99 lines
3.6 KiB
Python
99 lines
3.6 KiB
Python
import logging
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import json
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import os
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from django.conf import settings
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from openai import OpenAI
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from .models import AIEvaluation
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logger = logging.getLogger(__name__)
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class BailianService:
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def __init__(self):
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self.api_key = getattr(settings, 'DASHSCOPE_API_KEY', None)
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if not self.api_key:
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self.api_key = os.environ.get("DASHSCOPE_API_KEY")
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if self.api_key:
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self.client = OpenAI(
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api_key=self.api_key,
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base_url="https://dashscope.aliyuncs.com/compatible-mode/v1"
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)
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else:
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self.client = None
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logger.warning("DASHSCOPE_API_KEY not configured.")
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def evaluate_task(self, evaluation: AIEvaluation):
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"""
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执行AI评估
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"""
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if not self.client:
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evaluation.status = AIEvaluation.Status.FAILED
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evaluation.error_message = "服务未配置 (DASHSCOPE_API_KEY missing)"
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evaluation.save()
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return
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task = evaluation.task
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if not task.transcription:
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evaluation.status = AIEvaluation.Status.FAILED
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evaluation.error_message = "关联任务无逐字稿内容"
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evaluation.save()
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return
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evaluation.status = AIEvaluation.Status.PROCESSING
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evaluation.save()
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try:
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prompt = evaluation.prompt
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content = task.transcription
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# 截断过长的内容以防止超出Token限制 (简单处理，取前10000字)
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if len(content) > 10000:
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content = content[:10000] + "...(内容过长已截断)"
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# Construct messages
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messages = [
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{'role': 'system', 'content': 'You are a helpful assistant designed to output JSON.'},
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{'role': 'user', 'content': f"{prompt}\n\n以下是需要评估的内容：\n{content}"}
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]
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completion = self.client.chat.completions.create(
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model=evaluation.model_selection,
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messages=messages,
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response_format={"type": "json_object"}
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)
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response_content = completion.choices[0].message.content
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# Convert to dict for storage
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raw_response = completion.model_dump()
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evaluation.raw_response = raw_response
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# Parse JSON
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try:
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result = json.loads(response_content)
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evaluation.score = result.get('score')
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evaluation.evaluation = result.get('evaluation') or result.get('comment')
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# 尝试获取推理过程（如果模型返回了）
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evaluation.reasoning = result.get('reasoning') or result.get('analysis')
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if not evaluation.reasoning:
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# 如果JSON里没有，把整个JSON作为推理参考
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evaluation.reasoning = json.dumps(result, ensure_ascii=False, indent=2)
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evaluation.status = AIEvaluation.Status.COMPLETED
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except json.JSONDecodeError:
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evaluation.status = AIEvaluation.Status.FAILED
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evaluation.error_message = f"无法解析JSON响应: {response_content}"
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evaluation.reasoning = response_content
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evaluation.save()
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return evaluation
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except Exception as e:
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logger.error(f"AI Evaluation failed: {e}")
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evaluation.status = AIEvaluation.Status.FAILED
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evaluation.error_message = str(e)
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evaluation.save()
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return evaluation
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