feat: 新增 OCR 单据字段精确提取模块

- 新增 backend/ocr_extractor.py: 两阶段提取流水线 (文档分析 + 字段提取)
- 四种提取策略: 精确KV匹配/模糊KV匹配/正则模式/表格结构匹配
- agent/state.py: 新增 ocr_extraction_result 和 uploaded_file_path 字段
- agent/nodes.py: process_input() 中自动触发 OCR 提取钩子
- app.py: 文件上传时保留图片路径, 总结卡片中展示提取结果
- .env.example: 新增 OCR_USE_GPU / OCR_CONFIDENCE_THRESHOLD 配置项
- tests/test_ocr_extraction.py: 48 个单元测试全部通过

app.py

@@ -261,6 +261,14 @@ def run_agent(user_input: str):
     if stream_active:
         streaming_placeholder.empty()
 
+    # 清理已处理的临时文件
+    for p in st.session_state.get("uploaded_temp_paths", []):
+        try:
+            Path(p).unlink(missing_ok=True)
+        except Exception:
+            pass
+    st.session_state.uploaded_temp_paths = []
+
     # ---- 总结卡片 ----
     # 注：node_state 只含变更字段，用 agent_state（被所有节点就地修改）获取完整状态
     final_state = agent_state
@@ -324,6 +332,30 @@ def run_agent(user_input: str):
                     "content": f"❌ 经过 {retries} 次重试后仍无法生成有效的 JRXML。\n\n**错误:** {error_msg}\n\n💡 请直接描述修改需求，系统会自动加载失败上下文。",
                     "type": "error_explanation",
                 })
+
+            # OCR 字段提取结果展示
+            ocr_result = agent_state.get("ocr_extraction_result", {})
+            if ocr_result and ocr_result.get("ocr_available") and ocr_result.get("fields"):
+                with st.expander("🔍 OCR 单据字段提取结果", expanded=False):
+                    fields = ocr_result.get("fields", [])
+                    non_empty = [f for f in fields if f.get("field_value")]
+                    empty = [f for f in fields if not f.get("field_value")]
+                    if non_empty:
+                        st.markdown("**已提取字段:**")
+                        for f in non_empty:
+                            method = f.get("extraction_method", "")
+                            conf = f.get("confidence", 0)
+                            st.markdown(
+                                f"- **{f['field_name']}**: `{f['field_value']}` "
+                                f"（置信度: {conf:.0%}, 方法: {method}）"
+                            )
+                    if empty:
+                        st.caption(
+                            f"未提取到值的字段: {', '.join(f['field_name'] for f in empty)}"
+                        )
+                    st.caption(
+                        f"共检测到 {ocr_result.get('total_elements', 0)} 个文本元素"
+                    )
     else:
         st.error("未产生结果，请重试。")
 
@@ -443,6 +475,9 @@ with st.sidebar:
     if "uploaded_files" not in st.session_state:
         st.session_state.uploaded_files = []  # [{name, text, type}]
 
+    if "uploaded_temp_paths" not in st.session_state:
+        st.session_state.uploaded_temp_paths = []  # 待清理的临时文件路径
+
     uploaded = st.file_uploader(
         "选择文件",
         type=["png", "jpg", "jpeg", "bmp", "webp", "pdf", "docx", "txt", "csv", "json", "xml"],
@@ -513,8 +548,6 @@ with st.sidebar:
                         )
                     parsed_type = "image_reference"
 
-            Path(tmp_path).unlink(missing_ok=True)
-
             if parsed_text:
                 st.session_state.uploaded_files.append({
                     "name": uf.name,
@@ -522,6 +555,14 @@ with st.sidebar:
                     "type": parsed_type,
                 })
 
+            # 对图片类型，保存路径以便 OCR 字段提取（延迟到 process_input 阶段）
+            img_suffixes = (".png", ".jpg", ".jpeg", ".bmp", ".webp")
+            if suffix in img_suffixes and result.get("method") not in ("metadata_only", None):
+                st.session_state.agent_state["uploaded_file_path"] = tmp_path
+                st.session_state.uploaded_temp_paths.append(tmp_path)
+            else:
+                Path(tmp_path).unlink(missing_ok=True)
+
     if st.session_state.uploaded_files:
         for i, f in enumerate(st.session_state.uploaded_files):
             cols = st.columns([5, 1])