fix(fam-edge): 整视频上传方式修正 - Gemini 改 resumable 可续传协议(370MB 不再 raw 单发超时)；NVIDIA 改 Assets API 上传拿 asset_id(video_url 引用)，规避 25MB payload 上限

fam-edge/src/fam_edge/model_adapters/gemini_adapter.py

@@ -122,24 +122,52 @@ class GeminiAdapter(BaseModelAdapter):
             self._delete_file(file_uri)
 
     def _upload_file(self, video_path: str) -> Optional[str]:
-        """用 Files API 上传完整视频，返回可引用 URI。"""
+        """用 Files API resumable 可续传协议上传完整视频，返回可引用 URI。"""
         name = os.path.basename(video_path)
-        upload_url = f"{self._base_url}/files?key={self.api_key}"
+        size = os.path.getsize(video_path)
+        upload_timeout = max(self.timeout, 900)
+        base = f"{self._base_url}/files?key={self.api_key}"
+        # 1) 创建可续传上传会话
+        try:
+            r0 = requests.post(
+                base,
+                headers={
+                    "X-Goog-Upload-Protocol": "resumable",
+                    "X-Goog-Upload-Command": "start",
+                    "X-Goog-Upload-Header-Content-Length": str(size),
+                    "X-Goog-Upload-Header-Content-Type": "video/mp4",
+                    "X-Goog-Upload-File-Name": name,
+                    "Content-Type": "application/json",
+                },
+                json={"file": {"display_name": name}},
+                timeout=60,
+            )
+        except Exception as e:
+            logger.error(f"Gemini 创建上传会话异常: {e}")
+            return None
+        if r0.status_code not in (200, 201):
+            logger.warning(f"Gemini 创建上传会话失败 HTTP {r0.status_code}: {r0.text[:200]}")
+            return None
+        session_url = r0.headers.get('X-Goog-Upload-URL')
+        if not session_url:
+            logger.warning("Gemini 上传响应缺少 X-Goog-Upload-URL")
+            return None
+        # 2) 上传文件体（流式）
         try:
             with open(video_path, 'rb') as f:
-                data = f.read()
+                resp = requests.post(
-        except OSError as e:
+                    session_url,
-            logger.error(f"读取视频失败 {video_path}: {e}")
+                    headers={
-            return None
+                        "Content-Length": str(size),
-        headers = {
+                        "X-Goog-Upload-Command": "upload, finalize",
-            "X-Goog-Upload-Protocol": "raw",
+                        "X-Goog-Upload-Offset": "0",
-            "X-Goog-Upload-File-Name": name,
                         "Content-Type": "video/mp4",
-        }
+                    },
-        try:
+                    data=f,
-            resp = requests.post(upload_url, headers=headers, data=data, timeout=300)
+                    timeout=upload_timeout,
+                )
         except requests.Timeout:
-            logger.warning("Gemini 文件上传超时 (300s)")
+            logger.warning(f"Gemini 文件上传超时 ({upload_timeout}s)")
             return None
         except Exception as e:
             logger.error(f"Gemini 文件上传异常: {e}")

fam-edge/src/fam_edge/model_adapters/nvidia_adapter.py

@@ -5,12 +5,13 @@ provider_name = "nvidia"
 模型: nvidia/nemotron-nano-12b-v2-vl（NIM 官方支持整视频 video_url 输入，内部自行采样帧）
 角色: vision (整视频直出结构化 JSON) + 智能问答
 SDK: openai (NIM 兼容 OpenAI API 规范)
-整视频分析: 整视频 base64 经 video_url 单次调用 —— 本地不切片、不抽帧
+整视频分析: 先经 NVIDIA Assets API 上传完整视频拿 asset_id，再以 video_url 引用单次调用
+  —— 本地不切片、不抽帧（request payload 有 25MB 上限，base64 直塞不可行，必须走 Assets API）
 """
 import os
-import base64
 import json
 import re
+import requests
 from typing import Dict, List, Optional
 
 from .base_adapter import BaseModelAdapter
@@ -67,8 +68,59 @@ class NvidiaVisionAdapter(BaseModelAdapter):
             return False
 
     # ------------------------------------------------------------------
-    # 整视频分析：base64 整视频 -> video_url 单次调用
+    # 整视频分析：Assets API 上传 -> video_url(asset_id) 单次调用
     # ------------------------------------------------------------------
+    ASSET_API = "https://api.nvcf.nvidia.com/v2/nvcf/assets"
+
+    def _upload_asset(self, video_path: str) -> Optional[str]:
+        """用 NVIDIA Assets API 上传大视频文件，返回 asset_id 供 video_url 引用。"""
+        upload_timeout = max(self.timeout, 900)
+        try:
+            r = requests.post(
+                self.ASSET_API,
+                headers={
+                    "Authorization": f"Bearer {self.api_key}",
+                    "Content-Type": "application/json",
+                },
+                json={"contentType": "video/mp4", "description": "fam-edge video asset"},
+                timeout=60,
+            )
+        except Exception as e:
+            logger.warning(f"NVIDIA 创建 asset 异常: {e}")
+            return None
+        if r.status_code not in (200, 201):
+            logger.warning(f"NVIDIA 创建 asset 失败 HTTP {r.status_code}: {r.text[:200]}")
+            return None
+        try:
+            j = r.json()
+            asset_id = j.get("assetId")
+            upload_url = j.get("uploadUrl")
+        except ValueError:
+            logger.warning("NVIDIA asset 响应解析失败")
+            return None
+        if not asset_id or not upload_url:
+            logger.warning("NVIDIA asset 响应缺少 assetId/uploadUrl")
+            return None
+        try:
+            with open(video_path, 'rb') as f:
+                up = requests.put(
+                    upload_url,
+                    data=f,
+                    headers={"Content-Type": "application/octet-stream"},
+                    timeout=upload_timeout,
+                )
+        except requests.Timeout:
+            logger.warning(f"NVIDIA 上传 asset 超时 ({upload_timeout}s)")
+            return None
+        except Exception as e:
+            logger.warning(f"NVIDIA 上传 asset 异常: {e}")
+            return None
+        if up.status_code not in (200, 201):
+            logger.warning(f"NVIDIA 上传 asset 失败 HTTP {up.status_code}: {up.text[:200]}")
+            return None
+        logger.info(f"NVIDIA asset 上传成功: {asset_id}")
+        return asset_id
+
     def analyze_video(self, video_path: str,
                      known_members_context: str,
                      event_start_time: str = '') -> Optional[Dict]:
@@ -82,11 +134,9 @@ class NvidiaVisionAdapter(BaseModelAdapter):
             logger.warning(f"NVIDIA 视频文件不存在: {video_path}")
             return None
 
-        try:
+        asset_id = self._upload_asset(video_path)
-            with open(video_path, 'rb') as f:
+        if not asset_id:
-                b64 = base64.b64encode(f.read()).decode('utf-8')
+            self._cb.record_failure()
-        except Exception as e:
-            logger.warning(f"NVIDIA 读取视频失败: {e}")
             return None
 
         prompt = self._build_video_prompt(known_members_context, event_start_time)
@@ -96,7 +146,7 @@ class NvidiaVisionAdapter(BaseModelAdapter):
                 messages=[{"role": "user", "content": [
                     {"type": "text", "text": prompt},
                     {"type": "video_url", "video_url": {
-                        "url": f"data:video/mp4;base64,{b64}"}}
+                        "url": f"data:video/mp4;asset_id={asset_id}"}}
                 ]}],
                 temperature=0.2,
                 max_tokens=4096,