chore: initialize insar management system v2
This commit is contained in:
@@ -0,0 +1,402 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import io
|
||||
import base64
|
||||
import logging
|
||||
import os
|
||||
from datetime import datetime
|
||||
|
||||
from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException
|
||||
from pydantic import BaseModel, Field, field_validator
|
||||
from sqlalchemy import func, desc
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from sqlalchemy.future import select
|
||||
from typing import List, Optional
|
||||
|
||||
from ..ai_service import (
|
||||
analyze_map_with_vlm,
|
||||
get_model_info,
|
||||
is_model_trained,
|
||||
predict_quality,
|
||||
train_quality_model,
|
||||
)
|
||||
from ..database import get_db
|
||||
from ..config import read_int_env, settings
|
||||
from ..models import (
|
||||
AuthUserORM,
|
||||
AiDiagnosisORM,
|
||||
AiDiagnosisCreate,
|
||||
AiDiagnosisResponse,
|
||||
AiDiagnosisListResponse,
|
||||
)
|
||||
from ..services.dinsar_read_service import dinsar_read_service
|
||||
from ..services.job_queue_service import job_queue_service
|
||||
from ..services.task_service import task_service
|
||||
from ..services.ai_prompts import get_prompt_template, list_prompt_templates
|
||||
from .dependencies import _require_admin
|
||||
|
||||
router = APIRouter()
|
||||
logger = logging.getLogger(__name__)
|
||||
AI_ANALYZE_MAP_MAX_IMAGES = read_int_env(
|
||||
"AI_ANALYZE_MAP_MAX_IMAGES",
|
||||
4,
|
||||
minimum=1,
|
||||
maximum=50,
|
||||
)
|
||||
AI_ANALYZE_MAP_MAX_IMAGE_BASE64_CHARS = read_int_env(
|
||||
"AI_ANALYZE_MAP_MAX_IMAGE_BASE64_CHARS",
|
||||
12 * 1024 * 1024,
|
||||
minimum=1024,
|
||||
maximum=100 * 1024 * 1024,
|
||||
)
|
||||
AI_ANALYZE_MAP_PROMPT_MAX_CHARS = read_int_env(
|
||||
"AI_ANALYZE_MAP_PROMPT_MAX_CHARS",
|
||||
8000,
|
||||
minimum=32,
|
||||
maximum=200000,
|
||||
)
|
||||
|
||||
|
||||
class MapAnalysisRequest(BaseModel):
|
||||
images: List[str] = Field(default_factory=list) # Base64 strings
|
||||
prompt: Optional[str] = None
|
||||
|
||||
@field_validator("images", mode="before")
|
||||
@classmethod
|
||||
def _validate_images(cls, value):
|
||||
if value is None:
|
||||
return []
|
||||
if not isinstance(value, list):
|
||||
raise ValueError("images must be a list.")
|
||||
if len(value) == 0:
|
||||
raise ValueError("images must not be empty.")
|
||||
if len(value) > AI_ANALYZE_MAP_MAX_IMAGES:
|
||||
raise ValueError(
|
||||
f"images exceeds max count ({AI_ANALYZE_MAP_MAX_IMAGES})."
|
||||
)
|
||||
|
||||
normalized: List[str] = []
|
||||
for raw in value:
|
||||
img = str(raw or "").strip()
|
||||
if not img:
|
||||
continue
|
||||
if len(img) > AI_ANALYZE_MAP_MAX_IMAGE_BASE64_CHARS:
|
||||
raise ValueError(
|
||||
"one image exceeds max base64 length "
|
||||
f"({AI_ANALYZE_MAP_MAX_IMAGE_BASE64_CHARS} chars)."
|
||||
)
|
||||
normalized.append(img)
|
||||
|
||||
if not normalized:
|
||||
raise ValueError("images must contain at least one non-empty base64 string.")
|
||||
return normalized
|
||||
|
||||
@field_validator("prompt", mode="before")
|
||||
@classmethod
|
||||
def _validate_prompt(cls, value):
|
||||
if value is None:
|
||||
return None
|
||||
normalized = str(value).strip()
|
||||
if not normalized:
|
||||
return None
|
||||
if len(normalized) > AI_ANALYZE_MAP_PROMPT_MAX_CHARS:
|
||||
raise ValueError(
|
||||
f"prompt exceeds max length ({AI_ANALYZE_MAP_PROMPT_MAX_CHARS} chars)."
|
||||
)
|
||||
return normalized
|
||||
|
||||
|
||||
@router.post("/ai/train", status_code=202)
|
||||
async def train_ai_model(background_tasks: BackgroundTasks, admin_user: AuthUserORM = Depends(_require_admin)):
|
||||
"""
|
||||
使用已标记的数据训练AI模型。
|
||||
"""
|
||||
try:
|
||||
task_id = await task_service.create_task("AI_TRAIN", "AI 模型训练")
|
||||
await job_queue_service.create_job("AI_TRAIN", payload={}, task_id=task_id)
|
||||
return {"message": "AI模型训练任务已进入队列", "task_id": task_id}
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=409, detail=str(e))
|
||||
except Exception as e:
|
||||
logger.exception("AI 模型训练任务创建失败")
|
||||
raise HTTPException(status_code=500, detail="AI 模型训练任务创建失败，请查看后端日志")
|
||||
|
||||
|
||||
@router.post("/ai/predict-all", status_code=202)
|
||||
async def predict_all_quality(background_tasks: BackgroundTasks, admin_user: AuthUserORM = Depends(_require_admin)):
|
||||
"""
|
||||
使用训练好的模型预测所有结果的质量。
|
||||
"""
|
||||
try:
|
||||
task_id = await task_service.create_task("AI_PREDICT", "AI 质量预测")
|
||||
await job_queue_service.create_job("AI_PREDICT", payload={}, task_id=task_id)
|
||||
return {"message": "AI质量预测任务已进入队列", "task_id": task_id}
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=409, detail=str(e))
|
||||
except Exception as e:
|
||||
logger.exception("AI 质量预测任务创建失败")
|
||||
raise HTTPException(status_code=500, detail="AI 质量预测任务创建失败，请查看后端日志")
|
||||
|
||||
|
||||
@router.get("/ai/status")
|
||||
async def get_ai_status(db: AsyncSession = Depends(get_db)):
|
||||
"""
|
||||
获取AI模型状态和标记统计，并检测 Ollama 连通性。
|
||||
"""
|
||||
counts = await dinsar_read_service.get_ai_status_counts(db)
|
||||
|
||||
ollama_online = False
|
||||
try:
|
||||
import httpx
|
||||
async with httpx.AsyncClient(timeout=1.0) as client:
|
||||
ollama_base = settings.OLLAMA_BASE_URL
|
||||
response = await client.get(f"{ollama_base.rstrip('/')}/api/tags")
|
||||
ollama_online = response.status_code == 200
|
||||
except Exception:
|
||||
ollama_online = False
|
||||
|
||||
return {
|
||||
"is_model_trained": is_model_trained(),
|
||||
"model_info": get_model_info(),
|
||||
"labeled_count": counts["labeled_count"],
|
||||
"good_count": counts["good_count"],
|
||||
"bad_count": counts["bad_count"],
|
||||
"ollama_online": ollama_online
|
||||
}
|
||||
|
||||
|
||||
@router.post("/ai/warmup")
|
||||
async def warmup_ai_endpoint(background_tasks: BackgroundTasks, admin_user: AuthUserORM = Depends(_require_admin)):
|
||||
"""
|
||||
发起 AI 模型预热任务，提前将 VLM 加载至显存。
|
||||
"""
|
||||
try:
|
||||
task_id = await task_service.create_task("AI_WARMUP", "AI 模型预热")
|
||||
await job_queue_service.create_job("AI_WARMUP", payload={}, task_id=task_id)
|
||||
return {"task_id": task_id}
|
||||
except Exception as e:
|
||||
logger.exception("AI 模型预热任务创建失败")
|
||||
raise HTTPException(status_code=500, detail="AI 模型预热任务创建失败，请查看后端日志")
|
||||
|
||||
|
||||
@router.post("/ai/analyze-map")
|
||||
async def analyze_map_endpoint(request: MapAnalysisRequest, admin_user: AuthUserORM = Depends(_require_admin)):
|
||||
"""
|
||||
接收地图截图并调用本地 VLM 进行分析。
|
||||
"""
|
||||
try:
|
||||
analysis = await analyze_map_with_vlm(request.images, request.prompt)
|
||||
return {"analysis": analysis}
|
||||
except Exception as e:
|
||||
logger.exception("AI 地图分析失败")
|
||||
raise HTTPException(status_code=500, detail="AI 分析失败，请查看后端日志")
|
||||
|
||||
|
||||
@router.post("/ai/analyze-result/{result_id}", status_code=202)
|
||||
async def analyze_dinsar_result_endpoint(
|
||||
result_id: int,
|
||||
background_tasks: BackgroundTasks,
|
||||
admin_user: AuthUserORM = Depends(_require_admin),
|
||||
):
|
||||
"""
|
||||
异步自动分析指定的 D-InSAR 结果。
|
||||
"""
|
||||
try:
|
||||
task_id = await task_service.create_task("AI_ANALYZE", f"AI 诊断 (结果 ID: {result_id})", params={"result_id": result_id})
|
||||
payload = {"result_id": result_id}
|
||||
await job_queue_service.create_job("AI_ANALYZE", payload=payload, task_id=task_id)
|
||||
return {"message": "AI 智能诊断任务已进入队列", "task_id": task_id}
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=409, detail=str(e))
|
||||
|
||||
|
||||
# ============ 新版 AI 诊断 RESTful API ============
|
||||
|
||||
|
||||
@router.get("/ai/prompt-templates")
|
||||
async def get_prompt_templates():
|
||||
"""
|
||||
获取所有可用的 Prompt 模板列表。
|
||||
"""
|
||||
return list_prompt_templates()
|
||||
|
||||
|
||||
@router.post("/ai/diagnosis", status_code=202)
|
||||
async def create_diagnosis(
|
||||
request: AiDiagnosisCreate,
|
||||
db: AsyncSession = Depends(get_db),
|
||||
admin_user: AuthUserORM = Depends(_require_admin),
|
||||
):
|
||||
"""
|
||||
创建 AI 诊断任务（异步执行）。
|
||||
|
||||
简化流程：
|
||||
1. 验证 result_id 存在
|
||||
2. 创建 SystemTask 和 SystemJob
|
||||
3. 在 job handler 中创建诊断记录
|
||||
"""
|
||||
try:
|
||||
logger.info(f"收到 AI 诊断请求: result_id={request.result_id}, model={request.model_name}")
|
||||
|
||||
# 验证 result_id 存在
|
||||
logger.info("正在验证 result_id...")
|
||||
record = await dinsar_read_service.get_compat_record(
|
||||
db,
|
||||
compat_result_id=request.result_id,
|
||||
)
|
||||
if record is None:
|
||||
logger.warning(f"D-InSAR 结果 ID {request.result_id} 不存在")
|
||||
raise HTTPException(status_code=404, detail=f"D-InSAR 结果 ID {request.result_id} 不存在")
|
||||
|
||||
result_name = record.display_name
|
||||
logger.info(f"找到 D-InSAR 结果: {result_name}")
|
||||
|
||||
# 获取 Prompt 文本
|
||||
logger.info("正在获取 Prompt 文本...")
|
||||
if request.custom_prompt:
|
||||
prompt_text = request.custom_prompt
|
||||
else:
|
||||
try:
|
||||
prompt_text = get_prompt_template(request.prompt_template)
|
||||
except ValueError as e:
|
||||
logger.error(f"Prompt 模板错误: {e}")
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
|
||||
logger.info(f"Prompt 文本长度: {len(prompt_text)}")
|
||||
|
||||
# 创建后台任务
|
||||
logger.info("正在创建 SystemTask...")
|
||||
task_id = await task_service.create_task(
|
||||
"AI_DIAGNOSIS",
|
||||
f"AI 诊断 - {result_name}",
|
||||
params={
|
||||
"result_id": request.result_id,
|
||||
"product_id": record.product.product_id,
|
||||
"model_name": request.model_name,
|
||||
"prompt_template": request.prompt_template,
|
||||
}
|
||||
)
|
||||
logger.info(f"SystemTask 已创建: {task_id}")
|
||||
|
||||
logger.info("正在创建 SystemJob...")
|
||||
payload = {
|
||||
"result_id": request.result_id,
|
||||
"product_id": record.product.product_id,
|
||||
"model_name": request.model_name,
|
||||
"prompt_template": request.prompt_template,
|
||||
"prompt_text": prompt_text,
|
||||
}
|
||||
await job_queue_service.create_job("AI_DIAGNOSIS", payload=payload, task_id=task_id)
|
||||
logger.info("SystemJob 已创建")
|
||||
|
||||
logger.info(f"AI 诊断任务已创建: result_id={request.result_id}, task_id={task_id}")
|
||||
|
||||
return {
|
||||
"message": "AI 诊断任务已创建",
|
||||
"task_id": task_id,
|
||||
"result_id": request.result_id,
|
||||
}
|
||||
|
||||
except HTTPException:
|
||||
raise
|
||||
except ValueError as e:
|
||||
logger.error(f"创建任务失败 (ValueError): {str(e)}", exc_info=True)
|
||||
raise HTTPException(status_code=409, detail=str(e))
|
||||
except Exception as e:
|
||||
logger.error(f"创建任务失败 (Exception): {str(e)}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail="AI 诊断任务创建失败，请查看后端日志")
|
||||
|
||||
|
||||
@router.get("/ai/diagnosis", response_model=AiDiagnosisListResponse)
|
||||
async def list_diagnoses(
|
||||
result_id: Optional[int] = None,
|
||||
task_id: Optional[str] = None,
|
||||
risk_level: Optional[str] = None,
|
||||
page: int = 1,
|
||||
page_size: int = 20,
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""
|
||||
查询 AI 诊断记录列表（支持分页和过滤）。
|
||||
|
||||
- result_id: 按 D-InSAR 结果 ID 过滤
|
||||
- task_id: 按任务 ID 过滤
|
||||
- risk_level: 按风险等级过滤（low/medium/high/critical）
|
||||
- page: 页码（从 1 开始）
|
||||
- page_size: 每页数量（1-100）
|
||||
"""
|
||||
if page < 1:
|
||||
raise HTTPException(status_code=400, detail="page 必须 >= 1")
|
||||
if page_size < 1 or page_size > 100:
|
||||
raise HTTPException(status_code=400, detail="page_size 必须在 1-100 之间")
|
||||
|
||||
# 构建查询
|
||||
query = select(AiDiagnosisORM)
|
||||
|
||||
if result_id is not None:
|
||||
query = query.where(AiDiagnosisORM.result_id == result_id)
|
||||
if task_id is not None:
|
||||
query = query.where(AiDiagnosisORM.task_id == task_id)
|
||||
if risk_level is not None:
|
||||
query = query.where(AiDiagnosisORM.risk_level == risk_level)
|
||||
|
||||
# 总数查询
|
||||
count_query = select(func.count()).select_from(query.subquery())
|
||||
total_result = await db.execute(count_query)
|
||||
total = total_result.scalar_one()
|
||||
|
||||
# 分页查询（按创建时间倒序）
|
||||
query = query.order_by(desc(AiDiagnosisORM.created_at))
|
||||
query = query.offset((page - 1) * page_size).limit(page_size)
|
||||
|
||||
result = await db.execute(query)
|
||||
items = result.scalars().all()
|
||||
|
||||
return AiDiagnosisListResponse(
|
||||
items=[AiDiagnosisResponse.model_validate(item) for item in items],
|
||||
total=total,
|
||||
page=page,
|
||||
page_size=page_size
|
||||
)
|
||||
|
||||
|
||||
@router.get("/ai/diagnosis/{diagnosis_id}", response_model=AiDiagnosisResponse)
|
||||
async def get_diagnosis(
|
||||
diagnosis_id: int,
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""
|
||||
获取单个 AI 诊断记录详情。
|
||||
"""
|
||||
result = await db.execute(
|
||||
select(AiDiagnosisORM).where(AiDiagnosisORM.id == diagnosis_id)
|
||||
)
|
||||
diagnosis = result.scalar_one_or_none()
|
||||
|
||||
if not diagnosis:
|
||||
raise HTTPException(status_code=404, detail=f"诊断记录 ID {diagnosis_id} 不存在")
|
||||
|
||||
return diagnosis
|
||||
|
||||
|
||||
@router.delete("/ai/diagnosis/{diagnosis_id}", status_code=204)
|
||||
async def delete_diagnosis(
|
||||
diagnosis_id: int,
|
||||
db: AsyncSession = Depends(get_db),
|
||||
admin_user: AuthUserORM = Depends(_require_admin),
|
||||
):
|
||||
"""
|
||||
删除 AI 诊断记录。
|
||||
"""
|
||||
result = await db.execute(
|
||||
select(AiDiagnosisORM).where(AiDiagnosisORM.id == diagnosis_id)
|
||||
)
|
||||
diagnosis = result.scalar_one_or_none()
|
||||
|
||||
if not diagnosis:
|
||||
raise HTTPException(status_code=404, detail=f"诊断记录 ID {diagnosis_id} 不存在")
|
||||
|
||||
await db.delete(diagnosis)
|
||||
await db.commit()
|
||||
|
||||
logger.info(f"AI 诊断记录已删除: diagnosis_id={diagnosis_id}")
|
||||
Reference in New Issue
Block a user