113 lines
2.4 KiB
Python
113 lines
2.4 KiB
Python
"""
|
|
智能分析 API
|
|
"""
|
|
from typing import Optional
|
|
from fastapi import APIRouter, BackgroundTasks, HTTPException
|
|
from pydantic import BaseModel
|
|
|
|
router = APIRouter()
|
|
|
|
|
|
class QuestionRequest(BaseModel):
|
|
"""智能问答请求"""
|
|
question: str
|
|
context: Optional[str] = None
|
|
|
|
|
|
class GeneMiningRequest(BaseModel):
|
|
"""基因挖掘请求"""
|
|
sequence: str
|
|
algorithm: str = "blast"
|
|
parameters: Optional[dict] = None
|
|
|
|
|
|
class StrainEvaluationRequest(BaseModel):
|
|
"""菌株评估请求"""
|
|
strain_id: str
|
|
evaluation_type: str # growth/resistance/etc
|
|
|
|
|
|
@router.post("/qa")
|
|
async def intelligent_qa(request: QuestionRequest):
|
|
"""
|
|
智能问答
|
|
|
|
基于知识图谱的智能问答系统
|
|
"""
|
|
# TODO: 集成 AI 模型进行问答
|
|
return {
|
|
"question": request.question,
|
|
"answer": "This is a placeholder answer. AI integration pending.",
|
|
"confidence": 0.0
|
|
}
|
|
|
|
|
|
@router.post("/gene-mining")
|
|
async def gene_mining(
|
|
background_tasks: BackgroundTasks,
|
|
request: GeneMiningRequest
|
|
):
|
|
"""
|
|
基因挖掘
|
|
|
|
通过序列比对等方法挖掘功能基因
|
|
"""
|
|
# TODO: 实现基因挖掘算法
|
|
# background_tasks.add_task(run_gene_mining, request)
|
|
|
|
return {
|
|
"status": "processing",
|
|
"task_id": "task_123",
|
|
"message": "Gene mining task started"
|
|
}
|
|
|
|
|
|
@router.post("/strain-evaluation")
|
|
async def strain_evaluation(
|
|
background_tasks: BackgroundTasks,
|
|
request: StrainEvaluationRequest
|
|
):
|
|
"""
|
|
菌株评估
|
|
|
|
评估菌株的各项指标和应用潜力
|
|
"""
|
|
# TODO: 实现菌株评估逻辑
|
|
return {
|
|
"status": "processing",
|
|
"task_id": "task_456",
|
|
"message": "Strain evaluation started"
|
|
}
|
|
|
|
|
|
@router.get("/knowledge-graph")
|
|
async def get_knowledge_graph(
|
|
entity: Optional[str] = None,
|
|
relationship: Optional[str] = None,
|
|
):
|
|
"""
|
|
知识图谱查询
|
|
|
|
查询微生物知识图谱
|
|
"""
|
|
# TODO: 实现知识图谱查询
|
|
return {
|
|
"nodes": [],
|
|
"edges": [],
|
|
"message": "Knowledge graph feature pending"
|
|
}
|
|
|
|
|
|
@router.get("/task/{task_id}")
|
|
async def get_analysis_task_status(task_id: str):
|
|
"""
|
|
查询分析任务状态
|
|
"""
|
|
# TODO: 从数据库或缓存查询任务状态
|
|
return {
|
|
"task_id": task_id,
|
|
"status": "completed",
|
|
"progress": 100,
|
|
"result": None
|
|
}
|