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wanghep
263
backend/app/services/capital_image_service.py
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263
backend/app/services/capital_image_service.py
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import base64
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import json
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import re
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import urllib.error
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import urllib.request
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from datetime import datetime
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from pathlib import Path
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from uuid import uuid4
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from fastapi import HTTPException, UploadFile
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from app.core.config import BASE_DIR, CAPITAL_IMAGE_DB_FILE, CAPITAL_IMAGE_UPLOADS_DIR
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from app.repositories.monitoring_repository import MonitoringRepository
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from app.repositories.capital_image_repository import CapitalImageRepository
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def _extract_json_block(content: str) -> dict:
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fenced_match = re.search(r"```json\s*(\{.*?\})\s*```", content, flags=re.DOTALL)
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if fenced_match:
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return json.loads(fenced_match.group(1))
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object_match = re.search(r"(\{.*\})", content, flags=re.DOTALL)
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if object_match:
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return json.loads(object_match.group(1))
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raise ValueError("No JSON object found in model output")
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class CapitalImageService:
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def __init__(self) -> None:
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self.repository = CapitalImageRepository(CAPITAL_IMAGE_DB_FILE)
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self.monitoring_repository = MonitoringRepository()
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def list_records(self, trade_date: str | None = None, subject: str | None = None) -> dict:
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items = [
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self._serialize_record(record)
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for record in self.repository.list_records(trade_date=trade_date, subject=subject)
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]
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return {"items": items, "total": len(items)}
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def get_record(self, record_id: str) -> dict:
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record = self.repository.get_record(record_id)
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if record is None:
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raise HTTPException(status_code=404, detail="Record not found")
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return self._serialize_record(record)
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async def create_record(
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self,
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upload_file: UploadFile,
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trade_date: str | None = None,
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subject: str | None = None,
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) -> dict:
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suffix = Path(upload_file.filename or "upload.jpg").suffix or ".jpg"
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record_id = uuid4().hex
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image_name = upload_file.filename or f"{record_id}{suffix}"
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stored_path = CAPITAL_IMAGE_UPLOADS_DIR / f"{record_id}{suffix.lower()}"
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binary = await upload_file.read()
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stored_path.parent.mkdir(parents=True, exist_ok=True)
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stored_path.write_bytes(binary)
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extraction = self._extract_from_image(
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image_bytes=binary,
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original_filename=image_name,
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stored_path=stored_path,
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trade_date=trade_date,
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subject=subject,
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)
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now = datetime.now().isoformat(timespec="seconds")
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payload = {
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"id": record_id,
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"trade_date": extraction.get("trade_date") or trade_date,
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"subject": extraction.get("subject") or subject,
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"snapshot_time": extraction.get("snapshot_time"),
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"main_force_amount_yi": extraction.get("main_force_amount_yi"),
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"institution_amount_yi": extraction.get("institution_amount_yi"),
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"large_household_amount_yi": extraction.get("large_household_amount_yi"),
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"retail_amount_yi": extraction.get("retail_amount_yi"),
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"overall_trend": extraction.get("overall_trend"),
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"intraday_summary": extraction.get("intraday_summary"),
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"review_status": extraction.get("review_status", "pending_review"),
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"extraction_method": extraction.get("extraction_method", "fallback"),
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"image_name": image_name,
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"image_path": str(stored_path),
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"raw_extraction": extraction,
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"created_at": now,
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"updated_at": now,
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}
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record = self.repository.insert_record(payload)
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return {"item": self._serialize_record(record)}
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def _extract_from_image(
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self,
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image_bytes: bytes,
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original_filename: str,
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stored_path: Path,
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trade_date: str | None,
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subject: str | None,
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) -> dict:
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llm_config = self._get_llm_config()
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if llm_config["api_key"]:
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try:
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return self._extract_via_model(
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image_bytes=image_bytes,
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trade_date=trade_date,
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subject=subject,
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llm_config=llm_config,
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)
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except Exception as exc: # pragma: no cover
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return {
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**self._build_fallback_payload(original_filename, trade_date, subject),
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"review_status": "pending_review",
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"extraction_method": "fallback_after_model_error",
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"model_error": str(exc),
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}
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sidecar_payload = self._load_sidecar_payload(original_filename)
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if sidecar_payload is not None:
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return sidecar_payload
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return self._build_fallback_payload(original_filename, trade_date, subject)
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def _extract_via_model(
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self,
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image_bytes: bytes,
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trade_date: str | None,
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subject: str | None,
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llm_config: dict,
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) -> dict:
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api_key = llm_config["api_key"]
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base_url = llm_config["base_url"].rstrip("/")
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model = llm_config["model"]
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encoded_image = base64.b64encode(image_bytes).decode("utf-8")
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prompt = """
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You are extracting structured data from a Chinese stock capital flow screenshot.
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Return only JSON with these keys:
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trade_date, subject, snapshot_time, main_force_amount_yi, institution_amount_yi,
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large_household_amount_yi, retail_amount_yi, overall_trend, intraday_summary,
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review_status, extraction_method.
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Rules:
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1. intraday_summary must describe only the intraday capital-flow trend, not repeat raw numbers.
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2. overall_trend should be a short phrase like "震荡上行", "冲高回落", "弱势下探", "午后修复".
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3. If a number is not clearly visible, set it to null.
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4. review_status should be "extracted".
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5. extraction_method should be "vision_model".
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6. If trade_date is absent in the image, keep null.
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"""
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payload = {
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"model": model,
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"messages": [
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{
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"role": "system",
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"content": "You extract structured JSON from Chinese capital-flow screenshots."
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},
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{
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"role": "user",
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"content": [
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{"type": "text", "text": prompt},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{encoded_image}",
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},
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},
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],
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}
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],
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}
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request = urllib.request.Request(
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url=f"{base_url}/chat/completions",
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data=json.dumps(payload).encode("utf-8"),
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headers={
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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},
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method="POST",
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)
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try:
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with urllib.request.urlopen(request, timeout=180) as response:
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response_payload = json.loads(response.read().decode("utf-8"))
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except urllib.error.HTTPError as exc: # pragma: no cover
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error_text = exc.read().decode("utf-8", errors="ignore")
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raise RuntimeError(f"Model request failed: {error_text}") from exc
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choices = response_payload.get("choices", [])
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content = ""
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if choices:
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content = choices[0].get("message", {}).get("content", "")
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parsed = _extract_json_block(content)
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if subject and not parsed.get("subject"):
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parsed["subject"] = subject
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if trade_date and not parsed.get("trade_date"):
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parsed["trade_date"] = trade_date
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return parsed
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def _get_llm_config(self) -> dict:
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config = self.monitoring_repository.get_system_config()
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return {
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"provider": config.get("llm_provider", "openai_compatible"),
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"api_key": config.get("llm_api_key", ""),
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"base_url": config.get("llm_base_url", "https://api.openai.com/v1"),
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"model": config.get("llm_vision_model", "gpt-4.1-mini"),
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}
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def _load_sidecar_payload(self, original_filename: str) -> dict | None:
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candidate_paths = [
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BASE_DIR.parent / "zijin" / f"{Path(original_filename).stem}.json",
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BASE_DIR / "data" / "capital_images" / f"{Path(original_filename).stem}.json",
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]
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for candidate in candidate_paths:
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if candidate.exists():
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payload = json.loads(candidate.read_text(encoding="utf-8"))
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capital_flow = payload.get("capital_flow_amounts", {})
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overall_trend = payload.get("overall_trend", {})
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intraday_summary = overall_trend.get("summary") or payload.get("llm_summary")
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return {
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"trade_date": payload.get("date"),
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"subject": payload.get("subject"),
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"snapshot_time": payload.get("snapshot_time"),
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"main_force_amount_yi": capital_flow.get("main_force_yi"),
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"institution_amount_yi": capital_flow.get("institution_yi"),
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"large_household_amount_yi": capital_flow.get("large_household_yi"),
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"retail_amount_yi": capital_flow.get("retail_yi"),
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"overall_trend": overall_trend.get("direction"),
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"intraday_summary": intraday_summary,
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"review_status": "sidecar_loaded",
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"extraction_method": "sidecar_json",
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"sidecar_path": str(candidate),
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}
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return None
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def _build_fallback_payload(
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self,
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original_filename: str,
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trade_date: str | None,
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subject: str | None,
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) -> dict:
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return {
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"trade_date": trade_date,
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"subject": subject,
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"snapshot_time": None,
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"main_force_amount_yi": None,
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"institution_amount_yi": None,
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"large_household_amount_yi": None,
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"retail_amount_yi": None,
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"overall_trend": "待识别",
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"intraday_summary": "当前未配置视觉模型，图片已保存，待接入大模型后补充日内资金走势总结。",
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"review_status": "pending_review",
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"extraction_method": "storage_only",
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"fallback_reason": f"No vision model configured for {original_filename}",
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}
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def _serialize_record(self, record: dict) -> dict:
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return {
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**record,
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"image_url": f"/capital-images/uploads/{Path(record['image_path']).name}",
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}
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capital_image_service = CapitalImageService()
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