马一丁
284 lines
8.3 KiB
Python
284 lines
8.3 KiB
Python
"""
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图表API修复模块。
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提供调用4个Engine（ReportEngine, ForumEngine, InsightEngine, MediaEngine）的LLM API
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来修复图表数据的功能。
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"""
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from __future__ import annotations
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import json
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from typing import Any, Dict, List, Optional
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from loguru import logger
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from ReportEngine.utils.config import settings
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# 图表修复提示词
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CHART_REPAIR_SYSTEM_PROMPT = """你是一个专业的图表数据修复助手。你的任务是修复Chart.js图表数据中的格式错误，确保图表能够正常渲染。
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**Chart.js标准数据格式：**
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1. 标准图表（line, bar, pie, doughnut, radar, polarArea）：
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```json
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{
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"type": "widget",
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"widgetType": "chart.js/bar",
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"widgetId": "chart-001",
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"props": {
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"type": "bar",
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"title": "图表标题",
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"options": {
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"responsive": true,
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"plugins": {
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"legend": {
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"display": true
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}
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}
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}
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},
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"data": {
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"labels": ["A", "B", "C"],
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"datasets": [
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{
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"label": "系列1",
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"data": [10, 20, 30]
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}
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]
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}
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}
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```
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2. 特殊图表（scatter, bubble）：
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```json
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{
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"data": {
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"datasets": [
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{
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"label": "系列1",
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"data": [
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{"x": 10, "y": 20},
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{"x": 15, "y": 25}
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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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**修复原则：**
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1. **宁愿不改，也不要改错** - 如果不确定如何修复，保持原始数据
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2. **最小改动** - 只修复明确的错误，不要过度修改
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3. **保持数据完整性** - 不要丢失原始数据
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4. **验证修复结果** - 确保修复后符合Chart.js格式
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**常见错误及修复方法：**
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1. 缺少labels字段 → 根据数据生成默认labels
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2. datasets不是数组 → 转换为数组格式
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3. 数据长度不匹配 → 截断或补null
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4. 非数值数据 → 尝试转换或设为null
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5. 缺少必需字段 → 添加默认值
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请根据错误信息修复图表数据，并返回修复后的完整widget block（JSON格式）。
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"""
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def build_chart_repair_prompt(
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widget_block: Dict[str, Any],
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validation_errors: List[str]
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) -> str:
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"""
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构建图表修复提示词。
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Args:
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widget_block: 原始widget block
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validation_errors: 验证错误列表
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Returns:
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str: 提示词
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"""
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block_json = json.dumps(widget_block, ensure_ascii=False, indent=2)
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errors_text = "\n".join(f"- {error}" for error in validation_errors)
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prompt = f"""请修复以下图表数据中的错误：
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**原始数据：**
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```json
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{block_json}
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```
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**检测到的错误：**
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{errors_text}
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**要求：**
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1. 返回修复后的完整widget block（JSON格式）
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2. 只修复明确的错误，保持其他数据不变
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3. 确保修复后的数据符合Chart.js格式要求
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4. 如果无法确定如何修复，保持原始数据
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**重要的输出格式要求：**
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1. 只返回纯JSON对象，不要添加任何说明文字
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2. 不要使用```json```标记包裹
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3. 确保JSON语法完全正确
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4. 所有字符串使用双引号
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"""
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return prompt
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def create_llm_repair_functions() -> List:
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"""
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创建LLM修复函数列表。
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返回4个Engine的修复函数：
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1. ReportEngine
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2. ForumEngine (通过ForumHost)
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3. InsightEngine
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4. MediaEngine
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Returns:
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List[Callable]: 修复函数列表
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"""
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repair_functions = []
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# 1. ReportEngine修复函数
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if settings.REPORT_ENGINE_API_KEY and settings.REPORT_ENGINE_BASE_URL:
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def repair_with_report_engine(widget_block: Dict[str, Any], errors: List[str]) -> Optional[Dict[str, Any]]:
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"""使用ReportEngine的LLM修复图表"""
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try:
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from llm_client import LLMClient
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client = LLMClient(
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api_key=settings.REPORT_ENGINE_API_KEY,
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base_url=settings.REPORT_ENGINE_BASE_URL,
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model_name=settings.REPORT_ENGINE_MODEL_NAME or "gpt-4",
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provider="openai"
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)
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prompt = build_chart_repair_prompt(widget_block, errors)
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response = client.invoke(
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CHART_REPAIR_SYSTEM_PROMPT,
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prompt,
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temperature=0.0,
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top_p=0.05
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)
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if not response:
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return None
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# 解析响应
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repaired = json.loads(response)
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return repaired
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except Exception as e:
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logger.error(f"ReportEngine图表修复失败: {e}")
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return None
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repair_functions.append(repair_with_report_engine)
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# 2. ForumEngine修复函数
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if settings.FORUM_HOST_API_KEY and settings.FORUM_HOST_BASE_URL:
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def repair_with_forum_engine(widget_block: Dict[str, Any], errors: List[str]) -> Optional[Dict[str, Any]]:
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"""使用ForumEngine的LLM修复图表"""
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try:
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from llm_client import LLMClient
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client = LLMClient(
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api_key=settings.FORUM_HOST_API_KEY,
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base_url=settings.FORUM_HOST_BASE_URL,
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model_name=settings.FORUM_HOST_MODEL_NAME or "gpt-4",
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provider="openai"
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)
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prompt = build_chart_repair_prompt(widget_block, errors)
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response = client.invoke(
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CHART_REPAIR_SYSTEM_PROMPT,
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prompt,
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temperature=0.0,
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top_p=0.05
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)
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if not response:
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return None
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repaired = json.loads(response)
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return repaired
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except Exception as e:
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logger.error(f"ForumEngine图表修复失败: {e}")
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return None
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repair_functions.append(repair_with_forum_engine)
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# 3. InsightEngine修复函数
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if settings.INSIGHT_ENGINE_API_KEY and settings.INSIGHT_ENGINE_BASE_URL:
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def repair_with_insight_engine(widget_block: Dict[str, Any], errors: List[str]) -> Optional[Dict[str, Any]]:
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"""使用InsightEngine的LLM修复图表"""
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try:
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from llm_client import LLMClient
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client = LLMClient(
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api_key=settings.INSIGHT_ENGINE_API_KEY,
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base_url=settings.INSIGHT_ENGINE_BASE_URL,
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model_name=settings.INSIGHT_ENGINE_MODEL_NAME or "gpt-4",
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provider="openai"
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)
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prompt = build_chart_repair_prompt(widget_block, errors)
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response = client.invoke(
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CHART_REPAIR_SYSTEM_PROMPT,
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prompt,
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temperature=0.0,
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top_p=0.05
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)
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if not response:
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return None
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repaired = json.loads(response)
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return repaired
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except Exception as e:
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logger.error(f"InsightEngine图表修复失败: {e}")
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return None
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repair_functions.append(repair_with_insight_engine)
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# 4. MediaEngine修复函数
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if settings.MEDIA_ENGINE_API_KEY and settings.MEDIA_ENGINE_BASE_URL:
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def repair_with_media_engine(widget_block: Dict[str, Any], errors: List[str]) -> Optional[Dict[str, Any]]:
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"""使用MediaEngine的LLM修复图表"""
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try:
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from llm_client import LLMClient
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client = LLMClient(
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api_key=settings.MEDIA_ENGINE_API_KEY,
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base_url=settings.MEDIA_ENGINE_BASE_URL,
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model_name=settings.MEDIA_ENGINE_MODEL_NAME or "gpt-4",
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provider="openai"
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)
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prompt = build_chart_repair_prompt(widget_block, errors)
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response = client.invoke(
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CHART_REPAIR_SYSTEM_PROMPT,
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prompt,
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temperature=0.0,
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top_p=0.05
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)
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if not response:
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return None
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repaired = json.loads(response)
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return repaired
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except Exception as e:
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logger.error(f"MediaEngine图表修复失败: {e}")
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return None
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repair_functions.append(repair_with_media_engine)
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if not repair_functions:
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logger.warning("未配置任何Engine API，图表API修复功能将不可用")
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return repair_functions
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