feat（新功能）: 项目信息提取/生成接口

fix（修复bug）:
docs（文档变更）:
refactor（重构）:
test(增加测试):

app/api/api_extraction_project_info.py

@@ -0,0 +1,33 @@
+import logging
+
+from fastapi import APIRouter, HTTPException
+
+from app.schemas.project_info_extraction import ProjectInfoExtractionModel
+from app.schemas.response_template import ResponseModel
+from app.service.project_info_extraction.service_generate_brand_info import ProjectInfoExtraction
+
+router = APIRouter()
+logger = logging.getLogger()
+
+
+@router.post("/extraction_project_info")
+def extraction_project_info(request_data: ProjectInfoExtractionModel):
+    """
+        通过prompt 提取project_name,role ,gender ,style。
+        创建一个具有以下参数的请求体:
+        - **prompt**:
+
+        示例参数：
+        {
+          "prompt": "海边派对主题的系列设计"
+        }
+    """
+    try:
+        logger.info(f"extraction_project_info request item is : @@@@@@:{request_data}")
+        service = ProjectInfoExtraction(request_data)
+        data = service.get_result()
+        logger.info(f"extraction_project_info response @@@@@@:{data}")
+    except Exception as e:
+        logger.warning(f"extraction_project_info Run Exception @@@@@@:{e}")
+        raise HTTPException(status_code=404, detail=str(e))
+    return ResponseModel(data=data)

app/api/api_route.py

@@ -5,16 +5,16 @@ from app.api import api_attribute_retrieve, api_query_image
 from app.api import api_brand_dna
 from app.api import api_brighten
 from app.api import api_chat_robot
+from app.api import api_clothing_seg
 from app.api import api_design
 from app.api import api_design_pre_processing
+from app.api import api_extraction_project_info
 from app.api import api_generate_image
 from app.api import api_image2sketch
 from app.api import api_mannequins_edit
 from app.api import api_pose_transform
 from app.api import api_prompt_generation
-from app.api import api_clothing_seg
 from app.api import api_super_resolution
-from app.api import api_recommendation
 from app.api import api_test
 
 router = APIRouter()
@@ -36,3 +36,4 @@ router.include_router(api_mannequins_edit.router, tags=['api_mannequins_edit'],
 router.include_router(api_agent_generate_image.router, tags=['api_agent_generate_image'], prefix="/api")
 router.include_router(api_pose_transform.router, tags=['api_pose_transform'], prefix="/api")
 router.include_router(api_clothing_seg.router, tags=['api_clothing_seg'], prefix="/api")
+router.include_router(api_extraction_project_info.router, tags=['api_extraction_project_info'], prefix="/api")

app/schemas/project_info_extraction.py

@@ -0,0 +1,5 @@
+from pydantic import BaseModel
+
+
+class ProjectInfoExtractionModel(BaseModel):
+    prompt: str

app/service/project_info_extraction/service_generate_brand_info.py

@@ -0,0 +1,47 @@
+from langchain.output_parsers import ResponseSchema, StructuredOutputParser
+from langchain_community.chat_models import ChatTongyi
+from langchain_core.prompts import PromptTemplate
+
+from app.schemas.project_info_extraction import ProjectInfoExtractionModel
+
+
+class ProjectInfoExtraction:
+    def __init__(self, request_data):
+        # llm generate brand info init
+        self.model = ChatTongyi(model="qwen2.5-14b-instruct", api_key="sk-7658298c6b99443c98184a5e634fe6ab")
+
+        self.response_schemas = [
+            ResponseSchema(name="project_name", description="project name."),
+            ResponseSchema(name="role", description="The target role of the project."),
+            ResponseSchema(name="gender", description="The gender targeted by the project."),
+            ResponseSchema(name="style", description="Project style.")
+        ]
+        self.output_parser = StructuredOutputParser.from_response_schemas(self.response_schemas)
+        self.format_instructions = self.output_parser.get_format_instructions()
+        self.prompt = PromptTemplate(
+            template="你是一个时装品牌的设计师助理。根据用户输入提取出project_name,role ,gender ,style ."
+                     "gender部分请用以下:menswear,womenswear,childrenwear,如果全部都适用即all."
+                     "如果没有以上内容，需要你根据用户输入随意发挥.\n{format_instructions}\n{question}",
+            input_variables=["question"],
+            partial_variables={"format_instructions": self.format_instructions}
+        )
+        self._input = self.prompt.format_prompt(question=request_data.prompt)
+
+        self.result_data = {}
+
+    def get_result(self):
+        self.llm_extraction_project_info()
+        return self.result_data
+
+    def llm_extraction_project_info(self):
+        output = self.model(self._input.to_messages())
+        project_info = self.output_parser.parse(output.content)
+        self.result_data = project_info
+
+
+if __name__ == '__main__':
+    request_data = ProjectInfoExtractionModel(
+        prompt="海边派对主题的系列设计"
+    )
+    service = ProjectInfoExtraction(request_data)
+    print(service.get_result())