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1{
2 "name": "Help me reverse-engi",
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19 "text": "Help me reverse-engineer the Flux prompt for this artwork."
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23 "fileIdentifier": "1782325310659 - 847.png",
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47 "text": "A high-quality, anthropomorphic white wolf (furry) character standing in a forest by a stream.\n\n * *Subject:* Anthropomorphic female wolf (anthro).\n * *Coloring:* White/grey fur, blue eyes (heterochromia? one looks slightly different or just shaded), long flowing hair-like fur.\n * *Anatomy:* Humanoid body shape, slender build, large tail, pointed ears.\n * *Setting:* Forest, stream/river, rocks, sunlight filtering through trees (bokeh effect).\n * *Style:* 3D render, realistic textures, cinematic lighting, high detail (looks like Unreal Engine 5 or Octane Render style).\n\n * *Subject Keywords:* Anthropomorphic wolf, furry, female, white fur, long hair, blue eyes.\n * *Setting Keywords:* Forest, woodland, stream, river, rocks, nature, sunlight, dappled light.\n * *Style/Technical Keywords:* Photorealistic, 3D render, cinematic lighting, 8k, highly detailed, masterpiece, soft fur texture, depth of field.\n\n * *Option A: Descriptive & Natural (Good for Midjourney)*\n \"A photorealistic anthropomorphic white wolf standing by a forest stream. She has long flowing white hair and blue eyes. Cinematic lighting, dappled sunlight through trees, 8k resolution, highly detailed fur texture.\"\n\n * *Option B: Tag-based/Weighted (Good for Stable Diffusion)*\n \"anthro wolf, female, white fur, long hair, blue eyes, standing by a river, forest background, realistic, masterpiece, high quality, cinematic lighting, depth of field, 8k, ultra detailed.\"\n\n * *Option C: Artistic/Stylized (Focusing on the \"Vibe\")*\n \"A mystical white wolf spirit in a sunlit woodland. Ethereal atmosphere, soft fur, flowing hair, crystal clear water, hyper-realistic 3D render.\"\n\n * *Subject:* Anthropomorphic female wolf, white and grey fur, long flowing mane/hair, blue eyes.\n * *Environment:* Lush forest, rocky stream, sunlight filtering through leaves (God rays).\n * *Technical:* Unreal Engine 5 style, Octane Render, Ray tracing, Depth of Field (DoF), Subsurface scattering (for the fur).\n\n * Explain *why* these words were chosen.\n * Provide different versions based on common AI models (Midjourney vs. Stable Diffusion).",
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69 "text": "To reverse-engineer a prompt for an image like this, we need to break it down into four main components: **Subject, Environment, Style/Lighting, and Technical Quality.**\n\nBased on the visual data, here is how you would reconstruct the prompt for high-end AI generators (like Midjourney, Stable Diffusion, or DALL-E 3).\n\n### The \"Core\" Prompt\n> **A photorealistic anthropomorphic female white wolf standing by a forest stream. She has long flowing white hair, blue eyes, and highly detailed fur texture. Cinematic lighting with dappled sunlight filtering through trees, lush woodland background, 8k resolution, masterpiece.**\n\n---\n\n### Breakdown of the Elements (The \"Why\")\n\nIf you want to tweak the image, here is what each part of the prompt is doing:\n\n**1. The Subject (Anatomy & Character)**\n* **Keywords:** *Anthropomorphic wolf, furry, female, white fur, long flowing hair, blue eyes.*\n* **Details:** Notice how the fur transitions from white to grey on her arms. You could add \"gradient fur\" or \"grey-tipped fur\" to get that specific look.\n\n**2. The Environment (Setting)**\n* **Keywords:** *Forest stream, woodland, rocks, riverbank, dappled sunlight.*\n* **Details:** The background has a \"bokeh\" effect (blurred background). Adding \"shallow depth of field\" or \"soft focus background\" helps achieve this.\n\n**3. Style & Rendering (The \"Look\")**\n* **Keywords:** *Photorealistic, 3D render, Unreal Engine 5, Octane Render.*\n* **Details:** This image doesn't look like a painting; it looks like a high-end video game render. Using terms like \"subsurface scattering\" (which describes how light hits fur/skin) will make the fur look much more realistic.\n\n**4. Lighting & Color**\n* **Keywords:** *Cinematic lighting, golden hour, soft shadows.*\n* **Details:** The light is coming from above and slightly behind her, creating a \"rim light\" effect on her hair and ears.\n\n---\n\n### Variations for Different AI Models\n\nDepending on which tool you are using, the prompt structure changes:\n\n#### For Midjourney (Stylized & Descriptive)\n> **A stunning photorealistic anthropomorphic white wolf with long flowing hair standing in a sunlit forest by a clear stream, blue eyes, highly detailed fur texture, cinematic lighting, 8k, shot on 35mm lens --ar 2:3 --v 6.0**\n\n#### For Stable Diffusion (Tag-based)\n> **(masterpiece:1.2), (best quality), (photorealistic:1.3), 1girl, anthro wolf, white fur, long hair, blue eyes, standing by a river, forest background, dappled sunlight, depth of field, highly detailed fur, 8k, cinematic lighting.**\n\n#### For DALL-E 3 (Natural Language)\n> **A hyper-realistic 3D render of an anthropomorphic female wolf with white and grey fur. She has long, flowing hair and striking blue eyes. She is standing gracefully next to a rocky stream in a dense forest. Sunlight filters through the trees, creating a warm, dappled light effect on her fur.**",
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add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n type:{{ format_type_argument(item_value) }}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set 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{% endif -%}\n type:{{ format_type_argument(value['type']) }}}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:{{- format_type_argument(params['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] and ('object' in response_declaration['type'] or 'OBJECT' in response_declaration['type']) -%}\n type:{{- format_type_argument(response_declaration['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is iterable 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'{value:' + format_argument(response, escape_keys=False) + '}' -}}\n {%- endif -%}\n {{- '<tool_response|>' -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(prev_message_type=None) -%}\n{%- set loop_messages = messages -%}\n{{- bos_token -}}\n{#- Handle System/Tool Definitions Block -#}\n{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}\n {{- '<|turn>system\\n' -}}\n {#- Inject Thinking token at the very top of the FIRST system turn -#}\n {%- if enable_thinking is defined and enable_thinking -%}\n {{- '<|think|>\\n' -}}\n {%- set ns.prev_message_type = 'think' -%}\n {%- endif -%}\n {%- if messages[0]['role'] in ['system', 'developer'] -%}\n {%- if messages[0]['content'] is string -%}\n {{- messages[0]['content'] | trim -}}\n {%- elif messages[0]['content'] is iterable -%}\n {%- for item in messages[0]['content'] -%}\n {{- item['text'] | trim + ' '-}}\n {%- endfor -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n {%- endif -%}\n {%- if tools -%}\n {%- for tool in tools %}\n {{- '<|tool>' -}}\n {{- format_function_declaration(tool) | trim -}}\n {{- '<tool|>' -}}\n {%- endfor %}\n {%- set ns.prev_message_type = 'tool' -%}\n {%- endif -%}\n {{- '<turn|>\\n' -}}\n{%- endif %}\n\n{#- Pre-scan: find last user message index for reasoning guard -#}\n{%- set ns_turn = namespace(last_user_idx=-1) -%}\n{%- for i in range(loop_messages | length) -%}\n {%- if loop_messages[i]['role'] == 'user' -%}\n {%- set ns_turn.last_user_idx = i -%}\n {%- endif -%}\n{%- endfor -%}\n\n{#- Loop through messages -#}\n{%- for message in loop_messages -%}\n {%- if message['role'] != 'tool' -%}\n {%- set ns.prev_message_type = None -%}\n {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}\n {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}\n {%- set prev_nt = namespace(role=None, found=false) -%}\n {%- if loop.index0 > 0 -%}\n {%- for j in range(loop.index0 - 1, -1, -1) -%}\n {%- if not prev_nt.found -%}\n {%- if loop_messages[j]['role'] != 'tool' -%}\n {%- set prev_nt.role = loop_messages[j]['role'] -%}\n {%- set prev_nt.found = true -%}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}\n {%- if not continue_same_model_turn -%}\n {{- '<|turn>' + role + '\\n' }}\n {%- endif -%}\n\n {#- Render reasoning/reasoning_content as thinking channel -#}\n {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}\n {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}\n {{- '<|channel>thought\\n' + thinking_text + '\\n<channel|>' -}}\n {%- endif -%}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- set ns_tr_out = namespace(flag=false) -%}\n {%- if message.get('tool_responses') -%}\n {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endfor -%}\n {%- elif message.get('tool_calls') -%}\n {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}\n {%- set ns_tool_scan = namespace(stopped=false) -%}\n {%- for k in range(loop.index0 + 1, loop_messages | length) -%}\n {%- if ns_tool_scan.stopped -%}\n {%- elif loop_messages[k]['role'] != 'tool' -%}\n {%- set ns_tool_scan.stopped = true -%}\n {%- else -%}\n {%- set follow = loop_messages[k] -%}\n {#- Resolve tool_call_id to function name -#}\n {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}\n {%- for tc in message['tool_calls'] -%}\n {%- if tc.get('id') == follow.get('tool_call_id') -%}\n {%- set ns_tname.name = tc['function']['name'] -%}\n {%- endif -%}\n {%- endfor -%}\n {#- Handle content as string or content-parts array -#}\n {%- set tool_body = follow.get('content') -%}\n {%- if tool_body is string -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- elif tool_body is iterable and tool_body is not string -%}\n {%- set ns_txt = namespace(s='') -%}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'text' -%}\n {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'image' -%}\n {{- '<|image|>' -}}\n {%- elif part.get('type') == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- elif part.get('type') == 'video' -%}\n {{- '<|video|>' -}}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- endif -%}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n\n {%- set captured_content -%}\n {%- if message['content'] is string -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(message['content']) -}}\n {%- else -%}\n {{- message['content'] | trim -}}\n {%- endif -%}\n {%- elif message['content'] is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'text' -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(item['text']) -}}\n {%- else -%}\n {{- item['text'] | trim -}}\n {%- endif -%}\n {%- elif item['type'] == 'image' -%}\n {{- '<|image|>' -}}\n {%- set ns.prev_message_type = 'image' -%}\n {%- elif item['type'] == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- set ns.prev_message_type = 'audio' -%}\n {%- elif item['type'] == 'video' -%}\n {{- '<|video|>' -}}\n {%- set ns.prev_message_type = 'video' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- endset -%}\n\n {{- captured_content -}}\n {%- set has_content = captured_content | trim | length > 0 -%}\n\n {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}\n {{- '<|tool_response>' -}}\n {%- elif not (ns_tr_out.flag and not has_content) -%}\n {{- '<turn|>\\n' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}\n {{- '<|turn>model\\n' -}}\n {%- if not enable_thinking | default(false) -%}\n {{- '<|channel>thought\\n<channel|>' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endif -%}"
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196 "text": "A high-quality, photorealistic (or semi-realistic) image of an anthropomorphic elf/fantasy character.\n\n * *Subject:* Female Elf (pointed ears).\n * *Hair:* Long, silver/white hair in twin tails (pigtails), straight texture.\n * *Face:* East Asian features, pale skin, red lips, neutral expression.\n * *Outfit:* Ornate white and gold fantasy dress/corset. High collar with a ruby pendant. Gold filigree details.\n * *Setting:* Indoors, minimalist architectural background (neutral beige/cream walls).\n * *Lighting:* Soft, studio-style lighting, high key.\n * *Style:* 3D render / Hyper-realistic digital art (reminiscent of *Final Fantasy* or *Genshin Impact* high-fidelity renders).\n\n * *Subject Keywords:* Elf girl, pointed ears, silver hair, twin tails, long hair, white dress, gold trim.\n * *Setting Keywords:* Interior, palace, minimalist room, neutral background.\n * *Style/Technical Keywords:* Photorealistic, 3D render, Octane Render, Unreal Engine 5, masterpiece, high detail, soft lighting, depth of field.\n\n * **Option A: Descriptive & Natural (Midjourney style)**\n \"A hyper-realistic portrait of a beautiful elf girl with long silver hair in twin tails. She is wearing an ornate white and gold fantasy dress with a ruby pendant. Pointed ears, pale skin, neutral expression. Soft studio lighting, minimalist interior background, 8k resolution, cinematic.\"\n\n * **Option B: Tag-based/Weighted (Stable Diffusion style)**\n \"1girl, elf, pointed ears, silver hair, twin tails, white dress, gold filigree, ruby jewelry, masterpiece, photorealistic, highres, soft lighting, neutral background, 3D render, octane render.\"\n\n * **Option C: Artistic/Technical (Focusing on the \"Look\")**\n \"High-fidelity 3D character design of a fantasy elf. Intricate white and gold corset dress. Silver hair with realistic texture. Soft shadows, high key lighting, neutral beige background. Subsurface scattering on skin.\"\n\n * *Subject:* Elf girl, silver/white hair, twin tails (pigtails), pointed ears.\n * *Outfit:* White and gold fantasy gown, corset style, ruby accents.\n * *Environment:* Indoor studio setting, neutral colors.\n * *Technical:* 3D render, photorealistic, soft lighting.\n\n * Explain the components (Subject, Outfit, Style).\n * Provide specific prompts for different AI models.",
197 "fromDraftModel": false,
198 "tokensCount": 585,
199 "isStructural": false
200 }
201 ],
202 "defaultShouldIncludeInContext": true,
203 "shouldIncludeInContext": true,
204 "prefix": "",
205 "style": {
206 "type": "thinking",
207 "ended": true,
208 "title": "Thought for 5.21 seconds",
209 "forceRenderAsPlainText": false
210 }
211 },
212 {
213 "type": "contentBlock",
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215 "content": [
216 {
217 "type": "text",
218 "text": "To reverse-engineer this image, we need to identify the specific \"fantasy\" and \"technical\" markers that define its look. This is a high-fidelity 3D render of an **Elf** character in a **high-fantasy/RPG style**.\n\nHere is the breakdown of the prompt components:\n\n### The \"Core\" Prompt\n> **A hyper-realistic 3D render of a beautiful elf girl with long silver hair styled in twin tails. She has pointed ears and is wearing an ornate white and gold fantasy dress with intricate filigree and a ruby pendant. Soft studio lighting, neutral beige background, masterpiece, 8k resolution.**\n\n---\n\n### Breakdown of the Elements\n\n**1. The Subject (Character Design)**\n* **Keywords:** *Elf girl, pointed ears, silver hair, twin tails (pigtails), pale skin.*\n* **Details:** To get this specific look, you need to mention \"silver\" or \"platinum blonde\" hair and specify the hairstyle (\"twin tails\"). The facial features are very refined—adding \"East Asian features\" or \"doll-like face\" would help replicate that specific aesthetic.\n\n**2. The Outfit (Costume Design)**\n* **Keywords:** *Ornate white and gold dress, corset style, filigree, ruby jewelry.*\n* **Details:** The outfit is a mix of \"Paladin\" and \"Princess\" aesthetics. Using words like \"filigree,\" \"gold trim,\" and \"corset\" ensures the AI adds those complex metallic details to the fabric.\n\n**3. The Environment & Lighting (Atmosphere)**\n* **Keywords:** *Minimalist interior, neutral background, soft studio lighting.*\n* **Details:** Unlike the first image (which was outdoors), this is a **studio portrait**. The light is very even and soft, which minimizes harsh shadows. Using \"high-key lighting\" or \"soft focus\" will help achieve this clean look.\n\n**4. Technical Style (The Render)**\n* **Keywords:** *3D render, Octane Render, Unreal Engine 5, photorealistic.*\n* **Details:** This image looks like a high-end character model from a game like *Final Fantasy* or *Genshin Impact*. Using \"Subsurface scattering\" is a pro-tip—it tells the AI how light should penetrate the skin and hair to make it look realistic rather than plastic.\n\n---\n\n### Variations for Different AI Models\n\n#### For Midjourney (Descriptive & Artistic)\n> **A hyper-realistic portrait of a fantasy elf girl, long silver hair in twin tails, pointed ears, wearing an intricate white and gold royal gown with ruby accents. Soft cinematic lighting, neutral beige background, 8k, highly detailed textures, shot on 85mm lens --ar 2:3 --v 6.0**\n\n#### For Stable Diffusion (Tag-based)\n> **(masterpiece:1.2), (best quality), (photorealistic:1.3), 1girl, elf, pointed ears, silver hair, twin tails, white dress, gold filigree, ruby jewelry, neutral background, soft lighting, 3D render, octane render, highres.**\n\n#### For DALL-E 3 (Natural Language)\n> **A high-fidelity 3D character render of a beautiful elf girl. She has long silver hair tied into twin tails and pointed ears. She is wearing an elaborate white dress with gold embroidery and a ruby pendant. The background is a simple, neutral-colored room. The lighting is soft and professional, highlighting the realistic texture of her hair and clothes.**",
219 "fromDraftModel": false,
220 "tokensCount": 755,
221 "isStructural": false
222 }
223 ],
224 "genInfo": {
225 "indexedModelIdentifier": "aifeifei798/gemma-4-12B-it-qat-unquantized/gemma-4-12B-it-qat-q4_0-unquantized-Q4_K.gguf",
226 "identifier": "gemma-4-12b-it-qat-unquantized",
227 "loadModelConfig": {
228 "fields": [
229 {
230 "key": "llm.load.llama.cpuThreadPoolSize",
231 "value": 6
232 },
233 {
234 "key": "llm.load.contextLength",
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236 },
237 {
238 "key": "llm.load.llama.flashAttention",
239 "value": true
240 },
241 {
242 "key": "llm.load.llama.tryDirectIO",
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244 },
245 {
246 "key": "llm.load.llama.acceleration.offloadRatio",
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250 },
251 "predictionConfig": {
252 "fields": [
253 {
254 "key": "llm.prediction.temperature",
255 "value": 0.1
256 },
257 {
258 "key": "llm.prediction.promptTemplate",
259 "value": {
260 "type": "jinja",
261 "jinjaPromptTemplate": {
262 "template": "{%- macro format_parameters(properties, required, filter_keys=false) -%}\n {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in properties | dictsort -%}\n {%- set add_comma = false -%}\n {%- if not filter_keys or key not in standard_keys -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {{ key }}:{\n {%- if value['description'] -%}\n description:<|\"|>{{ value['description'] }}<|\"|>\n {%- set add_comma = true -%}\n {%- endif -%}\n {%- if value['type'] and ('string' in value['type'] or 'STRING' in value['type']) -%}\n {%- if value['enum'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n enum:{{ format_argument(value['enum']) }}\n {%- endif -%}\n {%- elif value['type'] and ('array' in value['type'] or 'ARRAY' in value['type']) -%}\n {%- if value['items'] is mapping and value['items'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n type:{{ format_type_argument(item_value) }}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n nullable:true\n {%- endif -%}\n {%- if value['type'] and ('object' in value['type'] or 'OBJECT' in value['type']) -%}\n {%- if value['properties'] is defined and value['properties'] is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value['properties'], value['required'] | default([])) -}}\n }\n {%- elif value is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}\n }\n {%- endif -%}\n {%- if value['required'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n required:[\n {%- for item in value['required'] | default([]) -%}\n <|\"|>{{- item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- endif -%}\n {%- endif -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n type:{{ format_type_argument(value['type']) }}}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:{{- format_type_argument(params['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] and ('object' in response_declaration['type'] or 'OBJECT' in response_declaration['type']) -%}\n type:{{- format_type_argument(response_declaration['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is iterable -%}\n {{- '[' -}}\n {%- for item in argument -%}\n {{- format_argument(item, escape_keys=escape_keys) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- ']' -}}\n {%- else -%}\n {{- argument -}}\n {%- endif -%}\n{%- endmacro -%}\n{%- macro strip_thinking(text) -%}\n {%- set ns = namespace(result='') -%}\n {%- for part in text.split('<channel|>') -%}\n {%- if '<|channel>' in part -%}\n {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}\n {%- else -%}\n {%- set ns.result = ns.result + part -%}\n {%- endif -%}\n {%- endfor -%}\n {{- ns.result | trim -}}\n{%- endmacro -%}\n\n{%- macro format_tool_response_block(tool_name, response) -%}\n {{- '<|tool_response>' -}}\n {%- if response is mapping -%}\n {{- 'response:' + tool_name + '{' -}}\n {%- for key, value in response | dictsort -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- '}' -}}\n {%- else -%}\n {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}\n {%- endif -%}\n {{- '<tool_response|>' -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(prev_message_type=None) -%}\n{%- set loop_messages = messages -%}\n{{- bos_token -}}\n{#- Handle System/Tool Definitions Block -#}\n{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}\n {{- '<|turn>system\\n' -}}\n {#- Inject Thinking token at the very top of the FIRST system turn -#}\n {%- if enable_thinking is defined and enable_thinking -%}\n {{- '<|think|>\\n' -}}\n {%- set ns.prev_message_type = 'think' -%}\n {%- endif -%}\n {%- if messages[0]['role'] in ['system', 'developer'] -%}\n {%- if messages[0]['content'] is string -%}\n {{- messages[0]['content'] | trim -}}\n {%- elif messages[0]['content'] is iterable -%}\n {%- for item in messages[0]['content'] -%}\n {{- item['text'] | trim + ' '-}}\n {%- endfor -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n {%- endif -%}\n {%- if tools -%}\n {%- for tool in tools %}\n {{- '<|tool>' -}}\n {{- format_function_declaration(tool) | trim -}}\n {{- '<tool|>' -}}\n {%- endfor %}\n {%- set ns.prev_message_type = 'tool' -%}\n {%- endif -%}\n {{- '<turn|>\\n' -}}\n{%- endif %}\n\n{#- Pre-scan: find last user message index for reasoning guard -#}\n{%- set ns_turn = namespace(last_user_idx=-1) -%}\n{%- for i in range(loop_messages | length) -%}\n {%- if loop_messages[i]['role'] == 'user' -%}\n {%- set ns_turn.last_user_idx = i -%}\n {%- endif -%}\n{%- endfor -%}\n\n{#- Loop through messages -#}\n{%- for message in loop_messages -%}\n {%- if message['role'] != 'tool' -%}\n {%- set ns.prev_message_type = None -%}\n {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}\n {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}\n {%- set prev_nt = namespace(role=None, found=false) -%}\n {%- if loop.index0 > 0 -%}\n {%- for j in range(loop.index0 - 1, -1, -1) -%}\n {%- if not prev_nt.found -%}\n {%- if loop_messages[j]['role'] != 'tool' -%}\n {%- set prev_nt.role = loop_messages[j]['role'] -%}\n {%- set prev_nt.found = true -%}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}\n {%- if not continue_same_model_turn -%}\n {{- '<|turn>' + role + '\\n' }}\n {%- endif -%}\n\n {#- Render reasoning/reasoning_content as thinking channel -#}\n {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}\n {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}\n {{- '<|channel>thought\\n' + thinking_text + '\\n<channel|>' -}}\n {%- endif -%}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- set ns_tr_out = namespace(flag=false) -%}\n {%- if message.get('tool_responses') -%}\n {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endfor -%}\n {%- elif message.get('tool_calls') -%}\n {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}\n {%- set ns_tool_scan = namespace(stopped=false) -%}\n {%- for k in range(loop.index0 + 1, loop_messages | length) -%}\n {%- if ns_tool_scan.stopped -%}\n {%- elif loop_messages[k]['role'] != 'tool' -%}\n {%- set ns_tool_scan.stopped = true -%}\n {%- else -%}\n {%- set follow = loop_messages[k] -%}\n {#- Resolve tool_call_id to function name -#}\n {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}\n {%- for tc in message['tool_calls'] -%}\n {%- if tc.get('id') == follow.get('tool_call_id') -%}\n {%- set ns_tname.name = tc['function']['name'] -%}\n {%- endif -%}\n {%- endfor -%}\n {#- Handle content as string or content-parts array -#}\n {%- set tool_body = follow.get('content') -%}\n {%- if tool_body is string -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- elif tool_body is iterable and tool_body is not string -%}\n {%- set ns_txt = namespace(s='') -%}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'text' -%}\n {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'image' -%}\n {{- '<|image|>' -}}\n {%- elif part.get('type') == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- elif part.get('type') == 'video' -%}\n {{- '<|video|>' -}}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- endif -%}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n\n {%- set captured_content -%}\n {%- if message['content'] is string -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(message['content']) -}}\n {%- else -%}\n {{- message['content'] | trim -}}\n {%- endif -%}\n {%- elif message['content'] is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'text' -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(item['text']) -}}\n {%- else -%}\n {{- item['text'] | trim -}}\n {%- endif -%}\n {%- elif item['type'] == 'image' -%}\n {{- '<|image|>' -}}\n {%- set ns.prev_message_type = 'image' -%}\n {%- elif item['type'] == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- set ns.prev_message_type = 'audio' -%}\n {%- elif item['type'] == 'video' -%}\n {{- '<|video|>' -}}\n {%- set ns.prev_message_type = 'video' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- endset -%}\n\n {{- captured_content -}}\n {%- set has_content = captured_content | trim | length > 0 -%}\n\n {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}\n {{- '<|tool_response>' -}}\n {%- elif not (ns_tr_out.flag and not has_content) -%}\n {{- '<turn|>\\n' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}\n {{- '<|turn>model\\n' -}}\n {%- if not enable_thinking | default(false) -%}\n {{- '<|channel>thought\\n<channel|>' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endif -%}"
263 },
264 "stopStrings": []
265 }
266 },
267 {
268 "key": "llm.prediction.llama.cpuThreads",
269 "value": 6
270 },
271 {
272 "key": "llm.prediction.vision.userMaxImageDimensionPixels",
273 "value": {
274 "checked": true,
275 "value": 2048
276 }
277 },
278 {
279 "key": "llm.prediction.vision.ignoreModelPreferredMaxImageDimension",
280 "value": false
281 },
282 {
283 "key": "llm.prediction.tools",
284 "value": {
285 "type": "none"
286 }
287 }
288 ]
289 },
290 "stats": {
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292 "tokensPerSecond": 112.3921025370282,
293 "timeToFirstTokenSec": 0.27226100000000003,
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295 "promptTokensCount": 1783,
296 "predictedTokensCount": 1345,
297 "totalTokensCount": 3128
298 }
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301 "shouldIncludeInContext": true
302 },
303 {
304 "type": "debugInfoBlock",
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306 "debugInfo": "Conversation naming technique: 'prompt'"
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312 },
313 {
314 "versions": [
315 {
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324 }
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329 },
330 {
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332 {
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345 "text": "A young woman in a casual outfit standing on a coastal structure (a concrete frame/archway) overlooking the ocean.\n\n * *Subject:* Young East Asian woman, smiling, short black bob haircut.\n * *Pose:* Standing, one hand raised to her forehead as if shading her eyes or saluting, looking at the camera.\n * *Outfit:* Light blue cropped t-shirt (short sleeves), black high-waisted denim shorts, white socks, white sneakers with black stripes (Adidas style), small black shoulder bag.\n * *Setting:* Coastal area, ocean waves, clear blue sky, concrete structure (weathered/aged), some green bushes on the right.\n * *Lighting:* Bright, direct sunlight (midday look), high contrast, natural colors.\n * *Style:* Real-life photography, \"candid\" or \"travel photo\" vibe, smartphone/DSLR aesthetic.\n\n * *Subject Keywords:* Young woman, East Asian, short black hair, bob cut, smiling, casual pose.\n * *Outfit Keywords:* Light blue crop top, black denim shorts, white socks, white sneakers, shoulder bag.\n * *Setting Keywords:* Coastal view, ocean waves, concrete archway, sunny day, clear sky, beach scenery.\n * *Style/Technical Keywords:* Photorealistic, travel photography, natural lighting, high resolution, 8k, sharp focus.\n\n * **Option A: Descriptive & Natural (Midjourney style)**\n \"A realistic photo of a young East Asian woman with short black hair standing on a weathered concrete structure by the ocean. She is wearing a light blue crop top and black denim shorts, smiling at the camera while shading her eyes. Bright sunny day, clear blue sky, waves crashing in the background.\"\n\n * **Option B: Tag-based/Weighted (Stable Diffusion style)**\n \"1girl, solo, east asian, short hair, black hair, bob cut, smiling, light blue crop top, black denim shorts, white socks, sneakers, shoulder bag, standing on concrete platform, ocean background, beach, sunny day, clear sky, photorealistic, high quality, 8k.\"\n\n * **Option C: Artistic/Technical (Focusing on the \"Look\")**\n \"Candid travel photography of a girl at the coast. Natural sunlight, vibrant colors, sharp focus on subject with slight depth of field for the ocean background. Realistic skin textures and fabric details.\"\n\n * Explain why these words were chosen.\n * Provide different versions based on common AI models (Midjourney vs. Stable Diffusion).\n * To reverse-engineer this image, we need to identify the \"lifestyle\" and \"environmental\" markers that define its look. This is a **realistic travel photograph** of a person in a coastal setting.\n\n * Breakdown: Subject, Outfit, Setting, Style/Lighting.",
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367 "text": "To reverse-engineer this image, we have to shift from the \"fantasy/3D render\" style of the previous two images to a **\"lifestyle photography\"** style. This is a realistic photo that mimics a travel snapshot or a social media post.\n\nHere is how you would reconstruct the prompt:\n\n### The \"Core\" Prompt\n> **A realistic full-body photo of a young East Asian woman with short black hair standing on a weathered concrete structure by the ocean. She is wearing a light blue crop top and black denim shorts, smiling at the camera while shading her eyes with one hand. Bright sunny day, clear blue sky, waves crashing in the background, high resolution.**\n\n---\n\n### Breakdown of the Elements\n\n**1. The Subject (Appearance & Pose)**\n* **Keywords:** *Young East Asian woman, short black hair, bob cut, smiling.*\n* **Details:** To get this specific look, you need to describe her hairstyle (\"short bob\") and her expression. Her pose is a \"candid\" style—mentioning that she is \"shading her eyes\" or \"looking at the camera\" helps the AI position her arms correctly.\n\n**2. The Outfit (Casual/Streetwear)**\n* **Keywords:** *Light blue crop top, black denim shorts, white socks, sneakers.*\n* **Details:** This is a very specific casual look. Using terms like \"denim shorts\" and \"crop top\" ensures the AI understands the proportions of the clothing.\n\n**3. The Setting (Environment)**\n* **Keywords:** *Coastal view, ocean waves, weathered concrete archway, sunny day.*\n* **Details:** The background is crucial here. It’s not just a beach; it's an industrial/weathered structure. Using \"weathered concrete\" or \"aged structure\" helps recreate that specific grey, textured frame she is standing under.\n\n**4. Style & Lighting (The Photography)**\n* **Keywords:** *Travel photography, natural sunlight, high contrast.*\n* **Details:** This image has very bright, direct light (likely midday). Unlike the soft \"studio\" lighting of the elf girl, this needs to be \"harsh\" or \"natural\" sunlight. Adding \"shot on 35mm lens\" or \"smartphone photography style\" can help achieve that realistic, non-artificial look.\n\n---\n\n### Variations for Different AI Models\n\n#### For Midjourney (Descriptive & Natural)\n> **A realistic full-body travel photo of a young East Asian woman with a black bob haircut standing on a concrete pier by the sea. She is wearing a light blue t-shirt and black shorts, smiling at the camera under a bright sunny sky. Ocean waves in the background, natural lighting, 8k resolution --ar 2:3 --v 6.0**\n\n#### For Stable Diffusion (Tag-based)\n> **(photorealistic:1.4), 1girl, solo, east asian, short hair, black hair, bob cut, smiling, light blue crop top, black denim shorts, white socks, sneakers, standing on concrete platform, ocean background, beach, sunny day, clear sky, highres, masterpiece.**\n\n#### For DALL-E 3 (Natural Language)\n> **A realistic photo of a young East Asian woman with short black hair. She is standing on an old concrete structure overlooking the blue ocean. She is wearing a light blue crop top and black denim shorts, smiling at the camera while holding one hand up to her forehead as if shading her eyes from the sun. The lighting is bright and natural, capturing a sunny day at the coast.**",
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411 "template": "{%- macro format_parameters(properties, required, filter_keys=false) -%}\n {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in properties | dictsort -%}\n {%- set add_comma = false -%}\n {%- if not filter_keys or key not in standard_keys -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {{ key }}:{\n {%- if value['description'] -%}\n description:<|\"|>{{ value['description'] }}<|\"|>\n {%- set add_comma = true -%}\n {%- endif -%}\n {%- if value['type'] and ('string' in value['type'] or 'STRING' in value['type']) -%}\n {%- if value['enum'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n enum:{{ format_argument(value['enum']) }}\n {%- endif -%}\n {%- elif value['type'] and ('array' in value['type'] or 'ARRAY' in value['type']) -%}\n {%- if value['items'] is mapping and value['items'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n type:{{ format_type_argument(item_value) }}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set 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{% endif -%}\n type:{{ format_type_argument(value['type']) }}}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:{{- format_type_argument(params['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] and ('object' in response_declaration['type'] or 'OBJECT' in response_declaration['type']) -%}\n type:{{- format_type_argument(response_declaration['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is iterable -%}\n {{- '[' -}}\n {%- for item in argument -%}\n {{- format_argument(item, escape_keys=escape_keys) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- ']' -}}\n {%- else -%}\n {{- argument -}}\n {%- endif -%}\n{%- endmacro -%}\n{%- macro strip_thinking(text) -%}\n {%- set ns = namespace(result='') -%}\n {%- for part in text.split('<channel|>') -%}\n {%- if '<|channel>' in part -%}\n {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}\n {%- else -%}\n {%- set ns.result = ns.result + part -%}\n {%- endif -%}\n {%- endfor -%}\n {{- ns.result | trim -}}\n{%- endmacro -%}\n\n{%- macro format_tool_response_block(tool_name, response) -%}\n {{- '<|tool_response>' -}}\n {%- if response is mapping -%}\n {{- 'response:' + tool_name + '{' -}}\n {%- for key, value in response | dictsort -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- '}' -}}\n {%- else -%}\n {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}\n {%- endif -%}\n {{- '<tool_response|>' -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(prev_message_type=None) -%}\n{%- set loop_messages = messages -%}\n{{- bos_token -}}\n{#- Handle System/Tool Definitions Block -#}\n{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}\n {{- '<|turn>system\\n' -}}\n {#- Inject Thinking token at the very top of the FIRST system turn -#}\n {%- if enable_thinking is defined and enable_thinking -%}\n {{- '<|think|>\\n' -}}\n {%- set ns.prev_message_type = 'think' -%}\n {%- endif -%}\n {%- if messages[0]['role'] in ['system', 'developer'] -%}\n {%- if messages[0]['content'] is string -%}\n {{- messages[0]['content'] | trim -}}\n {%- elif messages[0]['content'] is iterable -%}\n {%- for item in messages[0]['content'] -%}\n {{- item['text'] | trim + ' '-}}\n {%- endfor -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n {%- endif -%}\n {%- if tools -%}\n {%- for tool in tools %}\n {{- '<|tool>' -}}\n {{- format_function_declaration(tool) | trim -}}\n {{- '<tool|>' -}}\n {%- endfor %}\n {%- set ns.prev_message_type = 'tool' -%}\n {%- endif -%}\n {{- '<turn|>\\n' -}}\n{%- endif %}\n\n{#- Pre-scan: find last user message index for reasoning guard -#}\n{%- set ns_turn = namespace(last_user_idx=-1) -%}\n{%- for i in range(loop_messages | length) -%}\n {%- if loop_messages[i]['role'] == 'user' -%}\n {%- set ns_turn.last_user_idx = i -%}\n {%- endif -%}\n{%- endfor -%}\n\n{#- Loop through messages -#}\n{%- for message in loop_messages -%}\n {%- if message['role'] != 'tool' -%}\n {%- set ns.prev_message_type = None -%}\n {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}\n {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}\n {%- set prev_nt = namespace(role=None, found=false) -%}\n {%- if loop.index0 > 0 -%}\n {%- for j in range(loop.index0 - 1, -1, -1) -%}\n {%- if not prev_nt.found -%}\n {%- if loop_messages[j]['role'] != 'tool' -%}\n {%- set prev_nt.role = loop_messages[j]['role'] -%}\n {%- set prev_nt.found = true -%}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}\n {%- if not continue_same_model_turn -%}\n {{- '<|turn>' + role + '\\n' }}\n {%- endif -%}\n\n {#- Render reasoning/reasoning_content as thinking channel -#}\n {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}\n {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}\n {{- '<|channel>thought\\n' + thinking_text + '\\n<channel|>' -}}\n {%- endif -%}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- set ns_tr_out = namespace(flag=false) -%}\n {%- if message.get('tool_responses') -%}\n {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endfor -%}\n {%- elif message.get('tool_calls') -%}\n {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}\n {%- set ns_tool_scan = namespace(stopped=false) -%}\n {%- for k in range(loop.index0 + 1, loop_messages | length) -%}\n {%- if ns_tool_scan.stopped -%}\n {%- elif loop_messages[k]['role'] != 'tool' -%}\n {%- set ns_tool_scan.stopped = true -%}\n {%- else -%}\n {%- set follow = loop_messages[k] -%}\n {#- Resolve tool_call_id to function name -#}\n {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}\n {%- for tc in message['tool_calls'] -%}\n {%- if tc.get('id') == follow.get('tool_call_id') -%}\n {%- set ns_tname.name = tc['function']['name'] -%}\n {%- endif -%}\n {%- endfor -%}\n {#- Handle content as string or content-parts array -#}\n {%- set tool_body = follow.get('content') -%}\n {%- if tool_body is string -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- elif tool_body is iterable and tool_body is not string -%}\n {%- set ns_txt = namespace(s='') -%}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'text' -%}\n {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'image' -%}\n {{- '<|image|>' -}}\n {%- elif part.get('type') == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- elif part.get('type') == 'video' -%}\n {{- '<|video|>' -}}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- endif -%}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n\n {%- set captured_content -%}\n {%- if message['content'] is string -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(message['content']) -}}\n {%- else -%}\n {{- message['content'] | trim -}}\n {%- endif -%}\n {%- elif message['content'] 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'tool_response' and ns.prev_message_type != 'tool_call' -%}\n {{- '<|turn>model\\n' -}}\n {%- if not enable_thinking | default(false) -%}\n {{- '<|channel>thought\\n<channel|>' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endif -%}"
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494 "text": "A young East Asian woman in an all-white outfit against a vibrant blue sky.\n\n * *Subject:* Young East Asian woman, neutral/serious expression, long black hair blowing in the wind.\n * *Hair:* Long, straight, dark/black, windswept.\n * *Outfit:* All-white ensemble—a white baseball cap, a sheer/translucent white button-down shirt (worn open), a white tank top/camisole underneath, and white shorts.\n * *Setting:* Outdoors, clear deep blue sky with some fluffy white clouds at the bottom. Very minimalist background.\n * *Lighting:* Bright, direct sunlight (high key). High contrast between the white clothes and the blue sky.\n * *Style:* Fashion photography, high-end editorial look, clean aesthetic.\n\n * *Subject Keywords:* East Asian woman, long black hair, windswept hair, neutral expression.\n * *Outfit Keywords:* All-white outfit, white baseball cap, sheer white shirt, white tank top, white shorts.\n * *Setting Keywords:* Deep blue sky, fluffy clouds, minimalist background, outdoor fashion shoot.\n * *Style/Technical Keywords:* Fashion photography, high key lighting, 8k, photorealistic, sharp focus, cinematic color grading (vibrant blues).\n\n * **Option A: Descriptive & Natural (Midjourney style)**\n \"A high-fashion portrait of a young East Asian woman with long black hair blowing in the wind. She is wearing an all-white outfit including a white baseball cap and a sheer white shirt over a tank top. Against a vibrant deep blue sky with fluffy clouds. Bright sunlight, minimalist aesthetic, 8k resolution.\"\n\n * **Option B: Tag-based/Weighted (Stable Diffusion style)**\n \"1girl, solo, east asian, long black hair, windswept hair, white baseball cap, all-white outfit, sheer shirt, white shorts, neutral expression, deep blue sky, fluffy clouds, fashion photography, high key lighting, photorealistic, 8k.\"\n\n * **Option C: Artistic/Technical (Focusing on the \"Look\")**\n \"Editorial fashion shoot. High contrast between white clothing and a saturated blue sky. Sharp focus on facial features and hair texture. Soft shadows. Minimalist composition.\"\n\n * Explain why these words were chosen.\n * Provide different versions based on common AI models (Midjourney vs. Stable Diffusion).\n * To reverse-engineer this image, we need to identify the **\"high-fashion editorial\"** and **\"color contrast\"** markers. This is a clean, minimalist aesthetic that relies heavily on color theory (white vs. blue).\n\n * Breakdown: Subject, Outfit, Environment/Color, Style/Lighting.\n * Provide specific prompts for different AI models.",
495 "fromDraftModel": false,
496 "tokensCount": 614,
497 "isStructural": false
498 }
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500 "defaultShouldIncludeInContext": true,
501 "shouldIncludeInContext": true,
502 "prefix": "",
503 "style": {
504 "type": "thinking",
505 "ended": true,
506 "title": "Thought for 5.68 seconds",
507 "forceRenderAsPlainText": false
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514 {
515 "type": "text",
516 "text": "To reverse-engineer this image, we need to focus on the **\"high-fashion editorial\"** and **\"color contrast\"** markers. This style relies heavily on a minimalist aesthetic—specifically the sharp contrast between the all-white clothing and the saturated blue sky.\n\nHere is how you would reconstruct the prompt:\n\n### The \"Core\" Prompt\n> **A high-fashion portrait of a young East Asian woman with long black hair blowing in the wind. She is wearing an all-white outfit, including a white baseball cap and a sheer white button-down shirt over a tank top. Set against a vibrant, deep blue sky with fluffy white clouds. Bright sunlight, minimalist aesthetic, 8k resolution.**\n\n---\n\n### Breakdown of the Elements\n\n**1. The Subject (Expression & Movement)**\n* **Keywords:** *East Asian woman, long black hair, windswept hair, neutral expression.*\n* **Details:** To capture this specific vibe, you need to mention \"windswept\" or \"hair blowing in the wind.\" Her expression is not a smile; it’s a \"neutral\" or \"stoic\" look common in high-fashion photography.\n\n**2. The Outfit (Monochrome Aesthetic)**\n* **Keywords:** *All-white outfit, white baseball cap, sheer white shirt, white shorts.*\n* **Details:** The key here is the **texture**. Using the word \"sheer\" or \"translucent\" for the outer shirt is vital to get that light, airy fabric look. Specifying \"all-white\" ensures the AI doesn't add unwanted colors.\n\n**3. The Environment (Color Theory)**\n* **Keywords:** *Deep blue sky, fluffy clouds, minimalist background.*\n* **Details:** This image works because of the **complementary color contrast**. By specifying a \"vibrant deep blue sky,\" you force the AI to make the white clothes pop even more. Keeping the background \"minimalist\" prevents the scene from becoming cluttered.\n\n**4. Style & Lighting (Editorial Look)**\n* **Keywords:** *Fashion photography, high-key lighting, sharp focus.*\n* **Details:** This isn't a casual snapshot; it’s an editorial shoot. Using \"high-key lighting\" tells the AI to keep the image bright and airy with minimal heavy shadows.\n\n---\n\n### Variations for Different AI Models\n\n#### For Midjourney (Descriptive & Artistic)\n> **A high-fashion editorial portrait of a young East Asian woman, long black hair blowing in the wind, wearing an all-white outfit and a white baseball cap. Minimalist composition against a saturated deep blue sky with fluffy clouds. Bright natural sunlight, sharp focus, 8k resolution --ar 2:3 --v 6.0**\n\n#### For Stable Diffusion (Tag-based)\n> **(masterpiece:1.2), (best quality), (photorealistic:1.3), 1girl, solo, east asian, long black hair, windswept hair, white baseball cap, all-white outfit, sheer shirt, white shorts, neutral expression, deep blue sky, fluffy clouds, fashion photography, high key lighting, sharp focus.**\n\n#### For DALL-E 3 (Natural Language)\n> **A professional fashion photograph of a young East Asian woman with long black hair blowing in the wind. She is wearing an all-white ensemble consisting of a baseball cap and a sheer white shirt over a tank top. The background is a clear, vibrant deep blue sky with some white clouds at the bottom. The lighting is bright and sunny, creating a clean and minimalist aesthetic.**",
517 "fromDraftModel": false,
518 "tokensCount": 759,
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520 }
521 ],
522 "genInfo": {
523 "indexedModelIdentifier": "aifeifei798/gemma-4-12B-it-qat-unquantized/gemma-4-12B-it-qat-q4_0-unquantized-Q4_K.gguf",
524 "identifier": "gemma-4-12b-it-qat-unquantized",
525 "loadModelConfig": {
526 "fields": [
527 {
528 "key": "llm.load.llama.cpuThreadPoolSize",
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535 {
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539 {
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548 },
549 "predictionConfig": {
550 "fields": [
551 {
552 "key": "llm.prediction.temperature",
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554 },
555 {
556 "key": "llm.prediction.promptTemplate",
557 "value": {
558 "type": "jinja",
559 "jinjaPromptTemplate": {
560 "template": "{%- macro format_parameters(properties, required, filter_keys=false) -%}\n {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in properties | dictsort -%}\n {%- set add_comma = false -%}\n {%- if not filter_keys or key not in standard_keys -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {{ key }}:{\n {%- if value['description'] -%}\n description:<|\"|>{{ value['description'] }}<|\"|>\n {%- set add_comma = true -%}\n {%- endif -%}\n {%- if value['type'] and ('string' in value['type'] or 'STRING' in value['type']) -%}\n {%- if value['enum'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n enum:{{ format_argument(value['enum']) }}\n {%- endif -%}\n {%- elif value['type'] and ('array' in value['type'] or 'ARRAY' in value['type']) -%}\n {%- if value['items'] is mapping and value['items'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n type:{{ format_type_argument(item_value) }}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n nullable:true\n {%- endif -%}\n {%- if value['type'] and ('object' in value['type'] or 'OBJECT' in value['type']) -%}\n {%- if value['properties'] is defined and value['properties'] is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value['properties'], value['required'] | default([])) -}}\n }\n {%- elif value is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}\n }\n {%- endif -%}\n {%- if value['required'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n required:[\n {%- for item in value['required'] | default([]) -%}\n <|\"|>{{- item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- endif -%}\n {%- endif -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n type:{{ format_type_argument(value['type']) }}}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:{{- format_type_argument(params['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] and ('object' in response_declaration['type'] or 'OBJECT' in response_declaration['type']) -%}\n type:{{- format_type_argument(response_declaration['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is iterable -%}\n {{- '[' -}}\n {%- for item in argument -%}\n {{- format_argument(item, escape_keys=escape_keys) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- ']' -}}\n {%- else -%}\n {{- argument -}}\n {%- endif -%}\n{%- endmacro -%}\n{%- macro strip_thinking(text) -%}\n {%- set ns = namespace(result='') -%}\n {%- for part in text.split('<channel|>') -%}\n {%- if '<|channel>' in part -%}\n {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}\n {%- else -%}\n {%- set ns.result = ns.result + part -%}\n {%- endif -%}\n {%- endfor -%}\n {{- ns.result | trim -}}\n{%- endmacro -%}\n\n{%- macro format_tool_response_block(tool_name, response) -%}\n {{- '<|tool_response>' -}}\n {%- if response is mapping -%}\n {{- 'response:' + tool_name + '{' -}}\n {%- for key, value in response | dictsort -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- '}' -}}\n {%- else -%}\n {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}\n {%- endif -%}\n {{- '<tool_response|>' -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(prev_message_type=None) -%}\n{%- set loop_messages = messages -%}\n{{- bos_token -}}\n{#- Handle System/Tool Definitions Block -#}\n{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}\n {{- '<|turn>system\\n' -}}\n {#- Inject Thinking token at the very top of the FIRST system turn -#}\n {%- if enable_thinking is defined and enable_thinking -%}\n {{- '<|think|>\\n' -}}\n {%- set ns.prev_message_type = 'think' -%}\n {%- endif -%}\n {%- if messages[0]['role'] in ['system', 'developer'] -%}\n {%- if messages[0]['content'] is string -%}\n {{- messages[0]['content'] | trim -}}\n {%- elif messages[0]['content'] is iterable -%}\n {%- for item in messages[0]['content'] -%}\n {{- item['text'] | trim + ' '-}}\n {%- endfor -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n {%- endif -%}\n {%- if tools -%}\n {%- for tool in tools %}\n {{- '<|tool>' -}}\n {{- format_function_declaration(tool) | trim -}}\n {{- '<tool|>' -}}\n {%- endfor %}\n {%- set ns.prev_message_type = 'tool' -%}\n {%- endif -%}\n {{- '<turn|>\\n' -}}\n{%- endif %}\n\n{#- Pre-scan: find last user message index for reasoning guard -#}\n{%- set ns_turn = namespace(last_user_idx=-1) -%}\n{%- for i in range(loop_messages | length) -%}\n {%- if loop_messages[i]['role'] == 'user' -%}\n {%- set ns_turn.last_user_idx = i -%}\n {%- endif -%}\n{%- endfor -%}\n\n{#- Loop through messages -#}\n{%- for message in loop_messages -%}\n {%- if message['role'] != 'tool' -%}\n {%- set ns.prev_message_type = None -%}\n {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}\n {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}\n {%- set prev_nt = namespace(role=None, found=false) -%}\n {%- if loop.index0 > 0 -%}\n {%- for j in range(loop.index0 - 1, -1, -1) -%}\n {%- if not prev_nt.found -%}\n {%- if loop_messages[j]['role'] != 'tool' -%}\n {%- set prev_nt.role = loop_messages[j]['role'] -%}\n {%- set prev_nt.found = true -%}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}\n {%- if not continue_same_model_turn -%}\n {{- '<|turn>' + role + '\\n' }}\n {%- endif -%}\n\n {#- Render reasoning/reasoning_content as thinking channel -#}\n {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}\n {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}\n {{- '<|channel>thought\\n' + thinking_text + '\\n<channel|>' -}}\n {%- endif -%}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- set ns_tr_out = namespace(flag=false) -%}\n {%- if message.get('tool_responses') -%}\n {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endfor -%}\n {%- elif message.get('tool_calls') -%}\n {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}\n {%- set ns_tool_scan = namespace(stopped=false) -%}\n {%- for k in range(loop.index0 + 1, loop_messages | length) -%}\n {%- if ns_tool_scan.stopped -%}\n {%- elif loop_messages[k]['role'] != 'tool' -%}\n {%- set ns_tool_scan.stopped = true -%}\n {%- else -%}\n {%- set follow = loop_messages[k] -%}\n {#- Resolve tool_call_id to function name -#}\n {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}\n {%- for tc in message['tool_calls'] -%}\n {%- if tc.get('id') == follow.get('tool_call_id') -%}\n {%- set ns_tname.name = tc['function']['name'] -%}\n {%- endif -%}\n {%- endfor -%}\n {#- Handle content as string or content-parts array -#}\n {%- set tool_body = follow.get('content') -%}\n {%- if tool_body is string -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- elif tool_body is iterable and tool_body is not string -%}\n {%- set ns_txt = namespace(s='') -%}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'text' -%}\n {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'image' -%}\n {{- '<|image|>' -}}\n {%- elif part.get('type') == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- elif part.get('type') == 'video' -%}\n {{- '<|video|>' -}}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- endif -%}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n\n {%- set captured_content -%}\n {%- if message['content'] is string -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(message['content']) -}}\n {%- else -%}\n {{- message['content'] | trim -}}\n {%- endif -%}\n {%- elif message['content'] is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'text' -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(item['text']) -}}\n {%- else -%}\n {{- item['text'] | trim -}}\n {%- endif -%}\n {%- elif item['type'] == 'image' -%}\n {{- '<|image|>' -}}\n {%- set ns.prev_message_type = 'image' -%}\n {%- elif item['type'] == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- set ns.prev_message_type = 'audio' -%}\n {%- elif item['type'] == 'video' -%}\n {{- '<|video|>' -}}\n {%- set ns.prev_message_type = 'video' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- endset -%}\n\n {{- captured_content -}}\n {%- set has_content = captured_content | trim | length > 0 -%}\n\n {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}\n {{- '<|tool_response>' -}}\n {%- elif not (ns_tr_out.flag and not has_content) -%}\n {{- '<turn|>\\n' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}\n {{- '<|turn>model\\n' -}}\n {%- if not enable_thinking | default(false) -%}\n {{- '<|channel>thought\\n<channel|>' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endif -%}"
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643 "text": "A high-quality digital illustration of an anthropomorphic fox (furry) character in a poolside setting.\n\n * *Subject:* Anthropomorphic female fox (anthro).\n * *Coloring:* Brown/tan fur with white markings on the chest, belly, and tail tip. Blue eyes. Darker \"mask\" around the muzzle.\n * *Anatomy:* Humanoid body, large bushy tail, pointed ears, long hair-like fur (brownish).\n * *Outfit:* Black bikini/swimsuit with gold accents or ties.\n * *Setting:* Luxury poolside area. A swimming pool with blue water and a white lifebuoy. A covered patio/pavilion structure in the background with lounge chairs. Tropical plants on the right.\n * *Style:* 2D digital art, \"anime\" or \"semi-realistic\" furry style (clean lines, cel-shading mixed with soft gradients). High detail.\n\n * *Subject Keywords:* Anthro fox, furry girl, brown fur, white markings, blue eyes, long hair, bushy tail.\n * *Setting Keywords:* Luxury pool, swimming pool, patio, tropical garden, summer vibe, poolside.\n * *Style/Technical Keywords:* Digital illustration, anime style, high quality, vibrant colors, cinematic lighting, 2D art.\n\n * **Option A: Descriptive & Natural (Midjourney style)**\n \"A digital illustration of a beautiful anthropomorphic fox girl with brown fur and white markings. She has long hair, blue eyes, and a large bushy tail. She is wearing a black bikini and lounging by a luxury swimming pool under a patio. Tropical garden background, bright summer sunlight, high quality.\"\n\n * **Option B: Tag-based/Weighted (Stable Diffusion style)**\n \"1girl, anthro fox, furry, brown fur, white markings, blue eyes, long hair, bushy tail, black bikini, swimming pool, poolside, patio, tropical plants, sunny day, digital art, anime style, masterpiece, highres.\"\n\n * **Option C: Artistic/Technical (Focusing on the \"Look\")**\n \"High-quality 2D digital painting of a furry character. Soft shading, vibrant colors. Focus on fur texture and bikini details. Poolside setting with depth of field.\"\n\n * Explain why these words were chosen.\n * Provide different versions based on common AI models (Midjourney vs. Stable Diffusion).\n * To reverse-engineer this image, we need to identify the **\"digital illustration/anime\"** and **\"luxury lifestyle\"** markers. This is a stylized furry artwork that blends 2D aesthetics with high-end environmental rendering.\n\n * Breakdown: Subject, Outfit, Setting, Style/Lighting.\n * Provide specific prompts for different AI models.",
644 "fromDraftModel": false,
645 "tokensCount": 607,
646 "isStructural": false
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652 "style": {
653 "type": "thinking",
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655 "title": "Thought for 5.58 seconds",
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663 {
664 "type": "text",
665 "text": "To reverse-engineer this image, we need to identify the **\"digital illustration/anime\"** and **\"luxury lifestyle\"** markers. This is a stylized furry artwork that blends 2D character aesthetics with a high-end environmental background.\n\nHere is how you would reconstruct the prompt:\n\n### The \"Core\" Prompt\n> **A high-quality digital illustration of an anthropomorphic female fox (furry) lounging by a luxury swimming pool. She has brown and white fur, long hair, blue eyes, and a large bushy tail. She is wearing a black bikini. The background features a poolside patio with lounge chairs and tropical plants under bright summer sunlight.**\n\n---\n\n### Breakdown of the Elements\n\n**1. The Subject (Character Design)**\n* **Keywords:** *Anthro fox, furry girl, brown fur, white markings, blue eyes, long hair, bushy tail.*\n* **Details:** To get this specific look, you need to describe the \"mask\" around her muzzle and the contrast between her brown fur and white chest/belly. Mentioning a \"bushy tail\" is important for the silhouette.\n\n**2. The Outfit (Swimwear)**\n* **Keywords:** *Black bikini, poolside attire.*\n* **Details:** Because the character is an anthro, specifying \"bikini\" helps the AI understand how to drape the clothing over a non-human anatomy.\n\n**3. The Setting (Environment)**\n* **Keywords:** *Luxury pool, swimming pool, patio, tropical garden, summer vibe.*\n* **Details:** This isn't just a backyard; it’s a \"luxury\" setting. Including details like \"lounge chairs,\" \"patio structure,\" and \"tropical plants\" helps fill the background with the right atmosphere.\n\n**4. Style & Lighting (The Render)**\n* **Keywords:** *Digital illustration, anime style, vibrant colors, cinematic lighting.*\n* **Details:** This image is not a photo; it’s a high-quality 2D painting. Using \"digital illustration\" or \"anime style\" prevents the AI from trying to make it look like a real animal. The lighting should be described as \"bright summer sunlight\" to get those sharp highlights on her fur.\n\n---\n\n### Variations for Different AI Models\n\n#### For Midjourney (Descriptive & Artistic)\n> **A high-quality digital illustration of an anthropomorphic fox girl with brown and white fur, long hair, and blue eyes. She is wearing a black bikini and lounging by a luxury swimming pool under a patio. Tropical garden background, bright summer sunlight, vibrant colors, anime style --ar 2:3 --v 6.0**\n\n#### For Stable Diffusion (Tag-based)\n> **(masterpiece:1.2), (best quality), (photorealistic:0.8), 1girl, anthro fox, furry, brown fur, white markings, blue eyes, long hair, bushy tail, black bikini, swimming pool, poolside, patio, tropical plants, sunny day, digital art, anime style.**\n\n#### For DALL-E 3 (Natural Language)\n> **A high-quality digital illustration of a female anthropomorphic fox character. She has brown fur with white markings on her chest and tail, long hair, and blue eyes. She is wearing a black bikini and relaxing by the edge of a luxury swimming pool. The background shows a shaded patio area with lounge chairs and tropical greenery under a bright, sunny sky.**",
666 "fromDraftModel": false,
667 "tokensCount": 728,
668 "isStructural": false
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670 ],
671 "genInfo": {
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674 "loadModelConfig": {
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698 "predictionConfig": {
699 "fields": [
700 {
701 "key": "llm.prediction.temperature",
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703 },
704 {
705 "key": "llm.prediction.promptTemplate",
706 "value": {
707 "type": "jinja",
708 "jinjaPromptTemplate": {
709 "template": "{%- macro format_parameters(properties, required, filter_keys=false) -%}\n {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in properties | dictsort -%}\n {%- set add_comma = false -%}\n {%- if not filter_keys or key not in standard_keys -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {{ key }}:{\n {%- if value['description'] -%}\n description:<|\"|>{{ value['description'] }}<|\"|>\n {%- set add_comma = true -%}\n {%- endif -%}\n {%- if value['type'] and ('string' in value['type'] or 'STRING' in value['type']) -%}\n {%- if value['enum'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n enum:{{ format_argument(value['enum']) }}\n {%- endif -%}\n {%- elif value['type'] and ('array' in value['type'] or 'ARRAY' in value['type']) -%}\n {%- if value['items'] is mapping and value['items'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n type:{{ format_type_argument(item_value) }}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n nullable:true\n {%- endif -%}\n {%- if value['type'] and ('object' in value['type'] or 'OBJECT' in value['type']) -%}\n {%- if value['properties'] is defined and value['properties'] is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value['properties'], value['required'] | default([])) -}}\n }\n {%- elif value is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}\n }\n {%- endif -%}\n {%- if value['required'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n required:[\n {%- for item in value['required'] | default([]) -%}\n <|\"|>{{- item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- endif -%}\n {%- endif -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n type:{{ format_type_argument(value['type']) }}}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:{{- format_type_argument(params['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] and ('object' in response_declaration['type'] or 'OBJECT' in response_declaration['type']) -%}\n type:{{- format_type_argument(response_declaration['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is iterable -%}\n {{- '[' -}}\n {%- for item in argument -%}\n {{- format_argument(item, escape_keys=escape_keys) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- ']' -}}\n {%- else -%}\n {{- argument -}}\n {%- endif -%}\n{%- endmacro -%}\n{%- macro strip_thinking(text) -%}\n {%- set ns = namespace(result='') -%}\n {%- for part in text.split('<channel|>') -%}\n {%- if '<|channel>' in part -%}\n {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}\n {%- else -%}\n {%- set ns.result = ns.result + part -%}\n {%- endif -%}\n {%- endfor -%}\n {{- ns.result | trim -}}\n{%- endmacro -%}\n\n{%- macro format_tool_response_block(tool_name, response) -%}\n {{- '<|tool_response>' -}}\n {%- if response is mapping -%}\n {{- 'response:' + tool_name + '{' -}}\n {%- for key, value in response | dictsort -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- '}' -}}\n {%- else -%}\n {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}\n {%- endif -%}\n {{- '<tool_response|>' -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(prev_message_type=None) -%}\n{%- set loop_messages = messages -%}\n{{- bos_token -}}\n{#- Handle System/Tool Definitions Block -#}\n{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}\n {{- '<|turn>system\\n' -}}\n {#- Inject Thinking token at the very top of the FIRST system turn -#}\n {%- if enable_thinking is defined and enable_thinking -%}\n {{- '<|think|>\\n' -}}\n {%- set ns.prev_message_type = 'think' -%}\n {%- endif -%}\n {%- if messages[0]['role'] in ['system', 'developer'] -%}\n {%- if messages[0]['content'] is string -%}\n {{- messages[0]['content'] | trim -}}\n {%- elif messages[0]['content'] is iterable -%}\n {%- for item in messages[0]['content'] -%}\n {{- item['text'] | trim + ' '-}}\n {%- endfor -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n {%- endif -%}\n {%- if tools -%}\n {%- for tool in tools %}\n {{- '<|tool>' -}}\n {{- format_function_declaration(tool) | trim -}}\n {{- '<tool|>' -}}\n {%- endfor %}\n {%- set ns.prev_message_type = 'tool' -%}\n {%- endif -%}\n {{- '<turn|>\\n' -}}\n{%- endif %}\n\n{#- Pre-scan: find last user message index for reasoning guard -#}\n{%- set ns_turn = namespace(last_user_idx=-1) -%}\n{%- for i in range(loop_messages | length) -%}\n {%- if loop_messages[i]['role'] == 'user' -%}\n {%- set ns_turn.last_user_idx = i -%}\n {%- endif -%}\n{%- endfor -%}\n\n{#- Loop through messages -#}\n{%- for message in loop_messages -%}\n {%- if message['role'] != 'tool' -%}\n {%- set ns.prev_message_type = None -%}\n {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}\n {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}\n {%- set prev_nt = namespace(role=None, found=false) -%}\n {%- if loop.index0 > 0 -%}\n {%- for j in range(loop.index0 - 1, -1, -1) -%}\n {%- if not prev_nt.found -%}\n {%- if loop_messages[j]['role'] != 'tool' -%}\n {%- set prev_nt.role = loop_messages[j]['role'] -%}\n {%- set prev_nt.found = true -%}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}\n {%- if not continue_same_model_turn -%}\n {{- '<|turn>' + role + '\\n' }}\n {%- endif -%}\n\n {#- Render reasoning/reasoning_content as thinking channel -#}\n {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}\n {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}\n {{- '<|channel>thought\\n' + thinking_text + '\\n<channel|>' -}}\n {%- endif -%}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- set ns_tr_out = namespace(flag=false) -%}\n {%- if message.get('tool_responses') -%}\n {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endfor -%}\n {%- elif message.get('tool_calls') -%}\n {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}\n {%- set ns_tool_scan = namespace(stopped=false) -%}\n {%- for k in range(loop.index0 + 1, loop_messages | length) -%}\n {%- if ns_tool_scan.stopped -%}\n {%- elif loop_messages[k]['role'] != 'tool' -%}\n {%- set ns_tool_scan.stopped = true -%}\n {%- else -%}\n {%- set follow = loop_messages[k] -%}\n {#- Resolve tool_call_id to function name -#}\n {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}\n {%- for tc in message['tool_calls'] -%}\n {%- if tc.get('id') == follow.get('tool_call_id') -%}\n {%- set ns_tname.name = tc['function']['name'] -%}\n {%- endif -%}\n {%- endfor -%}\n {#- Handle content as string or content-parts array -#}\n {%- set tool_body = follow.get('content') -%}\n {%- if tool_body is string -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- elif tool_body is iterable and tool_body is not string -%}\n {%- set ns_txt = namespace(s='') -%}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'text' -%}\n {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'image' -%}\n {{- '<|image|>' -}}\n {%- elif part.get('type') == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- elif part.get('type') == 'video' -%}\n {{- '<|video|>' -}}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- endif -%}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n\n {%- set captured_content -%}\n {%- if message['content'] is string -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(message['content']) -}}\n {%- else -%}\n {{- message['content'] | trim -}}\n {%- endif -%}\n {%- elif message['content'] is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'text' -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(item['text']) -}}\n {%- else -%}\n {{- item['text'] | trim -}}\n {%- endif -%}\n {%- elif item['type'] == 'image' -%}\n {{- '<|image|>' -}}\n {%- set ns.prev_message_type = 'image' -%}\n {%- elif item['type'] == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- set ns.prev_message_type = 'audio' -%}\n {%- elif item['type'] == 'video' -%}\n {{- '<|video|>' -}}\n {%- set ns.prev_message_type = 'video' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- endset -%}\n\n {{- captured_content -}}\n {%- set has_content = captured_content | trim | length > 0 -%}\n\n {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}\n {{- '<|tool_response>' -}}\n {%- elif not (ns_tr_out.flag and not has_content) -%}\n {{- '<turn|>\\n' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}\n {{- '<|turn>model\\n' -}}\n {%- if not enable_thinking | default(false) -%}\n {{- '<|channel>thought\\n<channel|>' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endif -%}"
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790 {
791 "type": "text",
792 "text": "A person in a high-quality \"Kitsune\" (fox) fursuit/cosplay standing in what looks like an airport or hotel lobby.\n\n * *Subject:* Anthropomorphic fox (furry), specifically a Kitsune style.\n * *Coloring:* White fur, red markings around the eyes and ears, black accents on the muzzle and paws.\n * *Features:* Large pointed ears with red interiors, long white hair/mane, large bushy tail (white with red tips).\n * *Outfit:* Traditional Japanese Kimono/Yukata (red with floral patterns), a \"Kitsune\" mask-like face, oversized black paws/gloves.\n * *Setting:* Indoor public space (airport or hotel lobby), tiled floor, luggage carts in the background, people walking by.\n * *Style:* Real-life photography, candid shot, high resolution.\n\n * *Subject Keywords:* Kitsune fursuit, anthropomorphic fox, white fur, red markings, long hair, large ears, bushy tail.\n * *Outfit Keywords:* Japanese kimono, floral pattern, red and white, oversized paws.\n * *Setting Keywords:* Airport lobby, hotel interior, public space, candid photo.\n * *Style/Technical Keywords:* Photorealistic, real-life photography, sharp focus, natural indoor lighting.\n\n * **Option A: Descriptive & Natural (Midjourney style)**\n \"A realistic photo of a person in a high-quality Kitsune fursuit standing in an airport lobby. The suit is white with red markings and features long hair and large pointed ears. They are wearing a traditional red floral kimono. Candid shot, natural indoor lighting.\"\n\n * **Option B: Tag-based/Weighted (Stable Diffusion style)**\n \"1girl, anthro fox, kitsune, fursuit, white fur, red markings, long hair, large ears, bushy tail, japanese kimono, floral pattern, airport lobby, interior, photorealistic, high quality, 8k.\"\n\n * **Option C: Artistic/Technical (Focusing on the \"Look\")**\n \"Real-life photography of a fursuit performer. High detail on fur texture and fabric patterns. Indoor lighting with depth of field.\"\n\n * Explain why these words were chosen.\n * Provide different versions based on common AI models (Midjourney vs. Stable Diffusion).\n * To reverse-engineer this image, we need to identify the **\"fursuit/cosplay\"** and **\"real-life photography\"** markers. This is a real-world photo of a person in a costume, which requires specific keywords to distinguish it from 3D renders or drawings.\n\n * Breakdown: Subject, Outfit, Setting, Style/Lighting.\n * Provide specific prompts for different AI models.\nTo reverse-engineer this image, we need to identify the **\"fursuit/cosplay\"** and **\"real-life photography\"** markers. This is a real-world photo of a person in a costume, which requires specific keywords to distinguish it from 3D renders or drawings.\n\nHere is how you would reconstruct the prompt:\n\n### The \"Core\" Prompt\n> **A realistic photo of a person wearing a high-quality Kitsune fursuit standing in an airport lobby. The suit features white fur with red markings, long hair, and large pointed ears. They are dressed in a traditional Japanese kimono with a red floral pattern. Candid shot, natural indoor lighting.**\n\n---\n\n### Breakdown of the Elements\n\n**1. The Subject (Fursuit/Cosplay)**\n* **Keywords:** *Kitsune fursuit, anthro fox, white fur, red markings, long hair.*\n* **Details:** To get this specific look, you must use the word \"fursuit\" or \"cosplay.\" This tells the AI that it's a person in a costume rather than a 3D character. Mentioning \"Kitsune\" helps with the specific Japanese fox aesthetic (red markings and long hair).\n\n**2. The Outfit (Cultural Fusion)**\n* **Keywords:** *Japanese kimono, floral pattern, red and white.*\n* **Details:** The contrast between the modern fursuit and the traditional kimono is a key visual element. Specifying \"floral pattern\" ensures the AI adds those intricate details to the fabric.\n\n**3. The Setting (Real-World Context)**\n* **Keywords:** *Airport lobby, hotel interior, public space.*\n* **Details:** This provides the context for the background. Using \"airport lobby\" helps generate the specific flooring, lighting, and distant figures seen in the image.\n\n**4. Style & Lighting (Photography)**\n* **Keywords:** *Real-life photography, candid shot, natural indoor lighting.*\n* **Details:** Because this is a real photo, you want to avoid \"3D render\" or \"digital art.\" Using \"candid shot\" helps replicate the slightly unposed, \"caught in the moment\" feel of the original image.\n\n---\n\n### Variations for Different AI Models\n\n#### For Midjourney (Descriptive & Natural)\n> **A realistic photo of a person in a high-quality white and red Kitsune fursuit standing in an airport terminal. They are wearing a traditional Japanese kimono with floral patterns. Candid photography, natural indoor lighting, sharp focus --ar 2:3 --v 6.0**\n\n#### For Stable Diffusion (Tag-based)\n> **(photorealistic:1.4), 1girl, anthro fox, kitsune, fursuit, white fur, red markings, long hair, large ears, bushy tail, japanese kimono, floral pattern, airport lobby, interior, highres, masterpiece.**\n\n#### For DALL-E 3 (Natural Language)\n> **A realistic photo of a person wearing a detailed Kitsune fursuit in an airport. The suit is white with red markings and features long hair and large pointed ears. They are also wearing a traditional Japanese kimono with a red floral pattern. The background shows a public lobby area with people walking by.**",
793 "fromDraftModel": false,
794 "tokensCount": 1298,
795 "isStructural": false
796 }
797 ],
798 "genInfo": {
799 "indexedModelIdentifier": "aifeifei798/gemma-4-12B-it-qat-unquantized/gemma-4-12B-it-qat-q4_0-unquantized-Q4_K.gguf",
800 "identifier": "gemma-4-12b-it-qat-unquantized",
801 "loadModelConfig": {
802 "fields": [
803 {
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806 },
807 {
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811 {
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818 },
819 {
820 "key": "llm.load.llama.acceleration.offloadRatio",
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824 },
825 "predictionConfig": {
826 "fields": [
827 {
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830 },
831 {
832 "key": "llm.prediction.promptTemplate",
833 "value": {
834 "type": "jinja",
835 "jinjaPromptTemplate": {
836 "template": "{%- macro format_parameters(properties, required, filter_keys=false) -%}\n {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in properties | dictsort -%}\n {%- set add_comma = false -%}\n {%- if not filter_keys or key not in standard_keys -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {{ key }}:{\n {%- if value['description'] -%}\n description:<|\"|>{{ value['description'] }}<|\"|>\n {%- set add_comma = true -%}\n {%- endif -%}\n {%- if value['type'] and ('string' in value['type'] or 'STRING' in value['type']) -%}\n {%- if value['enum'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n enum:{{ format_argument(value['enum']) }}\n {%- endif -%}\n {%- elif value['type'] and ('array' in value['type'] or 'ARRAY' in value['type']) -%}\n {%- if value['items'] is mapping and value['items'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n type:{{ format_type_argument(item_value) }}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n nullable:true\n {%- endif -%}\n {%- if value['type'] and ('object' in value['type'] or 'OBJECT' in value['type']) -%}\n {%- if value['properties'] is defined and value['properties'] is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value['properties'], value['required'] | default([])) -}}\n }\n {%- elif value is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}\n }\n {%- endif -%}\n {%- if value['required'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n required:[\n {%- for item in value['required'] | default([]) -%}\n <|\"|>{{- item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- endif -%}\n {%- endif -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n type:{{ format_type_argument(value['type']) }}}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:{{- format_type_argument(params['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] and ('object' in response_declaration['type'] or 'OBJECT' in response_declaration['type']) -%}\n type:{{- format_type_argument(response_declaration['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is iterable -%}\n {{- '[' -}}\n {%- for item in argument -%}\n {{- format_argument(item, escape_keys=escape_keys) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- ']' -}}\n {%- else -%}\n {{- argument -}}\n {%- endif -%}\n{%- endmacro -%}\n{%- macro strip_thinking(text) -%}\n {%- set ns = namespace(result='') -%}\n {%- for part in text.split('<channel|>') -%}\n {%- if '<|channel>' in part -%}\n {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}\n {%- else -%}\n {%- set ns.result = ns.result + part -%}\n {%- endif -%}\n {%- endfor -%}\n {{- ns.result | trim -}}\n{%- endmacro -%}\n\n{%- macro format_tool_response_block(tool_name, response) -%}\n {{- '<|tool_response>' -}}\n {%- if response is mapping -%}\n {{- 'response:' + tool_name + '{' -}}\n {%- for key, value in response | dictsort -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- '}' -}}\n {%- else -%}\n {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}\n {%- endif -%}\n {{- '<tool_response|>' -}}\n{%- endmacro -%}\n\n{%- set ns = namespace(prev_message_type=None) -%}\n{%- set loop_messages = messages -%}\n{{- bos_token -}}\n{#- Handle System/Tool Definitions Block -#}\n{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}\n {{- '<|turn>system\\n' -}}\n {#- Inject Thinking token at the very top of the FIRST system turn -#}\n {%- if enable_thinking is defined and enable_thinking -%}\n {{- '<|think|>\\n' -}}\n {%- set ns.prev_message_type = 'think' -%}\n {%- endif -%}\n {%- if messages[0]['role'] in ['system', 'developer'] -%}\n {%- if messages[0]['content'] is string -%}\n {{- messages[0]['content'] | trim -}}\n {%- elif messages[0]['content'] is iterable -%}\n {%- for item in messages[0]['content'] -%}\n {{- item['text'] | trim + ' '-}}\n {%- endfor -%}\n {%- endif -%}\n {%- set loop_messages = messages[1:] -%}\n {%- endif -%}\n {%- if tools -%}\n {%- for tool in tools %}\n {{- '<|tool>' -}}\n {{- format_function_declaration(tool) | trim -}}\n {{- '<tool|>' -}}\n {%- endfor %}\n {%- set ns.prev_message_type = 'tool' -%}\n {%- endif -%}\n {{- '<turn|>\\n' -}}\n{%- endif %}\n\n{#- Pre-scan: find last user message index for reasoning guard -#}\n{%- set ns_turn = namespace(last_user_idx=-1) -%}\n{%- for i in range(loop_messages | length) -%}\n {%- if loop_messages[i]['role'] == 'user' -%}\n {%- set ns_turn.last_user_idx = i -%}\n {%- endif -%}\n{%- endfor -%}\n\n{#- Loop through messages -#}\n{%- for message in loop_messages -%}\n {%- if message['role'] != 'tool' -%}\n {%- set ns.prev_message_type = None -%}\n {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}\n {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}\n {%- set prev_nt = namespace(role=None, found=false) -%}\n {%- if loop.index0 > 0 -%}\n {%- for j in range(loop.index0 - 1, -1, -1) -%}\n {%- if not prev_nt.found -%}\n {%- if loop_messages[j]['role'] != 'tool' -%}\n {%- set prev_nt.role = loop_messages[j]['role'] -%}\n {%- set prev_nt.found = true -%}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}\n {%- if not continue_same_model_turn -%}\n {{- '<|turn>' + role + '\\n' }}\n {%- endif -%}\n\n {#- Render reasoning/reasoning_content as thinking channel -#}\n {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}\n {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}\n {{- '<|channel>thought\\n' + thinking_text + '\\n<channel|>' -}}\n {%- endif -%}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- set ns_tr_out = namespace(flag=false) -%}\n {%- if message.get('tool_responses') -%}\n {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endfor -%}\n {%- elif message.get('tool_calls') -%}\n {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}\n {%- set ns_tool_scan = namespace(stopped=false) -%}\n {%- for k in range(loop.index0 + 1, loop_messages | length) -%}\n {%- if ns_tool_scan.stopped -%}\n {%- elif loop_messages[k]['role'] != 'tool' -%}\n {%- set ns_tool_scan.stopped = true -%}\n {%- else -%}\n {%- set follow = loop_messages[k] -%}\n {#- Resolve tool_call_id to function name -#}\n {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}\n {%- for tc in message['tool_calls'] -%}\n {%- if tc.get('id') == follow.get('tool_call_id') -%}\n {%- set ns_tname.name = tc['function']['name'] -%}\n {%- endif -%}\n {%- endfor -%}\n {#- Handle content as string or content-parts array -#}\n {%- set tool_body = follow.get('content') -%}\n {%- if tool_body is string -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- elif tool_body is iterable and tool_body is not string -%}\n {%- set ns_txt = namespace(s='') -%}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'text' -%}\n {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}\n {%- endif -%}\n {%- endfor -%}\n {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}\n {%- for part in tool_body -%}\n {%- if part.get('type') == 'image' -%}\n {{- '<|image|>' -}}\n {%- elif part.get('type') == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- elif part.get('type') == 'video' -%}\n {{- '<|video|>' -}}\n {%- endif -%}\n {%- endfor -%}\n {%- else -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- endif -%}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n\n {%- set captured_content -%}\n {%- if message['content'] is string -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(message['content']) -}}\n {%- else -%}\n {{- message['content'] | trim -}}\n {%- endif -%}\n {%- elif message['content'] is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'text' -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(item['text']) -}}\n {%- else -%}\n {{- item['text'] | trim -}}\n {%- endif -%}\n {%- elif item['type'] == 'image' -%}\n {{- '<|image|>' -}}\n {%- set ns.prev_message_type = 'image' -%}\n {%- elif item['type'] == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- set ns.prev_message_type = 'audio' -%}\n {%- elif item['type'] == 'video' -%}\n {{- '<|video|>' -}}\n {%- set ns.prev_message_type = 'video' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- endset -%}\n\n {{- captured_content -}}\n {%- set has_content = captured_content | trim | length > 0 -%}\n\n {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}\n {{- '<|tool_response>' -}}\n {%- elif not (ns_tr_out.flag and not has_content) -%}\n {{- '<turn|>\\n' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}\n {{- '<|turn>model\\n' -}}\n {%- if not enable_thinking | default(false) -%}\n {{- '<|channel>thought\\n<channel|>' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endif -%}"
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838 "stopStrings": []
839 }
840 },
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852 {
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856 {
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860 }
861 }
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924 {
925 "type": "text",
926 "text": "A high-quality, close-up photo of a person in a \"fursuit\" (specifically an anthropomorphic cat/fox hybrid style).\n\n * *Subject:* Anthropomorphic feline/canine character (furry).\n * *Coloring:* Light blue and white fur with dark blue markings.\n * *Features:* Large, expressive eyes (blue/green), small nose, long \"hair\" or mane of light blue fur.\n * *Accessories:* Steampunk-style goggles (dark frames, gold/brass rims) resting on the head.\n * *Pose:* Close-up portrait, looking slightly off-camera with a neutral/curious expression.\n * *Setting:* Indoor, blurry background (bokeh), likely a convention or event space.\n * *Style:* Real-life photography of a fursuit. High detail on the \"fur\" texture and eye reflections.\n\n * *Subject Keywords:* Fursuit, anthro cat, blue fur, white markings, large eyes, long hair.\n * *Accessories:* Steampunk goggles, brass rims, dark frames.\n * *Setting Keywords:* Indoor event, convention center, bokeh background.\n * *Style/Technical Keywords:* Photorealistic, real-life photography, macro shot, high detail, soft lighting.\n\n * **Option A: Descriptive & Natural (Midjourney style)**\n \"A realistic close-up photo of a person in a high-quality blue and white fursuit. The character has large expressive eyes and long light blue hair. They are wearing steampunk goggles with brass rims on their head. Soft indoor lighting, blurry background, 8k resolution.\"\n\n * **Option B: Tag-based/Weighted (Stable Diffusion style)**\n \"1girl, anthro cat, fursuit, blue fur, white markings, large eyes, long hair, steampunk goggles, brass rims, close-up portrait, indoor event, bokeh, photorealistic, high quality, 8k.\"\n\n * **Option C: Artistic/Technical (Focusing on the \"Look\")**\n \"Macro photography of a fursuit head. Focus on eye reflections and fur texture. High contrast between blue and white colors. Soft depth of field.\"\n\n * Explain why these words were chosen.\n * Provide different versions based on common AI models (Midjourney vs. Stable Diffusion).\n * To reverse-engineer this image, we need to identify the **\"fursuit photography\"** and **\"steampunk accessory\"** markers. This is a real-life photo of a high-end fursuit head, which requires specific keywords to distinguish it from 3D renders or drawings.\n\n * Breakdown: Subject, Accessories, Style/Lighting.\n * Provide specific prompts for different AI models.\nTo reverse-engineer this image, we need to identify the **\"fursuit photography\"** and **\"steampunk accessory\"** markers. This is a real-life photo of a high-end fursuit head, which requires specific keywords to distinguish it from 3D renders or drawings.\n\nHere is how you would reconstruct the prompt:\n\n### The \"Core\" Prompt\n> **A realistic close-up photo of a person in a high-quality blue and white fursuit. The character has large expressive eyes and long light blue hair, with steampunk goggles resting on its head. Soft indoor lighting, blurry background, 8k resolution.**\n\n---\n\n### Breakdown of the Elements\n\n**1. The Subject (Fursuit Details)**\n* **Keywords:** *Fursuit, anthro cat, blue fur, white markings, large eyes.*\n* **Details:** To get this specific look, you must use the word \"fursuit.\" This tells the AI it's a physical costume. Mentioning \"blue and white\" with \"large expressive eyes\" captures the character's unique color palette and facial structure.\n\n**2. The Accessories (Steampunk Aesthetic)**\n* **Keywords:** *Steampunk goggles, brass rims, dark frames.*\n* **Details:** The goggles are a major visual anchor. Using \"steampunk\" helps the AI understand the style of the metalwork and the overall vibe of the accessory.\n\n**3. The Style (Photography & Depth)**\n* **Keywords:** *Close-up portrait, bokeh background, real-life photography.*\n* **Details:** This is a macro/close-up shot. Using \"bokeh\" or \"blurry background\" ensures that the focus remains entirely on the fursuit's face and textures while blurring out the convention/event environment behind it.\n\n**4. Technical Quality (Texture)**\n* **Keywords:** *High detail, fur texture, soft lighting.*\n* **Details:** Because high-end fursuits are made of faux fur, mentioning \"fur texture\" helps the AI generate those fine, individual strands rather than a flat, solid color.\n\n---\n\n### Variations for Different AI Models\n\n#### For Midjourney (Descriptive & Natural)\n> **A realistic close-up photo of a person in a high-quality blue and white fursuit with long hair and large expressive eyes. They are wearing steampunk goggles with brass rims on their head. Soft indoor lighting, blurry background, 8k resolution --ar 1:1 --v 6.0**\n\n#### For Stable Diffusion (Tag-based)\n> **(photorealistic:1.4), 1girl, anthro cat, fursuit, blue fur, white markings, large eyes, long hair, steampunk goggles, brass rims, close-up portrait, indoor event, bokeh, highres, masterpiece.**\n\n#### For DALL-E 3 (Natural Language)\n> **A realistic close-up photo of a person wearing a high-quality fursuit. The character has light blue and white fur, long hair, and large expressive eyes. They are wearing steampunk goggles with brass rims on their head. The background is softly blurred, and the lighting is soft and natural.**",
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970 "template": "{%- macro format_parameters(properties, required, filter_keys=false) -%}\n {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in properties | dictsort -%}\n {%- set add_comma = false -%}\n {%- if not filter_keys or key not in standard_keys -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {{ key }}:{\n {%- if value['description'] -%}\n description:<|\"|>{{ value['description'] }}<|\"|>\n {%- set add_comma = true -%}\n {%- endif -%}\n {%- if value['type'] and ('string' in value['type'] or 'STRING' in value['type']) -%}\n {%- if value['enum'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n enum:{{ format_argument(value['enum']) }}\n {%- endif -%}\n {%- elif value['type'] and ('array' in value['type'] or 'ARRAY' in value['type']) -%}\n {%- if value['items'] is mapping and value['items'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n items:{\n {%- set ns_items = namespace(found_first=false) -%}\n {%- for item_key, item_value in value['items'] | dictsort -%}\n {%- if item_value is not none -%}\n {%- if ns_items.found_first %},{% endif -%}\n {%- set ns_items.found_first = true -%}\n {%- if item_key == 'properties' -%}\n properties:{\n {%- if item_value is mapping -%}\n {{- format_parameters(item_value, value['items']['required'] | default([])) -}}\n {%- endif -%}\n }\n {%- elif item_key == 'required' -%}\n required:[\n {%- for req_item in item_value -%}\n <|\"|>{{- req_item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- elif item_key == 'type' -%}\n type:{{ format_type_argument(item_value) }}\n {%- else -%}\n {{ item_key }}:{{ format_argument(item_value) }}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n }\n {%- endif -%}\n {%- endif -%}\n {%- if value['nullable'] %}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n nullable:true\n {%- endif -%}\n {%- if value['type'] and ('object' in value['type'] or 'OBJECT' in value['type']) -%}\n {%- if value['properties'] is defined and value['properties'] is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value['properties'], value['required'] | default([])) -}}\n }\n {%- elif value is mapping -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n properties:{\n {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}\n }\n {%- endif -%}\n {%- if value['required'] -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n required:[\n {%- for item in value['required'] | default([]) -%}\n <|\"|>{{- item -}}<|\"|>\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n ]\n {%- endif -%}\n {%- endif -%}\n {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}\n type:{{ format_type_argument(value['type']) }}}\n {%- endif -%}\n {%- endfor -%}\n{%- endmacro -%}\n{%- macro format_function_declaration(tool_data) -%}\n declaration:{{- tool_data['function']['name'] -}}{description:<|\"|>{{- tool_data['function']['description'] -}}<|\"|>\n {%- set params = tool_data['function']['parameters'] -%}\n {%- if params -%}\n ,parameters:{\n {%- if params['properties'] -%}\n properties:{ {{- format_parameters(params['properties'], params['required']) -}} },\n {%- endif -%}\n {%- if params['required'] -%}\n required:[\n {%- for item in params['required'] -%}\n <|\"|>{{- item -}}<|\"|>\n {{- ',' if not loop.last -}}\n {%- endfor -%}\n ],\n {%- endif -%}\n {%- if params['type'] -%}\n type:{{- format_type_argument(params['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n {%- if 'response' in tool_data['function'] -%}\n {%- set response_declaration = tool_data['function']['response'] -%}\n ,response:{\n {%- if response_declaration['description'] -%}\n description:<|\"|>{{- response_declaration['description'] -}}<|\"|>,\n {%- endif -%}\n {%- if response_declaration['type'] and ('object' in response_declaration['type'] or 'OBJECT' in response_declaration['type']) -%}\n type:{{- format_type_argument(response_declaration['type']) -}}}\n {%- endif -%}\n {%- endif -%}\n }\n{%- endmacro -%}\n{%- macro format_argument(argument, escape_keys=True) -%}\n {%- if argument is string -%}\n {{- '<|\"|>' + argument + '<|\"|>' -}}\n {%- elif argument is boolean -%}\n {{- 'true' if argument else 'false' -}}\n {%- elif argument is mapping -%}\n {{- '{' -}}\n {%- set ns = namespace(found_first=false) -%}\n {%- for key, value in argument | dictsort -%}\n {%- if ns.found_first %},{% endif -%}\n {%- set ns.found_first = true -%}\n {%- if escape_keys -%}\n {{- '<|\"|>' + key + '<|\"|>' -}}\n {%- else -%}\n {{- key -}}\n {%- endif -%}\n :{{- format_argument(value, escape_keys=escape_keys) -}}\n {%- endfor -%}\n {{- '}' -}}\n {%- elif argument is iterable -%}\n {{- '[' -}}\n {%- for item in argument -%}\n {{- format_argument(item, escape_keys=escape_keys) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- ']' -}}\n {%- else -%}\n {{- argument -}}\n {%- endif -%}\n{%- endmacro -%}\n{%- macro strip_thinking(text) -%}\n {%- set ns = namespace(result='') -%}\n {%- for part in text.split('<channel|>') -%}\n {%- if '<|channel>' in part -%}\n {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}\n {%- else -%}\n {%- set ns.result = ns.result + part -%}\n {%- endif -%}\n {%- endfor -%}\n {{- ns.result | trim -}}\n{%- endmacro -%}\n\n{%- macro format_tool_response_block(tool_name, response) -%}\n {{- '<|tool_response>' -}}\n {%- if response is mapping -%}\n {{- 'response:' + tool_name + '{' -}}\n {%- for key, value in response | dictsort -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- if not loop.last %},{% endif -%}\n {%- endfor -%}\n {{- '}' -}}\n {%- else -%}\n {{- 'response:' + tool_name + 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> 0 -%}\n {%- for j in range(loop.index0 - 1, -1, -1) -%}\n {%- if not prev_nt.found -%}\n {%- if loop_messages[j]['role'] != 'tool' -%}\n {%- set prev_nt.role = loop_messages[j]['role'] -%}\n {%- set prev_nt.found = true -%}\n {%- endif -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}\n {%- if not continue_same_model_turn -%}\n {{- '<|turn>' + role + '\\n' }}\n {%- endif -%}\n\n {#- Render reasoning/reasoning_content as thinking channel -#}\n {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}\n {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}\n {{- '<|channel>thought\\n' + thinking_text + '\\n<channel|>' -}}\n {%- endif -%}\n\n {%- if message['tool_calls'] -%}\n {%- for tool_call in message['tool_calls'] -%}\n {%- set function = tool_call['function'] -%}\n {{- '<|tool_call>call:' + function['name'] + '{' -}}\n {%- if function['arguments'] is mapping -%}\n {%- set ns_args = namespace(found_first=false) -%}\n {%- for key, value in function['arguments'] | dictsort -%}\n {%- if ns_args.found_first %},{% endif -%}\n {%- set ns_args.found_first = true -%}\n {{- key -}}:{{- format_argument(value, escape_keys=False) -}}\n {%- endfor -%}\n {%- elif function['arguments'] is string -%}\n {{- function['arguments'] -}}\n {%- endif -%}\n {{- '}<tool_call|>' -}}\n {%- endfor -%}\n {%- set ns.prev_message_type = 'tool_call' -%}\n {%- endif -%}\n\n {%- set ns_tr_out = namespace(flag=false) -%}\n {%- if message.get('tool_responses') -%}\n {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}\n {%- for tool_response in message['tool_responses'] -%}\n {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}\n {%- set ns_tr_out.flag = true -%}\n {%- set ns.prev_message_type = 'tool_response' -%}\n {%- endfor -%}\n {%- elif message.get('tool_calls') -%}\n {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}\n {%- set ns_tool_scan = namespace(stopped=false) -%}\n {%- for k in range(loop.index0 + 1, loop_messages | length) -%}\n {%- if ns_tool_scan.stopped -%}\n {%- elif loop_messages[k]['role'] != 'tool' -%}\n {%- set ns_tool_scan.stopped = true -%}\n {%- else -%}\n {%- set follow = loop_messages[k] -%}\n {#- Resolve tool_call_id to function name -#}\n {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}\n {%- for tc in message['tool_calls'] -%}\n {%- if tc.get('id') == follow.get('tool_call_id') -%}\n {%- set ns_tname.name = tc['function']['name'] -%}\n {%- endif -%}\n {%- endfor -%}\n {#- Handle content as string or content-parts array -#}\n {%- set tool_body = follow.get('content') -%}\n {%- if tool_body is string -%}\n {{- format_tool_response_block(ns_tname.name, tool_body) -}}\n {%- elif tool_body is iterable and tool_body is not string -%}\n {%- set 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is iterable -%}\n {%- for item in message['content'] -%}\n {%- if item['type'] == 'text' -%}\n {%- if role == 'model' -%}\n {{- strip_thinking(item['text']) -}}\n {%- else -%}\n {{- item['text'] | trim -}}\n {%- endif -%}\n {%- elif item['type'] == 'image' -%}\n {{- '<|image|>' -}}\n {%- set ns.prev_message_type = 'image' -%}\n {%- elif item['type'] == 'audio' -%}\n {{- '<|audio|>' -}}\n {%- set ns.prev_message_type = 'audio' -%}\n {%- elif item['type'] == 'video' -%}\n {{- '<|video|>' -}}\n {%- set ns.prev_message_type = 'video' -%}\n {%- endif -%}\n {%- endfor -%}\n {%- endif -%}\n {%- endset -%}\n\n {{- captured_content -}}\n {%- set has_content = captured_content | trim | length > 0 -%}\n\n {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}\n {{- '<|tool_response>' -}}\n {%- elif not (ns_tr_out.flag and not has_content) -%}\n {{- '<turn|>\\n' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}\n {{- '<|turn>model\\n' -}}\n {%- if not enable_thinking | default(false) -%}\n {{- '<|channel>thought\\n<channel|>' -}}\n {%- endif -%}\n {%- endif -%}\n{%- endif -%}"
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