeJFGjynJxgDH6mgsQkl6fFU1RNIfko0M_-aCSvwSHTvFxmEqx47aOA1KTqkRXZX4a52A22iKBT9nI1Xe6bmYdej6QsuSh5JQShrZGP8FlDYRw6em1y7t3Bx99cW-LuLmBQ0-xVoCSNWrDTYby2EdieT7xZPXlZjU0hFDLzSqYjqajREKTe13DbNYNCZkBXpGJd9sRwTd_BkCGO8wOvsP-IOY12wpzkQqUJKFf3uPD3lQ3HweWLiR8hnW3e57nK4jOx8AAegg9gr0YMOWf438E_q00Yttho7-KOuafWejD3blWm-Arm2oWP-t84zDT0Yh_CqrZeJRbzKakO9ONni9njpSBJ1fHY0VOo81iQD137elYRBablwyNMPsjr_-fwSoVjvGcXMuYVuXXamlY28lBe1P7uZOpoevv8-6hUo5Lykfm4SPiwxdNYBIqZ5OP0_fYg2fxkkxuHxxYQ2Fw0YXbSCH90xDw0NxsMZpcmnF6z_3VelZ41h2c3_S78LC2OaPMvANTl5QwF8IrSwljowAoyoLhW9JZhjulW1755aGR6hQdv-OgmC_BC-_6","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0b555c6c819faa31d67444bd49a9","index":66}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQtyUovDD5yZFM9JcM1KrEmWGQrLi9HTaw8xPz-8tgir_VwYGYcbjPiJx0iKpzHplnMnXRKBPdqetyHHkca_7cdbKe25wRuLSQZ59fyERMcQ_ClNCUkCCZj0Dr-r6LA8EG7f8-SUJ5Lvap4anXQKrrlVomemgrbVr8Tcd1Xr57Pmi9dSJZ8SxuTOChc_-QRkiZ-s8jv5WCErp8xZLJ092Owj2XFB7R31GC4fjvbS0bDApR61NNboUboACtk7jW2lZLblk7Wvyb2D8pp_22sfvWbLZzXAzfY0IFuLRadFkTjdWQcuo1fWo9ipFuV6xcBCDOwSDrFCbTrCM-kPMopgX1dbgdSGNnPn4lQM6Lh7G0RlkFwekyx1NiwL7MCxpeFIS5XxH7hP43bNbejncE9CFm7Da8sa4jZ2hmj5T5xjjInW36LTdkVZNZkhUDovOYQMsMhC_3qxFSGaHgT90g0aa20K_xF4Uip5Q1x5vJxjrnYV9lqrlb3m4vIeZggmYIYNyU2TgysKD6oSkB8M-95_hKqAVFTj4-JIJ6m2vKpl9zhU9qBxI753CC_a2K4U6W-Xk-0IcWQyvNzM-PQyunG9lV_0qzMz8dPoIxXJldiBW8sjtF6WTXY0Km8VZAlKBuU__4E0f2jtJmZ3L0XxNbJY9qg9IlEtsXONyfQMxI2Z2O9Qpaj5GSOxcBR4JUJJ4d1XlF5wv3Oe8LzLJOxdOjrD_bBgqUfXlQae0vOrHpTZ7qINfNq4IhZw8iiUQKjMJFhV5bGcSk--OnUnxGKTHGxZ2xkNBdE6KP644RmbuG4MEdqEEd4mRvr8dhjXNW64pK2z3b7WoUtSSfklVTg4JkPSHofxAjUwNvbzXP3vTCrEOGREBXkxvdHS4I9x5mu_5yvTxvZ5S8GMk_FPAYp1GTKsKByAokNGEvVsNlgZYnr2J2aY7BSSvDW9S5IOLvmG5Bw5exFbTJHp7hh9cbNFHChK5ZbSd6NRJ98Qs0GlihjAMlUPdT1uwW_QraVmT38C-lvo__PTKa6rGO1VDXvNlVe9ujFYMwJs-b1nwV4FrEuVIrpKewdQEKTIjGbSy56XMNxp7E1DSpcUejIrmJGeHnIhxry2TuHkmk5CQnTMwVxINxc6814MT0f8HJXRIvgBbS9yHt318fQdeRQFrWan06cq8YV3JJrytWne8ch03zJlKY60VFYpeJdC_vhgzwkmTBQyJOTIiijwGALaKr80eU0bDBf_xlGWmBNpEBFPmrDAzm2QZsfcPqH-4HQ4ts6pxskbwsbIadx4XVOwCtkAs1sJ3HTQFAkQ_xcEPaiYs0I3xSzWoNJnYaGhgO6z4upIHM-UXjahKDeYlBNAvAhPWV70_p_o4UeEA9X3A_ILonWF_uRnigSND1UNZafRTyyutaOL4Ra5FpFFK6aUCnVbRYwfBSpC-wta3PMEOpKuISuAnCThH8APoRKmUbg6jSmwagTV7KO-B2iKUbn5KGtEIjrn4Sv4MQ7ao46df44MPSBHil8FuH6UfMiIwPZUgJGSsqCVqmd3sRedrvU1vRFlZchXLKcy4T0lS_597yhZoyRibyVoGVwTdg13XIQYgOu1PlBqWmLbPqF_ABlkZrvhkSBQCQFaiPz0tqUfMtetPNYFfhkXBmFpy7B9eoU2Af4Z2B4cc2haogW6tduXqm2nJlNNb2p-uepouOTlnjeKX1Z6SFkenKFUYOU9SLL0QmF4f49XfLY2eKnU1KmgHdX0gtVHAT4bBhOR-RLbZ3_z8aIgcLqQXf1jZpR19fCBX972CCp15t6n0laLYEeIkxlP6iOLbHLVcKnX-WFkUD6Ri0zp7YC6MXbXCi-T4vkxHEuHIQtB12wPT2R9sVTtygz6B3h7p2GaUQvXMhGGwrzsAmlelMWTaF_uVjYlQpyQ1sVetRGIWHSOn2ynX1VTmWCcB9vNIUjGGBkbYFtmfCEAxQydqRptU-zUSaIUTYk6QULJeHJUX3xQC8dIyIB3sj0fctzI-7C4JiUp3PVPVfRpN-sMoegOB2hC8aGEN9-JlEH-Tgv8fqvEVnNJj9MBonIauxkJlm5bqSIA1dVZzHwwrprQn-jF_WvG9EgjhQxmKYvqYF-74dMdz4yx9m8yHvmzsuCSjVanqDCcSGtDZhzZjgWQR8PTW_2JxbKG5zCfbggyEtxh-Kon6run1VUaHroy6uZyDgBCAbW4sdBcpP7ORImFqbDSoajoajUfOHyV6KjhWOaBgpclrZABedfYDYk0LXOizqKgjZKjocTXcOgUWm0W163KcQITIzwscZ-Y7y-euoa8lF5FhIC_CPEMPru2IWhOBn92IySIsUkV8uFnVujZa-VH7Kb3F7VXQKfVPIJcG0PMoAkfcR7JmHx36RPLVfNZYmaGir-1gUFPFKhGXQHjQcfLVDAzGpogSYStFpEzcRrKrzTtK3Y8VER1GL4LnvRtZm-PkZVOrgiZ_QnNIxA02Erz3LAkcDajqjZTk9tG6gTSnBX6-fhYv7RlQVSRnwHTIChfsxXhenjDvcQtZhoZJKbyKgl4A50otzYsbryBEGtZ7Ag-84XxJlsgGEU5wveTxZ28pcSCvq1hjPRane8jMYF9LjC48bVLIXLNN2nkZlJVdAUdGf1Y548iFoX2exw7SOpdwj2kjed4eOQ6sm0VICTDiaWHvwkFxB-o2ub9QsSEyHNnXj_U40BQ9umrCCUscxSdLFJPAGPLoy6Fa7b4TmAgOW9uHkLvFoKROFJo0whS3KviXrr-ApxStturaNEalUxn8Tn5dld4lNCYsdoftZKV4x9TdRr_JtrpAf5CiY3ILIWYNSr1vpMBE32QgLL8LGkINW-OWqmJpaN4MFI7sTV1xk8Zng8XfggKc1Ipk75rFh4dokr_bw47z4HMtTc81op6tEQouq9_81K-h92lNU1lMfdY1abFfWq7I830hIV_wl24DRK0oBuEqTty4BkQs4exDdRp3eHshzT0tXFot8UYHTcdkGhkaUh4Mwkdv7zslCk5o-3X5Feo9Y6UWTEwixS-kxWSUiW0xy5PNUGN7Q-WkWDG52jf7YyCP2gR5FVAciBvpJVh-OJni2pmE9LhxZufgYnnzeqh4cQGs4RM51ZdZJy5Ovk8bTT6DtEZveHqUOMA17QUh6jxDF7m4mapcS1dDCNLbg3-S6ugQaGWgnHkppT25kqE5h43WVdfL26AUYRl46tOi5FNLY47k1l8pTlCjcerb4Vl8Ipldps3sp0cR6j8bboRLzXtQhXm3sGrPzJf4VBEFLpUBUklhFAbPnRXhuCxlarcdpRYVtYoOqF9WVoTzpBVGHAtQfNrfcYeuG6Twuo0RmeM4jnNN0GOoNlpFN4sUZ6q2WlTPWL7D0y-MyUqp9VrAk26n6hYfh3hFNYrviYqsgGKIrJErh8Us_oDbrlJqYQmY6meTDKXg7xZJgwYjB3Q9qyiQ4V3l4U9jIwf6B8MPJ0lkKv2JLmNELDIbDelRc5nAUyiVZhWBFIHu0e3TTEuYFDGteGK9UPFnXdnsDa1nlwlFxZcYx56Vm0fb8QjIR3IWwy_onYO_MkiPYoP9o4YWuk-vBuSslCLxF1_63I_PbHDtyemRUnfvEfMQ7ZwoEt_Hr6kSRUy6KzC5znafj_SVIEQ7MyhEMviQ3ClXdcUE6bIywHTcvop9diLG17aeH6PKHTRh2q7NQ1anamG8rk8xong36fQGLY8jriZz8oKdWhdSUMm8JxsYJkNMAaSYusXPGPcK_RREqtiU0WssQnzR3J7G4GZSITfI1z6_3lj90MSebGpEMD6N6kU9C5Jt6r0qD-CZIT67Xfmbb4kUYaqmnPitLhmvrFbOaJMfaRH73WztV_-UGGkHjV5QOvRJ0oNspI4FDVVsj8opDSdNPFfVcV_PW3UvYyX1fsWXo3xMrqno9ox3K4FJ_CZVa-IeaImczRWt-3pBCQVcLzJtHhueQA2bAqfeMhqh6dMIE2FqBFSyVIjoxY5SNURIIY9eLs8q559QX6R84Bux64u8B1mMrKr-W-inDNe0C_BSSadozPJQU8lDbM8Bq4ISQ==","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0b689998819f994e4fd722294ab4","index":68}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQusQvJi8JtmKRMiaTtEk1-kMBQk5D7H8Ox1RfBzTaTLRmTZszIB0mcSoU4GDnzZdTh9TzOFXgVpvNlIEjJHPo6dw98XX5L_Vj_NttaP2vSai2FBAemvahpWbh4LjwJfd5-LcEQuDY10fSPZ6bqxqlAoE3dLAlrK6HQHX2ou8oenN9_zYZUvEkNLoPdZkA1iDXWfvQbUvbRr_krKpjxrbEnPml1P9BNC_DJI6rVGzTZOLjxUTi5jrX_hIKvaOa8UBJmPlcbOojd0bs63Q3AQ1ZWymeIMX9QIltgAaqWG81-yI_HMW6rJoHY8gNp8M1Ul9b6hXzAVbNex_Y7XCgjCwk1xauVSRE1TIIyDqEl4_apvNG7MbB6gSQykLjFhLbGCVPU-tqwfi03eyD0mVSBaYQyHOgwwWZENRDO2xbyfQLVk-U67EUXd_jtbZVthPcv6AEZTi_IGHU0KYIDH91-zmHAL06cEQv64a0yEwvJFkAa2GZeDZH-R2SnMkDNoSn1Ks-YLfLqA03Pzw67AfbsGWE65x00-tPbCYkzZ3kwGt07oMKPsW9xVpkdPqo4zUfPw4iPRtVZxe3Ll-ZDt9wsJN2XDl3R5SGTvq4Hfghb23CpAeFxHGCi71NQJ4ASHpkWuevhRME0GATHtey9nv3mjGbzzwisqkAb5y5K2kW__gck3Hq_WIdWZx-0T2KLMqFHQcqvtXd2zGNsSc6SQnBhyeWG0Jj2UVHBVsgSGo2VhsRNzhzwdFnvOdTnwcZey65MHulWbOpvFyyoIw7vB_bRDRTIEtmb3IXMgYufAJiXN1b78v26AUYTGfjnL2zmjX-9hTxO_ZgJ8A7wh8RwkQsQejI7NIrzn6-czlwZf5ns44WA6hxaAdigtJvqDPtvAHbmyaN1BmydbDK-oi3Kpq65_qegCrrsDG91lsGsZouH6p7AaoQGyLxjgcSJ_5rTnL0hpyr5-Sikn_x6oWvl-PvVdxeUe4ml9xe2KJ7PM0DYqQJmOgwAaEGxltIDEZqVWPb9TwmPjzJjePRhWfcieZO6ynN8tUwmB4dWA4yQkQwORP3h23_UT57Y-fAquOKz0JFdTub6WxciDvWyMoZUoheO6_tuzxemCFqePllrq79c63KT-I0LI4WGEf6ozX1A-v8rZ-OXa61QdK4N0WR6TFvsUzdkin5rXWTPSN_pop3AaXVMmpZRuN5jWNq1dPC4k21vhpB_5vz_0jxy9wbg-1WI9tmXefnW4fwlvTiWUT8Gt0ZSDqQ6pOTelQX5XLLzd3ruBIQL6O8nxCTswj-NmRQJZ-BGPfnl1nRoyU0xcDrLVu_6v-ePSVepUM433lVgM8DaocqWJO_A6R3jsLcM7fnpOohWALrrqx0KHb8mz5bzcqSRnPzqxWYRSng0qLvRGgWXjdsJmsGM-vUY_KVPd1FNQ2fVf5cF-LwbIoREEI_wUhgBU3I0rNyaPGCORjs8iP2Uva60vLgyOCxzo-s1GVXsXN7Rvxz1oqmsDNVmer6OA8xjC5_WdR0p7bbWcRvwmA0-78X1nkSzFO5S1p7opfyqNYgFvFRjVvHsOGm3oiCafnEPNI1DhXevmz3MnyefNbpJyaNlJ_TCnQ6LoIt7yOCSu1AOo6BonrzW0FRwgVGTFIputOdBgu0rDz8kCF8ncgwT3YrJM_qpvKdKLOkV5WEBKECVlbQspW8WP8c3TjWeDcI-KS-KbkxChP9a5f6bzI1ZxjaruGl_LoEAaOgGgjmFOiyVWS5kHGssX4KT0he0gBhjMlQq877oYTBhNYEZY0MZpEKxnkGL_MSWN89N44AzwgkCp5hH1fRXQBJfCHnKeiiLp8r5zvhtyiNBBsI1JlxQ_hovvEAxQ77w12j4C8ziSu97w5GWQTxL05M2E-TnQTDP43I76hT3xr_ApTGzND_f7Reul7RL4jnrD6fnYvCTaHwrWNHoHteVf5w0DJBmQsD2QtPyJFplkZVfzdcem2bodWUx7yHVHqxdBPzHimYQm_EuEC3bisgBuu49IxrkHkFd0_ucsAsgc7N6KkGH_3IPieEic1UVbba25DNx6qBEii3bU2r8f71V5Zo65k1T8mBFQpVBbKQZICGZ3QwiWF8b8uR_GUWLbFTKdB9AlRwN0GCeukRWahIz3kDYnuO94UGhlyjgyz00S0nTYMc36wrMz3cTQTUtxhn8A2crRHHOyysTax9Zi3Xfr2OvlL7-8gWQ9eelcKvKsoMZYoeq9XmEIZsP6swdaD9-eZpX1DxvPfpzMDPwQF0YPbGE4vp1XgKw3dtDukWXasu1P_cMWvjvKfMclQjlXt9AAhNI2Ol095ax_Yt62ujXyRGQU66eSVQgWVCNn53T2n97_2Wa_KmKcCOJ7c-RStj31BdL-L6kVILysvjSEvje9dn_SlLq9ZvY9TpYRUVJFhsK-LMEsOM4g-YIoE1yrgVGoZs-A8_FSgu1pXEHDFBbZTAhVcca8lpyyamw7JFcBVf7ydc3aB5ZO2RK5ApXcrbQ8NrK1rqB-QVAY8f7VE6RoDbZaZzKPpHR7lSfIsANDDkpjEmNttc4GLw3UjRSJm44Lu1VXn_Xzlk-f6HiaDSh5Z1j5sIeMPAR1bpv41qN7DTHplEZHtoDdS7S2celCNK_rc76K3ykpYnRXxbFTsNTS4l11xBrCrwqLeg-tytOkIX2SKPBu8MNSQ_oayHIh_3ctJ0Qoa--eo2ulK4CezpEdY2wDxBY3cOWKTGzGjKKVd6_4nsQPQXYAmTnLErg4E33ab3QuqAd_Tqqy-rZT1dAN9tDIdt_8I_P_3mUoOzNGapsPMJd0jfvVfzZhUBXQz0pPPWZAeJtFvuHwCtVj63A3iqtjh-jn6AyG3bHHz2UzlX6kGVUbu-m59WiGNs3uM5BLHgoAvnyD7sYIpuRq7wvJhDbLfmWsh3vybXr2bPRm7xEdI9NbJJkaqHyjfJJDJnXYXbWVHhJVjYB_EBDRsVTaTN0aiZJ-BdArlMrJRgt1loL1Sy35TMcYYKPONX-riGavzXKkvq81FHJBnihaysEIFTyfTPW1jP7YTHKdkFNKcYrfU2_GZe8UduWCum2xUEGX16oam23oZnP8qAZc41OZokAvBtIrAPL-XvWEk_Hu7n-oVJlcws88Na9ed3QOXzRoKbcmGuaujMX1wykZUtQ-IyboxLJ7G0_BVDsQAXWsx3RXvnc-8T0ayFTuAnHSqLIAMTRfDRPbv_wzwFkv5LG3bsuwPc_50RhkQisKWSBbeY2xVZa8uMDNX9gH83-y7FkrRcEh0L3HCszZzyx3cTfOe6qtKtxeZ17oaDqSXLW9WaB6fy4ZBIcno6CG-bPJhxf7T9o-MDCn-56d5mNm4vUetOOc1kl3Lhww2Xm5GFXf_6dLx-Vy-d7ciGypjk1wt-vaI5FM2aCIq4VcB5PIQJgin3MA5Jq5PWVfwya6iuvfL-hJJrd4fkYg1Lk3jElAKu8WyC8VayG1aLmOli8R78UfZUpbWX9Y83Lwee78Pu0B4N4mtyJjldDvl0jJ6h6uvf8kAnOjXWioUiEUlD-IYf3hm7XDVr6pMcCyV6q2Tz46uw32MnzYarWMEidJ1BhLE7Yl6Q2eVbZDvMcb3ReJ_N3HO3724_HQrdZHMM8pbEEkjBFC-ToWStOkozwuED_DAz2sZayymAJ2B2avAzIJmK6xoBfIJHWsnJ8FcB2sitnc0a0FTEG4X_F3wUFPUZXm2JOjyuy4xBvX7DNlTr7s9AoqYs39raGYwt_wiV38YXHBufCK6wbWY_QYqUXC9Y2tIk13DAHnP7uLDzpgxA==","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0ba21940819f9e5336950a35aa69","index":76}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQu_qqF8OZenmfsgr4GsyQiJJvjX7lW7DyHF-8OLzswqbUJh3xp1Xto38-gm8sYje5kt3KYKoCykRIuULT9svNNRdIECp5WRGtXejSpDJGECwlaqn3-JH1-C5oTMUHf55anJH-l9kYw7x9MYJG8XbKYh6aXKq-dzAPq5BNp_CRWaMimxMkegrgguO0FVvuvN1yX1YafWu-LEJ1H89AhczhZ6ly8zCJZJiTNURw2tnZg6oWrPdXldJ2M5vcK1iT27t7DA1WvkPsscixqbSAU88AHe1jOti7iMWmwAD4vk1jpF985jPu8pmrsIexuvqCcTb-p0wh_BmuIPnMxTDLH0QupdkyCrNebM2DkvSb-lmgVUGp7uOcW-MhnAqScNGDHh9z0aEVN6M0FhGAZhkBlioqYC7Fgi1OisaLUSsPHnUYN4NAHlq3xFrYuGHXbZQsvegGzlKpmaJmsUhV0oM2BWMrLTnndloVcRsBmwKH0-eVuOtzrjlBsMssFipfZgqyj5DPxdaKYgbN_WaWk4BVWecQtzAYgxUD4HRsev5pz79t9DWMudSe3CHH8IiAbA1V7M7JtQWPmhAwW4rVwapTjVQIz2Dvd4KXF_umL_ySwHxSLLKIjJMRKMlnwAvAGpH2n4T-oVO4RuaNIxPSbHSsVn4xVq8e0vbY8bKcUhonpIStqVFMGsNunL_PhlsAu6Ges0dX-5L87AKoGN-5HvYRSyOmTWa5fiMduhdeQj9dyQ1qMdHCTD1ijOmWWyttKtJvBJBnLwAXe806IBqdrJo3duZQtnXrLKNz_xuZSc2QlAihOoEllYWY_V6i32GYm69dP3fMdUT_n3vJ50iPk1qISPrxLrHbueSn3hxbl0u6w8OaWM5rtqc4rYhzTCwZm74-_gdslsJuTY6aQADCE1Qnk3TV-Y31cfFyBejfsFkgdIiZZq7-hIFnnzVTSrRMfKxRNCLLUfnYjaeEwuQQ6AomTklwovUVw2meIifNQlMvHGK-ZUxNkYdOj4Wj80dOa1URNruZGzjV_WUF2TmmBfrMfgCBGrgsvuZOjEsJL3Lj25hVCr8G4dx1Pwl5-G3rad6hHRCQZbbGVwfVKsRCLBZWEhqkl54K5J2u442YSVuBH34tZTj6rHtkSagWqw6hdu6JpJw4dCqPJ4G7rD3BlbK44-d_v86vTK-yFM1gmlgKCgeRxVIJALuH1tVszHehdreJhWZEzcd6xfeoqJiAQFUpcMsDQ-cI5tE2mVpM1VCaeHv8g1SXlkOpBxthmR0CAmu1H9M9lnIpZatXD8CMVGiaqpJ1K4L_K__YmFLSo1Klwnq7N6rvNG_SLhryKWkqwXfSlLxrkJxqqAd_N_7WQsVssaPLSz04lTKj_i-WQWhaaTlnKwLtRFZpj9KM-mDdOH5fYQpNylQLksht2JUNTZD9Ztey-4DzG1ZqLuIx8drJSfSUprKDpPMJCxd9nKwPYTua3PnGH9aJMFOP8zmqrKHF9weZSC-5gQrukrOnSApRM79wYYpjB96DGH0C8p8MrnCX3H8X4XryoMXvc_T2T_6XwvfEJC4fb20l1FeGrp58ciUzTXbUO83ppAvt6CmX0LDu4y_U8ckVDuJfb_6BJ1zitg2MonreN9kgJw9lFYAD_fMeBoj4Tu0jBfPz-DKOnPgc6TMY5BGt7NCTjPjidtehjpGDpTHWH5P2ei7iy1IekomKlsMM_XWMIemt2lOKQJgeFh9IV27TZHUubcNuv6DUZ765t3H3xHfkM8X4-ai2u11AMIO3bEZ9tIvPev-2bK_homLShKOUY_F53FXtyDLvKXmsgTLBstK_o603Hnakbc5ryL8bZeXcSeTAfP-GATG2qizrI-8eaeONlYjFu9sj12k2JL15AVq-Ckoo0W8Kd8TQ45yoKbh4n4VA7rgPgHqshIB8D3-f9XrBESSrdTjUr9tjrcRLyxVHOIExpk67jx57wLKN_5HbtCA-qdOJGX7mEsmqH-kbjUtWUwRd4fIYP8cFqrafxi5lrvn6nWMAQNnmGB6Ncgnykbah31fqeoIO3ZT1OLLQuIEolBFTUKQjr-KMG4oe5J-uOc2MdckCSoipHxsJm2GErKdoAhloMDmeNZ26VCR-GA-Y_bm1eiQW7k4HMzym8mHjSFOCcJiUTYyPmHg0F3tLa_QU17SwzB2tb7X_9ZwAe81FY87Ia6IiTt9Z58MIa0TyD1D7nVJjf72iZPm5W3Nf9rxl8v7Uwwkn5aLT66L6WrNsOJQHeO8TNa1_dQzOHCLBhdIxms2yi4u-GXwYCXVGtiE7bfqx4h2-f4XKKMa2xHj1S752-Z8e1oSJ0x9PAnjzL23iz0ud6Ac1lYk0SwO93KLFDvVcTqOTa6RkJ9Vd9xkHyEsMVXUH_Ks-OnzaOMFDSIcHb5Fvq104YO48-WSkYrNpm5B-rR2QvyzzLw0SP6o028ES8OAkzpdkC_GcmeU7n7TjETcrLW0FJ02VQe3Mf8RNy0WmfI8Po-Gj9b8IkFxmyxzbXlVCKqwJ7D3DwwGAHA_0eUTAMnsHwMiTfJyZQs6V_IPOfwlWzvLYHO0otWFWsjHj74Qa-_bUVoEPAvucrw_K1GyV7NTJBkZpBp0uNI202913Y6bQfcrtF39KQjUTbqQo9Cal5NWFeMUd_xwNZZw6DGh_T_vVgNc_AEvq9fhdzg53pr5AdlkIDZ--wO2Yyc-Il4Aux147DM6t-HO080zD95d-ktlGbcTkJsD0jB-0GBpvW-YXADAcxEnoN51Ti3B74MX5MULOwr4vwdJ_J_dqG0evnnLpkkKM7gW4Bxe9CTwPaEMytuAH8wkYwgsxk_ZKbwHIaJ-hyYrAcJbA5i_vp4uHQQu4jeOXcy0pvI7JT0mBRFhCjuvdFXVmhRZZ2YXrfdcRudo9-bY45nUrbptrLCRYR_rUyJmeHuO6xKxnbaacO7mDDsgUlHucLiflBvZgk4qS4eFVgYb3_iYhq4YVZKsC7uRzDR5faMjWb-U-XFaBll5R_VGNPs09GxT3Yku5eChofdCmqSvewizPudzwxWbPxS9JiwlVamhTIfI8S6RwOSf-KEp0CjfE2SfMLcgymy6yGRspuDo9SfaT1K-e9-XIiAnx3KMjhM-cmE9txNzW9felsarJTan6bd0eVuvpAAz9yGasbnsRH-OKag5JKx5en41PfGWa9ucvOnLgy-LrzlWyMrmy5eoKk317bbMiedJZBRgLARWenFcB5QAIyN-US8hMw8-1uaBvdzw6HORne5K2D0BqlIIqDeq4lZ843vxcHMHvtYdTQY9DO5mf5QY-wYW8zmO8xHla6TzHQaZw-OW7JRXBoYuO_PhICOd44rETmBiHe64lKB-i-s7xyQQuMS6kO8R21byKgCbprd05l002m6noTDzwi9kuNzDpa5u488nX2bRXay04GpzVTodbYvwWusddnRARTNB9hkUqIItkq6DGQSWu9Elk7IhBnw6_epnFNFGjjWrvQr12X-sSAge0UX873i3vXoc9elYjpJbJ6C7CQ1OYdXU9FrouYjeibMdvHpsPcfIGomKf12FDrExZncqTm-pNyhrfOR6TAowNN7ujJIj5W4TxDgTyCb9IPExVfoFtLshWoWaiP-ulJu1A4QESSvBNu_omP_7lkiSH5bo2MF4vacnnIScxl77Q7_jlE6hxLle0Y0iW1No_FxIc3l6aAo3eQNbAJxVcfB3-7z-RkuU2EPcW7jEWLZBnoZ5_kxLaeqgo7gcpaCZCmUlHk3fxkc8O4yC6MfinOhDS6iS5Uo2bqpKyrXEHWgYQLOWQlb6MPhc6snflDOSi56spL9_qq5wxUaAnY9O6WIclMMT789LEPjHXJdZmno4t9F2VlTsg==","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0bb566f8819fb02cf195649326b0","index":78}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQvTMQNkd_W3YPoeIGaiWub7z4eHBNTJjGigAVtsJxFpnuN0qwR3YwSCvhvt1ZLmBCuUuzuw9Uv2tnw9LEfhRMiAAt18wdCwf8IeggwPo2KD6im4A5tWvxb_uNg7xnesRzM28jHSlT3bjWClGZtzJuKwzJn4fh6o99tfwgtC-cY32eKeOk41ORFluncYZlRlManLFUCKHeWnpR5c4s7QYBTWaSWuUXW9VNGHP4Yyol9gVoup-6WMQuKxApFBfWKVibiylNBLyQ00FFqne0S6-2EJ2fSXxbzUbQcIl82P8cIl4nJkQVPUuVnCSZPfJSDEs_EbDemsqf2ds99I9JJmD1uRdj52csqQKijRgbavB3Hw5YAA9vgZDJV_xrcLaNb5Xxrxd0F12VAIi33OVc0KDyX8GznS1-SW6_ex19uvgynhDFhEoo0kozMnbGfUSaVQI3c7AfbXMmbFQH0UVtFjJ-MBSkcchBPPfvhzBQfg9rLaguZxiG-P-s7xGICwvsakLsuVav3fCmzuT9f-PHywu1rSj0MrPMxv0jUju4zHX-W_G3EhtCcMXWyBkNN2dP3rWdi4fGdl5jFgabh9suz_H_Q-6hOJt2rNslyt_BFLgbYn5RRNZA7yPApLNh1-f05zeZvzmOu13g_ecnNmAG-ba_QkA36wSp2i1CuVXqYJwXxEqdySojmSWOV8gKyG-BYxgF93Iq_CLm8ffCR-wIRdaZTJmy2FV5N5cb09HNOxnz4uIsXPfB8bM6yjVpsv0UxYq-GCQbbb97_7ftnmNfyUYDQVtRhgszeLdnpTyXwdLa70f0Qo4Qx8Oa1tMOobcsowfULq4Jo951yH075tfuXdGtYNQSmqji3erl9ipurU8YjZpJ9MDlKTBbkKnqbxQx3UTWQL8fNroeOgWcpQI0MaFxQf2Xz_Onf5Nzi7VB0hZ4SKbENXes-fZx9LfZmUcM7drvrx88xXdX7r5IioOxwk6Ts-76gzQRvzbcojeVWKSQ4AXyk9oP-ocFB35ANPv8O-w7MCIIhZ0JVp1o3fHSP1WFMzBq13baKYN3b9ZrXEyfY57vO6ngCeQd9FRkfCWsZfupoSBHJVzSDUJ46vsp-Un1oRi6J2nbMU0HnbtnCQAmqj7QtiN3dvCLqXNeNMIfaS67X7Y9KReXp81xMyAhrRRdXqweuQjAjNxOJ-dIqBGgS7md_wB874jeHo3DH9UMO1IDTxvG6VoHy639IK_1T4z6Z9q0E2tGpw01uJGnMqixGI_q5fs0i45g8o_NzRkQPMkj_UibgB4Fh40t8EQ8TBfmU-aAmP8LNBVScS8pTckWW8nOB6MadLhqoGqUPodvzi_CcvKZHODb7SL42VVzCZxxGJ1omvJv2dEJleeTJJkG6ulQNDXrvhGnq8zAwy1RSUm6PUHVpdGYkOXwaOd9wm05ZlbdWe3ZdwtLcEtFoA_wN1Q0dVvOoeV_BRi1Kpt64NPkJnV3FxrCdhGuv0nxynJsb-yz1irm6iZ4n70dpSxuCFwfdZkhmSIlQmiICveMXazdJGUSBXt9f4PSo0eXsw8pi2-SRBG9oHnoivaNeVXzrPqJRMf6IM2QYeoWEKJd5Jx4O7ffyyrZocaTiY6B8n1IZbO_tbkDWUIg91iuj9V9EANvjh2V8nEJQsHVfMox50ISQH8zCA6OTMkqoVeFlFEE68vSrnHqoKuxB3CgGATpbjIK1ugHXWUF_7dRN7qFNy3JgUKku0O6XCAstaMApoqYFYXBLrT7wdnOVqFFnvsj3QcXFW-71dUBraxxjAcrwHN8nCjkV7sWpTI-zCTvtTiuhepbHtoPkwwlh5xqWtBr9B-KDCoEAa1Que0_CgeTvflJO7yZcmOuc7RHlvkElZOB8f4nbS4z8ulpDu2k4n0AJPVGKv5lf4PaGRBtw4uBnL1orTOc18FMAPm7wxe6yGBxkTSpCu60rCCgo2HgTsX6OQm52W9LtZWR1SzZl_WXxapHlv1_2SQGkQggIgOn35jcJHAWlEXHVL7D1CeoJxCOsLiT0Vf3QZPOmatsRsQ9VHmsfj5cjZxcdv5Y7dv9dfhGdYhv6pBUsXtUouxc_cIg-x9piVMebAItET-Pmon826VEEjy8pNhh-Qrp0EaxivvfeEMYgVuiwsoNu1HB7DPp2RDKxRFe7cd-FS-CVYUMp9du4ZegwLxyFczQ4n5FO-gtvNkZTEnIfEHaBpxziiQbo6psS3JL_5hy6wmtnzLnnY-3gLHgnKWjzyR2uPe6fZPdrx7coik4pfJHPveLSBG1-EwbMWyZxRO5VHLMCBNm9gbOrU-KZ8AOtCIJmUDB3jJ2-4gTne-TcJt1AEMQvF55wSlXpodwrpY8EtngNuqZLX28BbuMTar1tJWNu3a6UYBkg1uKzhXFyJSUYH-W4maDRL2Ue3uB3Fu_oN8C-KJgCEmNzOGG-c1ZkKbcgKIxQHN8nGBLkJBEENiHnybeETlqvCa2-Wjk6we_zBTfDb5uLmW7beSbeuYLKsvnOYggksyYOlbDp9UifYJ2konzP1DEA17igoQbBWWDZtPXhwu7_6S6IjcTnQE5CMM8_eWveTrfntcnWeXl1iZ-Z13VYYe7QTAZw0yeI73JVdvuoe9ZgOiJ05MxI6dCR9XagoMahihKiKVA_IzMvQ5IAyy6c2MAvofTxvQWENQ63owUHPK9_6yR725kACMDHHLAGYmfP_sp7qvXOZEOBdImCvymYqhr_-UwL6k3KObXrdYB5Nb_0Axn5gF3LaCsDCzi8u4C-uvwVONPFFN8ywGwMU-5z7Ag_W3J_gnRef6r6rSBh5K_160eIGic3O2pllAYO8jysWQZBrujfwqkoj2DVZ9caHbF3xoIsQTYhW3GM47NUoYrAe8CEVIZ4rqKWf1wJByBkAY0kEUwcb0tDBg_bu3gjYDB_I19cICD0VnA-9_r8OLUymwRJmrVCQDfUEEDECNBpTbmb9-lb4mgtsnkamXZpgkUVmxqaNj6GM3bcUW80vBVbgDEaP49dv06yfWZ0ZsfNUhWTtSZkVeCgKbmIu9eNQZlardnjjq3JMn9RSCZN9jjj4ck_Zyj0Sj3oPmtFpYPjlyDAmvCdBZgRDLAYg3TKyv5c7MsyE0hU1cl551r6MAIlay8M2O4lyz7S4rSI408T-BhuVy-QvE1um4f24o6rsuDi1_0ssiSNaHsoLRFXvwREmyIH2xUZTWptrX5PdsDMrdwI9GNywTfQW2tT3GSxeAIyy692xhCaSs5Aj4IRPumVb7j02z_MQ_4U3uFd32Yon0AIUnooDoBgBtxn3QEie6UGLFOaI5q67OUqkhCSJoGfjpShoSNob3TUlWlHTn4MJ2eaeVRbt_HjSusReud52MnHLXqpwirdQn4RWigwr8-AvSzP5wNA3tblkA7NnQtCRgjqU8J_mgNuGQ6DGOQEVApi57BnasVIqjlxYEKOGvDtV0qoRF9KaAf67ymmp2A1d8utHnVJS8wWZ18FQwZt0-5k_HOH1q8hh4hbXzYg_LB7-lK4SncDgf0jeIYUkQGgGf9q8NxX9xWtuQFRZCX9L2ZHVGs4fzqGk4zCB95P-gvox7xN5Z6EavgtHDOC27GtYzkul6nWND4Vehokgr1OrfsztRyKIAjaX4OQNP3j1kEKriI0ERMbjUgtOpHjgNiKaYzapooZhdM6CbozxEAollDy3aWk78lvRobupsNFuglrKoQrduLFLQiU_CuG25k65Xj_Nc_PZvJwC7HxvVVbGCtVFeVxSzKiUEgSZNBRlQyjfZpoKTOdH54OkbjdcI0h-CtAy4XXGtTEBZdnE1XlKlMYMM-bOVJzEsBbuRL4N_j9PvCW1Xi58iITRhSJUSZogn_Q8QgLnyzOrze9YyrSrJGQHBjQKLK7XysT2lzev61I9rd-DjMssgeCmo1bNs0owO6n_Og1iHw-5Ccjh-BMFx2T91P8UrSEgB3uS4zohqjUAr-CM","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0bcafeb8819fbefb5a7b22cbd87e","index":80}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

data: {"id":"gen-1784482209-0HLqz8AQpZyMpUUm95xb","object":"chat.completion.chunk","created":1784482209,"model":"openai/gpt-5.6-sol","provider":"OpenAI","choices":[{"index":0,"delta":{"content":"","role":"assistant","reasoning":null,"reasoning_details":[{"type":"reasoning.encrypted","data":"gAAAAABqXQvbaVzLlYzhuPvfaFZTTfH1BN3hKcBKtyIg2xglZQ2GoBmB_aW7j-06l276iBZMwhDGosIY63U0RCyqDAuJnu28JV9xPm2LDNYABTFHtT7g-plK8QsA0FljIyRGWUAuXZSA0nv-fyjndGKUWBCHIGeSoq4Xx8YlP7wHzc6qAPbgZOq4FwIsguqp3T29GZuCiy9QLqKZpgsQgqKzgwDGtjXEBv63v0TZpUKUw_arxD9kU8p1QvEhYngD6zYgR0M2OxGne7ED4vPsaHY3nbRP9N2QGSHE8Uk5B1vVUmkr4UMH4SIVJdWZa2egPQmsCY2d63bxQRTUAtOJ7mvNugv3MY4aWfyN0C6iwWevjRXbbj84PL7kaesgj-ll-84QOw06xf_iW_zflLS2kAO8FfFKY8mJGr8bW9Gw7S8rLEC5VLDgEoyGQwxKbWWSs8z-yZnmWJJ0fSbHYnQqOS4fuOtr6sfmxfdXEJjLm7H_mvZ2eK_aNk0DD5AniR3f7QBe8ULDYWHQUj6b7P9tPUQvPsAa8MoWVVIiUody5d_y5SGPGZRR4oADDds1dt_l_UOQdQ5Bj1IYG2sTCy1KJ2lmEdpTK3_pFBDJyqlrlJMhvvua7ivfZkU7cqwUG3yR6iTS8toTlfOW5zreWc7FFdQ1IAr4_GIgVd1tDIQqtQvBxaCS4uhOkwwRVpqQhh0cgIyyfi5Y5mRFuaemFuJE-kSl8AjKPFNXWf9dbVYg8o1LW4eUKh55uyVZ_lPPP-kCKyTMcNpP616aB8feqDMfefZ_NoOfbBW2IFdccSbpab_G0rAO74XXm728aEFt_Nr3DMGn66KHTQUo11gEG2sTnXSoRzblyQM04iwkWR2IMwEVEoHm1s9RJjP-uMLDUlXuJf0z5ZXKrObtNJPG5qEAZQBe87hkRvuohEtKHLgbphCCQ0TinOZNm1kYQwNFXHN-S6ibzll8i64pZ3UGoHUu6jDHrT_9WjNxeQlz4qRDsQG29kke5oAKfh0zf4E8Xz45pY_vr_3pZ60T2PsHAunN6kR1f5lSu9OHY30xHcu0h4-4PI76QvLFomVmUy-lUkIlJE1Xxa-8TLhdz6ltsmAi-2Uw7rIiUhLD5fRrORcej_EHrDXlgThtZKyhqz2P2ZfoZAD6ysyVjOhW-NPWhl2CU3wfq4H9MjH1AdiBx1_NzCPxpz0JvQMKTFB_CZCbnODMAvdDUDt8lvUPyrwY8o1qaqyWPa9tu4DwSxy-Zf7iGVvoAL3ZkSBtnVenMezxotp_KKxgOLiekBvl_dLipvhmTak6VkRx-Ff94nkmyCwu-YPVmNXdbGXrDzAZ6Bp5snZI1E0y0FS3REoc3p5oTbXZ6T05mmAYNcdA6Fzq5mgOq4rDlW5MIxaO_HYZBFTIQab41HEkVbgtnZsoqbY93loP0jqSXI0mr0Fa9VgEV_Hc8IRH_fKFhfT-V-ynBVcrvRb62KoGozjtbfNcf3kkSCqdnUQfZR9KBWOsQk1V3HbEvuxH-UW1NICFGUE_R8G7-4OR5MmfjTs229J3RBdQd53i39tEfz38_whSXzj8CiLMsu7BJoNxZeyO92LVikwP3mSCFqTTu7lh__IlovpgauQfOPlburA07tgBP5lZ4kq59CdteWSXBuFX1Tdg7PAJJ6lX6Xt4l8q-BF1Sy1UUM397XFkqY21u90MUN19MsAjrv28fhaxvzyYyYzepnLFJDaWyoQSX1uhYRZgoBSyLVldi4yLkngL8BbFTgvObq7ryQ_BDefkB6RgOji94Yb-Bh6WCk7t8OzlQM0F1zPAWe9dk5ZWnw2EpiQig4GVudKeLM_k1dhpeuyGdgvuC1gxbxizoKnTAvuoCeGrfiqZ907U7G5gV6CwJBcPlS4q7Fdqs_iUHwFpvqntrQxrE8HfbX8_F6PcZGk1SMml6OKM7DK21Fixm-mulo68qLW6H2_iqfiGiYutn6PnPLaKbUGAM4zI57-0Vgi8ouMxy6FMLXnvHN1hVujjfNqMKe4gDI4FFceUhejopajMJx4jpkCiOeBPRzfOSaA4jffT7E8sxlDSp_q1h2s3UP8wMjadLf773mg1WvP6pWPJtMRj8pwu_V855Hi8M9HxPahbAjUqxwOPyuZtUfs2VS00H2CWYOA6TXzqIl5zvMgUaksfIYCf22xNEBKJCjFiJz0y1TROLswjfwHxpxla03_-n1-GWuCun-RgGYOOMaJv07Pbg9WHGVbccH6s7wBp7doirvML0mRq5vRdu6xZ9-AiYn-t1TlW38WuU6Pb9pN29tdlAQO8G3nmPU3GdN_v7szFzzrQe2ylxq5SKyIeQtfVCbwHqPxJW4bUD5rcsqXIAHVuJM_ezlJCag-wYG_Gi8i3uVxGphz_Od69ZV25TMg_QuduKk_dcqtZUW6gs2KpeqlwlIoOp6CrFKqIxxClhllPFtJoPx3uUJKOZg8VUYSfbeBLWkdpIsjI_zOtHSFJC_PHZfd5cT3KpscNU7ClC09WqZ-Gsee3pnQTZQL-4QHXT35JGlN00_ZkuOhHwvU3nHQNdHKDV4uYjPzu3CIISn8oxyEuRItYErTidH4Av7LVd7OBvMlJ8mVfG-Bf8DdVxg6hopdpZ_AbH-kdAyG4X2KyLJt2WYysNPpu0vUoIURYp2Akr37JRjN2C1sdeJmgYdUBaUCJDeeFp0CnlFAlojAYkvuc2ZJ-FnN7-B7CBSYakCkMeipxlICizneZAZBrmsjtaSoYZvSQC5M5DCc10EINnAD7-V4UnnoKCBCpWcUflkEkZyhdylXO4OToIeBvF4wGSYvWufVgEXsWi-GDuOG-3xWh5Kd7QRS4y6NOveStQuTgwdNaqvDZP2fbZ70jYUNxl79wDcHEs52NgMHz_cs7NpeF-wMBmItN1xDmeTGsZIGhbcn9Ml1H4RVLq_8XLaWc9Ern5Si_QtfCboWkqCPy1Frk4y4sK61PU71eZLWKvupEdiOzV8dKJBN8b9ShMYjFZdsEgrJKPScY0_e3dNq0kHmxLjmLfJ2GLqMIRbiGSQLQK9saEuliE_KHK3yY01gKOfZBQpdl1ozc-EA_8012g8zejnT-APFE78WEewOnicXasvA3Sv5Y1lhuf-VS1fP1d8a4MxOoQTSrH9enSgCTlSBEps8bU1DHCwosq6-amcm-HLWsxGY-2z9JQbTSkCXIRVR6V7QnTyoCcp0ct9LQ527m3t2MwdpB-IdOIa7He2ngziEY6KJKhu4T0jOkufE2h0XRAH_LYKMCFj50EBJ7w83TiUlJYDVNvLLphD-SM44t9GQbuH49tsLCPf4rYpgNIEFmcHL14nYWTlN41lE1jX2tfSy01oCT0TDbvQhssj42RtXJxDcWFNAeIoZeo5lUMbqy8cbb68dbtItXFBGJ3aDQ1i3KvXigQZayzvGdc4NypLr8lPioaydpxDjqlIbDVOgE6RXqiXeY3SgXgNCJNLkWhyno3mkY61AQW4CDp_M1nyO1NfqMQbODhy2G5XJwpkVrLJiYKhAsKo5W3-rB1g8MdcqaAWPnA6tBtCmBGeUibrwDSl1pL7pPn6VZSKkcC0rSQ1mYgTla8SbXkylHLjc9RSsuHcO0tAKh-V53Ol3f2NghBcora1wMYnNdKfHYJUCu6B9x7gcX2S9kD878yNVQxJfbdsmYQpxpkWiWku0o7UYBA4A-TGP0jJ3uNpeCUJWaM8_6mMOgE0Bd9Z6M8EHXjX_rzTjRD71-uLsYTyu-tOOWiNiK6QXUOLD96BwrTtlB9UCRVQlCoINF0FtwhfGUw72OJNDpP5VzbUg8xnaaOkM-t0wVZXbRenLY-OMN59-2k6VBQ3ULY-UVi34xb","format":"openai-responses-v1","id":"rs_0e1fc247381f86ab016a5d0bd3a6a0819fae66d5c295dd8b52","index":81}]},"finish_reason":null,"native_finish_reason":null}]}

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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: OPENROUTER PROCESSING

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```python
import bpy
import math
import random
from mathutils import Vector

random.seed(7319)

# ---------------------------------------------------------------------
# Scene setup
# ---------------------------------------------------------------------

bpy.ops.object.select_all(action='SELECT')
bpy.ops.object.delete(use_global=False)

scene = bpy.context.scene
scene.render.engine = 'CYCLES'
scene.render.resolution_x = 768
scene.render.resolution_y = 768
scene.render.resolution_percentage = 100
scene.render.image_settings.file_format = 'PNG'
scene.render.film_transparent = False
scene.cycles.samples = 64
scene.cycles.use_denoising = True
scene.cycles.max_bounces = 8
scene.cycles.diffuse_bounces = 4
scene.cycles.glossy_bounces = 4
scene.cycles.transparent_max_bounces = 8
scene["description"] = "An abandoned village reclaimed by grass, moss, ivy, shrubs, and trees."

try:
    scene.view_settings.view_transform = 'AgX'
    scene.view_settings.look = 'AgX - Medium High Contrast'
    scene.view_settings.exposure = -0.15
except Exception:
    pass

# ---------------------------------------------------------------------
# Utility functions
# ---------------------------------------------------------------------

def set_socket(node, names, value):
    for name in names:
        socket = node.inputs.get(name)
        if socket is not None:
            socket.default_value = value
            return

def make_simple_material(name, color, roughness=0.7, metallic=0.0,
                         alpha=1.0, transmission=0.0):
    mat = bpy.data.materials.new(name)
    mat.use_nodes = True
    mat.diffuse_color = color
    bsdf = mat.node_tree.nodes.get("Principled BSDF")
    set_socket(bsdf, ["Base Color"], color)
    set_socket(bsdf, ["Roughness"], roughness)
    set_socket(bsdf, ["Metallic"], metallic)
    set_socket(bsdf, ["Alpha"], alpha)
    set_socket(bsdf, ["Transmission Weight", "Transmission"], transmission)
    if alpha < 1.0:
        try:
            mat.surface_render_method = 'DITHERED'
        except Exception:
            pass
    return mat

def make_noise_material(name, c1, c2, roughness=0.75, metallic=0.0,
                        scale=4.0, detail=4.0, bump_strength=0.18,
                        bump_distance=0.12, mid=None):
    mat = bpy.data.materials.new(name)
    mat.use_nodes = True
    avg = tuple((c1[i] + c2[i]) * 0.5 for i in range(3)) + (1.0,)
    mat.diffuse_color = avg

    nodes = mat.node_tree.nodes
    links = mat.node_tree.links
    nodes.clear()

    output = nodes.new("ShaderNodeOutputMaterial")
    bsdf = nodes.new("ShaderNodeBsdfPrincipled")
    texcoord = nodes.new("ShaderNodeTexCoord")
    noise = nodes.new("ShaderNodeTexNoise")
    ramp = nodes.new("ShaderNodeValToRGB")
    bump = nodes.new("ShaderNodeBump")

    noise.noise_dimensions = '3D'
    if noise.inputs.get("Scale"):
        noise.inputs["Scale"].default_value = scale
    if noise.inputs.get("Detail"):
        noise.inputs["Detail"].default_value = detail
    if noise.inputs.get("Roughness"):
        noise.inputs["Roughness"].default_value = 0.72

    ramp.color_ramp.elements[0].color = c1
    ramp.color_ramp.elements[0].position = 0.18
    ramp.color_ramp.elements[1].color = c2
    ramp.color_ramp.elements[1].position = 0.82
    if mid is not None:
        elem = ramp.color_ramp.elements.new(0.50)
        elem.color = mid

    set_socket(bsdf, ["Roughness"], roughness)
    set_socket(bsdf, ["Metallic"], metallic)
    bump.inputs["Strength"].default_value = bump_strength
    bump.inputs["Distance"].default_value = bump_distance

    links.new(texcoord.outputs["Generated"], noise.inputs["Vector"])
    links.new(noise.outputs["Fac"], ramp.inputs["Fac"])
    links.new(ramp.outputs["Color"], bsdf.inputs["Base Color"])
    links.new(noise.outputs["Fac"], bump.inputs["Height"])
    links.new(bump.outputs["Normal"], bsdf.inputs["Normal"])
    links.new(bsdf.outputs["BSDF"], output.inputs["Surface"])
    return mat

def assign_material(obj, mat):
    if mat is not None and hasattr(obj.data, "materials"):
        obj.data.materials.append(mat)

def make_empty(name, loc=(0, 0, 0), rot=(0, 0, 0), parent=None):
    obj = bpy.data.objects.new(name, None)
    scene.collection.objects.link(obj)
    obj.location = loc
    obj.rotation_euler = rot
    obj.empty_display_type = 'PLAIN_AXES'
    obj.empty_display_size = 0.35
    if parent is not None:
        obj.parent = parent
    return obj

def add_box(name, loc, dims, mat=None, rot=(0, 0, 0), parent=None,
            bevel=0.0):
    bpy.ops.mesh.primitive_cube_add(location=loc, rotation=rot)
    obj = bpy.context.object
    obj.name = name
    obj.scale = (dims[0] * 0.5, dims[1] * 0.5, dims[2] * 0.5)
    bpy.ops.object.transform_apply(location=False, rotation=False, scale=True)
    if parent is not None:
        obj.parent = parent
    assign_material(obj, mat)
    if bevel > 0:
        mod = obj.modifiers.new("Soft weathered edges", 'BEVEL')
        mod.width = bevel
        mod.segments = 2
        mod.limit_method = 'ANGLE'
    return obj

def add_mesh_obj(name, verts, faces, mats=None, mat_indices=None,
                 parent=None, smooth=False):
    mesh = bpy.data.meshes.new(name + "_Mesh")
    mesh.from_pydata(verts, [], faces)
    mesh.update()
    obj = bpy.data.objects.new(name, mesh)
    scene.collection.objects.link(obj)
    if parent is not None:
        obj.parent = parent
    if mats:
        for mat in mats:
            mesh.materials.append(mat)
    if mat_indices:
        for poly, idx in zip(mesh.polygons, mat_indices):
            poly.material_index = idx
    if smooth:
        for poly in mesh.polygons:
            poly.use_smooth = True
    return obj

def add_ico(name, loc, scale, mat, parent=None, subdivisions=1,
            rot=(0, 0, 0), smooth=False):
    bpy.ops.mesh.primitive_ico_sphere_add(
        subdivisions=subdivisions, radius=1.0, location=loc
    )
    obj = bpy.context.object
    obj.name = name
    obj.scale = scale
    obj.rotation_euler = rot
    if parent is not None:
        obj.parent = parent
    assign_material(obj, mat)
    if smooth:
        for poly in obj.data.polygons:
            poly.use_smooth = True
    return obj

def add_cone_between(name, p1, p2, r1, r2, mat, parent=None,
                     vertices=8, smooth=False):
    p1 = Vector(p1)
    p2 = Vector(p2)
    vec = p2 - p1
    length = vec.length
    if length < 0.0001:
        return None
    midpoint = (p1 + p2) * 0.5
    bpy.ops.mesh.primitive_cone_add(
        vertices=vertices, radius1=r1, radius2=r2,
        depth=length, location=midpoint
    )
    obj = bpy.context.object
    obj.name = name
    obj.rotation_mode = 'QUATERNION'
    obj.rotation_quaternion = vec.to_track_quat('Z', 'Y')
    if parent is not None:
        obj.parent = parent
    assign_material(obj, mat)
    if smooth:
        for poly in obj.data.polygons:
            poly.use_smooth = True
    return obj

def add_beam_between(name, p1, p2, thickness, mat, parent=None,
                     bevel=0.015):
    p1 = Vector(p1)
    p2 = Vector(p2)
    vec = p2 - p1
    if vec.length < 0.0001:
        return None
    obj = add_box(
        name, (p1 + p2) * 0.5,
        (thickness, thickness, vec.length),
        mat, parent=parent, bevel=bevel
    )
    obj.rotation_mode = 'QUATERNION'
    obj.rotation_quaternion = vec.to_track_quat('Z', 'Y')
    return obj

def create_curve_mesh(name, points, bevel_depth, mat, parent=None,
                      bevel_resolution=1):
    if len(points) < 2:
        return None
    curve = bpy.data.curves.new(name + "_Curve", type='CURVE')
    curve.dimensions = '3D'
    curve.resolution_u = 1
    curve.bevel_depth = bevel_depth
    curve.bevel_resolution = bevel_resolution
    curve.fill_mode = 'FULL'
    spline = curve.splines.new('POLY')
    spline.points.add(len(points) - 1)
    for i, p in enumerate(points):
        spline.points[i].co = (p[0], p[1], p[2], 1.0)
    obj = bpy.data.objects.new(name, curve)
    scene.collection.objects.link(obj)
    if parent is not None:
        obj.parent = parent
    curve.materials.append(mat)

    bpy.ops.object.select_all(action='DESELECT')
    obj.select_set(True)
    bpy.context.view_layer.objects.active = obj
    try:
        bpy.ops.object.convert(target='MESH')
        obj = bpy.context.object
        for poly in obj.data.polygons:
            poly.use_smooth = True
    except Exception:
        pass
    return obj

def create_leaf_mesh(name, centers, plane, mats, parent=None,
                     size_range=(0.11, 0.22)):
    verts = []
    faces = []
    mat_indices = []
    for center in centers:
        c = Vector(center)
        length = random.uniform(*size_range)
        width = length * random.uniform(0.42, 0.64)
        ang = random.uniform(0, math.tau)

        if plane == 'front':
            a = Vector((math.cos(ang), 0, math.sin(ang)))
            b = Vector((-math.sin(ang), 0, math.cos(ang)))
            normal = Vector((0, -1, 0))
        elif plane == 'side':
            a = Vector((0, math.cos(ang), math.sin(ang)))
            b = Vector((0, -math.sin(ang), math.cos(ang)))
            normal = Vector((1, 0, 0))
        else:
            a = Vector((math.cos(ang), math.sin(ang), 0))
            b = Vector((-math.sin(ang), math.cos(ang), 0))
            normal = Vector((0, 0, 1))

        base = len(verts)
        verts.extend([
            tuple(c + a * (length * 0.5)),
            tuple(c + b * (width * 0.5)),
            tuple(c - a * (length * 0.5)),
            tuple(c - b * (width * 0.5)),
            tuple(c + normal * 0.022),
        ])
        faces.extend([
            (base, base + 1, base + 4),
            (base + 1, base + 2, base + 4),
            (base + 2, base + 3, base + 4),
            (base + 3, base, base + 4),
        ])
        idx = random.randrange(len(mats))
        mat_indices.extend([idx] * 4)

    if not faces:
        return None
    return add_mesh_obj(name, verts, faces, mats, mat_indices, parent)

def terrain_z(x, y):
    return (
        -0.16
        + 0.075 * math.sin(x * 0.31)
        + 0.055 * math.sin(y * 0.24 + 0.7)
        + 0.035 * math.sin(x * 0.73 + y * 0.39)
        + 0.018 * math.sin(x * 1.47 - y * 0.81)
    )

def path_x(y):
    return 0.55 * math.sin((y + 1.5) * 0.24) + 0.18 * math.sin(y * 0.72)

# ---------------------------------------------------------------------
# Materials
# ---------------------------------------------------------------------

GROUND = make_noise_material(
    "Uneven meadow earth",
    (0.025, 0.047, 0.018, 1),
    (0.18, 0.145, 0.055, 1),
    roughness=0.96, scale=5.0, detail=6.0,
    bump_strength=0.28, bump_distance=0.18,
    mid=(0.065, 0.09, 0.025, 1)
)
HILL_MAT = make_noise_material(
    "Distant muted hillside",
    (0.055, 0.075, 0.042, 1),
    (0.14, 0.16, 0.09, 1),
    roughness=1.0, scale=2.4, detail=3.0,
    bump_strength=0.1, bump_distance=0.2
)
PATH_MAT = make_noise_material(
    "Old muddy lane",
    (0.055, 0.028, 0.014, 1),
    (0.22, 0.13, 0.052, 1),
    roughness=0.94, scale=7.0, detail=5.0,
    bump_strength=0.24, bump_distance=0.12
)
DAMP = make_noise_material(
    "Damp wall stains",
    (0.018, 0.025, 0.012, 1),
    (0.10, 0.085, 0.035, 1),
    roughness=0.98, scale=3.0, detail=4.0,
    bump_strength=0.15, bump_distance=0.06
)

WALL1 = make_noise_material(
    "Faded lime plaster",
    (0.19, 0.18, 0.145, 1),
    (0.53, 0.49, 0.37, 1),
    roughness=0.95, scale=4.2, detail=6.0,
    bump_strength=0.32, bump_distance=0.09,
    mid=(0.34, 0.32, 0.25, 1)
)
WALL2 = make_noise_material(
    "Cold weathered plaster",
    (0.16, 0.17, 0.15, 1),
    (0.46, 0.43, 0.34, 1),
    roughness=0.96, scale=4.8, detail=5.0,
    bump_strength=0.3, bump_distance=0.09
)
WALL_GREEN = make_noise_material(
    "Faded sage plaster",
    (0.11, 0.14, 0.10, 1),
    (0.38, 0.40, 0.29, 1),
    roughness=0.97, scale=4.3, detail=5.0,
    bump_strength=0.28, bump_distance=0.1
)

WOOD = make_noise_material(
    "Rotten brown timber",
    (0.035, 0.016, 0.007, 1),
    (0.24, 0.10, 0.035, 1),
    roughness=0.93, scale=4.0, detail=5.0,
    bump_strength=0.3, bump_distance=0.07
)
WOOD_DARK = make_noise_material(
    "Blackened structural wood",
    (0.012, 0.008, 0.005, 1),
    (0.09, 0.045, 0.018, 1),
    roughness=0.96, scale=4.0, detail=5.0,
    bump_strength=0.25, bump_distance=0.06
)
WOOD_GRAY = make_noise_material(
    "Silvered fence wood",
    (0.055, 0.052, 0.045, 1),
    (0.25, 0.23, 0.19, 1),
    roughness=0.98, scale=5.0, detail=5.0,
    bump_strength=0.28, bump_distance=0.07
)

RUST1 = make_noise_material(
    "Orange corroded iron",
    (0.045, 0.012, 0.004, 1),
    (0.56, 0.145, 0.018, 1),
    roughness=0.78, metallic=0.46,
    scale=5.0, detail=7.0,
    bump_strength=0.38, bump_distance=0.07,
    mid=(0.25, 0.055, 0.009, 1)
)
RUST2 = make_noise_material(
    "Deep brown roof rust",
    (0.025, 0.009, 0.004, 1),
    (0.34, 0.075, 0.016, 1),
    roughness=0.84, metallic=0.38,
    scale=6.5, detail=6.0,
    bump_strength=0.42, bump_distance=0.065
)
RUST3 = make_noise_material(
    "Remnant oxidized steel",
    (0.065, 0.07, 0.065, 1),
    (0.31, 0.18, 0.075, 1),
    roughness=0.7, metallic=0.58,
    scale=5.5, detail=6.0,
    bump_strength=0.32, bump_distance=0.055
)
RUST_DARK = make_simple_material(
    "Dark rusted iron", (0.075, 0.025, 0.009, 1),
    roughness=0.86, metallic=0.44
)
ROOF_MATS = [RUST1, RUST2, RUST3, RUST1, RUST2]

MOSS = make_noise_material(
    "Deep roof moss",
    (0.018, 0.05, 0.009, 1),
    (0.19, 0.27, 0.045, 1),
    roughness=1.0, scale=4.0, detail=5.0,
    bump_strength=0.35, bump_distance=0.08
)
MOSS_LIGHT = make_noise_material(
    "Yellow green moss",
    (0.055, 0.085, 0.013, 1),
    (0.35, 0.39, 0.075, 1),
    roughness=1.0, scale=4.0, detail=5.0,
    bump_strength=0.3, bump_distance=0.07
)

VINE_STEM = make_simple_material(
    "Old ivy stems", (0.035, 0.047, 0.012, 1), roughness=0.95
)
VINE_BROWN = make_simple_material(
    "Woody vine", (0.065, 0.032, 0.009, 1), roughness=0.96
)
LEAF1 = make_simple_material(
    "Ivy leaf green", (0.035, 0.115, 0.018, 1), roughness=0.86
)
LEAF2 = make_simple_material(
    "Ivy leaf yellow green", (0.13, 0.22, 0.025, 1), roughness=0.88
)
LEAF_DARK = make_simple_material(
    "Deep foliage", (0.018, 0.065, 0.013, 1), roughness=0.9
)
LEAF_HAZE = make_simple_material(
    "Distant desaturated foliage", (0.105, 0.145, 0.085, 1), roughness=0.96
)
LEAF_DRY = make_simple_material(
    "Dead leaves", (0.27, 0.12, 0.018, 1), roughness=0.92
)

GRASS1 = make_simple_material(
    "Grass dark", (0.025, 0.08, 0.012, 1), roughness=0.95
)
GRASS2 = make_simple_material(
    "Grass green", (0.09, 0.18, 0.022, 1), roughness=0.93
)
GRASS_DRY = make_simple_material(
    "Dry straw grass", (0.30, 0.22, 0.055, 1), roughness=0.96
)
FERN_MAT = make_simple_material(
    "Fern fronds", (0.035, 0.145, 0.025, 1), roughness=0.9
)

STONE1 = make_noise_material(
    "Old foundation stone",
    (0.055, 0.052, 0.043, 1),
    (0.34, 0.32, 0.25, 1),
    roughness=0.98, scale=4.0, detail=5.0,
    bump_strength=0.3, bump_distance=0.08
)
STONE2 = make_simple_material(
    "Warm gray stone", (0.19, 0.17, 0.13, 1), roughness=0.98
)
STONE3 = make_simple_material(
    "Dark wet stone", (0.075, 0.075, 0.061, 1), roughness=0.96
)
BRICK = make_noise_material(
    "Old red brick",
    (0.12, 0.026, 0.011, 1),
    (0.43, 0.105, 0.036, 1),
    roughness=0.93, scale=4.0, detail=4.0,
    bump_strength=0.24, bump_distance=0.05
)
BRICK2 = make_simple_material(
    "Blackened brick", (0.16, 0.047, 0.018, 1), roughness=0.95
)
MORTAR = make_simple_material(
    "Exposed old mortar", (0.12, 0.105, 0.077, 1), roughness=1.0
)

DARK = make_simple_material(
    "Unlit abandoned interior", (0.0025, 0.003, 0.0025, 1), roughness=1.0
)
CRACK = make_simple_material(
    "Deep plaster cracks", (0.018, 0.012, 0.007, 1), roughness=1.0
)
GLASS = make_simple_material(
    "Dusty broken glass", (0.16, 0.28, 0.29, 0.33),
    roughness=0.18, alpha=0.33, transmission=0.35
)
WATER = make_simple_material(
    "Dark rain puddles", (0.025, 0.075, 0.09, 1),
    roughness=0.14, metallic=0.1
)
ROPE = make_simple_material(
    "Old well rope", (0.16, 0.08, 0.025, 1), roughness=0.98
)

# ---------------------------------------------------------------------
# Terrain, lane, puddles, stones, and ground vegetation
# ---------------------------------------------------------------------

x0, x1 = -19.0, 19.0
y0, y1 = -11.0, 34.0
nx, ny = 60, 70
verts = []
faces = []
for j in range(ny + 1):
    y = y0 + (y1 - y0) * j / ny
    for i in range(nx + 1):
        x = x0 + (x1 - x0) * i / nx
        verts.append((x, y, terrain_z(x, y)))
for j in range(ny):
    for i in range(nx):
        a = j * (nx + 1) + i
        b = a + 1
        d = (j + 1) * (nx + 1) + i
        c = d + 1
        faces.append((a, b, c, d))
ground = add_mesh_obj("Rolling overgrown village ground", verts, faces, [GROUND], smooth=True)

# Low rolling backdrop to hide the terrain edge naturally.
for idx, (loc, scale) in enumerate([
    ((-11, 30.5, -1.25), (10.5, 5.6, 2.7)),
    ((1.0, 31.7, -1.4), (12.5, 5.3, 2.9)),
    ((12.5, 30.5, -1.35), (9.0, 5.6, 2.6)),
]):
    add_ico("Distant rolling hill %02d" % idx, loc, scale, HILL_MAT,
            subdivisions=2, smooth=True)

# Winding mud lane.
path_verts = []
path_faces = []
samples = 58
for i in range(samples):
    y = -9.0 + 36.0 * i / (samples - 1)
    width = 1.18 + 0.22 * math.sin(y * 0.31 + 0.8)
    cx = path_x(y)
    path_verts.extend([
        (cx - width, y, terrain_z(cx - width, y) + 0.025),
        (cx + width, y, terrain_z(cx + width, y) + 0.025)
    ])
for i in range(samples - 1):
    a = i * 2
    path_faces.append((a, a + 1, a + 3, a + 2))
add_mesh_obj("Narrow muddy village lane", path_verts, path_faces, [PATH_MAT])

# Embedded remnants of old cobbles.
stone_verts = []
stone_faces = []
stone_mats = []
for s in range(118):
    y = random.uniform(-7.8, 23.0)
    cx = path_x(y)
    x = cx + random.uniform(-0.93, 0.93)
    if random.random() < 0.16:
        x += random.choice([-1, 1]) * random.uniform(0.25, 0.55)
    z = terrain_z(x, y) + 0.037
    rx = random.uniform(0.12, 0.30)
    ry = random.uniform(0.10, 0.24)
    h = random.uniform(0.045, 0.105)
    sides = 6
    base = len(stone_verts)
    for k in range(sides):
        ang = math.tau * k / sides
        jitter = random.uniform(0.86, 1.12)
        stone_verts.append((x + math.cos(ang) * rx * jitter,
                            y + math.sin(ang) * ry * jitter, z))
    for k in range(sides):
        ang = math.tau * k / sides
        jitter = random.uniform(0.86, 1.10)
        stone_verts.append((x + math.cos(ang) * rx * jitter,
                            y + math.sin(ang) * ry * jitter, z + h))
    stone_faces.append(tuple(base + sides + k for k in range(sides)))
    stone_mats.append(random.randrange(3))
    for k in range(sides):
        stone_faces.append((
            base + k,
            base + (k + 1) % sides,
            base + sides + (k + 1) % sides,
            base + sides + k
        ))
        stone_mats.append(random.randrange(3))
add_mesh_obj("Scattered sunken cobblestones", stone_verts, stone_faces,
             [STONE1, STONE2, STONE3], stone_mats)

# Puddles on the abandoned lane.
for pi, y in enumerate([-5.2, 0.2, 5.9, 12.1]):
    cx = path_x(y) + random.uniform(-0.35, 0.35)
    cy = y
    ring = []
    count = 13
    center_z = terrain_z(cx, cy) + 0.067
    ring.append((cx, cy, center_z))
    for k in range(count):
        ang = math.tau * k / count
        rr = random.uniform(0.78, 1.15)
        ring.append((
            cx + math.cos(ang) * random.uniform(0.42, 0.84) * rr,
            cy + math.sin(ang) * random.uniform(0.18, 0.38) * rr,
            center_z
        ))
    puddle_faces = []
    for k in range(count):
        puddle_faces.append((0, 1 + k, 1 + (k + 1) % count))
    add_mesh_obj("Rain puddle %02d" % pi, ring, puddle_faces, [WATER])

planned_houses = [
    (-3.7, 3.0, 3.15),
    (4.15, 5.45, 2.75),
    (-5.1, 11.7, 2.45),
    (5.0, 14.6, 2.8),
]

# Thousands of visible blades, combined into one GLB-friendly mesh.
grass_verts = []
grass_faces = []
grass_indices = []
accepted = 0
attempts = 0
while accepted < 1050 and attempts < 10000:
    attempts += 1
    x = random.uniform(-14.5, 14.5)
    y = random.uniform(-8.8, 24.5)
    blocked = False
    for hx, hy, hr in planned_houses:
        if (x - hx) ** 2 + (y - hy) ** 2 < (hr * 0.78) ** 2:
            blocked = True
            break
    if blocked:
        continue
    if (x - 0.1) ** 2 + (y - 9.0) ** 2 < 1.25 ** 2:
        continue
    if abs(x - path_x(y)) < 1.05 and random.random() < 0.72:
        continue

    z = terrain_z(x, y) + 0.025
    for blade in range(random.randint(3, 5)):
        bx = x + random.uniform(-0.11, 0.11)
        by = y + random.uniform(-0.11, 0.11)
        bz = terrain_z(bx, by) + 0.025
        ang = random.uniform(0, math.tau)
        width = random.uniform(0.012, 0.026)
        height = random.uniform(0.16, 0.58)
        if random.random() < 0.08:
            height *= 1.5
        right = Vector((math.cos(ang), math.sin(ang), 0)) * width
        bend = Vector((random.uniform(-0.08, 0.08),
                       random.uniform(-0.08, 0.08), height))
        basev = Vector((bx, by, bz))
        top = basev + bend
        index = len(grass_verts)
        grass_verts.extend([
            tuple(basev - right),
            tuple(basev + right),
            tuple(top + right * 0.15),
            tuple(top - right * 0.15)
        ])
        grass_faces.append((index, index + 1, index + 2, index + 3))
        r = random.random()
        grass_indices.append(0 if r < 0.42 else (1 if r < 0.83 else 2))
    accepted += 1
add_mesh_obj("Wild grass carpet", grass_verts, grass_faces,
             [GRASS1, GRASS2, GRASS_DRY], grass_indices)

# Fallen leaves scattered through the foreground and lane.
leaf_verts = []
leaf_faces = []
leaf_indices = []
for i in range(230):
    x = random.uniform(-10.5, 10.5)
    y = random.uniform(-7.5, 17.5)
    z = terrain_z(x, y) + 0.048
    ang = random.uniform(0, math.tau)
    length = random.uniform(0.055, 0.145)
    width = length * random.uniform(0.35, 0.6)
    a = Vector((math.cos(ang), math.sin(ang), 0)) * length
    b = Vector((-math.sin(ang), math.cos(ang), 0)) * width
    c = Vector((x, y, z))
    index = len(leaf_verts)
    leaf_verts.extend([tuple(c + a), tuple(c + b), tuple(c - a), tuple(c - b)])
    leaf_faces.append((index, index + 1, index + 2, index + 3))
    leaf_indices.append(random.randrange(3))
add_mesh_obj("Fallen leaf litter", leaf_verts, leaf_faces,
             [LEAF_DRY, GRASS_DRY, VINE_BROWN], leaf_indices)

# ---------------------------------------------------------------------
# Architectural detail helpers
# ---------------------------------------------------------------------

def add_front_window(root, d, x, z, width, height, name,
                     broken=True, shutter=False):
    y = -d * 0.5
    add_box(name + " black opening", (x, y - 0.025, z),
            (width + 0.08, 0.04, height + 0.08), DARK, parent=root)
    fy = y - 0.095
    frame = random.choice([WOOD, WOOD_DARK, WOOD_GRAY])
    add_box(name + " left jamb", (x - width * 0.5, fy, z),
            (0.105, 0.11, height + 0.17), frame, parent=root, bevel=0.015)
    add_box(name + " right jamb", (x + width * 0.5, fy, z),
            (0.105, 0.11, height + 0.17), frame, parent=root, bevel=0.015)
    add_box(name + " sill", (x, fy - 0.005, z - height * 0.5),
            (width + 0.21, 0.14, 0.105), frame, parent=root, bevel=0.015)
    add_box(name + " sagging lintel", (x, fy, z + height * 0.5),
            (width + 0.22, 0.12, 0.11), frame,
            rot=(0, 0, random.uniform(-0.035, 0.035)),
            parent=root, bevel=0.015)

    if broken:
        add_box(name + " broken lower mullion",
                (x + random.uniform(-0.06, 0.06), fy - 0.015,
                 z - height * 0.22),
                (0.07, 0.09, height * 0.48), frame,
                rot=(0, 0, random.uniform(-0.11, 0.11)),
                parent=root, bevel=0.01)
        add_box(name + " broken cross piece",
                (x - width * 0.24, fy - 0.02, z + 0.04),
                (width * 0.42, 0.085, 0.065), frame,
                rot=(0, 0, random.uniform(-0.05, 0.05)),
                parent=root, bevel=0.008)

        gy = fy - 0.075
        glass_verts = [
            (x - width * 0.43, gy, z + height * 0.40),
            (x - width * 0.03, gy, z + height * 0.40),
            (x - width * 0.35, gy, z + height * 0.06),
            (x + width * 0.45, gy, z - height * 0.40),
            (x + width * 0.08, gy, z - height * 0.36),
            (x + width * 0.38, gy, z - height * 0.05),
        ]
        add_mesh_obj(name + " surviving glass shards", glass_verts,
                     [(0, 1, 2), (3, 4, 5)], [GLASS], parent=root)
    else:
        add_box(name + " center mullion", (x, fy - 0.015, z),
                (0.065, 0.08, height), frame, parent=root, bevel=0.008)
        add_box(name + " center crossbar", (x, fy - 0.015, z),
                (width, 0.08, 0.065), frame, parent=root, bevel=0.008)

    add_ico(name + " mossy sill", (x - width * 0.18, fy - 0.045,
                                   z - height * 0.5 + 0.065),
            (width * 0.25, 0.055, 0.065),
            random.choice([MOSS, MOSS_LIGHT]), root, subdivisions=1)

    if shutter:
        hinge = make_empty(name + " shutter hinge",
                           (x - width * 0.5 - 0.03, fy - 0.03, z),
                           parent=root)
        hinge.rotation_euler[2] = math.radians(-58)
        sw = width * 0.52
        add_box(name + " hanging shutter", (sw * 0.5, 0, 0),
                (sw, 0.075, height * 0.96), WOOD_DARK,
                parent=hinge, bevel=0.018)
        add_box(name + " shutter brace 1", (sw * 0.5, -0.045, height * 0.26),
                (sw * 0.88, 0.035, 0.08), WOOD,
                parent=hinge, bevel=0.008)
        add_box(name + " shutter brace 2", (sw * 0.5, -0.045, -height * 0.23),
                (sw * 0.88, 0.035, 0.08), WOOD,
                parent=hinge, bevel=0.008)

def add_side_window(root, w_house, y, z, width, height, name, broken=True):
    x = w_house * 0.5
    add_box(name + " black opening", (x + 0.025, y, z),
            (0.04, width + 0.08, height + 0.08), DARK, parent=root)
    fx = x + 0.095
    frame = random.choice([WOOD, WOOD_DARK, WOOD_GRAY])
    add_box(name + " near jamb", (fx, y - width * 0.5, z),
            (0.11, 0.105, height + 0.16), frame, parent=root, bevel=0.014)
    add_box(name + " far jamb", (fx, y + width * 0.5, z),
            (0.11, 0.105, height + 0.16), frame, parent=root, bevel=0.014)
    add_box(name + " side sill", (fx, y, z - height * 0.5),
            (0.14, width + 0.2, 0.105), frame, parent=root, bevel=0.014)
    add_box(name + " side lintel", (fx, y, z + height * 0.5),
            (0.13, width + 0.2, 0.105), frame, parent=root, bevel=0.014)
    if broken:
        add_box(name + " crooked side mullion", (fx + 0.01, y, z - 0.12),
                (0.08, 0.07, height * 0.68), frame,
                rot=(random.uniform(-0.08, 0.08), 0, 0),
                parent=root, bevel=0.008)
    else:
        add_box(name + " side crossbar", (fx + 0.01, y, z),
                (0.08, width, 0.065), frame, parent=root, bevel=0.008)

def add_back_window(root, d, x, z, width, height, name):
    y = d * 0.5
    add_box(name + " dark recess", (x, y + 0.025, z),
            (width, 0.04, height), DARK, parent=root)
    fy = y + 0.09
    for xx in [x - width * 0.5, x + width * 0.5]:
        add_box(name + " back jamb", (xx, fy, z),
                (0.095, 0.11, height + 0.12), WOOD_GRAY,
                parent=root, bevel=0.012)
    for zz in [z - height * 0.5, z + height * 0.5]:
        add_box(name + " back rail", (x, fy, zz),
                (width + 0.17, 0.11, 0.095), WOOD_GRAY,
                parent=root, bevel=0.012)

def add_front_door(root, d, x, name, open_angle=-28):
    y = -d * 0.5
    width = 1.12
    height = 2.24
    z = 0.25 + height * 0.5
    add_box(name + " pitch black doorway", (x, y - 0.025, z),
            (width + 0.12, 0.045, height + 0.1), DARK, parent=root)
    fy = y - 0.10
    add_box(name + " door left post", (x - width * 0.5, fy, z),
            (0.14, 0.15, height + 0.2), WOOD_DARK,
            parent=root, bevel=0.02)
    add_box(name + " door right post", (x + width * 0.5, fy, z),
            (0.14, 0.15, height + 0.2), WOOD_DARK,
            parent=root, bevel=0.02)
    add_box(name + " bowed door lintel", (x, fy, z + height * 0.5),
            (width + 0.25, 0.16, 0.15), WOOD_DARK,
            rot=(0, 0, math.radians(random.uniform(-2.0, 2.0))),
            parent=root, bevel=0.02)

    hinge = make_empty(name + " open door hinge",
                       (x - width * 0.5, y - 0.14, z), parent=root)
    hinge.rotation_euler[2] = math.radians(open_angle)
    add_box(name + " warped open door", (width * 0.5, 0, 0),
            (width, 0.105, height), WOOD, parent=hinge, bevel=0.022)
    for p in range(1, 5):
        px = width * p / 5
        add_box(name + " plank gap %02d" % p, (px, -0.06, 0),
                (0.024, 0.012, height * 0.94), WOOD_DARK,
                parent=hinge)
    add_box(name + " diagonal door brace", (width * 0.5, -0.07, 0),
            (width * 0.92, 0.045, 0.09), WOOD_DARK,
            rot=(0, 0, math.radians(28)), parent=hinge, bevel=0.008)
    add_ico(name + " rusty handle", (width * 0.86, -0.105, 0.02),
            (0.055, 0.035, 0.055), RUST_DARK, hinge, subdivisions=1)

def add_barn_doors(root, d, name):
    y = -d * 0.5
    z = 1.46
    add_box(name + " barn darkness", (0, y - 0.025, z),
            (2.65, 0.045, 2.52), DARK, parent=root)
    fy = y - 0.105
    add_box(name + " barn opening left post", (-1.35, fy, z),
            (0.18, 0.16, 2.72), WOOD_DARK, parent=root, bevel=0.022)
    add_box(name + " barn opening right post", (1.35, fy, z),
            (0.18, 0.16, 2.72), WOOD_DARK, parent=root, bevel=0.022)
    add_box(name + " barn lintel", (0, fy, 2.76),
            (2.88, 0.18, 0.18), WOOD_DARK,
            rot=(0, 0, math.radians(-1.7)), parent=root, bevel=0.022)

    left = add_box(name + " left barn door", (-0.70, fy - 0.06, z),
                   (1.25, 0.10, 2.40), WOOD, parent=root, bevel=0.018)
    left.rotation_euler[2] = math.radians(-4)
    right = add_box(name + " hanging barn door", (1.06, fy - 0.13, 1.30),
                    (0.92, 0.10, 2.20), WOOD_DARK,
                    rot=(0, 0, math.radians(11)), parent=root, bevel=0.018)
    for xx in [-1.05, -0.7, -0.35]:
        add_box(name + " barn plank seam", (xx, fy - 0.12, z),
                (0.025, 0.018, 2.25), WOOD_DARK, parent=root)

def add_brick_patch_front(root, d, cx, cz, sx, sz, name):
    y = -d * 0.5 - 0.05
    outline = [
        (cx - sx * 0.48, y, cz - sz * 0.16),
        (cx - sx * 0.36, y, cz - sz * 0.48),
        (cx + sx * 0.08, y, cz - sz * 0.52),
        (cx + sx * 0.50, y, cz - sz * 0.20),
        (cx + sx * 0.40, y, cz + sz * 0.34),
        (cx + sx * 0.05, y, cz + sz * 0.52),
        (cx - sx * 0.45, y, cz + sz * 0.27),
    ]
    add_mesh_obj(name + " missing plaster", outline,
                 [tuple(range(len(outline)))], [MORTAR], parent=root)
    bw = sx / 4.0
    bh = sz / 6.0
    for row in range(5):
        for col in range(3):
            bx = cx + (col - 1) * bw + (0.5 * bw if row % 2 else 0)
            bz = cz + (row - 2) * bh
            if ((bx - cx) / (sx * 0.52)) ** 2 + ((bz - cz) / (sz * 0.55)) ** 2 < 0.9:
                add_box(name + " exposed brick", (bx, y - 0.035, bz),
                        (bw * 0.82, 0.055, bh * 0.58),
                        random.choice([BRICK, BRICK2]), parent=root,
                        bevel=0.01)

def add_brick_patch_side(root, w, cy, cz, sy, sz, name):
    x = w * 0.5 + 0.05
    outline = [
        (x, cy - sy * 0.48, cz - sz * 0.20),
        (x, cy - sy * 0.36, cz - sz * 0.50),
        (x, cy + sy * 0.18, cz - sz * 0.48),
        (x, cy + sy * 0.50, cz - sz * 0.12),
        (x, cy + sy * 0.37, cz + sz * 0.43),
        (x, cy - sy * 0.10, cz + sz * 0.51),
        (x, cy - sy * 0.46, cz + sz * 0.22),
    ]
    add_mesh_obj(name + " missing side plaster", outline,
                 [tuple(range(len(outline)))], [MORTAR], parent=root)
    bw = sy / 4.0
    bh = sz / 6.0
    for row in range(5):
        for col in range(3):
            by = cy + (col - 1) * bw + (0.5 * bw if row % 2 else 0)
            bz = cz + (row - 2) * bh
            if ((by - cy) / (sy * 0.54)) ** 2 + ((bz - cz) / (sz * 0.55)) ** 2 < 0.92:
                add_box(name + " exposed side brick", (x + 0.035, by, bz),
                        (0.055, bw * 0.82, bh * 0.58),
                        random.choice([BRICK, BRICK2]), parent=root,
                        bevel=0.01)

def add_window_sprout(root, d, x, z, name):
    y = -d * 0.5 - 0.10
    points = [
        (x, y, z - 0.16),
        (x + 0.12, y - 0.35, z + 0.02),
        (x - 0.05, y - 0.68, z + 0.28),
        (x + 0.28, y - 0.92, z + 0.53),
    ]
    create_curve_mesh(name + " branch through window", points, 0.025,
                      VINE_BROWN, root)
    branch = [
        points[2],
        (x - 0.35, y - 0.77, z + 0.42),
        (x - 0.52, y - 0.86, z + 0.56)
    ]
    create_curve_mesh(name + " window branch fork", branch, 0.015,
                      VINE_STEM, root)
    centers = [
        points[1], points[2], points[3],
        branch[1], branch[2],
        (x + 0.10, y - 0.72, z + 0.37),
        (x + 0.36, y - 0.86, z + 0.48),
    ]
    create_leaf_mesh(name + " leaves through window", centers, 'front',
                     [LEAF1, LEAF2], root, (0.13, 0.24))

def add_ivy_front(root, w, d, eave, roof_h, x0, name, density=1.0):
    y = -d * 0.5 - 0.135
    n = 11
    max_z = eave + roof_h * 0.56
    main = []
    for i in range(n):
        t = i / (n - 1)
        z = 0.08 + t * (max_z - 0.08)
        x = x0 * (1.0 - 0.50 * t) + 0.19 * math.sin(t * 11.5 + x0)
        main.append((x, y, z))
    create_curve_mesh(name + " main ivy trunk", main, 0.027,
                      VINE_BROWN, root)

    leaves = []
    for i in range(1, n):
        p = Vector(main[i])
        leaves.append(tuple(p + Vector((random.uniform(-0.12, 0.12),
                                        -0.02,
                                        random.uniform(-0.10, 0.12)))))
        if random.random() < 0.75 * density:
            leaves.append(tuple(p + Vector((random.uniform(-0.18, 0.18),
                                            -0.025,
                                            random.uniform(-0.08, 0.15)))))

    branch_ids = [2, 4, 6, 8]
    for bi, idx in enumerate(branch_ids):
        start = Vector(main[idx])
        sign = -1 if bi % 2 == 0 else 1
        reach = random.uniform(0.45, 0.82) * density
        branch = [
            tuple(start),
            tuple(start + Vector((sign * reach * 0.55, -0.01, 0.18))),
            tuple(start + Vector((sign * reach, -0.015, 0.34)))
        ]
        create_curve_mesh(name + " ivy branch %02d" % bi, branch, 0.014,
                          VINE_STEM, root)
        leaves.extend([
            branch[1], branch[2],
            tuple(Vector(branch[2]) + Vector((sign * 0.12, -0.02, -0.08)))
        ])
    create_leaf_mesh(name + " ivy leaves", leaves, 'front',
                     [LEAF_DARK, LEAF1, LEAF2], root,
                     (0.11, 0.22))

def add_ivy_side(root, w, d, eave, y0, name):
    x = w * 0.5 + 0.135
    main = []
    for i in range(9):
        t = i / 8
        y = y0 * (1.0 - 0.42 * t) + 0.16 * math.sin(t * 10.0)
        z = 0.07 + t * (eave - 0.15)
        main.append((x, y, z))
    create_curve_mesh(name + " side ivy trunk", main, 0.025,
                      VINE_BROWN, root)
    leaves = []
    for i in range(1, 9):
        leaves.extend([
            main[i],
            (x + 0.025, main[i][1] + random.uniform(-0.20, 0.20),
             main[i][2] + random.uniform(-0.08, 0.12))
        ])
    for bi, idx in enumerate([2, 4, 6]):
        start = Vector(main[idx])
        sign = -1 if bi % 2 == 0 else 1
        branch = [
            tuple(start),
            tuple(start + Vector((0.01, sign * 0.38, 0.16))),
            tuple(start + Vector((0.015, sign * 0.69, 0.29)))
        ]
        create_curve_mesh(name + " side ivy fork %02d" % bi, branch,
                          0.013, VINE_STEM, root)
        leaves.extend([branch[1], branch[2]])
    create_leaf_mesh(name + " side ivy leaves", leaves, 'side',
                     [LEAF_DARK, LEAF1, LEAF2], root,
                     (0.11, 0.21))

def create_loose_sheet(name, parent, loc, size, rot):
    sx, sy = size
    nu, nv = 11, 18
    verts = []
    faces = []
    for j in range(nv + 1):
        v = j / nv
        yy = -sy * 0.5 + sy * v
        corr = 0.025 * math.sin(v * math.tau * 8)
        for i in range(nu + 1):
            u = i / nu
            xx = -sx * 0.5 + sx * u
            verts.append((xx, yy, corr))
    for j in range(nv):
        for i in range(nu):
            a = j * (nu + 1) + i
            faces.append((a, a + 1, a + nu + 2, a + nu + 1))
    obj = add_mesh_obj(name, verts, faces, [random.choice(ROOF_MATS)],
                       parent=parent, smooth=True)
    obj.location = loc
    obj.rotation_euler = rot
    solid = obj.modifiers.new("Ragged sheet thickness", 'SOLIDIFY')
    solid.thickness = 0.025
    return obj

def roof_holes(side, variant):
    if variant == 0:
        return ([(0.48, 0.32, 0.15, 0.085),
                 (0.73, 0.68, 0.09, 0.06)]
                if side == 1 else [(0.68, 0.56, 0.08, 0.05)])
    if variant == 1:
        return ([(0.39, 0.42, 0.21, 0.12),
                 (0.80, 0.17, 0.16, 0.10)]
                if side == 1 else [(0.60, 0.64, 0.12, 0.07)])
    if variant == 2:
        return [(0.73, 0.42, 0.10, 0.06)] if side == 1 else []
    return [(0.64, 0.32, 0.14, 0.08)] if side == 1 else []

def create_corrugated_roof(root, w, d, eave, rh, variant, name):
    span = w * 0.5 + 0.30
    ymin = -d * 0.5 - 0.32
    ymax = d * 0.5 + 0.32
    length = ymax - ymin
    nu = 17
    nv = max(48, int(length / 0.07))
    waves = max(13, int(length / 0.235))

    for side in [-1, 1]:
        holes = roof_holes(side, variant)
        verts = []
        faces = []
        indices = []
        panel_count = max(4, int(round(length / 0.78)))
        panel_assign = [random.randrange(len(ROOF_MATS))
                        for _ in range(panel_count)]
        for j in range(nv + 1):
            v = j / nv
            y = ymin + v * length
            corr = 0.034 * math.sin(v * math.tau * waves)
            for i in range(nu + 1):
                u = i / nu
                x = side * span * u
                z = eave + rh * (1.0 - u) + corr
                verts.append((x, y, z))
        for j in range(nv):
            vc = (j + 0.5) / nv
            for i in range(nu):
                uc = (i + 0.5) / nu
                missing = False
                for hu, hv, hru, hrv in holes:
                    if ((uc - hu) / hru) ** 2 + ((vc - hv) / hrv) ** 2 < 1.0:
                        missing = True
                        break
                if missing:
                    continue
                a = j * (nu + 1) + i
                b = a + 1
                d0 = (j + 1) * (nu + 1) + i
                c = d0 + 1
                if side == 1:
                    faces.append((a, b, c, d0))
                else:
                    faces.append((a, d0, c, b))
                panel = min(panel_count - 1, int(vc * panel_count))
                indices.append(panel_assign[panel])

        roof = add_mesh_obj(
            name + (" right corroded roof" if side == 1 else " left corroded roof"),
            verts, faces, ROOF_MATS, indices, root, smooth=True
        )
        solid = roof.modifiers.new("Thin torn metal edges", 'SOLIDIFY')
        solid.thickness = 0.025
        solid.offset = 0.0

        # Rafters visible beneath holes and at the open front edge.
        rafter_ys = [ymin + 0.06]
        for hole in holes:
            rafter_ys.extend([
                ymin + (hole[1] - hole[3] * 0.35) * length,
                ymin + (hole[1] + hole[3] * 0.35) * length
            ])
        for ri, ry in enumerate(rafter_ys):
            add_beam_between(
                name + " exposed rafter %d %d" % (side, ri),
                (side * 0.035, ry, eave + rh - 0.12),
                (side * (span - 0.07), ry, eave - 0.10),
                0.095, WOOD_DARK, root, bevel=0.01
            )

    add_cone_between(name + " rusted ridge cap",
                     (0, ymin, eave + rh + 0.045),
                     (0, ymax, eave + rh + 0.045),
                     0.095, 0.095, RUST_DARK, root,
                     vertices=12, smooth=True)

    # Broken guttering and downpipe.
    add_cone_between(name + " broken right gutter front",
                     (span + 0.02, ymin, eave - 0.03),
                     (span + 0.02, -0.12, eave - 0.03),
                     0.065, 0.065, RUST_DARK, root,
                     vertices=10, smooth=True)
    add_cone_between(name + " broken right gutter rear",
                     (span + 0.02, 0.26, eave - 0.05),
                     (span + 0.02, ymax, eave - 0.05),
                     0.065, 0.055, RUST_DARK, root,
                     vertices=10, smooth=True)
    add_cone_between(name + " left gutter",
                     (-span - 0.02, ymin, eave - 0.04),
                     (-span - 0.02, ymax * 0.65, eave - 0.04),
                     0.055, 0.055, RUST_DARK, root,
                     vertices=10, smooth=True)
    downpipe = [
        (span + 0.02, ymin + 0.04, eave - 0.02),
        (span + 0.06, ymin + 0.02, eave - 1.05),
        (span - 0.01, ymin - 0.02, eave - 2.00),
        (span + 0.19, ymin - 0.17, eave - 2.48),
    ]
    create_curve_mesh(name + " bent downpipe", downpipe, 0.052,
                      RUST_DARK, root)

    # Moss spread across both roof slopes.
    moss_count = 15 if variant in (0, 3) else 11
    for mi in range(moss_count):
        side = 1 if random.random() < 0.66 else -1
        u = random.uniform(0.28, 0.97)
        y = random.uniform(ymin + 0.12, ymax - 0.12)
        x = side * span * u
        z = eave + rh * (1.0 - u) + 0.065
        slope_angle = side * math.atan(rh / span)
        add_ico(
            name + " rooftop moss %02d" % mi,
            (x, y, z),
            (random.uniform(0.22, 0.63),
             random.uniform(0.16, 0.48),
             random.uniform(0.035, 0.075)),
            random.choice([MOSS, MOSS, MOSS_LIGHT]),
            root, subdivisions=2,
            rot=(0, slope_angle, random.uniform(-0.35, 0.35))
        )

    # Grass rooted in seams and blocked gutters.
    weed_verts = []
    weed_faces = []
    weed_indices = []
    for wi in range(15 if variant == 0 else 10):
        side = 1 if random.random() < 0.75 else -1
        u = random.uniform(0.72, 0.97)
        y = random.uniform(ymin + 0.12, ymax - 0.12)
        x = side * span * u
        z = eave + rh * (1.0 - u) + 0.07
        for blade in range(2):
            ang = random.uniform(0, math.tau)
            right = Vector((math.cos(ang), math.sin(ang), 0)) * 0.014
            base = Vector((x + random.uniform(-0.06, 0.06),
                           y + random.uniform(-0.06, 0.06), z))
            top = base + Vector((random.uniform(-0.05, 0.05),
                                 random.uniform(-0.05, 0.05),
                                 random.uniform(0.20, 0.48)))
            idx = len(weed_verts)
            weed_verts.extend([
                tuple(base - right), tuple(base + right),
                tuple(top + right * 0.12), tuple(top - right * 0.12)
            ])
            weed_faces.append((idx, idx + 1, idx + 2, idx + 3))
            weed_indices.append(random.choice([0, 0, 1]))
    add_mesh_obj(name + " plants growing from roof",
                 weed_verts, weed_faces,
                 [GRASS2, GRASS_DRY], weed_indices, root)

def add_brick_chimney(root, w, d, eave, rh, name):
    span = w * 0.5 + 0.30
    x = 0.72
    y = d * 0.15
    u = abs(x) / span
    roof_z = eave + rh * (1.0 - u)
    add_box(name + " crumbling brick chimney",
            (x, y, roof_z + 0.64),
            (0.58, 0.62, 1.34), BRICK, parent=root, bevel=0.025)
    for i in range(4):
        add_box(name + " chimney mortar band %02d" % i,
                (x, y, roof_z + 0.18 + i * 0.29),
                (0.605, 0.645, 0.035), MORTAR, parent=root)
    add_box(name + " soot-filled chimney mouth",
            (x, y, roof_z + 1.325),
            (0.43, 0.46, 0.025), DARK, parent=root)
    add_box(name + " broken chimney brick",
            (x + 0.17, y - 0.13, roof_z + 1.42),
            (0.24, 0.30, 0.20), BRICK2,
            rot=(0.05, 0.03, 0.09), parent=root, bevel=0.015)
    add_ico(name + " chimney base moss", (x, y, roof_z + 0.04),
            (0.38, 0.36, 0.07), MOSS, root, subdivisions=2)

def add_metal_stovepipe(root, w, d, eave, rh, name):
    span = w * 0.5 + 0.30
    x = -0.62
    y = 0.55
    u = abs(x) / span
    roof_z = eave + rh * (1.0 - u)
    points = [
        (x, y, roof_z - 0.04),
        (x, y, roof_z + 1.05),
        (x + 0.18, y, roof_z + 1.18),
    ]
    create_curve_mesh(name + " bent rusted stovepipe", points, 0.105,
                      RUST_DARK, root, bevel_resolution=2)
    add_cone_between(name + " stovepipe cap",
                     (x + 0.02, y, roof_z + 1.25),
                     (x + 0.33, y, roof_z + 1.25),
                     0.17, 0.11, RUST1, root, vertices=10, smooth=True)

# ---------------------------------------------------------------------
# House construction
# ---------------------------------------------------------------------

def create_house(name, loc, rot_z, w, d, h, rh, variant):
    root = make_empty(name + " ROOT",
                      (loc[0], loc[1], terrain_z(loc[0], loc[1]) + 0.025),
                      (0, 0, rot_z))
    base = 0.24
    eave = base + h
    wall_mat = [WALL1, WALL2, WALL_GREEN, WALL2][variant]

    add_box(name + " solid weathered shell",
            (0, 0, base + h * 0.5), (w, d, h),
            wall_mat, parent=root, bevel=0.045)

    # Triangular gable walls.
    gable_verts = [
        (-w * 0.5, -d * 0.5, eave),
        (w * 0.5, -d * 0.5, eave),
        (0, -d * 0.5, eave + rh),
        (w * 0.5, d * 0.5, eave),
        (-w * 0.5, d * 0.5, eave),
        (0, d * 0.5, eave + rh),
    ]
    add_mesh_obj(name + " plaster gables", gable_verts,
                 [(0, 1, 2), (3, 4, 5)], [wall_mat], parent=root)

    # Dark ceiling makes the roof holes visibly hollow.
    add_box(name + " dark exposed attic",
            (0, 0, eave + 0.02),
            (w - 0.22, d - 0.22, 0.07), DARK, parent=root)

    # Rotten front gable timbers.
    front_y = -d * 0.5 - 0.075
    add_beam_between(name + " left gable fascia",
                     (-w * 0.5, front_y, eave),
                     (0, front_y, eave + rh),
                     0.105, WOOD_DARK, root)
    add_beam_between(name + " right gable fascia",
                     (0, front_y, eave + rh),
                     (w * 0.5, front_y, eave),
                     0.105, WOOD_DARK, root)
    add_beam_between(name + " warped eave beam",
                     (-w * 0.5, front_y, eave),
                     (w * 0.5, front_y, eave),
                     0.12, WOOD_DARK, root)

    create_corrugated_roof(root, w, d, eave, rh, variant, name)

    # Irregular stone foundation on all sides.
    nfront = max(6, int(w / 0.62))
    nside = max(5, int(d / 0.62))
    for side_y in [-1, 1]:
        for i in range(nfront):
            if random.random() < 0.08:
                continue
            x = -w * 0.5 + (i + 0.5) * w / nfront
            y = side_y * (d * 0.5 + 0.035)
            add_ico(
                name + " foundation stone F",
                (x + random.uniform(-0.035, 0.035),
                 y + random.uniform(-0.025, 0.025),
                 0.17 + random.uniform(-0.02, 0.02)),
                (random.uniform(0.25, 0.34),
                 random.uniform(0.17, 0.23),
                 random.uniform(0.13, 0.19)),
                random.choice([STONE1, STONE1, STONE2, STONE3]),
                root, subdivisions=1,
                rot=(random.uniform(-0.15, 0.15),
                     random.uniform(-0.15, 0.15),
                     random.uniform(0, math.tau))
            )
    for side_x in [-1, 1]:
        for i in range(nside):
            if random.random() < 0.09:
                continue
            y = -d * 0.5 + (i + 0.5) * d / nside
            x = side_x * (w * 0.5 + 0.035)
            add_ico(
                name + " foundation stone S",
                (x + random.uniform(-0.025, 0.025),
                 y + random.uniform(-0.035, 0.035),
                 0.17 + random.uniform(-0.02, 0.02)),
                (random.uniform(0.17, 0.23),
                 random.uniform(0.25, 0.34),
                 random.uniform(0.13, 0.19)),
                random.choice([STONE1, STONE1, STONE2, STONE3]),
                root, subdivisions=1,
                rot=(random.uniform(-0.15, 0.15),
                     random.uniform(-0.15, 0.15),
                     random.uniform(0, math.tau))
            )

    # Dampness and moss spreading up the wall bases.
    for i in range(7):
        x = random.uniform(-w * 0.43, w * 0.43)
        z = random.uniform(0.30, 0.83)
        add_ico(name + " front wall moss %02d" % i,
                (x, -d * 0.5 - 0.035, z),
                (random.uniform(0.22, 0.60), 0.035,
                 random.uniform(0.11, 0.32)),
                random.choice([DAMP, MOSS, MOSS_LIGHT]),
                root, subdivisions=1)
    for i in range(5):
        y = random.uniform(-d * 0.42, d * 0.42)
        z = random.uniform(0.35, 1.05)
        add_ico(name + " side wall moss %02d" % i,
                (w * 0.5 + 0.035, y, z),
                (0.035, random.uniform(0.22, 0.58),
                 random.uniform(0.12, 0.36)),
                random.choice([DAMP, MOSS]),
                root, subdivisions=1)
    for i in range(3):
        x = random.uniform(-w * 0.35, w * 0.35)
        add_ico(name + " dark rain streak %02d" % i,
                (x, -d * 0.5 - 0.025, random.uniform(1.9, eave - 0.3)),
                (random.uniform(0.08, 0.15), 0.022,
                 random.uniform(0.32, 0.60)),
                DAMP, root, subdivisions=1)

    # Ground moss at the corners.
    for i in range(5):
        ang = random.uniform(0, math.tau)
        xx = math.cos(ang) * random.uniform(w * 0.45, w * 0.68)
        yy = math.sin(ang) * random.uniform(d * 0.45, d * 0.68)
        add_ico(name + " foundation ground moss %02d" % i,
                (xx, yy, 0.035),
                (random.uniform(0.32, 0.80),
                 random.uniform(0.26, 0.65),
                 random.uniform(0.025, 0.055)),
                random.choice([MOSS, MOSS_LIGHT]), root,
                subdivisions=2)

    # Cracks in the plaster.
    crack_x = random.uniform(-w * 0.3, w * 0.3)
    crack_points = [
        (crack_x, -d * 0.5 - 0.074, eave - 0.22),
        (crack_x - 0.10, -d * 0.5 - 0.076, eave - 0.73),
        (crack_x + 0.04, -d * 0.5 - 0.077, eave - 1.16),
        (crack_x - 0.16, -d * 0.5 - 0.078, eave - 1.65),
    ]
    create_curve_mesh(name + " main plaster crack", crack_points,
                      0.012, CRACK, root)
    fork = [
        crack_points[2],
        (crack_x + 0.34, -d * 0.5 - 0.078, eave - 1.35),
        (crack_x + 0.48, -d * 0.5 - 0.078, eave - 1.62)
    ]
    create_curve_mesh(name + " plaster crack fork", fork,
                      0.009, CRACK, root)

    if variant == 0:
        add_front_door(root, d, 1.22, name + " front")
        add_front_window(root, d, -1.20, 1.76, 1.30, 1.37,
                         name + " broken front window",
                         broken=True, shutter=True)
        add_front_window(root, d, 0.0, eave + rh * 0.38, 0.76, 0.68,
                         name + " shattered attic window",
                         broken=True, shutter=False)
        add_side_window(root, w, -0.42, 1.74, 1.20, 1.28,
                        name + " side window", True)
        add_back_window(root, d, -0.65, 1.63, 1.05, 1.12,
                        name + " rear window")
        add_window_sprout(root, d, -1.20, 1.76,
                          name + " living branch")
        add_brick_patch_side(root, w, 0.94, 1.48, 1.28, 1.22,
                             name + " exposed side bricks")
        add_ivy_front(root, w, d, eave, rh, -2.05,
                      name + " facade", 1.15)
        add_ivy_side(root, w, d, eave, 1.20,
                     name + " right wall")
        create_loose_sheet(name + " fallen roof sheet", root,
                           (w * 0.5 + 0.58, 1.17, 0.64),
                           (1.15, 1.52),
                           (0.10, math.radians(67), 0.14))
        add_brick_chimney(root, w, d, eave, rh, name)

    elif variant == 1:
        add_front_door(root, d, -1.05, name + " front", open_angle=-20)
        add_front_window(root, d, 0.86, 1.64, 1.18, 1.26,
                         name + " broken front window",
                         broken=True, shutter=False)
        add_front_window(root, d, 0.0, eave + rh * 0.36, 0.65, 0.58,
                         name + " loft hole", broken=True)
        add_side_window(root, w, 0.36, 1.64, 1.12, 1.22,
                        name + " broken side window", True)
        add_back_window(root, d, 0.55, 1.55, 0.92, 1.05,
                        name + " rear window")
        add_window_sprout(root, d, 0.86, 1.64,
                          name + " shrub through window")
        add_brick_patch_front(root, d, 1.72, 0.98, 1.02, 0.95,
                              name + " front exposed bricks")
        add_ivy_front(root, w, d, eave, rh, 1.82,
                      name + " facade", 1.0)
        add_ivy_side(root, w, d, eave, -1.12,
                     name + " side")
        create_loose_sheet(name + " hanging collapsed roof panel", root,
                           (0.70, -d * 0.5 - 0.48, eave - 0.32),
                           (1.10, 1.25),
                           (math.radians(48), 0.05, -0.10))
        add_metal_stovepipe(root, w, d, eave, rh, name)

    elif variant == 2:
        add_front_door(root, d, 0.72, name + " front", open_angle=-18)
        add_front_window(root, d, -0.98, 1.49, 1.03, 1.13,
                         name + " front window", True, False)
        add_side_window(root, w, -0.20, 1.48, 0.92, 1.06,
                        name + " side window", True)
        add_back_window(root, d, 0.45, 1.40, 0.88, 0.98,
                        name + " back window")
        add_brick_patch_front(root, d, -1.62, 0.86, 0.74, 0.72,
                              name + " crumbled plaster")
        add_ivy_front(root, w, d, eave, rh, -1.50,
                      name + " facade", 0.86)
        add_brick_chimney(root, w, d, eave, rh, name)

    else:
        add_barn_doors(root, d, name)
        add_front_window(root, d, 0.0, eave + rh * 0.37, 0.88, 0.66,
                         name + " empty hayloft", True, False)
        add_side_window(root, w, -0.35, 1.62, 1.12, 1.24,
                        name + " barn side window", True)
        add_back_window(root, d, -0.75, 1.56, 1.02, 1.10,
                        name + " barn rear window")
        add_brick_patch_side(root, w, 0.86, 1.05, 1.12, 0.98,
                             name + " barn side brick patch")
        add_ivy_front(root, w, d, eave, rh, 2.02,
                      name + " barn facade", 1.04)
        add_ivy_side(root, w, d, eave, 1.12,
                     name + " barn side")
    return root

hero_house = create_house(
    "Forsaken Cottage", (-3.7, 3.0), math.radians(5),
    5.25, 4.20, 3.60, 2.12, 0
)
right_house = create_house(
    "Collapsed Lane Cottage", (4.15, 5.45), math.radians(18),
    4.55, 3.78, 3.18, 1.72, 1
)
back_house = create_house(
    "Distant Sage Cottage", (-5.10, 11.70), math.radians(-6),
    4.05, 3.22, 2.84, 1.52, 2
)
barn_house = create_house(
    "Overgrown Village Barn", (5.0, 14.60), math.radians(11),
    5.05, 3.72, 3.12, 1.48, 3
)

# ---------------------------------------------------------------------
# Nature: ferns, shrubs, trees, and seed heads
# ---------------------------------------------------------------------

def create_fern(name, loc, scale=1.0):
    root = make_empty(name + " ROOT",
                      (loc[0], loc[1], terrain_z(loc[0], loc[1]) + 0.02))
    leaf_verts = []
    leaf_faces = []
    for frond in range(6):
        ang = math.tau * frond / 6 + random.uniform(-0.18, 0.18)
        radius = random.uniform(0.42, 0.68) * scale
        points = [
            (0, 0, 0.03),
            (math.cos(ang) * radius * 0.38,
             math.sin(ang) * radius * 0.38, 0.28 * scale),
            (math.cos(ang) * radius * 0.72,
             math.sin(ang) * radius * 0.72, 0.39 * scale),
            (math.cos(ang) * radius,
             math.sin(ang) * radius, 0.30 * scale),
        ]
        create_curve_mesh(name + " frond stem %02d" % frond,
                          points, 0.009 * scale, VINE_STEM, root)
        direction = Vector((math.cos(ang), math.sin(ang), 0))
        lateral = Vector((-math.sin(ang), math.cos(ang), 0))
        for j in range(2, 8):
            t = j / 8.0
            center = direction * radius * t
            center.z = (0.12 + 0.30 * math.sin(t * math.pi)) * scale
            leaflet_len = (0.15 * (1.0 - t * 0.55) + 0.035) * scale
            base_width = 0.035 * scale
            for sign in [-1, 1]:
                idx = len(leaf_verts)
                tip = center + lateral * sign * leaflet_len + direction * 0.025
                leaf_verts.extend([
                    tuple(center - direction * base_width),
                    tuple(tip),
                    tuple(center + direction * base_width),
                ])
                leaf_faces.append((idx, idx + 1, idx + 2))
    add_mesh_obj(name + " fern leaflets", leaf_verts, leaf_faces,
                 [FERN_MAT], parent=root)
    return root

def create_shrub(name, loc, size=1.0):
    root = make_empty(name + " ROOT",
                      (loc[0], loc[1], terrain_z(loc[0], loc[1]) + 0.01))
    tips = []
    for i in range(7):
        ang = math.tau * i / 7 + random.uniform(-0.32, 0.32)
        r = random.uniform(0.45, 0.78) * size
        tip = (math.cos(ang) * r, math.sin(ang) * r,
               random.uniform(0.72, 1.25) * size)
        mid = (math.cos(ang) * r * 0.45,
               math.sin(ang) * r * 0.45,
               tip[2] * 0.53)
        add_cone_between(name + " shrub branch A", (0, 0, 0.04),
                         mid, 0.035 * size, 0.022 * size,
                         VINE_BROWN, root, vertices=7)
        add_cone_between(name + " shrub branch B", mid, tip,
                         0.025 * size, 0.010 * size,
                         VINE_BROWN, root, vertices=7)
        tips.append(Vector(tip))
    for i, tip in enumerate(tips):
        for j in range(random.randint(1, 2)):
            offset = Vector((random.uniform(-0.22, 0.22),
                             random.uniform(-0.22, 0.22),
                             random.uniform(-0.12, 0.16))) * size
            add_ico(name + " shrub foliage %02d" % (i * 2 + j),
                    tuple(tip + offset),
                    (random.uniform(0.30, 0.48) * size,
                     random.uniform(0.27, 0.45) * size,
                     random.uniform(0.27, 0.48) * size),
                    random.choice([LEAF_DARK, LEAF1, LEAF2]),
                    root, subdivisions=1,
                    rot=(random.random(), random.random(), random.random()),
                    smooth=False)
    return root

def create_main_tree(name, loc, scale=1.0):
    root = make_empty(name + " ROOT",
                      (loc[0], loc[1], terrain_z(loc[0], loc[1]) + 0.01))
    S = lambda p: tuple(v * scale for v in p)
    trunk_points = [
        S((0, 0, 0)),
        S((0.18, 0.02, 1.8)),
        S((-0.10, 0.08, 3.55)),
        S((0.30, 0.02, 5.25)),
        S((0.12, 0.18, 7.10)),
        S((-0.18, 0.24, 8.35)),
    ]
    radii = [0.60, 0.52, 0.43, 0.34, 0.25]
    for i in range(len(trunk_points) - 1):
        add_cone_between(name + " gnarled trunk %02d" % i,
                         trunk_points[i], trunk_points[i + 1],
                         radii[i] * scale, radii[i + 1] * scale,
                         WOOD_DARK, root, vertices=10)

    branches = [
        ((-0.06, 0.05, 3.45), (-1.30, 0.10, 4.85), (-3.05, 0.35, 6.20), True),
        ((0.17, 0.02, 4.15), (1.42, -0.35, 5.35), (3.18, -0.62, 6.35), False),
        ((0.24, 0.10, 5.22), (1.55, 0.66, 6.72), (2.52, 1.25, 8.05), True),
        ((0.12, 0.16, 6.02), (-1.25, 0.70, 7.34), (-2.35, 1.50, 8.35), True),
        ((0.04, 0.20, 6.90), (1.10, -0.08, 8.10), (1.55, -0.55, 9.10), True),
        ((-0.03, 0.20, 7.28), (-0.70, -0.55, 8.45), (-1.25, -1.05, 9.05), False),
    ]
    foliage_points = []
    for i, (p0, p1, p2, leafy) in enumerate(branches):
        p0s, p1s, p2s = S(p0), S(p1), S(p2)
        add_cone_between(name + " heavy branch A %02d" % i,
                         p0s, p1s, 0.22 * scale, 0.12 * scale,
                         WOOD_DARK, root, vertices=8)
        add_cone_between(name + " heavy branch B %02d" % i,
                         p1s, p2s, 0.13 * scale, 0.045 * scale,
                         WOOD_DARK, root, vertices=8)
        if leafy:
            foliage_points.extend([Vector(p1s), Vector(p2s)])

    # Dead twigs over the cottage.
    twig_specs = [
        ((3.18, -0.62, 6.35), (3.75, -0.92, 7.05)),
        ((3.18, -0.62, 6.35), (3.50, -0.15, 7.28)),
        ((-1.25, -1.05, 9.05), (-1.75, -1.45, 9.62)),
    ]
    for i, (a, b) in enumerate(twig_specs):
        add_cone_between(name + " bare twig %02d" % i, S(a), S(b),
                         0.045 * scale, 0.012 * scale,
                         WOOD_DARK, root, vertices=7)

    foliage_points.extend([
        Vector(S((-1.55, 0.62, 7.30))),
        Vector(S((0.75, 0.72, 8.25))),
        Vector(S((-0.35, 0.25, 9.00))),
        Vector(S((1.45, 0.10, 8.85))),
    ])
    for i, center in enumerate(foliage_points):
        for j in range(2):
            offset = Vector((random.uniform(-0.42, 0.42),
                             random.uniform(-0.42, 0.42),
                             random.uniform(-0.28, 0.32))) * scale
            add_ico(name + " sparse crown %02d" % (i * 2 + j),
                    tuple(center + offset),
                    (random.uniform(0.62, 1.05) * scale,
                     random.uniform(0.52, 0.92) * scale,
                     random.uniform(0.55, 1.00) * scale),
                    random.choice([LEAF_DARK, LEAF1, LEAF2]),
                    root, subdivisions=2, smooth=True)

    # Exposed roots.
    for i, ang in enumerate([-2.7, -1.65, -0.55, 0.45, 1.6, 2.55]):
        end = (math.cos(ang) * random.uniform(1.2, 2.2) * scale,
               math.sin(ang) * random.uniform(1.0, 1.8) * scale,
               0.03)
        add_cone_between(name + " exposed root %02d" % i,
                         (0, 0, 0.22 * scale), end,
                         0.17 * scale, 0.025 * scale,
                         WOOD_DARK, root, vertices=8)
    add_ico(name + " moss on trunk", (0.36 * scale, -0.18 * scale, 0.62 * scale),
            (0.34 * scale, 0.25 * scale, 0.46 * scale),
            MOSS, root, subdivisions=2)

    ivy_points = [
        S((0.42, -0.18, 0.12)),
        S((0.50, -0.25, 1.35)),
        S((0.20, -0.31, 2.65)),
        S((0.38, -0.26, 4.10)),
        S((0.05, -0.18, 5.22)),
    ]
    create_curve_mesh(name + " trunk ivy", ivy_points,
                      0.035 * scale, VINE_BROWN, root)
    create_leaf_mesh(name + " trunk ivy leaves",
                     [ivy_points[1], ivy_points[2], ivy_points[3],
                      ivy_points[4],
                      S((0.60, -0.27, 2.0)),
                      S((-0.05, -0.25, 3.45))],
                     'front', [LEAF_DARK, LEAF1], root,
                     (0.14 * scale, 0.25 * scale))
    return root

def create_background_tree(name, loc, height, haze=False):
    root = make_empty(name + " ROOT",
                      (loc[0], loc[1], terrain_z(loc[0], loc[1]) + 0.01))
    foliage_mat = LEAF_HAZE if haze else LEAF_DARK
    p0 = (0, 0, 0)
    p1 = (random.uniform(-0.18, 0.18), 0, height * 0.52)
    p2 = (random.uniform(-0.28, 0.28), random.uniform(-0.12, 0.12), height)
    add_cone_between(name + " trunk lower", p0, p1,
                     height * 0.055, height * 0.033,
                     WOOD_DARK, root, vertices=8)
    add_cone_between(name + " trunk upper", p1, p2,
                     height * 0.034, height * 0.015,
                     WOOD_DARK, root, vertices=8)
    for i in range(6):
        ang = math.tau * i / 6 + random.uniform(-0.4, 0.4)
        center = (
            p2[0] + math.cos(ang) * random.uniform(0.45, 1.25),
            p2[1] + math.sin(ang) * random.uniform(0.30, 1.0),
            height * random.uniform(0.72, 1.04)
        )
        add_ico(name + " distant crown %02d" % i, center,
                (random.uniform(0.75, 1.35),
                 random.uniform(0.65, 1.2),
                 random.uniform(0.75, 1.4)),
                foliage_mat if random.random() < 0.7 else LEAF_DARK,
                root, subdivisions=1, smooth=True)
    return root

create_main_tree("Ancient Reclaiming Tree", (-8.25, 7.8), 1.18)

for i, (x, y, h) in enumerate([
    (-13.2, 23.5, 7.6),
    (-9.1, 27.0, 8.3),
    (-1.5, 26.6, 7.1),
    (8.8, 25.8, 8.8),
    (13.2, 22.7, 7.4),
]):
    create_background_tree("Background tree %02d" % i, (x, y), h, haze=True)

for i, (x, y, size) in enumerate([
    (-6.55, 5.55, 1.10),
    (-0.72, 4.85, 0.82),
    (6.52, 7.25, 1.08),
    (2.55, 12.0, 0.90),
    (-7.1, 13.2, 0.96),
    (7.55, 16.0, 1.10),
    (-1.15, 16.8, 0.78),
]):
    create_shrub("Wild shrub %02d" % i, (x, y), size)

for i, (x, y, size) in enumerate([
    (-5.45, 0.72, 1.0),
    (-0.92, 3.65, 1.08),
    (2.35, 3.55, 0.92),
    (-0.78, 8.52, 1.06),
    (2.75, -2.85, 0.95),
    (5.95, 4.15, 0.90),
]):
    create_fern("Wild fern %02d" % i, (x, y), size)

# Moss mats spreading across the ground around each building.
for hi, (hx, hy, hr) in enumerate(planned_houses):
    for j in range(4):
        ang = random.uniform(0, math.tau)
        rr = random.uniform(hr * 0.70, hr * 1.05)
        x = hx + math.cos(ang) * rr
        y = hy + math.sin(ang) * rr
        add_ico("Ground moss patch %02d %02d" % (hi, j),
                (x, y, terrain_z(x, y) + 0.035),
                (random.uniform(0.45, 1.10),
                 random.uniform(0.32, 0.80),
                 random.uniform(0.025, 0.055)),
                random.choice([MOSS, MOSS_LIGHT]),
                subdivisions=2)

# Tall dry seed heads.
for i in range(25):
    for attempt in range(20):
        x = random.uniform(-10.0, 10.0)
        y = random.uniform(-6.5, 17.0)
        if abs(x - path_x(y)) > 0.45 or random.random() < 0.35:
            break
    z = terrain_z(x, y) + 0.03
    height = random.uniform(0.42, 0.92)
    lean = Vector((random.uniform(-0.08, 0.08),
                   random.uniform(-0.08, 0.08), height))
    add_cone_between("Dry weed stalk %02d" % i,
                     (x, y, z), Vector((x, y, z)) + lean,
                     0.013, 0.006, GRASS_DRY, vertices=6)
    tip = Vector((x, y, z)) + lean
    add_ico("Dry seed head %02d" % i, tip,
            (0.045, 0.045, 0.075), GRASS_DRY,
            subdivisions=1)

# ---------------------------------------------------------------------
# Abandoned stone well
# ---------------------------------------------------------------------

def create_well(loc):
    root = make_empty("Overgrown Village Well ROOT",
                      (loc[0], loc[1], terrain_z(loc[0], loc[1]) + 0.015),
                      (0, 0, math.radians(4)))
    stones = 15
    for layer in range(2):
        for i in range(stones):
            ang = math.tau * (i + layer * 0.5) / stones
            radius = 0.84
            x = math.cos(ang) * radius
            y = math.sin(ang) * radius
            z = 0.17 + layer * 0.27
            add_box("Well ring stone", (x, y, z),
                    (0.48, 0.34, 0.255),
                    random.choice([STONE1, STONE1, STONE2, STONE3]),
                    rot=(random.uniform(-0.08, 0.08),
                         random.uniform(-0.08, 0.08),
                         ang + math.pi * 0.5 + random.uniform(-0.06, 0.06)),
                    parent=root, bevel=0.055)
            if layer == 1 and i % 4 == 0:
                add_ico("Moss on well stone", (x, y, z + 0.145),
                        (0.25, 0.18, 0.045),
                        random.choice([MOSS, MOSS_LIGHT]),
                        root, subdivisions=2)
    bpy.ops.mesh.primitive_cylinder_add(vertices=32, radius=0.68,
                                       depth=0.035,
                                       location=(0, 0, 0.60))
    opening = bpy.context.object
    opening.name = "Black water deep in well"
    opening.parent = root
    assign_material(opening, DARK)

    left_post = add_box("Well left rotten post", (-1.10, 0, 1.56),
                        (0.21, 0.24, 2.45), WOOD_DARK,
                        rot=(0.02, -0.05, -0.025),
                        parent=root, bevel=0.025)
    right_post = add_box("Well right leaning post", (1.10, 0, 1.50),
                         (0.21, 0.24, 2.34), WOOD_DARK,
                         rot=(0.04, 0.09, 0.04),
                         parent=root, bevel=0.025)
    add_beam_between("Broken well crossbeam",
                     (-1.18, 0, 2.76), (1.17, 0, 2.70),
                     0.19, WOOD_DARK, root, bevel=0.025)
    add_cone_between("Well spindle",
                     (-0.72, -0.02, 2.05), (0.72, -0.02, 2.05),
                     0.10, 0.10, WOOD, root, vertices=10)
    create_curve_mesh("Well rope",
                      [(0.08, -0.03, 2.05),
                       (0.10, -0.05, 1.42),
                       (0.04, -0.03, 0.62)],
                      0.024, ROPE, root)
    add_ivy_side(root, 2.17, 0.45, 2.55, 0.05, "Well post ivy")
    return root

create_well((0.15, 9.0))

# ---------------------------------------------------------------------
# Broken wheelbarrow in the foreground
# ---------------------------------------------------------------------

def create_wheelbarrow(loc):
    root = make_empty("Abandoned Rusty Wheelbarrow ROOT",
                      (loc[0], loc[1], terrain_z(loc[0], loc[1]) + 0.02),
                      (0, 0, math.radians(-18)))

    verts = [
        (-0.42, -0.27, 0.22),
        (0.42, -0.27, 0.22),
        (0.38, 0.28, 0.22),
        (-0.38, 0.28, 0.22),
        (-0.74, -0.50, 0.72),
        (0.74, -0.50, 0.72),
        (0.64, 0.51, 0.72),
        (-0.64, 0.51, 0.72),
    ]
    faces = [
        (0, 3, 2, 1),
        (0, 1, 5, 4),
        (1, 2, 6, 5),
        (2, 3, 7, 6),
        (3, 0, 4, 7),
    ]
    bowl = add_mesh_obj("Corroded wheelbarrow basin", verts, faces,
                        [RUST1], parent=root)
    bowl.rotation_euler[0] = math.radians(-5)
    solid = bowl.modifiers.new("Pitted basin thickness", 'SOLIDIFY')
    solid.thickness = 0.025

    add_box("Soil collected in wheelbarrow", (0, -0.02, 0.57),
            (0.86, 0.56, 0.05), GROUND, parent=root, bevel=0.03)

    bpy.ops.mesh.primitive_torus_add(
        major_radius=0.34, minor_radius=0.055,
        major_segments=24, minor_segments=7,
        location=(0, 0.82, 0.34),
        rotation=(0, math.pi * 0.5, 0)
    )
    wheel = bpy.context.object
    wheel.name = "Wheelbarrow rusted wheel"
    wheel.parent = root
    assign_material(wheel, RUST_DARK)
    for poly in wheel.data.polygons:
        poly.use_smooth = True
    add_cone_between("Wheelbarrow axle",
                     (-0.43, 0.82, 0.34), (0.43, 0.82, 0.34),
                     0.04, 0.04, RUST_DARK, root, vertices=10)

    add_cone_between("Wheelbarrow left handle",
                     (-0.35, -0.26, 0.42), (-0.50, -1.42, 0.29),
                     0.045, 0.035, WOOD_DARK, root, vertices=8)
    add_cone_between("Wheelbarrow right handle",
                     (0.35, -0.26, 0.42), (0.50, -1.42, 0.29),
                     0.045, 0.035, WOOD_DARK, root, vertices=8)
    add_cone_between("Wheelbarrow broken leg",
                     (-0.29, -0.34, 0.34), (-0.36, -0.58, 0.03),
                     0.035, 0.025, RUST_DARK, root, vertices=7)

    # Weeds growing from the soil in the basin.
    for i in range(7):
        bx = random.uniform(-0.34, 0.34)
        by = random.uniform(-0.18, 0.20)
        height = random.uniform(0.25, 0.55)
        add_cone_between("Wheelbarrow weed %02d" % i,
                         (bx, by, 0.59),
                         (bx + random.uniform(-0.06, 0.06),
                          by + random.uniform(-0.06, 0.06),
                          0.59 + height),
                         0.012, 0.005,
                         random.choice([GRASS1, GRASS2, GRASS_DRY]),
                         root, vertices=6)
    return root

create_wheelbarrow((2.05, -2.25))

# ---------------------------------------------------------------------
# Broken fences with vines
# ---------------------------------------------------------------------

def create_fence(name, points):
    post_tops = []
    for i, (x, y) in enumerate(points):
        z = terrain_z(x, y)
        height = random.uniform(1.35, 1.75)
        post = add_box(name + " leaning post %02d" % i,
                       (x, y, z + height * 0.5),
                       (0.18, 0.18, height),
                       WOOD_GRAY,
                       rot=(random.uniform(-0.10, 0.10),
                            random.uniform(-0.10, 0.10),
                            random.uniform(-0.08, 0.08)),
                       bevel=0.025)
        post_tops.append((x, y, z, height))

    for i in range(len(points) - 1):
        if i == 1:
            # Deliberately missing upper rail.
            levels = [0.72]
        else:
            levels = [0.72, 1.25]
        for level in levels:
            x1, y1, z1, h1 = post_tops[i]
            x2, y2, z2, h2 = post_tops[i + 1]
            p1 = (x1, y1, z1 + min(level, h1 - 0.12))
            p2 = (x2, y2, z2 + min(level + random.uniform(-0.08, 0.08),
                                   h2 - 0.12))
            add_beam_between(name + " rotten rail", p1, p2,
                             0.12, WOOD_GRAY, bevel=0.018)

    # Ivy climbing the middle post.
    mid = len(points) // 2
    x, y = points[mid]
    z = terrain_z(x, y)
    vine = [
        (x - 0.09, y - 0.08, z + 0.02),
        (x + 0.08, y - 0.10, z + 0.48),
        (x - 0.06, y - 0.12, z + 0.94),
        (x + 0.07, y - 0.12, z + 1.43),
    ]
    create_curve_mesh(name + " fence ivy", vine, 0.022, VINE_BROWN)
    create_leaf_mesh(name + " fence ivy leaves",
                     [vine[1], vine[2], vine[3],
                      (x + 0.20, y - 0.12, z + 0.73),
                      (x - 0.22, y - 0.12, z + 1.16)],
                     'front', [LEAF_DARK, LEAF1, LEAF2],
                     size_range=(0.12, 0.23))

create_fence("Broken foreground fence",
             [(-8.2, -4.6), (-7.9, -2.6), (-7.55, -0.6), (-7.15, 1.15)])
create_fence("Distant broken fence",
             [(7.8, 8.2), (8.15, 10.2), (8.65, 12.0)])

# ---------------------------------------------------------------------
# Lighting, world, and presentation camera
# ---------------------------------------------------------------------

world = bpy.data.worlds.new("Clouded late-afternoon world")
world.use_nodes = True
scene.world = world
wnodes = world.node_tree.nodes
wlinks = world.node_tree.links
wnodes.clear()
wout = wnodes.new("ShaderNodeOutputWorld")
wbg = wnodes.new("ShaderNodeBackground")
sky = wnodes.new("ShaderNodeTexSky")
sky.sky_type = 'NISHITA'
sky.sun_elevation = math.radians(16)
sky.sun_rotation = math.radians(218)
try:
    sky.altitude = 0.15
    sky.air_density = 1.2
    sky.dust_density = 3.0
    sky.ozone_density = 1.15
    sky.sun_disc = True
    sky.sun_size = math.radians(2.5)
except Exception:
    pass
wbg.inputs["Strength"].default_value = 0.29
wlinks.new(sky.outputs["Color"], wbg.inputs["Color"])
wlinks.new(wbg.outputs["Background"], wout.inputs["Surface"])

def add_area_light(name, loc, target, energy, size, color):
    data = bpy.data.lights.new(name + " Data", type='AREA')
    data.energy = energy
    data.shape = 'DISK'
    data.size = size
    data.color = color
    obj = bpy.data.objects.new(name, data)
    scene.collection.objects.link(obj)
    obj.location = loc
    direction = Vector(target) - Vector(loc)
    obj.rotation_mode = 'QUATERNION'
    obj.rotation_quaternion = direction.to_track_quat('-Z', 'Y')
    return obj

def add_sun(name, loc, target, energy, angle, color):
    data = bpy.data.lights.new(name + " Data", type='SUN')
    data.energy = energy
    data.angle = angle
    data.color = color
    obj = bpy.data.objects.new(name, data)
    scene.collection.objects.link(obj)
    obj.location = loc
    direction = Vector(target) - Vector(loc)
    obj.rotation_mode = 'QUATERNION'
    obj.rotation_quaternion = direction.to_track_quat('-Z', 'Y')
    return obj

add_area_light(
    "Warm cloud-broken key",
    (-10.5, -9.0, 16.5), (-1.0, 6.0, 2.5),
    1550.0, 8.5, (1.0, 0.70, 0.45)
)
add_area_light(
    "Cool soft fill",
    (12.0, 1.5, 11.5), (0.0, 6.5, 2.5),
    520.0, 10.0, (0.46, 0.62, 0.82)
)
add_sun(
    "Low amber sun",
    (-12.0, -13.0, 20.0), (0.0, 7.0, 0.0),
    1.35, math.radians(10), (1.0, 0.67, 0.39)
)

camera_data = bpy.data.cameras.new("Presentation Camera Data")
camera = bpy.data.objects.new("Presentation Camera", camera_data)
scene.collection.objects.link(camera)
scene.camera = camera
camera.location = (13.8, -18.2, 9.25)
target = Vector((0.0, 6.2, 3.05))
direction = target - camera.location
camera.rotation_euler = direction.to_track_quat('-Z', 'Y').to_euler()
camera_data.lens = 50.0
camera_data.sensor_width = 36.0
camera_data.clip_start = 0.1
camera_data.clip_end = 180.0

focus = make_empty("Camera focus", (-0.7, 5.5, 2.55))
camera_data.dof.use_dof = True
camera_data.dof.focus_object = focus
camera_data.dof.aperture_fstop = 8.5
camera_data.dof.aperture_blades = 7

bpy.context.view_layer.update()
```