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Browse files- prompt_gen.py +39 -39
- sugg_gene.py +34 -34
prompt_gen.py
CHANGED
@@ -1,39 +1,39 @@
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import pandas as pd
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import os
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from openai import OpenAI
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nv_prompt_file = pd.read_excel('汉服-女词库.xlsx')
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na_prompt_file = pd.read_excel('汉服-男词库.xlsx')
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nv_prompt = nv_prompt_file.to_string(index=False)
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na_prompt = na_prompt_file.to_string(index=False)
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os.environ["OPENAI_API_KEY"] = "sk-
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os.environ["OPENAI_BASE_URL"] = "http://15.204.101.64:4000/v1"
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def prompt_gen(advise, gender):
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prompt = nv_prompt
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trigger = "a Hanfu"
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if gender == "男":
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prompt = na_prompt
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trigger = "A Hanfu"
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elif gender == "女":
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prompt = nv_prompt
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trigger = "a Hanfu"
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client = OpenAI()
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completion = client.chat.completions.create(
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model="gpt-4o",
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messages=[
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{"role": "system",
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"content": "You are a helpful assistant.",},
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{"role": "user",
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"content": advise + "根据上述建议,从以下prompt库中的触发词、种类、上衣、裙子、领子、袖子、袖口、腰饰、裙子详述中每个挑选一个词,分点描述,触发"
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"词固定选择为" + trigger + ",然后在最下面列出所有Prompt,以‘Begin’为开头后换行, 输出所有英文描述,用逗"
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"号间隔,再加上‘, white background’, 再然后换行后以'End'结尾。prompt库如下:" + prompt,
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}
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]
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)
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print(completion.choices[0].message.content)
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return completion.choices[0].message.content
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import pandas as pd
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import os
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from openai import OpenAI
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nv_prompt_file = pd.read_excel('汉服-女词库.xlsx')
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na_prompt_file = pd.read_excel('汉服-男词库.xlsx')
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nv_prompt = nv_prompt_file.to_string(index=False)
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na_prompt = na_prompt_file.to_string(index=False)
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os.environ["OPENAI_API_KEY"] = "sk-dmnUpbXYsserAa5r76B321546d464aFbBf515f94F4229294"
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os.environ["OPENAI_BASE_URL"] = "http://15.204.101.64:4000/v1"
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def prompt_gen(advise, gender):
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prompt = nv_prompt
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trigger = "a Hanfu"
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if gender == "男":
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prompt = na_prompt
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trigger = "A Hanfu"
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elif gender == "女":
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prompt = nv_prompt
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trigger = "a Hanfu"
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client = OpenAI()
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completion = client.chat.completions.create(
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model="gpt-4o",
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messages=[
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{"role": "system",
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"content": "You are a helpful assistant.",},
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{"role": "user",
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"content": advise + "根据上述建议,从以下prompt库中的触发词、种类、上衣、裙子、领子、袖子、袖口、腰饰、裙子详述中每个挑选一个词,分点描述,触发"
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"词固定选择为" + trigger + ",然后在最下面列出所有Prompt,以‘Begin’为开头后换行, 输出所有英文描述,用逗"
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"号间隔,再加上‘, white background’, 再然后换行后以'End'结尾。prompt库如下:" + prompt,
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}
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]
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)
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print(completion.choices[0].message.content)
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return completion.choices[0].message.content
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sugg_gene.py
CHANGED
@@ -1,34 +1,34 @@
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from suggestion import generate_outfit_advice
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from clothGen import pro_gen
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import os
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from openai import OpenAI
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os.environ["OPENAI_API_KEY"] = "sk-
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os.environ["OPENAI_BASE_URL"] = "http://15.204.101.64:4000/v1"
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def suggest_gene(user_name, height, weight, waist, chest, hip, shoulder_width, leg_length, arm_length, gender,
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body_type, skin_color, style_preference, lifestyle_requirements, special_requirements,
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feedback, user_pic):
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analyse = generate_outfit_advice(user_name, height, weight, waist, chest, hip, shoulder_width, leg_length,
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arm_length, gender, body_type, skin_color, style_preference,
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lifestyle_requirements, special_requirements, feedback, user_pic)
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prompts = ""
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for i in range(1, 4):
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prompts += pro_gen(analyse, gender, i)
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client = OpenAI()
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completion = client.chat.completions.create(
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model="gpt-4o",
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messages=[
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{"role": "system",
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"content": "You are a helpful assistant.", },
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{"role": "user",
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"content": "你是一位专业的民族服饰搭配大师,你需要充分了解中华民族的所有民族服饰的相关知识,包括不同民族服饰适合什么样的人群等。"
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"以下是用户分析与三套服饰描述,请据此给出穿搭建议,要求以三段提示词为主要建议参考" + analyse + prompts,
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}
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]
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)
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print(completion.choices[0].message.content)
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return completion.choices[0].message.content
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from suggestion import generate_outfit_advice
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from clothGen import pro_gen
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import os
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from openai import OpenAI
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os.environ["OPENAI_API_KEY"] = "sk-dmnUpbXYsserAa5r76B321546d464aFbBf515f94F4229294"
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os.environ["OPENAI_BASE_URL"] = "http://15.204.101.64:4000/v1"
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def suggest_gene(user_name, height, weight, waist, chest, hip, shoulder_width, leg_length, arm_length, gender,
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body_type, skin_color, style_preference, lifestyle_requirements, special_requirements,
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feedback, user_pic):
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analyse = generate_outfit_advice(user_name, height, weight, waist, chest, hip, shoulder_width, leg_length,
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arm_length, gender, body_type, skin_color, style_preference,
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lifestyle_requirements, special_requirements, feedback, user_pic)
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prompts = ""
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for i in range(1, 4):
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prompts += pro_gen(analyse, gender, i)
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client = OpenAI()
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completion = client.chat.completions.create(
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model="gpt-4o",
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messages=[
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{"role": "system",
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"content": "You are a helpful assistant.", },
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{"role": "user",
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"content": "你是一位专业的民族服饰搭配大师,你需要充分了解中华民族的所有民族服饰的相关知识,包括不同民族服饰适合什么样的人群等。"
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"以下是用户分析与三套服饰描述,请据此给出穿搭建议,要求以三段提示词为主要建议参考" + analyse + prompts,
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}
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]
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)
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print(completion.choices[0].message.content)
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return completion.choices[0].message.content
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