feat(eval): add report quality evaluation module and UI integration (#776)

* feat(eval): add report quality evaluation module

Addresses issue #773 - How to evaluate generated report quality objectively.

This module provides two evaluation approaches:
1. Automated metrics (no LLM required):
   - Citation count and source diversity
   - Word count compliance per report style
   - Section structure validation
   - Image inclusion tracking

2. LLM-as-Judge evaluation:
   - Factual accuracy scoring
   - Completeness assessment
   - Coherence evaluation
   - Relevance and citation quality checks

The combined evaluator provides a final score (1-10) and letter grade (A+ to F).

Files added:
- src/eval/__init__.py
- src/eval/metrics.py
- src/eval/llm_judge.py
- src/eval/evaluator.py
- tests/unit/eval/test_metrics.py
- tests/unit/eval/test_evaluator.py

* feat(eval): integrate report evaluation with web UI

This commit adds the web UI integration for the evaluation module:

Backend:
- Add EvaluateReportRequest/Response models in src/server/eval_request.py
- Add /api/report/evaluate endpoint to src/server/app.py

Frontend:
- Add evaluateReport API function in web/src/core/api/evaluate.ts
- Create EvaluationDialog component with grade badge, metrics display,
  and optional LLM deep evaluation
- Add evaluation button (graduation cap icon) to research-block.tsx toolbar
- Add i18n translations for English and Chinese

The evaluation UI allows users to:
1. View quick metrics-only evaluation (instant)
2. Optionally run deep LLM-based evaluation for detailed analysis
3. See grade (A+ to F), score (1-10), and metric breakdown

* feat(eval): improve evaluation reliability and add LLM judge tests

- Extract MAX_REPORT_LENGTH constant in llm_judge.py for maintainability
- Add comprehensive unit tests for LLMJudge class (parse_response,
  calculate_weighted_score, evaluate with mocked LLM)
- Pass reportStyle prop to EvaluationDialog for accurate evaluation criteria
- Add researchQueries store map to reliably associate queries with research
- Add getResearchQuery helper to retrieve query by researchId
- Remove unused imports in test_metrics.py

* fix(eval): use resolveServiceURL for evaluate API endpoint

The evaluateReport function was using a relative URL '/api/report/evaluate'
which sent requests to the Next.js server instead of the FastAPI backend.
Changed to use resolveServiceURL() consistent with other API functions.

* fix: improve type accuracy and React hooks in evaluation components

- Fix get_word_count_target return type from Optional[Dict] to Dict since it always returns a value via default fallback
- Fix useEffect dependency issue in EvaluationDialog using useRef to prevent unwanted re-evaluations
- Add aria-label to GradeBadge for screen reader accessibility

web/messages/zh.json

@@ -150,6 +150,7 @@
       "downloadWord": "Word (.docx)",
       "downloadImage": "图片 (.png)",
       "exportFailed": "导出失败，请重试",
+      "evaluateReport": "评估报告质量",
       "searchingFor": "搜索",
       "reading": "阅读中",
       "runningPythonCode": "运行 Python 代码",
@@ -163,6 +164,31 @@
       "errorGeneratingPodcast": "生成播客时出错。请重试。",
       "downloadPodcast": "下载播客"
     },
+    "evaluation": {
+      "title": "报告质量评估",
+      "description": "使用自动化指标和 AI 分析评估您的报告。",
+      "evaluating": "正在评估报告...",
+      "analyzing": "正在进行深度分析...",
+      "overallScore": "总体评分",
+      "metrics": "报告指标",
+      "wordCount": "字数",
+      "citations": "引用数",
+      "sources": "独立来源",
+      "images": "图片数",
+      "sectionCoverage": "章节覆盖率",
+      "detailedAnalysis": "详细分析",
+      "deepEvaluation": "深度评估 (AI)",
+      "strengths": "优势",
+      "weaknesses": "改进建议",
+      "scores": {
+        "factual_accuracy": "事实准确性",
+        "completeness": "完整性",
+        "coherence": "连贯性",
+        "relevance": "相关性",
+        "citation_quality": "引用质量",
+        "writing_quality": "写作质量"
+      }
+    },
     "messages": {
       "replaying": "回放中",
       "replayDescription": "DeerFlow 正在回放对话...",