'commit'
This commit is contained in:
HuangHai
@@ -98,6 +98,191 @@ class ReadImageKit:
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return "[]"
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_prompt_detail = (
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"仅输出JSON对象（不含任何说明文字），识别充电站详情图片中的以下信息：\n"
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"1. station_name: 场站名称；\n"
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"2. address: 场站完整地址（通常在定位图标旁）。\n"
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"\n"
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"特别说明：\n"
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"- 严禁输出 Markdown 代码块标签，严格返回纯JSON对象。"
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)
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@staticmethod
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def _to_minutes(t_str: str) -> int:
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"""HH:MM -> 分钟数"""
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if not t_str or ":" not in t_str:
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return 0
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try:
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h, m = map(int, t_str.split(":"))
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return h * 60 + m
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except:
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return 0
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@staticmethod
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def _fmt(t: int) -> str:
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"""分钟数 -> HH:MM"""
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h = t // 60
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m = t % 60
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return f"{h:02d}:{m:02d}"
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@staticmethod
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def expand_schedule_to_24h(rows: list) -> list:
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"""
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将时段列表规整为全天24个整点小时段
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"""
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# 预处理：转换为分钟区间
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intervals = []
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for r in rows:
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s = ReadImageKit._to_minutes(r.get("start"))
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e = ReadImageKit._to_minutes(r.get("end"))
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if e <= s and e != 0: # 处理 00:00-00:00 这种可能
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if e == 0: e = 1440
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else: continue
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if e == 0 and s > 0: e = 1440
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s = max(0, s)
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e = min(1440, e)
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intervals.append({
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"s": s, "e": e,
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"price": r.get("price")
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})
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# 排序
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intervals.sort(key=lambda x: (x["s"], x["e"]))
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result = []
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for h in range(24):
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hs = h * 60
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he = (h + 1) * 60
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best_price = None
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# 找到覆盖当前小时段的价格
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for it in intervals:
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# 计算重叠
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overlap_s = max(hs, it["s"])
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overlap_e = min(he, it["e"])
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if overlap_e > overlap_s:
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best_price = it["price"]
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break # 简单处理，取第一个覆盖的
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result.append({
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"start": ReadImageKit._fmt(hs),
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"end": ReadImageKit._fmt(he),
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"price": best_price
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})
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return result
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_prompt_price_detail = (
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"仅输出JSON对象（不含任何说明文字），识别充电价格详情图片中的分时段电价信息。图片中通常包含“充电时段”、“单价”、“电费”、“服务费”等列。\n"
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"请识别出所有的时段行，返回一个列表，每个元素包含：\n"
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"1. start: 开始时间 (HH:MM)；\n"
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"2. end: 结束时间 (HH:MM)；\n"
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"3. price: 总单价 (数字，如 0.6100)；\n"
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"4. ele_fee: 电费 (数字)；\n"
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"5. ser_fee: 服务费 (数字)。\n"
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"\n"
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"注意：\n"
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"- 只需识别“直流桩”或当前选中的桩型下的数据。\n"
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"- 严禁输出 Markdown 代码块标签，严格返回纯JSON对象。"
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)
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@classmethod
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async def get_price_detail_from_image(cls, image_path: str):
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"""
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使用 VL 模型从三级价格详情页截图中识别分时段电价
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"""
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if not os.path.exists(image_path):
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logger.error(f"Image not found: {image_path}")
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return None
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with open(image_path, "rb") as image_file:
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encoded_image = base64.b64encode(image_file.read()).decode("utf-8")
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try:
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response = await asyncio.to_thread(
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cls._client.chat.completions.create,
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model=VL_MODEL_NAME,
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messages=[
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{
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"role": "user",
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"content": [
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{"type": "text", "text": cls._prompt_price_detail},
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{
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"type": "image_url",
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"image_url": {"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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max_tokens=2000,
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temperature=0.01
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)
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content = response.choices[0].message.content
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logger.info(f"VL Price Detail Response: {content}")
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json_str = cls._extract_json(content)
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data = json.loads(json_str)
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# 兼容性处理：如果返回的是对象且包含列表字段，提取列表
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if isinstance(data, dict):
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for key in ["price_list", "prices", "schedule", "data"]:
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if key in data and isinstance(data[key], list):
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return data[key]
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# 如果本身就是个包含列表的字典，也可能需要根据实际情况调整
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# 这里假设 prompt 引导它返回一个包含列表的对象或直接是列表
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if "items" in data: return data["items"]
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return data
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except Exception as e:
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logger.error(f"Error calling VL model for price detail: {e}")
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return None
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@classmethod
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async def get_station_detail_from_image(cls, image_path: str):
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"""
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使用 VL 模型从详情页截图中识别地址、名称和电价
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"""
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if not os.path.exists(image_path):
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logger.error(f"Image not found: {image_path}")
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return None
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with open(image_path, "rb") as image_file:
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encoded_image = base64.b64encode(image_file.read()).decode("utf-8")
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try:
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response = await asyncio.to_thread(
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cls._client.chat.completions.create,
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model=VL_MODEL_NAME,
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messages=[
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{
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"role": "user",
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"content": [
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{"type": "text", "text": cls._prompt_detail},
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{
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"type": "image_url",
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"image_url": {"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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max_tokens=1000,
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temperature=0.01
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)
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content = response.choices[0].message.content
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logger.info(f"VL Detail Response: {content}")
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json_str = cls._extract_json(content)
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detail = json.loads(json_str)
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return detail
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except Exception as e:
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logger.error(f"Error calling VL model for detail: {e}")
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return None
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@classmethod
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async def get_stations_from_image(cls, image_path: str, device_info=None):
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"""
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