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20 Commits

Author SHA1 Message Date
zcr
a36235d58e 1 2026-04-14 10:11:29 +08:00
zcr
433aa3e751 Merge remote-tracking branch 'origin/main'
# Conflicts:
#	docker-compose.yml
2026-04-14 10:10:56 +08:00
zcr
7bf080b3e7 1 2026-04-14 10:10:00 +08:00
zcr
03c4759895 fix:更新occasion映射服装类别 2026-03-05 15:41:39 +08:00
03ff6605a3 更新 docker-compose.yml 2026-02-09 14:54:17 +08:00
4b3b0f6aa8 更新 .gitea/workflows/prod_build_manual.yaml 2026-02-09 14:50:25 +08:00
zcr
c798d37fdd fix:防止服务宕机,增加自动重启 2026-02-03 15:34:10 +08:00
zcr
43fd576da6 fix:启动端口改由环境变量控制 2026-01-27 10:40:50 +08:00
zcr
1bbb9c945e fix:启动端口改由环境变量控制 2026-01-27 10:33:35 +08:00
pangkaicheng
3ca6b16eaf UPDATE: update prompt. Make generate button bold 2026-01-19 13:18:21 +08:00
pangkaicheng
f9d83f6a99 UPDATE: chat basic prompt. Limit Chatbot to conclude within three turns. 2026-01-19 12:16:47 +08:00
pangkaicheng
496e7ad590 FIX: delete iterative mode 2026-01-14 12:22:13 +08:00
pangkaicheng
a7b101253b UPDATE; fullfill LC request for lacking layering of Evening/workwear occasions 2026-01-14 12:22:13 +08:00
pangkaicheng
077ceea219 merge clothing stage and accessories stage of stylist guide 2026-01-14 12:22:13 +08:00
zcr
4fa815158f fix:推荐逻辑更新 弃用慢推荐 2026-01-12 11:24:55 +08:00
pangkaicheng
46793ba271 UPDATE: add color constrain in vector database for wedding occasion avoiding black items. 2026-01-07 17:26:44 +08:00
pangkaicheng
773db4fcc3 UPDATE: 1. update general rule. 2. ADD retry feature in quick mode if outfit is considered as incomplete 2026-01-07 16:21:17 +08:00
pangkaicheng
13b99f4dd3 FIX: Failed to find single item will not terminate whole process 2026-01-07 12:19:50 +08:00
pangkaicheng
9d6fbc92f1 UPDATE: subcategories filtering, General rules updates 2026-01-06 15:42:30 +08:00
pangkaicheng
e7ec547671 Modify DOC workflow 2026-01-02 19:45:52 +08:00
23 changed files with 746 additions and 597 deletions

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@@ -7,7 +7,7 @@ jobs:
runs-on: ubuntu-latest runs-on: ubuntu-latest
env: env:
REMOTE_DEPLOY_PATH: /workspace/Trinity/Litserve_LC_Prod/lc_stylist_agent REMOTE_DEPLOY_PATH: /workspace/LC_Workspace/LitServe_Server_Workspace/lc_stylist_agent
steps: steps:
- name: 1.检出代码 - name: 1.检出代码

View File

@@ -17,7 +17,11 @@ class Settings(BaseSettings):
extra='ignore' # 忽略环境变量中多余的键 extra='ignore' # 忽略环境变量中多余的键
) )
# 启动端口 # 启动端口
SERVE_PROD: int = Field(default=8000, description='') SERVE_PORT: int = Field(default=8000, description='')
# 换脸模型服务
RE_FACE_MODEL_URL: str = Field(default="10.1.1.240:10071", description='')
# 调试配饰 # 调试配饰
LOCAL: int = Field(default=0, description="是否在本地运行1表示本地运行0表示生产环境运行") LOCAL: int = Field(default=0, description="是否在本地运行1表示本地运行0表示生产环境运行")

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@@ -27,4 +27,4 @@ if __name__ == "__main__":
agent_api = LCAgent(enable_async=True, api_path='/api/v1/agent') agent_api = LCAgent(enable_async=True, api_path='/api/v1/agent')
reface_api = ReFace(api_path='/api/v1/reface') reface_api = ReFace(api_path='/api/v1/reface')
server = ls.LitServer([chat_boot_api, agent_api, reface_api]) server = ls.LitServer([chat_boot_api, agent_api, reface_api])
server.run(port=settings.SERVE_PROD) server.run(port=8000)

View File

@@ -43,7 +43,7 @@ class OccasionEnum(str, Enum):
class StylistResponse(BaseModel): class StylistResponse(BaseModel):
occasions: List[OccasionEnum] = Field( occasions: List[OccasionEnum] = Field(
description="A list of **applicable** occasions that are most strongly implied or explicitly requested by the user's conversation history. These occasions are used later in item retrieval for filtering and must strictly match the predefined OccasionEnum list." description="A list of **applicable** occasions that are most strongly implied or explicitly requested by the user's conversation history. The first occasion in this list is the most applicable one. These occasions are used later in item retrieval for filtering and must strictly match the predefined OccasionEnum list."
) )
summary: str = Field( summary: str = Field(
description="A detailed summary of the user's styling requirements, preferences, constraints, and specific item requests." description="A detailed summary of the user's styling requirements, preferences, constraints, and specific item requests."
@@ -196,14 +196,19 @@ class LCAgent(ls.LitAPI):
stylist_agent_kwages = self.stylist_agent_kwages.copy() stylist_agent_kwages = self.stylist_agent_kwages.copy()
tasks_mapping = {} tasks_mapping = {}
if num_outfits == 1:
tasks_mapping[outfit_ids[0]] = "fast" # 历史1快3慢推荐逻辑
else: # if num_outfits == 1:
for i in range(num_outfits): # tasks_mapping[outfit_ids[0]] = "fast"
if i == 0: # else:
tasks_mapping[outfit_ids[i]] = "fast" # for i in range(num_outfits):
else: # if i == 0:
tasks_mapping[outfit_ids[i]] = "slow" # tasks_mapping[outfit_ids[i]] = "fast"
# else:
# tasks_mapping[outfit_ids[i]] = "slow"
for i in range(num_outfits):
tasks_mapping[outfit_ids[i]] = "fast"
for k, v in tasks_mapping.items(): for k, v in tasks_mapping.items():
logger.info(f"fast request outfit_id is : {k}") logger.info(f"fast request outfit_id is : {k}")
@@ -357,15 +362,15 @@ if __name__ == "__main__":
request_data = json.load(f) request_data = json.load(f)
tasks_with_metadata = [] tasks_with_metadata = []
for test_content in request_data[14:20]: for test_content in request_data[6:7]:
occasions = test_content['occasions'] occasions = test_content['occasions']
request_summary = test_content['request_summary'] request_summary = test_content['request_summary']
for stylist_name in ["edi"]: for stylist_name in ["crystal", "mini", "vera", "edi"]:
stylist_agent_kwages['outfit_id'] = test_content['test_case_id'] + "_" + "_".join(occasions) + f"_{stylist_name}" stylist_agent_kwages['outfit_id'] = test_content['test_case_id'] + '_' + test_content['occasions'][0].replace('/', '_') + f"_{stylist_name}"
stylist_agent_kwages['stylist_name'] = stylist_name stylist_agent_kwages['stylist_name'] = stylist_name
stylist_agent_kwages['gender'] = "female" stylist_agent_kwages['gender'] = "female"
stylist_agent_kwages['callback_url'] = ""
agent = AsyncStylistAgent(**stylist_agent_kwages) agent = AsyncStylistAgent(**stylist_agent_kwages)
# coro = agent.run_iterative_styling(
coro = agent.run_quick_batch_styling( coro = agent.run_quick_batch_styling(
request_summary=request_summary, request_summary=request_summary,
occasions=occasions, occasions=occasions,

View File

@@ -49,10 +49,18 @@ class LCChatBot(ls.LitAPI):
user_msg = Message(role=Role.USER, content=user_message) user_msg = Message(role=Role.USER, content=user_message)
chat_history = self.redis.get_history(session_id) chat_history = self.redis.get_history(session_id)
chat_history.append(user_msg) chat_history.append(user_msg)
turn_count = sum(1 for msg in chat_history if msg.role == Role.USER)
if request.gender == 'male': if request.gender == 'male':
prompt = BASIC_PROMPT.format(gender='men') system_instruction = BASIC_PROMPT.format(gender='men')
else: else:
prompt = BASIC_PROMPT.format(gender='women') system_instruction = BASIC_PROMPT.format(gender='women')
if turn_count >= 3:
system_instruction += "\n\nCRITICAL: This is the final turn. Do not ask questions. Provide a brief summary and use the mandatory closing phrase."
else:
system_instruction += f"\n\nCURRENT STATE: This is turn {turn_count} of 3. Keep gathering info efficiently or provide a brief summary and use the mandatory closing phrase if you have sufficient information."
contents = [] contents = []
@@ -68,7 +76,7 @@ class LCChatBot(ls.LitAPI):
model='gemini-2.5-flash', model='gemini-2.5-flash',
contents=contents, contents=contents,
config=types.GenerateContentConfig( config=types.GenerateContentConfig(
system_instruction=prompt, system_instruction=system_instruction,
# temperature=0.3, # temperature=0.3,
) )
) )
@@ -99,7 +107,7 @@ class LCChatBot(ls.LitAPI):
if __name__ == "__main__": if __name__ == "__main__":
sys.stdout = open('permanent.log', 'w', encoding='utf-8') # sys.stdout = open('permanent.log', 'w', encoding='utf-8')
import asyncio import asyncio
@@ -137,23 +145,67 @@ if __name__ == "__main__":
print(chunk, end="", flush=True) print(chunk, end="", flush=True)
text_list = [ # text_list = [
'我要去参加好朋友的婚礼,你能帮我挑一套衣服吗?', # '我要去参加好朋友的婚礼,你能帮我挑一套衣服吗?',
'I need something to wear for a big presentation at work tomorrow. I want to look powerful but still approachable.', # 'I need something to wear for a big presentation at work tomorrow. I want to look powerful but still approachable.',
'Who do you think is the best world leader right now?', # 'Who do you think is the best world leader right now?',
'Im going on a trip to Paris next week and need some outfits.', # 'Im going on a trip to Paris next week and need some outfits.',
'Help me find a cool outfit for a rock concert. I hate wearing dresses.', # 'Help me find a cool outfit for a rock concert. I hate wearing dresses.',
'I want to look very cool, 或者是那种很有个性的风格 for a gallery opening.', # 'I want to look very cool, 或者是那种很有个性的风格 for a gallery opening.',
"I'm going to a gala. Please list 5 different dress styles for me and use bold text for the names.", # "I'm going to a gala. Please list 5 different dress styles for me and use bold text for the names.",
"I'm feeling really sad today and just want an outfit that matches my mood." # "I'm feeling really sad today and just want an outfit that matches my mood."
] # ]
for text in text_list: # for text in text_list:
asyncio.run(run_simple_test(text)) # asyncio.run(run_simple_test(text))
# print("\n" + "=" * 50)
# # 启动异步事件循环
# try: async def run_interactive_test():
# asyncio.run(run_simple_test()) """
# except Exception as e: 手动输入测试:模拟真实用户与 AI 的多轮对话
# print(f"\n发生致命错误: {e}") """
# # 1. 初始化
sys.stdout.close() chatbot_api = LCChatBot()
chatbot_api.setup(device="cpu")
session_id = "manual_test_session"
user_id = "test_user"
print("--- 👗 欢迎进入 AI 造型师测试 (输入 'quit' 退出) ---")
# 清空旧的测试记录,开始新会话
chatbot_api.redis.clear_history(session_id)
print("✅ 已清空历史记录,开始新会话。")
while True:
# 2. 获取手动输入
user_input = input("\nUser (你): ")
if user_input.lower() in ['quit', 'exit', '退出']:
break
# 3. 构造请求
request_data = PredictRequest(
user_id=user_id,
session_id=session_id,
user_message=user_input,
gender="female" # 或者根据需要修改
)
print("Agent (AI): ", end="")
# 4. 调用并流式打印
# 注意:这里的 predict 内部现在会计算 turn_count
response_generator = chatbot_api.predict(request_data)
full_response = ""
async for chunk in response_generator:
print(chunk, end="", flush=True)
full_response += chunk
# 将 AI 的回复存入 Redis (如果你的 predict 函数里没存的话)
# chatbot_api.redis.add_message(session_id, Role.ASSISTANT, full_response)
print() # 换行
asyncio.run(run_interactive_test())

View File

@@ -1,26 +1,3 @@
BASIC_PROMPT_OLD = """You are a professional, friendly, and insightful AI {gender}'s styling assistant.
Your primary mission is to engage in a multi-turn conversation with the user to fully understand their dressing intent. You must adopt a professional yet approachable tone.
CONVERSATION GOALS:
1. **Occasion:** Determine the specific event (e.g., romantic dinner, summer wedding, business meeting).
2. **Style:** Pinpoint the desired aesthetic (e.g., classic elegance, edgy, minimalist, bohemian).
3. **Vibe/Details:** Gather any mood or specific constraints (e.g., needs to be comfortable, requires light colors, no bare shoulders).
4. **Item Preference:** Ask the user if they have any specific preferences for an item type or silhouette (e.g., preference for a dress, skirt, tailored pants, or a particular neckline/length).
GUIDANCE FOR RESPONSE GENERATION:
- After the user's initial request (e.g., "I want a chic outfit for dinner."), immediately reply with a friendly, targeted follow-up question to elicit the most crucial missing information (usually a combination of **Occasion** and **Style**).
- Be concise. Ask only 1 to 2 essential questions per turn.
- You must gather sufficient, clear intent before proceeding to actual clothing recommendations.
OUTPUT FORMAT INSTRUCTION:
- **DO NOT** use any Markdown formatting whatsoever (e.g., do not use asterisks (*), bold text (**), lists, or code blocks).
- **ONLY** output the plain text response spoken by the AI Assistant.
Example Follow-up (mimicking a conversational flow):
User: I want a chic outfit for dinner.
Your Response: Hey there! A chic dinner outfit, I love that! To give you the perfect recommendations, tell me: is this a romantic date, business dinner, or celebration with friends? And what's your go-to style vibe: classic elegance or something with more edge?"""
BASIC_PROMPT = """ BASIC_PROMPT = """
You are a professional, friendly, and insightful AI {gender}'s styling assistant. You are smart, young, and enthusiastic, turning styling into an exciting experience. Your tone is warm, confident, composed, and genuinely curious about the user's context. You are a professional, friendly, and insightful AI {gender}'s styling assistant. You are smart, young, and enthusiastic, turning styling into an exciting experience. Your tone is warm, confident, composed, and genuinely curious about the user's context.
@@ -30,6 +7,16 @@ CONVERSATION GOALS:
3. **Vibe/Details:** Gather mood or constraints (e.g., comfort, specific colors). 3. **Vibe/Details:** Gather mood or constraints (e.g., comfort, specific colors).
4. **Item Preference:** Identify preferences for silhouettes or specific items. 4. **Item Preference:** Identify preferences for silhouettes or specific items.
CONVERSATION FLOW:
- You have a maximum of 3 turns (one turn = one user message and one assistant response) to gather information.
- On the 3rd turn, or *once you have sufficient info*, do NOT ask further questions.
- MANDATORY CLOSING: You must end your final response using the FINAL TURN CLOSING RULE below.
FINAL TURN CLOSING RULE:
- Once requirements are gathered, do NOT ask any more questions.
- End your final response with a creative and friendly variation of the closing phrase.
- REQUIRED COMPONENTS: Every variation MUST mention the "**Generate button**" (this phrase must be bounded using double asterisks).
PERSONALITY AND COMMUNICATION RULES: PERSONALITY AND COMMUNICATION RULES:
- Always reply in English only. If the user speaks another language, state in English that you cannot speak that language and steer back to styling. - Always reply in English only. If the user speaks another language, state in English that you cannot speak that language and steer back to styling.
- Keep responses extremely SHORT (maximum 2 sentences). - Keep responses extremely SHORT (maximum 2 sentences).
@@ -47,7 +34,7 @@ OUTPUT FORMAT INSTRUCTION:
- **ONLY** output the plain text response spoken by the AI Assistant. - **ONLY** output the plain text response spoken by the AI Assistant.
EXAMPLE DIALOGUES: EXAMPLE DIALOGUES:
User: 我想找件衣服参加婚礼。 Response: I am so sorry, but I can only speak English! I would love to help you find the perfect wedding guest look if you can tell me the dress code or the venue vibe. User: 我想找件衣服参加婚礼。 Response: I would love to help you find the perfect wedding guest look if you can tell me the dress code or the venue vibe.
User: I need a chic outfit for dinner. Response: That sounds like a fabulous evening! Is this a romantic date or a casual night out with friends, and do you prefer a sleek dress or tailored separates? User: I need a chic outfit for dinner. Response: That sounds like a fabulous evening! Is this a romantic date or a casual night out with friends, and do you prefer a sleek dress or tailored separates?
@@ -64,159 +51,113 @@ Your task is to:
Extract this information accurately from the chat history. Extract this information accurately from the chat history.
""" """
from app.taxonomy import FASHION_TAXONOMY, IGNORE_SUBCATEGORY, ALL_SUBCATEGORY_LIST from app.taxonomy import FASHION_TAXONOMY, IGNORE_SUBCATEGORY
GENERAL_RULES = """## General Rule
### **Color:**
* Limit your outfit in two-three color shades max.
* Pair one accent color item with neutral colors
* Don't show neon color items
* Pair colors in warm tone/cool tone
* Denim and black and white is a neutral color matches with every other color.
core_outfit_template = f""" ### **Layering:**
You are a professional fashion stylist Agent, specialized in creating complete, tailored outfits for {{gender}}. Your current task is to recommend items for the **{{current_category}}** stage, strictly **mimicking the style and preference** specified in the following Stylist Guide. * Style at least 2-3 layers
* Show white t-shirt, shirt hem under pull over cardigan and hoodies; Don't show hem in layerinmg except sweaters, cardigan and hoodies (if capable)
Your task is to **create a cohesive and complete outfit**, strictly adhering to **BOTH** the user's explicit **Request Summary** and the **Outfit Style Guide**. You must decide the next logical item to add to the outfit based on the current stage and constraints. Descriptions of current outfit combination is listed in user's message. * Style hoodie under blazer/ bomber jacker, leathe jacket/ trechcoat to create a street style casual look (if capable)
## RULE HIERARCHY (Priority Order):
1. **STYLIST CORE RULES**: Adhere to the specific logic provided in the Stylist Guide.
2. **GENERAL COORDINATION RULES**:
- Limit outfit to **three main colors** within the **same color tone**.
- Preferred composition: **Two neutrals and one accent color**.
- **Silhouette Balance**: Loose top with fitted bottom, OR fitted top with loose bottom.
- **Pants Logic**: Strictly NO mid-calf length pants. Cropped pants MUST be paired with loafers or ankle boots.
---
## Request from the User:
{{request_summary}}
## Core Guidance Document: Stylist Guide
{{stylist_guide}}
---
## Your Workflow and Constraints
1. **Style Adherence**: You must follow the Rule Hierarchy. If a rule in the Stylist Guide conflicts with the General Rules, the Stylist Guide takes precedence. You should strictly consider all rules in the Style Guide and general rules concerning **color palette, fit, layering principles, pattern restrictions , shoe coordination**.
2. **Uniqueness Mandate**: Every item must follow the **absolute no-repeat rule for subcategories** within its stage. Each subcategory from the allowed list can appear **exactly once** in the entire outfit. Furthermore, the categories 'dresses' and 'pants' and 'skirts' are mutually exclusive; they NORMALLY cannot be included in the same outfit.
3. **Step Planning**: The styling sequence must follow a logical approach (e.g., top-down, inside-out for clothing). Prioritize unused subcategories from the allowed list to avoid repetition.
4. **Structured Output**: Your output MUST be a valid JSON object. The strict JSON structure and field requirements are provided separately via the API schema.
You must only output one of two actions: "recommend_item" or "stop".
4.1. **recommend_item**: Use this action to suggest the next single item.
* **subcategory**: Must be strictly no repeats, and drawn from the allowed list.
* **description**: This must be an **extremely detailed and precise** description for the vector search. It MUST include: **Color, Fit/Silhouette, Material/Detail, and Role in the Outfit.**
You must strictly use the **JSON format** for your output, as follows:
```json
{{{{
"action": "recommend_item",
"subcategory": "YOUR_ITEM_SUBCATEGORY",
"description": "YOUR_DETAILED_DESCRIPTION",
"reason": "YOUR_RECOMMENDATION_REASON"
}}}}
4.2. **stop**: Use this action when the Termination Condition is met.
* **reason**: This field is mandatory when stopping, and must clearly state why the outfit is complete.
You must strictly use the **JSON format** for your output, as follows:
{{{{
"action": "stop",
"subcategory": "",
"description": "",
"reason": "CORE_OUTFIT_COMPLETE"
}}}}
5. **Termination Condition**: Terminate when the below condition is fully met
5.1. **CLOTHING Stage**: The core clothing part of the outfit is complete, meaning the combination of items effectively achieves **full body coverage** (e.g., includes both a top/upper garment and a bottom/lower garment, or a single full-body piece like a dress/jumpsuit). Additionally, **all mandatory elements** stipulated in the Style Guide are satisfied. *(Note: Typically, {{max_len}} items are sufficient for this stage.)*
5.2. **SHOES Stage**: **Exactly one (1) item** has been successfully recommended, as shoes are a **mandatory component** for any complete outfit.
5.3. **BAGS Stage**: **Exactly one (1) item** has been successfully recommended, **OR** the recommendation is skipped if the Style Guide or the User Request **does not mandate** a bag for the specific occasion (i.e., the bag is considered optional).
6. **Context Dependency**: The user's next input (if not Start) will contain the **image and description of the selected item**. When recommending the next item:
a) First verify the subcategories of all already selected items to ensure no duplicates;
b) Select an unused subcategory from the allowed list as the priority;
c) Ensure the recommended item coordinates with the already selected items and complies with all rules in the Style Guide.
Now, please start building an outfit (with strictly unique categories for all items) and output the JSON for the first item.
""" """
accessories_template = f""" GENERAL_RULES_DICT = {
You are a professional fashion stylist Agent, specialized in creating complete, tailored outfits for {{gender}}. Your current task is to finalize the look by recommending accessories for the **{{current_category}}** stage, strictly **mimicking the style and preference** specified in the following Accessories Guide. 'clothing': """### **Body items mix & match:**
* Loose/oversized pair with fitted bottoms. Wide bottoms pair with fitted top.
* With loose clothing, use a belt or a "French tuck" (tucking just the front of the shirt) to define waistline
* Pair casual items with dressy items. Wear a blazer with a graphic tee, or a silk skirt with a chunky knit sweater.
* Always add an outer on a top and bottom to finish the outfit, mix and match in at least 2 layers.
* Mix menswear-inspired pieces (blazers, loafers, trousers) with feminine pieces (lace, silk, florals) for a dynamic look.
* one print per outfit""",
'bags': """### **Bag matching:**
* Large totes are for day/work; clutches and mini bags are for evening. Never bring a giant work tote to a cocktail event.
* A smooth satin dress pair with a leather, a beaded or velvet bag ; Heavy wool pair with a sleek leather bag
* Match bag and shoes in same color or match bag and coat in same color
* Straw and canvas bags for spring/summer. Velvet and faux fur bags for autumn/winter. Leather works year-round.""",
'shoes': """### **Shoes matching:**
* Dress with heels ; Jeans and trousers with heels or loafers
* Match shoes with skin tone or the bottom piece
* Chunky winter layers pair with a boot, platform shoe (boot, platform).
* Crop pants pair with ankle boots, don't show skin ; Don't show calf length pants ; Always suggest wide leg floor length pants
* Wide-leg trousers pair with a heel ; loafer ; heel boots ; or a sneaker.
* No socks with sandals.""",
'accessories': """### **Accessory matching:**
* Acceesory wear in a set of same metal colour (gold earrings with gold belt buckle)
* Wear chokers or short necklaces with V-necks; wear long pendants with crew necks or turtlenecks.
* Wear a belt in tuck-in outfits
* Style silk scarf for the neck; tie it on your bag handle, around your wrist, or use it as a belt for a pop of color.
* No watches, No hats, No sunglasses""",
}
Your final task is to **select the perfect set of accessories** to complete the given outfit. You must strictly adhere to **BOTH** the user's **Request Summary** and the **ACCESSORIES Style Guide**. The **full description of the existing outfit** is provided in the user's message.
## RULE HIERARCHY (Priority Order):
1. **ABSOLUTE PROHIBITION (Highest Priority)**:
- **NO WATCHES**.
- **NO HATS**.
- **NO SOCKS**.
- Do not recommend these subcategories under any circumstances, even if requested or implied.
2. **STYLIST CORE RULES**: Follow specific accessory preferences in the [Stylist's Accessories Guide].
3. **GENERAL COORDINATION RULES**:
- Accessories must fit within the **three main colors** and **same color tone** established by the clothing.
- Maintain the **two neutrals and one accent color** balance.
---
## CONTEXT
[User Request]: {{request_summary}}
[Stylist's Accessories Guide]:
{{stylist_guide}}
---
## ACCESSORIES GENERATION RULES
1. **Batch Recommendation**: You must output the **COMPLETE LIST of accessories** in a single response using the 'recommended_accessories' list defined in the schema. Do not recommend items one by one.
2. **Quantity Constraint**: The total number of accessories recommended in the list must not exceed **{{max_len}}** items. Typically, 1 to {{max_len}} distinct items are required to complete a look.
3. **Harmony & Guide Compliance**:
- Assess the existing outfit (provided in the user's message) and ensure all accessories complement its style, color palette, and occasion.
- **Strictly follow the [Accessories Style Guide]** regarding material types (e.g., metals like gold/silver), total numbers allowed, and specific layering requirements (e.g., mandated watch or jewelry layering).
4. **Exclusion List**: Subcategories in the following list are strictly excluded from recommendation: ({IGNORE_SUBCATEGORY}).
5. **Description Quality**: The 'description' field for each accessory must be **extremely detailed and precise** for high-accuracy vector search, including: **Color, Material/Detail, and the specific Role in the Outfit.**
Generate the final, complete accessories list now.
"""
all_items_template = f""" all_items_template = f"""
You are a professional fashion stylist Agent, specialized in creating complete, tailored outfits for {{gender}}. Your task is to **generate a Complete, Head-to-Toe Outfit** in a **Single Batch**, strictly **mimicking the style and preference** specified in the Stylist Guide. # ROLE: Professional Fashion Stylist Agent
You are a professional fashion stylist for {{gender}}. Your goal is to generate a Complete, Head-to-Toe Outfit in a Single Batch.
You must create a cohesive look that includes **Clothing, Shoes, Bags, and Accessories**. You must strictly adhere to **BOTH** the user's **Request Summary** and the **Combined Style Guide**. ## 1. INTEGRATION LOGIC (How to Think)
1. **Analyze User Request**: Identify the target occasion, mood, and specific color/item preferences from the [Request Summary].
2. **Apply Stylist Filter**: Use the [Stylist Guide] as the primary aesthetic filter. If the user request and Stylist Guide conflict, the user request takes precedence.
3. **Synthesis with Material**: Incorporate the [Material Hint] into your item descriptions to ensure the outfit is contextually appropriate for the {{occasion}} and better performance in item retrieval.
4. **Final Rule Check**: Validate the outfit against [General Rules] and ensure no items from the [Exclusion List] are included.
## RULE HIERARCHY (Priority Order): ## 2. RULE HIERARCHY
1. **ABSOLUTE PROHIBITION**: Strictly NO hats or watches or socks. 1. **USER REQUEST**: (Highest Priority)
2. **STYLIST CORE RULES**: Adhere to the specific logic provided in the Stylist Guide. 1. **STYLIST CORE RULES**: (Secondary Priority)
3. **GENERAL COORDINATION RULES**: 2. **GENERAL COORDINATION RULES**: (Standard Professional Logic)
- Limit outfit to **three main colors** within the **same color tone**.
- Preferred composition: **Two neutrals and one accent color**.
- **Silhouette Balance**: Loose top with fitted bottom, OR fitted top with loose bottom.
- **Pants Logic**: Strictly NO mid-calf length pants. Cropped pants MUST be paired with loafers or ankle boots.
--- ---
## Request from the User:
## 3. CONTEXT & GUIDANCE
### [User Request Summary]
{{request_summary}} {{request_summary}}
## Core Guidance Document: Combined Style Guide ### [Target Occasion]
{{occasion}}
### [Stylist Guide]
{{stylist_guide}} {{stylist_guide}}
### [Material Hint]
{{material_hint}}
### [General Rules]
{{general_rule}}
--- ---
## GENERATION WORKFLOW & RULES ## 4. CONSTRAINTS & WORKFLOW
1. **Selection Pool (Mandatory)**: You MUST only choose items from the following **[Allowed Subcategories]**. Do not recommend any subcategory outside this list.
**ALLOWED**: {{allowed_subcategories}}
1. **Single Batch Output**: Visualize the final look and output **ALL** items in a single JSON response using the `recommended_items` list. 2. **Exclusion List**: Strictly FORBIDDEN to recommend: {",".join(IGNORE_SUBCATEGORY)}.
2. **Full Body Coverage & Composition (Mandatory)**: 3. **Mandatory Composition**:
* **Clothing**: You MUST ensure **full body coverage**. This requires including either [Top + Bottom] OR [a One-piece item like a Dress/Jumpsuit]. - **Clothing**: Follow the stylist and general rules for clothing selection.
* **Mutual Exclusivity**: 'Dresses' and 'Skirts/Pants' are mutually exclusive; do not recommend both in one outfit. - **Shoes**: Exactly one (1) pair is mandatory.
* **Shoes**: Exactly **one (1) pair** of shoes is MANDATORY for every outfit. - **Bags & Accessories**: These are **CONDITIONAL**.
* **Bags**: Recommend **0 or 1 bag**. - If NO subcategories related to Bags or Accessories appear in the **[ALLOWED]** list, DO NOT recommend them.
* **Accessories**: Recommend a set of accessories (e.g., jewelry, eyewear). - Simply omit these categories from your output if they are not in the allowed pool for the current {{occasion}}.
- Do not invent subcategories that are not explicitly listed in the [ALLOWED] section.
3. **Strict Uniqueness Mandate (No Repeats)**: 4. **Uniqueness**: Each **subcategory** (e.g., 'earrings', 't-shirts') can appear **EXACTLY ONCE**. No repeats.
* Each **subcategory** (e.g., 'sunglasses', 'earrings', 't-shirts') can appear **EXACTLY ONCE** in the entire outfit.
* DO NOT recommend two items from the same subcategory (e.g., do not recommend two different necklaces or two pairs of sunglasses).
4. **Style Adherence**: 5. **Visual Balance**: Explicitly describe the fit (Loose vs. Fitted) to maintain silhouette balance according to General Rules.
- **Proportions**: Explicitly describe the fit (Loose vs. Fitted) to show the required silhouette balance.
- **Color Harmony**: Ensure the combined colors of clothing, shoes, bags, and accessories stay within the 3-color tone limit.
5. **Exclusion List**: 6. Max item number is {{max_len}}.
- The following subcategories are **STRICTLY FORBIDDEN**: ({IGNORE_SUBCATEGORY}).
6. **Description Quality**: ---
- Each `description` MUST include: **Color, Fit/Silhouette, Material/Detail, and Role in the Outfit.**
## OUTPUT FORMAT ## 5. OUTPUT REQUIREMENT
Output a valid JSON object matching the provided API schema. The `recommended_items` array must contain all the items for this outfit. - **Format**: Valid JSON matching the provided API schema (`recommended_items` list).
- **Description Quality**: Each 'description' field must be a precise string for vector search: **subcategory + Color + Fit/Silhouette + Material/Detail.**
- **Reasoning**: In the 'reason' field, explain how the outfit satisfies the User's Request while maintaining the Stylist's DNA.
Generate the complete outfit list now. Generate the complete outfit list now
""" """
@@ -241,14 +182,12 @@ def build_iterative_schema(current_category):
return schema return schema
def build_batch_schema(specified_category: str = ""): def build_batch_schema(specified_category: str = "", subcategory_list: list = []):
assert (specified_category in FASHION_TAXONOMY.keys() or specified_category == "") assert (specified_category in FASHION_TAXONOMY.keys() or specified_category == "all")
if not specified_category: if specified_category == "all":
category_range_desc = "the complete final outfit (including all categories)" category_range_desc = "all categories of the outfit"
subcategory_list = ALL_SUBCATEGORY_LIST
else: else:
category_range_desc = specified_category category_range_desc = f"only *{specified_category}* part of the outfit"
subcategory_list = FASHION_TAXONOMY[specified_category]
schema = { schema = {
"type": "object", "type": "object",
"properties": { "properties": {
@@ -262,7 +201,7 @@ def build_batch_schema(specified_category: str = ""):
"items": { "items": {
"type": "object", "type": "object",
"properties": { "properties": {
"description": {"type": "string", "description": f"The detailed description for this {specified_category} item."}, "description": {"type": "string", "description": f"The detailed description for this recommended item."},
"subcategory": { "subcategory": {
"type": "string", "type": "string",
"description": "The subcategory of the recommended item.", "description": "The subcategory of the recommended item.",

View File

@@ -15,18 +15,22 @@ from app.server.utils.minio_client import minio_client, oss_upload_image
from app.server.utils.request_post import post_request from app.server.utils.request_post import post_request
from app.config import settings from app.config import settings
from app.server.ChatbotAgent.core.prompt import ( from app.server.ChatbotAgent.core.prompt import (
core_outfit_template, GENERAL_RULES,
accessories_template, GENERAL_RULES_DICT,
all_items_template, all_items_template,
build_iterative_schema, build_iterative_schema,
build_batch_schema build_batch_schema
) )
from app.taxonomy import FASHION_TAXONOMY, ALL_SUBCATEGORY_LIST from app.taxonomy import FASHION_TAXONOMY, ALL_SUBCATEGORY_LIST, OCCASION_CATEGORY_MAP, OCCASION_MATERIAL_MAP, SUBCATEGORY_MERGE_MAP
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
class AsyncStylistAgent: class AsyncStylistAgent:
ONE_PIECE_SUBS = {"dresses", "suits", "jumpsuits", "bodysuits", "swimwear", "underwear", "lingerie", "pajamas"}
TOP_SUBS = {"t-shirts", "shirts", "blouses", "polo shirts", "tank tops", "sweaters", "cardigans", "pullovers", "hoodies", "sweatshirts", "vests", "coats", "jackets", "blazers", "bras"}
BOTTOM_SUBS = {"trousers", "pants", "jeans", "joggers", "leggings", "shorts", "skirts", "skorts"}
def __init__(self, local_db: str, gemini_model_name: str, outfit_id: str, stylist_name: str, gender: str, callback_url: str): def __init__(self, local_db: str, gemini_model_name: str, outfit_id: str, stylist_name: str, gender: str, callback_url: str):
# self.outfit_items: List[Dict[str, str]] = [] # self.outfit_items: List[Dict[str, str]] = []
self.outfit_id = outfit_id self.outfit_id = outfit_id
@@ -54,18 +58,54 @@ class AsyncStylistAgent:
self.minio_bucket = "lanecarford" self.minio_bucket = "lanecarford"
self.callback_url = f'{callback_url}/api/style/callback' self.callback_url = f'{callback_url}/api/style/callback'
def _is_outfit_complete(self, occasion: str, first_try: bool = True) -> bool:
"""
判断当前的 self.outfit_items 是否满足该场合的完整性要求
"""
if occasion not in OCCASION_CATEGORY_MAP:
# 兜底逻辑:如果场合没定义,至少要有衣服和鞋子
raise ValueError(f"Provided {occasion} is not defined in OCCASION_CATEGORY_MAP.")
requirements = OCCASION_CATEGORY_MAP[occasion]
current_subs = [item['subcategory'] for item in self.outfit_items]
current_cats = [item['category'] for item in self.outfit_items]
# --- 1. 鞋子检查 ---
# 如果该场合允许穿鞋List不为空则必须至少有一双鞋
if requirements.get("shoes") and "shoes" not in current_cats:
return False
# --- 2. 衣服检查 (最核心) ---
# 检查是否有全身单品 (One-piece)
has_one_piece = any(sub in self.ONE_PIECE_SUBS for sub in current_subs)
if not has_one_piece:
# 如果没有连体衣,必须同时有上装和下装
has_top = any(sub in self.TOP_SUBS for sub in current_subs)
has_bottom = any(sub in self.BOTTOM_SUBS for sub in current_subs)
if not (has_top and has_bottom):
return False
# --- 3. 包包检查 ---
# 如果该场合(如 Evening明确需要包且目前还没找到可以返回 False 继续重试
if requirements.get("bags") and "bags" not in current_cats and first_try:
return False
# --- 4. 配饰检查 ---
if requirements.get("accessories") and "accessories" not in current_cats and first_try:
return False
return True
def _load_style_guide(self, stylist_name: str): def _load_style_guide(self, stylist_name: str):
"""加载 markdown 风格指南内容。""" """加载 markdown 风格指南内容。"""
guide_path = os.path.join(settings.STYLIST_GUIDE_DIR, f"{stylist_name}_en.md") guide_path = os.path.join(settings.STYLIST_GUIDE_DIR, f"{stylist_name}_en.md")
acc_guide_path = os.path.join(settings.STYLIST_GUIDE_DIR, f"{stylist_name}_acc.md")
try: try:
with open(guide_path, 'r', encoding='utf-8') as file: with open(guide_path, 'r', encoding='utf-8') as file:
stylist_guide = file.read() stylist_guide = file.read()
with open(acc_guide_path, 'r', encoding='utf-8') as file: return stylist_guide
accessories_guide = file.read()
return stylist_guide, accessories_guide
except Exception as e: except Exception as e:
raise Exception(f"Failed to load style guide from {guide_path}, {acc_guide_path}: {e}") raise Exception(f"Failed to load style guide from {guide_path}: {e}")
async def _call_gemini(self, user_input: str, user_id: str, file_name: str, output_schema: Dict[str, Any], image_bytes: bytes = None, system_prompt: str = "") -> str: async def _call_gemini(self, user_input: str, user_id: str, file_name: str, output_schema: Dict[str, Any], image_bytes: bytes = None, system_prompt: str = "") -> str:
""" """
@@ -166,55 +206,73 @@ class AsyncStylistAgent:
""" """
# 1. 生成查询嵌入 # 1. 生成查询嵌入
query_embedding = self.local_db.get_clip_embedding(item_description, is_image=False) query_embedding = self.local_db.get_clip_embedding(item_description, is_image=False)
search_subcategories = SUBCATEGORY_MERGE_MAP.get(subcategory, [subcategory])
# 特殊逻辑处理Clutch 和 Crossbody 在同一场合下不应互换(根据你的规则)
# 2. 执行查询,并过滤类别 # 2. 执行查询,并过滤类别
try: try:
results = self.local_db.get_matched_item( results = self.local_db.get_matched_item(
query_embedding, query_embedding,
category, category,
subcategory, search_subcategories,
occasions=occasions, occasions=occasions,
batch_sources=batch_sources, batch_sources=batch_sources,
gender=gender, gender=gender,
n_results=1 n_results=1
) )
except ValueError as e:
print(f"检测到无效参数错误:{e}")
results = []
if not results: if not results:
self.post_operation( print(f"No matching item found for description: {item_description}, category: {category}, subcategory: {subcategory}")
status="failed", return None
message=f"数据库中未找到符合 '{category}' 和描述的单品。",
callback_url=self.callback_url,
img_path="",
)
raise Exception(f"数据库中未找到符合 '{category}' 和描述的单品。")
# 3. 模拟 Agent 审核(实际应用中,你需要将图片发回给 Agent进行审核) # 3. 模拟 Agent 审核(实际应用中,你需要将图片发回给 Agent进行审核)
best_meta = results[0] # 第一个 batch 的第一个 metadata best_meta = results[0] # 第一个 batch 的第一个 metadata
item_id = best_meta['item_id'].replace("_img", "") item_id = best_meta['item_id'].replace("_img", "")
batch_source = best_meta['batch_source'] batch_source = best_meta['batch_source']
return { return {
"item_id": item_id, # 从 metadata 字典中安全获取 "item_id": item_id, # 从 metadata 字典中安全获取
"category": best_meta['category'], "category": best_meta['category'],
'description': best_meta['description'], 'description': best_meta['description'],
"subcategory": best_meta['subcategory'], "subcategory": best_meta['subcategory'],
"brand": best_meta['brand'], "brand": best_meta['brand'],
"gpt_description": item_description, "gpt_description": item_description,
"gpt_subcategory": subcategory, "gpt_subcategory": subcategory,
# 假设 'item_path' 存储在 metadata 中,或从 'item_id' 推导 "image_path": os.path.join(settings.DATA_ROOT, batch_source, 'image_data', f"{item_id}.jpg")
# 这里假设 item_id 就是文件名的一部分 }
"image_path": os.path.join(settings.DATA_ROOT, batch_source, 'image_data', f"{item_id}.jpg") except Exception as e:
} print((f"Internal error in _get_next_item: {str(e)}"))
return None
def _build_system_prompt(self, template: str, request_summary: str = "", stylist_guide: str = "", current_category: str = "clothing", max_len: int = 4) -> str: def _build_system_prompt(self, template: str, general_rule: str, request_summary: str = "", occasion: str = "", stylist_guide: str = "", current_category: str = "clothing", allowed_subcategories: list = [], max_len: int = 4) -> str:
# 1. 材质偏好 (Occasion Material Map)
material_hint = OCCASION_MATERIAL_MAP.get(occasion, "")
# Insert the style_guide content into the template # Insert the style_guide content into the template
if occasion == "Bridal / Wedding":
request_summary += "IMPORTANT: Strictly only recommend colorful or white items (clothing, shoes, and bags)."
elif occasion == "Evening":
request_summary += (" **EVENING STYLE MANDATE:** Prioritize high textural contrast. Avoid flat/matte monochrome or total black looks. Ensure visual depth through layering "
"(e.g., varying lengths or sheer panels). Use statement accessories to break simple silhouettes.")
elif occasion == "Business / workwear":
request_summary += (" **WORKWEAR STYLE MANDATE:** Focus on 'Power Dressing' silhouettes—prioritize sharp, oversized blazers paired with floor-length wide-leg trousers. "
"Use tonal dressing to create a sophisticated, elongated look. Balance masculine tailoring with polished, feminine textures. "
"Select structured, architectural bags and pointed-toe or sleek loafers. MANDATORY: Include a complete gold or silver jewelry set "
"(earrings, necklaces, bracelets, and rings).")
elif occasion == "Outdoor":
request_summary += " **OUTDOOR STYLE MANDATE:** No jeans allowed. Focus on functional yet polished alternatives like chinos, technical fabrics, or tailored shorts."
elif occasion == "Festival / Concert":
request_summary += " **FESTIVAL STYLE MANDATE:** No maxi dresses or maxi skirts. Prioritize shorter hemlines, sets, or trousers to ensure ease of movement."
elif occasion == "Beach / Swim":
request_summary += " **BEACH STYLE MANDATE:** No denim allowed. Focus on breathable, lightweight fabrics like linen, silk, or crochet."
sys_template = template.format( sys_template = template.format(
gender=self.gender, gender=self.gender,
current_category=current_category.upper(), current_category=current_category.upper(),
general_rule=general_rule,
request_summary=request_summary, request_summary=request_summary,
stylist_guide=stylist_guide, stylist_guide=stylist_guide,
occasion=occasion,
material_hint=material_hint,
allowed_subcategories=','.join(allowed_subcategories),
max_len=max_len max_len=max_len
) )
return sys_template.strip() return sys_template.strip()
@@ -265,7 +323,7 @@ class AsyncStylistAgent:
if status in ['failed']: if status in ['failed']:
# 失败直接打印参数 不发送结果 # 失败直接打印参数 不发送结果
response_data['message'] = message response_data['message'] = message
logger.info(f"request data {json.dumps(response_data, ensure_ascii=False, indent=2)}") logger.error(f"request data {json.dumps(response_data, ensure_ascii=False, indent=2)}")
else: else:
response = post_request(url=callback_url, data=json.dumps(response_data)) response = post_request(url=callback_url, data=json.dumps(response_data))
logger.info(f"request data {json.dumps(response_data, ensure_ascii=False, indent=2)} | JAVA callback info -> status:{response.status_code} | message:{response.text}") logger.info(f"request data {json.dumps(response_data, ensure_ascii=False, indent=2)} | JAVA callback info -> status:{response.status_code} | message:{response.text}")
@@ -273,100 +331,6 @@ class AsyncStylistAgent:
else: else:
return {} return {}
async def _execute_iterative_recommendation(
self,
current_category: str,
system_prompt: str,
schema: Dict,
max_len: int,
occasions: List[str],
batch_sources: List[str],
user_id: str,
url: str
):
recommend_timestep = 0
gemini_data = {'action': 'start'}
existing_subcategories = []
while recommend_timestep < max_len and gemini_data.get('action') != 'stop':
recommend_timestep += 1
# 1. 准备用户输入(上下文)
user_input = self._build_user_input(current_category, ", ".join(existing_subcategories))
# 2. 把图片组装起来供api调用
merged_image_path, image_bytes = await self._merge_images(self.outfit_id, user_id, self.stylist_name)
# 3. 调用 Gemini Agent
gemini_response_text = await self._call_gemini(
user_input,
user_id,
self.outfit_id,
schema,
image_bytes,
system_prompt
)
gemini_data = self._parse_gemini_response(gemini_response_text)
if not gemini_data:
self.post_operation(
status="failed",
message="Agent returned invalid response, terminating process.",
callback_url=url,
img_path=merged_image_path,
)
raise Exception("Agent 返回无效响应,终止流程。")
# 处理推荐单品
if gemini_data.get('action') == 'recommend_item':
subcategory = gemini_data.get('subcategory')
description = gemini_data.get('description')
# 4a. 检查类别是否有效 (重要步骤)
if subcategory not in FASHION_TAXONOMY[current_category]:
self.post_operation(
status="continue",
message=f"Invalid subcategory recommended by Agent: {subcategory}. Requesting Agent to re-output.",
callback_url=url,
img_path=merged_image_path,
)
continue
# 4b. 在本地 DB 中查询单品
new_item = self._get_next_item(description, current_category, subcategory, occasions, batch_sources, self.gender)
if not new_item:
self.post_operation(
status="continue",
message=f"No matching item is found. Ask Gemini to re-output.",
callback_url=url,
img_path=merged_image_path,
)
continue
elif new_item['subcategory'] in [x['subcategory'] for x in self.outfit_items]:
self.post_operation(
status="continue",
message=f"{new_item['item_id']}'s subcategory {new_item['subcategory']} duplicated. Ask Gemini to re-output.",
callback_url=url,
img_path=merged_image_path,
)
continue
elif new_item['item_id'] in [x['item_id'] for x in self.outfit_items]:
self.post_operation(
status="continue",
message=f"Item {new_item['item_id']} duplicated. Ask Gemini to re-output.",
callback_url=url,
img_path=merged_image_path,
)
continue
else:
self.outfit_items.append(new_item)
existing_subcategories.append(new_item["subcategory"])
self.post_operation(
status="ok",
message=f"Add new item {new_item['item_id']} in category {new_item['category']} successfully.",
callback_url=url,
img_path=merged_image_path,
)
print(f"Stage {current_category.upper()}, Step {recommend_timestep}: {gemini_data}, found item: {new_item['item_id']}")
async def _execute_batch_recommendation( async def _execute_batch_recommendation(
self, self,
current_category: str, # this can be any category or all current_category: str, # this can be any category or all
@@ -408,99 +372,59 @@ class AsyncStylistAgent:
for idx, rec_item in enumerate(recommended_items): for idx, rec_item in enumerate(recommended_items):
subcategory = rec_item.get('subcategory') subcategory = rec_item.get('subcategory')
description = rec_item.get('description') description = rec_item.get('description')
# 4a. 检查类别是否有效 (重要步骤)
if subcategory not in ALL_SUBCATEGORY_LIST:
continue
# 4b. 在本地 DB 中查询单品
# we need first determine the category if current category is 'all' # we need first determine the category if current category is 'all'
if current_category == "all": if current_category == "all":
for category, subcategories_list in FASHION_TAXONOMY.items(): category = self._identify_category(subcategory)
# 将子类别列表转换为集合 (set) 可以提高查找效率,
# 特别是当列表很长时。
if subcategory in subcategories_list:
break
else: else:
category = current_category category = current_category
new_item = self._get_next_item(description, category, subcategory, occasions, batch_sources, self.gender) allowed_subcategories = self._get_allowed_subcategories(occasions[0], category)
if not new_item or new_item['item_id'] in [x['item_id'] for x in self.outfit_items]: # 4a. 检查类别是否有效 (重要步骤)
if subcategory not in allowed_subcategories:
failed_found_item_count += 1 failed_found_item_count += 1
logger.warning(f"Failed to found Item {idx + 1}: ({subcategory}) {rec_item}, invalid subcategory {subcategory} recommended by Agent.")
continue
# 4b. 如果这个子类别已经被推荐过了,就舍弃
if subcategory in [x['subcategory'] for x in self.outfit_items]:
logger.warning(f"Subcategory {subcategory} already recommended, skipping.")
continue
# 4c. 在本地 DB 中查询单品
new_item = self._get_next_item(description, category, subcategory, occasions, batch_sources, self.gender)
if not new_item:
failed_found_item_count += 1
logger.warning(f"Failed to found Item {idx + 1}: ({subcategory}) {rec_item}, no matching item is found.")
continue
elif new_item['item_id'] in [x['item_id'] for x in self.outfit_items]:
logger.warning(f"Found Item {idx + 1}: ({subcategory}) {rec_item}, found item is duplicated.")
continue continue
else: else:
self.outfit_items.append(new_item) self.outfit_items.append(new_item)
print(f"Item {idx + 1}: ({subcategory}) {rec_item}, found item: {new_item}") logger.info(f"Item {idx + 1}: ({subcategory}) {rec_item}, found item: {new_item}")
# 如果没有找到的item过于多需要重试
if failed_found_item_count / len(recommended_items) > 0.5:
self.post_operation(
status="failed",
message=f"There are {failed_found_item_count} items (total {len(recommended_items)}) are not found in the database",
callback_url=url,
img_path=merged_image_path
)
raise Exception(f"There are {failed_found_item_count} items (total {len(recommended_items)}) are not found in the database")
return reason return reason
def _get_allowed_subcategories(self, occasion: str, category: str) -> List[str]:
"""根据场景和分类获取合法的子类别列表"""
# 如果 occasion 不在配置中,回退到全局分类
occ_config = OCCASION_CATEGORY_MAP.get(occasion, {})
if category == "all":
# 获取该场景下所有分类的合集
all_subs = []
for cat_subs in occ_config.values():
all_subs.extend(cat_subs)
return all_subs if all_subs else ALL_SUBCATEGORY_LIST
# 返回特定分类下的子类
return occ_config.get(category, FASHION_TAXONOMY.get(category, []))
async def run_iterative_styling(self, request_summary, occasions, start_outfit: Optional[List] = None, batch_sources: List = [], user_id="test", callback_url=""): def _identify_category(self, subcategory: str) -> str:
start_time = time.monotonic() """反向查找:通过子类确定它属于哪个大类"""
STAGES = ['clothing', 'shoes', 'bags'] for cat, subs in FASHION_TAXONOMY.items():
# 深拷贝start_outfit 避免实例之间的参数泄漏 确保每个实例都有自己的 start_outfit 副本 if subcategory in subs:
if start_outfit is None: return cat
self.outfit_items = [] return "unknown"
else:
self.outfit_items = deepcopy(start_outfit)
stylist_guide, accessories_guide = self._load_style_guide(self.stylist_name)
url = f'{callback_url}/api/style/callback'
"""主流程控制循环。"""
print(f"--- Starting Agent (Outfit ID: {self.outfit_id}) ---")
for current_category in STAGES:
max_len = 4 if current_category == 'clothing' else 1
system_prompt = self._build_system_prompt(core_outfit_template, request_summary, stylist_guide, current_category, max_len)
await self._execute_iterative_recommendation(
current_category,
system_prompt,
build_iterative_schema(current_category),
max_len,
occasions,
batch_sources,
user_id,
url
)
# 根据stylist要求增加配饰 3-4个配饰
MAX_LEN_ACC = 3
acc_system_prompt = self._build_system_prompt(accessories_template, request_summary, accessories_guide, 'accessories', MAX_LEN_ACC)
reason = await self._execute_batch_recommendation(
'accessories', # can be 'accessories' or 'all'
acc_system_prompt,
build_batch_schema(current_category),
occasions,
batch_sources,
user_id,
url
)
final_image_path, _ = await self._merge_images(self.outfit_id, user_id, self.stylist_name)
# 推荐完成返回
response_data = self.post_operation(
status="stop",
message=reason,
callback_url=url,
img_path=final_image_path,
request_summary=request_summary,
occasions=occasions
)
end_time = time.monotonic()
total_duration = end_time - start_time
if settings.LOCAL == 1:
with open(os.path.join(settings.OUTFIT_OUTPUT_DIR, self.stylist_name, f'{self.outfit_id}.json'), 'w') as f:
json.dump({"request_summary": request_summary, "occasions": occasions, "items": self.outfit_items, "total_duration": total_duration}, f, indent=2)
return response_data, total_duration
async def run_quick_batch_styling(self, request_summary, occasions, start_outfit: Optional[List] = None, batch_sources: List = [], user_id="test", callback_url=""): async def run_quick_batch_styling(self, request_summary, occasions, start_outfit: Optional[List] = None, batch_sources: List = [], user_id="test", callback_url=""):
start_time = time.monotonic() start_time = time.monotonic()
@@ -509,22 +433,52 @@ class AsyncStylistAgent:
self.outfit_items = [] self.outfit_items = []
else: else:
self.outfit_items = deepcopy(start_outfit) self.outfit_items = deepcopy(start_outfit)
stylist_guide, accessories_guide = self._load_style_guide(self.stylist_name) stylist_guide = self._load_style_guide(self.stylist_name)
url = f'{callback_url}/api/style/callback' url = f'{callback_url}/api/style/callback'
print(f"--- Starting Agent (Outfit ID: {self.outfit_id}) ---")
MAX_LEN = 9 MAX_LEN = 9
system_prompt = self._build_system_prompt(all_items_template, request_summary, stylist_guide + accessories_guide, "", MAX_LEN) if not occasions:
reason = await self._execute_batch_recommendation( occasions = ["Casual"]
'all', # can be 'accessories' or 'all' logger.info(f"""--- Starting Agent (Outfit ID: {self.outfit_id}) ---
system_prompt, Occasion: {occasions[0]}. Stylist: {self.stylist_name}. User ID: {user_id}. Request Summary: {request_summary}. Batch sources: {batch_sources}""")
build_batch_schema(),
occasions, general_rules = "\n".join(GENERAL_RULES_DICT.values()) + '\n' + GENERAL_RULES
batch_sources, allowed_subcategories = self._get_allowed_subcategories(occasions[0], "all")
user_id, system_prompt = self._build_system_prompt(
url all_items_template,
general_rules,
request_summary,
occasions[0],
stylist_guide,
"",
allowed_subcategories,
MAX_LEN
) )
max_retries = 2
for attempt in range(max_retries):
logger.info(f"Batch recommendation attempt {attempt + 1}")
reason = await self._execute_batch_recommendation(
'all', # can be 'accessories' or 'all'
system_prompt,
build_batch_schema(specified_category="all", subcategory_list=allowed_subcategories),
occasions,
batch_sources,
user_id,
url
)
if self._is_outfit_complete(occasions[0], first_try=(attempt==0)):
logger.info(f"Successfully assembled a complete outfit for {occasions[0]} after {attempt + 1} attempts. Reason: {reason}")
break
else:
self.post_operation(
status="failed",
message=f"Failed to assemble a complete outfit after {max_retries} attempts for {occasions[0]}. Current items: {self.outfit_items}. Subcategories required by this occasion is {allowed_subcategories}",
callback_url=url,
img_path=""
)
raise Exception(f"Failed to assemble a complete outfit after {max_retries} attempts for {occasions[0]}. Current items: {self.outfit_items}. Subcategories required by this occasion is {allowed_subcategories}")
# 推荐即将完成 回调通知前端 # 推荐即将完成 回调通知前端
self.post_operation( self.post_operation(
status="almost_done", status="almost_done",

View File

@@ -46,7 +46,9 @@ class VectorDatabase():
return features.cpu().numpy().flatten().tolist() return features.cpu().numpy().flatten().tolist()
def get_matched_item(self, embedding: List[float], category: str, subcategory: str, occasions: List[str] = [], batch_sources: List[str] = [], gender: str = 'female', n_results: int = 1) -> List[Dict[str, Any]]: def get_matched_item(self, embedding: List[float], category: str, search_subcategories: List[str], occasions: List[str] = [], batch_sources: List[str] = [], gender: str = 'female', n_results: int = 1) -> List[Dict[str, Any]]:
if 'ties' in search_subcategories or 'cufflinks' in search_subcategories:
gender = "male"
if category not in CATEGORY_LIST: if category not in CATEGORY_LIST:
raise ValueError(f"Recommended {category} is not valid.") raise ValueError(f"Recommended {category} is not valid.")
@@ -57,7 +59,7 @@ class VectorDatabase():
{"gender": gender}, {"gender": gender},
{"gender": "unisex"}, {"gender": "unisex"},
]}, ]},
{"subcategory": {"$nin": IGNORE_SUBCATEGORY}} {"subcategory": {"$in": search_subcategories}}
] ]
# 加了一条限制但是部署到生产的时候把他设定为False # 加了一条限制但是部署到生产的时候把他设定为False
@@ -65,16 +67,12 @@ class VectorDatabase():
if brand_strication: if brand_strication:
and_conditions.append({"brand": {"$in": BRAND_WHITELIST}}) and_conditions.append({"brand": {"$in": BRAND_WHITELIST}})
if batch_sources and len(batch_sources) > 0: # 加一条occasion限制婚礼不能穿黑色
if len(batch_sources) == 1: if any(o in ["Bridal / Wedding", "Beach / Swim"] for o in occasions):
and_conditions.append({"batch_source": batch_sources[0]}) and_conditions.append({"color": {"$nin": ["BLACK", "DARK GREY", "DARK BLUE", "NAVY"]}})
else:
source_conditions = []
for source in batch_sources:
source_conditions.append({"batch_source": source})
# 将 Batch Source 的 OR 子句添加到主 AND 条件中 if batch_sources and len(batch_sources) > 0:
and_conditions.append({"$or": source_conditions}) and_conditions.append({"batch_source": {"$in": batch_sources}})
results = self.collection.query( results = self.collection.query(
query_embeddings=[embedding], query_embeddings=[embedding],
@@ -86,16 +84,17 @@ class VectorDatabase():
return [] return []
metadatas = results['metadatas'][0] # List[Dict[str, Any]] metadatas = results['metadatas'][0] # List[Dict[str, Any]]
candidate_pool = [] item_rank_list = []
all_scores = [] all_scores = []
for idx, metadata in enumerate(metadatas): for idx, metadata in enumerate(metadatas):
dist_img = results['distances'][0][idx] dist_img = results['distances'][0][idx]
score_vec = 1 - dist_img # cosine similarity range: [-1, 1] score_vec = 1 - dist_img # cosine similarity range: [-1, 1]
score_subcategory = 0.0 score_subcategory = 1.0
if subcategory == metadata['subcategory']: # if subcategory == metadata['subcategory']:
score_subcategory = 1 # score_subcategory = 1
score_occ = 0.0 score_occ = 0.0
occasions = occasions[0:1] # 目前只考虑第一个场合
if occasions: if occasions:
count = 0 count = 0
for occ in occasions: for occ in occasions:
@@ -114,28 +113,26 @@ class VectorDatabase():
final_score = 0.5 * score_vec + 0.1 * score_occ + 0.5 * score_subcategory final_score = 0.5 * score_vec + 0.1 * score_occ + 0.5 * score_subcategory
all_scores.append(final_score) all_scores.append(final_score)
if final_score > 0: item_rank_list.append({
candidate_pool.append({ "score": final_score,
"score": final_score, "metadata": metadata
"metadata": metadata })
})
item_rank_list.sort(key=lambda x: x['score'], reverse=True)
candidate_pool = [item for item in item_rank_list if item['score'] > 0.0]
if not candidate_pool: if not candidate_pool:
print(f"All scores are negative: Ignore") print(f"Warning: No positive scores found for {search_subcategories}. Falling back to top matches.")
return [] return [item['metadata'] for item in item_rank_list[:n_results]]
# 采取topk截断 # 采取topk截断
candidate_pool.sort(key=lambda x: x['score'], reverse=True)
current_k = min(10, len(candidate_pool)) current_k = min(10, len(candidate_pool))
top_candidates = candidate_pool[:current_k] top_candidates = candidate_pool[:current_k]
top_scores = np.array([x['score'] for x in top_candidates]) top_scores = np.array([x['score'] for x in top_candidates])
#降低温度,使得选择稳定 #降低温度,使得选择稳定
temperature = 0.2 temperature = 0.2
scaled_scores = top_scores / temperature exp_scores = np.exp((top_scores - np.max(top_scores)) / temperature)
# Softmax: 将分数转换为概率
exp_scores = np.exp(scaled_scores - np.max(scaled_scores))
probabilities = exp_scores / np.sum(exp_scores) probabilities = exp_scores / np.sum(exp_scores)
# 采样 (或直接取 Top 1) # 采样 (或直接取 Top 1)

View File

@@ -4,6 +4,8 @@ import litserve as ls
import requests import requests
from pydantic import BaseModel from pydantic import BaseModel
from app.config import settings
class PredictRequest(BaseModel): class PredictRequest(BaseModel):
input_image_list: list[str] # 待换脸图片 input_image_list: list[str] # 待换脸图片
@@ -17,7 +19,7 @@ class ReFace(ls.LitAPI):
def predict(self, request): def predict(self, request):
# 服务的 URL # 服务的 URL
url = "http://10.1.1.240:10071/predict" url = f"http://{settings.RE_FACE_MODEL_URL}/predict"
# 请求头 # 请求头
headers = { headers = {

View File

@@ -91,7 +91,8 @@ def merge_images_to_square(outfit_items: List[Dict[str, str]], max_len=9, add_te
raise ValueError("No valid images were loaded.") raise ValueError("No valid images were loaded.")
if num_images > max_len: if num_images > max_len:
raise ValueError(f"Valid item number {num_images} exceed max limit {max_len}") valid_images = valid_images[:max_len]
print(f"Valid item number {num_images} exceed max limit {max_len}, only first {max_len} items will be processed.")
# Get the correct list of target areas based on the number of valid images # Get the correct list of target areas based on the number of valid images
target_areas = quadrants.get(num_images, []) target_areas = quadrants.get(num_images, [])
@@ -103,6 +104,7 @@ def merge_images_to_square(outfit_items: List[Dict[str, str]], max_len=9, add_te
for i, (img, item) in enumerate(zip(valid_images, outfit_items)): for i, (img, item) in enumerate(zip(valid_images, outfit_items)):
item_id = item['item_id'] item_id = item['item_id']
category = item['category'] category = item['category']
subcategory = item['subcategory']
if i >= len(target_areas): if i >= len(target_areas):
# This should not happen if num_images <= 4 # This should not happen if num_images <= 4
break break
@@ -155,7 +157,7 @@ def merge_images_to_square(outfit_items: List[Dict[str, str]], max_len=9, add_te
# --- 文本居中与定位 --- # --- 文本居中与定位 ---
full_text = f"ID: {item_id}, Category: {category}" full_text = f"ID: {item_id}, Subcategory: {subcategory}"
if add_text: if add_text:
try: try:
# 推荐使用:计算文本的实际尺寸 (width, height) # 推荐使用:计算文本的实际尺寸 (width, height)

View File

@@ -15,7 +15,6 @@ FASHION_TAXONOMY = {
'blouses', # 女式衬衫 'blouses', # 女式衬衫
'polo shirts', # Polo衫 'polo shirts', # Polo衫
'tank tops', # 背心/坎肩 'tank tops', # 背心/坎肩
'camisoles', # 吊带背心
# --- Knits/Sweaters --- # --- Knits/Sweaters ---
'sweaters', # 毛衣 (泛指) 'sweaters', # 毛衣 (泛指)
'cardigans', # 开衫 'cardigans', # 开衫
@@ -91,7 +90,7 @@ FASHION_TAXONOMY = {
CATEGORY_LIST = list(FASHION_TAXONOMY.keys()) CATEGORY_LIST = list(FASHION_TAXONOMY.keys())
ALL_SUBCATEGORY_LIST = sum(FASHION_TAXONOMY.values(), []) ALL_SUBCATEGORY_LIST = sum(FASHION_TAXONOMY.values(), [])
IGNORE_SUBCATEGORY = ['socks', 'watches', 'hats'] IGNORE_SUBCATEGORY = ['socks', 'watches', 'hats', 'eyewear']
BRAND_WHITELIST = [ BRAND_WHITELIST = [
"ALAÏA", "ALAÏA",
@@ -130,4 +129,140 @@ BRAND_WHITELIST = [
"THOM BROWNE", "THOM BROWNE",
"THE FRANKIE SHOP", "THE FRANKIE SHOP",
"TOTEME", "TOTEME",
] ]
OCCASION_CATEGORY_MAP = {
"Casual": {
"clothing": ["trousers", "pants", "jeans", "t-shirts", "tank tops", "polo shirts", "hoodies", "leggings", "shorts", "skirts"],
"shoes": ["sneakers", "flats", "boots"],
"bags": ["shoulder bags", "crossbody"],
"accessories": ["earrings", "necklaces", "bracelets", "rings"]
},
"Formal": {
"clothing": ["suits", "trousers", "shirts", "blazers", "skirts", "dresses", "coats"],
"shoes": ["formal shoes"],
"bags": [],
"accessories": ["ties", "earrings", "necklaces", "bracelets", "rings"]
},
"Activewear": {
"clothing": ["leggings", "tank tops", "pants", "joggers", "hoodies", "jackets"],
"shoes": ["sneakers"],
"bags": ["travel bags"],
"accessories": []
},
"Resort": {
"clothing": ["dresses", "shorts", "tank tops", "swimwear"],
"shoes": ["sandals"],
"bags": ["tote bags"],
"accessories": ["earrings", "necklaces", "bracelets", "rings", "scarves"]
},
"Evening": {
"clothing": ["dresses", "blazers", "coats"],
"shoes": ["heels"],
"bags": ["clutch bags"],
"accessories": ["earrings", "necklaces", "bracelets", "rings"]
},
"Outdoor": {
"clothing": ["jackets", "sweaters", "pants", "joggers", "leggings", "shorts"],
"shoes": ["boots"],
"bags": ["backpacks", "travel bags"],
"accessories": []
},
"Business / workwear": {
"clothing": ["trousers", "blouses", "blazers", "skirts"],
"shoes": ["formal shoes", "heels", "flats"],
"bags": ["tote bags", "shoulder bags"],
"accessories": []
},
"Cocktail / Semi-Formal": {
"clothing": ["dresses", "jumpsuits", "skirts", "blouses", "blazers", "coats"],
"shoes": ["heels"],
"bags": ["clutch bags", "shoulder bags"],
"accessories": ["earrings", "necklaces", "bracelets", "rings", "scarves"]
},
"Black Tie / White Tie": {
"clothing": ["dresses", "suits"],
"shoes": ["formal shoes"],
"bags": ["clutch bags"],
"accessories": ["earrings", "necklaces", "bracelets", "rings"]
},
"Bridal / Wedding": {
"clothing": ["dresses", "suits"],
"shoes": ["heels", "formal shoes"],
"bags": ["clutch bags"],
"accessories": ["earrings", "necklaces", "bracelets", "rings"]
},
"Festival / Concert": {
"clothing": ["jackets", "shorts", "tank tops", "skirts"],
"shoes": ["boots"],
"bags": ["crossbody", "shoulder bags"],
"accessories": ["earrings", "necklaces", "bracelets", "rings"]
},
"Party / Clubbing": {
"clothing": ["jackets", "dresses", "skirts", "bodysuits"],
"shoes": ["heels", "boots"],
"bags": ["clutch bags"],
"accessories": []
},
"Travel / Transit": {
"clothing": ["joggers", "sweatshirts", "t-shirts", "hoodies", "sweaters", "jackets"],
"shoes": ["sneakers"],
"bags": ["backpacks", "travel bags", "tote bags"],
"accessories": []
},
"Athleisure": {
"clothing": ["leggings", "hoodies", "tank tops", "joggers", "jackets"],
"shoes": ["sneakers"],
"bags": ["travel bags", "tote bags"],
"accessories": ["earrings", "bracelets"]
},
"Beach / Swim": {
"clothing": ["swimwear", "shorts", "dresses"],
"shoes": ["sandals"],
"bags": ["tote bags"],
"accessories": ["earrings", "necklaces", "bracelets", "rings"]
},
"Ski / Snow / Mountain": {
"clothing": ["jackets", "coats", "sweaters", "hoodies", "pants"],
"shoes": ["boots"],
"bags": [],
"accessories": ["gloves"]
},
"Garden Party / Daytime Event": {
"clothing": ["dresses", "skirts", "blouses", "cardigans"],
"shoes": ["sandals"],
"bags": ["shoulder bags", "crossbody"],
"accessories": ["earrings", "necklaces", "bracelets", "rings"]
}
}
OCCASION_MATERIAL_MAP = {
"Casual": "Cotton, denim, jersey, fleece, relaxed fits, distressed textures.",
"Formal": "Wool, silk, crisp cotton, structured tailoring, cufflinks, leather soles.",
"Activewear": "Spandex, moisture-wicking synthetics, mesh, breathable fabrics, compression.",
"Resort": "Linen, crochet, chiffon, straw/raffia, tropical prints, breezy silhouettes.",
"Evening": "Silk, satin, velvet, sequins, lace, sheer panels, metallic finishes.",
"Outdoor": "Gore-Tex, fleece, down, wool, waterproof leather, corduroy, flannel.",
"Business / workwear": "Gabardine, crepe, silk blends, modest cuts, structured leather bags.",
"Cocktail / Semi-Formal": "Satin, crepe, lace details, ruffles, asymmetric hems, polished hardware.",
"Black Tie / White Tie": "Tulle, silk taffeta, fine wool, crystals, pearls, opera gloves.",
"Bridal / Wedding": "Chiffon, lace, silk, floral prints (for guests), pastel tones.",
"Festival / Concert": "Denim, fringe, leather, crochet, sequins, bold prints, band tees.",
"Party / Clubbing": "Sequins, leather/pleather, mesh, cut-outs, bodycon fits, latex.",
"Travel / Transit": "Cotton jersey, cashmere blends, stretch denim, soft knits, layers.",
"Athleisure": "Scuba fabric, tech fleece, rib-knit, clean lines, logo details.",
"Beach / Swim": "Lycra, terry cloth, linen, straw, quick-dry fabrics, sheer voile.",
"Ski / Snow / Mountain": "Down feathers, wool, thermal tech, faux fur, waterproof shells.",
"Garden Party / Daytime Event": "Floral prints, linen, eyelet lace, cotton poplin, gingham, straw accessories."
}
SUBCATEGORY_MERGE_MAP = {
"clutch bags": ["clutch bags", "shoulder bags"],
"shoulder bags": ["shoulder bags", "clutch bags"],
"crossbody": ["crossbody", "shoulder bags"],
"luggage": ["luggage", "backpacks", "travel bags"],
"jumpsuits": ["jumpsuits", "dresses"],
"bodysuits": ["bodysuits", "dresses"],
"suits": ["suits", "dresses"],
"pullovers": ["pullovers", "sweaters"],
}

View File

@@ -1,5 +1,6 @@
services: services:
lc_agent_server: lc_agent_server:
container_name: LC_Agent_Server
build: build:
context: . context: .
dockerfile: Dockerfile dockerfile: Dockerfile
@@ -9,12 +10,12 @@ services:
DEBUG: 0 DEBUG: 0
volumes: volumes:
- ./app:/app/app - ./app:/app/app
- ./.prod_env:/app/.env - ./.env:/app/.env
- ./data:/data - ./data:/data
- ./google_application_credentials.json:/google_application_credentials.json - ./google_application_credentials.json:/google_application_credentials.json
- /etc/localtime:/etc/localtime:ro - /etc/localtime:/etc/localtime:ro
ports: ports:
- "10070:8000" - "${SERVE_PORT}:8000"
deploy: deploy:
resources: resources:
reservations: reservations:
@@ -22,4 +23,10 @@ services:
# 告诉 Docker 使用所有可用的 NVIDIA GPU # 告诉 Docker 使用所有可用的 NVIDIA GPU
- driver: nvidia - driver: nvidia
device_ids: [ '0' ] device_ids: [ '0' ]
capabilities: [ gpu ] capabilities: [ gpu ]
networks:
- lc_app_net
networks:
lc_app_net:
external: true
name: lc_app_net

BIN
docs/2025_q4 stat.xlsx Normal file

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@@ -1,17 +0,0 @@
# Crystal's Accessory Guide: Pure Balance
This guide strictly outlines accessory selection, emphasizing Gold Tones and pure, solid colors to stabilize the outfit's primary focus on bold pattern clashing.
## I. Color, Pattern, and Material Constraints
Color & Tone: All jewelry must be in Gold Tones. Vector-style accessories are prohibited.
Accessory Pattern: Bags and shoes must be Solid Color only. Patterned or printed bags and shoes are strictly prohibited.
## II. Mandatory & Stacking Requirements
The use of accessories is essential to complete the look, focusing on stacking and specific shapes:
Mandatory Jewelry: A Necklace is mandatory (minimum one piece). A Watch must be included as part of the wrist stack.
Earrings: Must be Hoop Earrings.
Stacking: Encourage stacking of Bracelets and Rings alongside the mandatory watch.

View File

@@ -36,4 +36,19 @@ This stylist's style prioritizes visual impact through **clashing prints** rathe
4. **Color Base**: No strict color restrictions on garments, but shoes must be **pure, solid colors**. 4. **Color Base**: No strict color restrictions on garments, but shoes must be **pure, solid colors**.
5. **Shoe Principle**: Shoes should provide height (low heel, platform, boots). 5. **Shoe Principle**: Shoes should provide height (low heel, platform, boots).
6. **Overall Balance**: If clothing patterns are complex, shoes must be **simple and pure** to ground the look. Style leans toward **mixed-casual and energetic**, avoiding blandness. 6. **Overall Balance**: If clothing patterns are complex, shoes must be **simple and pure** to ground the look. Style leans toward **mixed-casual and energetic**, avoiding blandness.
8. **Scene Adaptability**: Add **cargo pants/low heels** for casual settings; **yoga sets** for sportier looks; use **denim** to balance out heavy prints. 8. **Scene Adaptability**: Add **cargo pants/low heels** for casual settings; **yoga sets** for sportier looks; use **denim** to balance out heavy prints.
---
## Accessory Guide: Pure Balance
This section strictly outlines accessory selection, emphasizing Gold Tones and pure, solid colors to stabilize the outfit's primary focus on bold pattern clashing.
### I. Color, Pattern, and Material Constraints
Color & Tone: All jewelry must be in Gold Tones. Vector-style accessories are prohibited.
Accessory Pattern: Bags and shoes must be Solid Color only. Patterned or printed bags and shoes are strictly prohibited.
### II. Mandatory & Stacking Requirements
The use of accessories is essential to complete the look, focusing on stacking and specific shapes:
Mandatory Jewelry: A Necklace is mandatory (minimum one piece). A Watch must be included as part of the wrist stack.
Earrings: Must be Hoop Earrings.
Stacking: Encourage stacking of Bracelets and Rings alongside the mandatory watch.

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# Accessory Style Guide
This guide strictly outlines accessory selection, emphasizing a flexible approach to metal tones and highlighting the aesthetic of long-worn items.
# I. Color and Material Constraints
Metal Tones: Both Gold and Silver metals are preferred and should be mixed and matched together.
Aesthetic Preference: Items that show wear, such as Silver items that have changed color over time, are acceptable as they present a unique personal preference.
# II. Mandatory & Stacking Requirements
Mandatory Items: No specific jewelry piece is listed as mandatory, but the style encourages mixing both gold and silver jewelry.

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@@ -17,4 +17,14 @@ Bags: Functional bags that can hold "everything" are preferred over mini bags. A
Color Mixing: All color tones are acceptable for mixing together, including highly varied tones (e.g., rainbow colors), as long as they create a mutual harmony. Color Mixing: All color tones are acceptable for mixing together, including highly varied tones (e.g., rainbow colors), as long as they create a mutual harmony.
## II. Styling Pattern: Functional and Harmonious ## II. Styling Pattern: Functional and Harmonious
This stylist prioritizes practical, comfortable items (functional bag, sneakers) while embracing complex color and print compositions that lean on Black as a foundational element. The style aims for a unique, harmonious look achieved through flexible mixing. This stylist prioritizes practical, comfortable items (functional bag, sneakers) while embracing complex color and print compositions that lean on Black as a foundational element. The style aims for a unique, harmonious look achieved through flexible mixing.
## Accessory Style Guide
This section strictly outlines accessory selection, emphasizing a flexible approach to metal tones and highlighting the aesthetic of long-worn items.
### I. Color and Material Constraints
Metal Tones: Both Gold and Silver metals are preferred and should be mixed and matched together.
Aesthetic Preference: Items that show wear, such as Silver items that have changed color over time, are acceptable as they present a unique personal preference.
### II. Mandatory & Stacking Requirements
Mandatory Items: No specific jewelry piece is listed as mandatory, but the style encourages mixing both gold and silver jewelry.

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Stylist Accessories Guide
I. Gold Jewelry
Preference: Necklace, Bracelet, and Earrings must all be present and layered.
Prohibition: Avoid Large/Bulky Earrings or Vector-style accessories.
II. Watch
Preference: Mandatory item.
Prohibition: N/A.
III. Accent Colors
Preference: Added via accessories (e.g., scarves); Max 2 accent colors in total.
Prohibition: Avoid Bright/Vivid colors dominating the outfit.

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@@ -34,4 +34,19 @@ This stylist's outfits emphasize **comfort** and **layering** (creating depth).
3. **Fit Requirements**: All items should lean toward a **loose/oversize** fit to prioritize comfort; tailoring must be **clean and sharp**. 3. **Fit Requirements**: All items should lean toward a **loose/oversize** fit to prioritize comfort; tailoring must be **clean and sharp**.
4. **Pattern Restriction**: Only **plaid/checkered or stripes** are acceptable as subtle accents; **strictly no florals**, unless an extremely minimal exception is made. 4. **Pattern Restriction**: Only **plaid/checkered or stripes** are acceptable as subtle accents; **strictly no florals**, unless an extremely minimal exception is made.
5. **Shoe/Bag Coordination**: Footwear must be **flat and casual** (white sneakers are preferred). 5. **Shoe/Bag Coordination**: Footwear must be **flat and casual** (white sneakers are preferred).
6. **Overall Balance**: When the upper body is complex (layered), the lower body should remain **simple**; the overall style is **neutral and polished**, avoiding highly feminine heels or boots. 6. **Overall Balance**: When the upper body is complex (layered), the lower body should remain **simple**; the overall style is **neutral and polished**, avoiding highly feminine heels or boots.
---
## Stylist Accessories Guide
### I. Gold Jewelry
Preference: Necklace, Bracelet, and Earrings must all be present and layered.
Prohibition: Avoid Large/Bulky Earrings or Vector-style accessories.
### II. Watch
Preference: Mandatory item.
Prohibition: N/A.
### III. Accent Colors
Preference: Added via accessories (e.g., scarves); Max 2 accent colors in total.
Prohibition: Avoid Bright/Vivid colors dominating the outfit.

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# Accessory Style Guide
This guide outlines accessory selection based on the desired overall aesthetic, emphasizing a balanced approach to metal tones.
# I. Metal Tone and Aesthetic Constraints
Jewelry Tone: Prefers Gold for a vintage and nostalgic feel.
Jewelry Tone: Prefers Silver for grungier looks.
Wear Preference: Wears both Gold and Silver, depending on the outfit's desired aesthetic.

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# Outfit Style Guide # Outfit Style Guide
This guide summarizes the preferred styling logic, colors, patterns, and structure for Vera's outfits, emphasizing harmony in color mixing and the use of statement bags. This guide summarizes the preferred styling logic, colors, patterns, and structure for Vera's outfits, emphasizing harmony in color mixing and the use of statement bags.
# I. Core Preferences and Prohibitions ## I. Core Preferences and Prohibitions
Primary Colors: Most often wears Khakis, Black, Creams, and sometimes Burgundies. Primary Colors: Most often wears Khakis, Black, Creams, and sometimes Burgundies.
Dominant Colors: Maximum of two dominant colors per outfit, handled with care. Dominant Colors: Maximum of two dominant colors per outfit, handled with care.
@@ -20,5 +20,16 @@ Bags: Prefers Bigger bags and bags that make a statement. Specific examples incl
Prohibited Bags: Not a fan of crossbody or micro mini bags. Prohibited Bags: Not a fan of crossbody or micro mini bags.
# II. Styling Pattern: Harmonious Statement ## II. Styling Pattern: Harmonious Statement
This stylist prioritizes a core color palette of neutrals and deep tones (Khakis, Black, Creams, Burgundies) and uses print mixing (e.g., different sized polka dots or florals) only when colors and shapes are harmonized. The overall look is anchored by comfortable shoes (loafers) and a large, functional, statement bag. This stylist prioritizes a core color palette of neutrals and deep tones (Khakis, Black, Creams, Burgundies) and uses print mixing (e.g., different sized polka dots or florals) only when colors and shapes are harmonized. The overall look is anchored by comfortable shoes (loafers) and a large, functional, statement bag.
## Accessory Style Guide
This section outlines accessory selection based on the desired overall aesthetic, emphasizing a balanced approach to metal tones.
### I. Metal Tone and Aesthetic Constraints
Jewelry Tone: Prefers Gold for a vintage and nostalgic feel.
Jewelry Tone: Prefers Silver for grungier looks.
Wear Preference: Wears both Gold and Silver, depending on the outfit's desired aesthetic.