feat(note): 添加视频理解功能- 在 GPT 模型中增加 video_img_urls 字段用于存储视频截图

- 在笔记生成请求中添加视频理解相关参数
- 实现视频截图功能，支持按指定间隔生成截图
- 更新笔记生成逻辑，支持视频理解功能- 在前端服务中添加视频理解相关参数

backend/app/utils/video_reader.py

@@ -0,0 +1,134 @@
+import base64
+import os
+import re
+import subprocess
+import ffmpeg
+from PIL import Image, ImageDraw, ImageFont
+
+from app.utils.logger import get_logger
+
+logger = get_logger(__name__)
+class VideoReader:
+    def __init__(self,
+                 video_path: str,
+                 grid_size=(3, 3),
+                 frame_interval=2,
+                 unit_width=960,
+                 unit_height=540,
+                 save_quality=90,
+                 font_path="fonts/arial.ttf",
+                 frame_dir="data/output_frames",
+                 grid_dir="data/grid_output"):
+        self.video_path = video_path
+        self.grid_size = grid_size
+        self.frame_interval = frame_interval
+        self.unit_width = unit_width
+        self.unit_height = unit_height
+        self.save_quality = save_quality
+        self.font_path = font_path
+        self.frame_dir = frame_dir
+        self.grid_dir = grid_dir
+
+    def format_time(self, seconds: float) -> str:
+        mm = int(seconds // 60)
+        ss = int(seconds % 60)
+        return f"{mm:02d}_{ss:02d}"
+
+    def extract_time_from_filename(self, filename: str) -> float:
+        match = re.search(r"frame_(\d{2})_(\d{2})\.jpg", filename)
+        if match:
+            mm, ss = map(int, match.groups())
+            return mm * 60 + ss
+        return float('inf')
+
+    def extract_frames(self, max_frames=1000) -> list[str]:
+
+        try:
+            os.makedirs(self.frame_dir, exist_ok=True)
+            duration = float(ffmpeg.probe(self.video_path)["format"]["duration"])
+            timestamps = [i for i in range(0, int(duration), self.frame_interval)][:max_frames]
+
+            image_paths = []
+            for ts in timestamps:
+                time_label = self.format_time(ts)
+                output_path = os.path.join(self.frame_dir, f"frame_{time_label}.jpg")
+                cmd = ["ffmpeg", "-ss", str(ts), "-i", self.video_path, "-frames:v", "1", "-q:v", "2", "-y", output_path,
+                       "-hide_banner", "-loglevel", "error"]
+                subprocess.run(cmd, check=True)
+                image_paths.append(output_path)
+            return image_paths
+        except Exception as e:
+            logger.error(f"分割帧发生错误：{str(e)}")
+            raise ValueError("视频处理失败")
+
+    def group_images(self) -> list[list[str]]:
+        image_files = [os.path.join(self.frame_dir, f) for f in os.listdir(self.frame_dir) if
+                       f.startswith("frame_") and f.endswith(".jpg")]
+        image_files.sort(key=lambda f: self.extract_time_from_filename(os.path.basename(f)))
+        group_size = self.grid_size[0] * self.grid_size[1]
+        return [image_files[i:i + group_size] for i in range(0, len(image_files), group_size)]
+
+    def concat_images(self, image_paths: list[str], name: str) -> str:
+        os.makedirs(self.grid_dir, exist_ok=True)
+        font = ImageFont.truetype(self.font_path, 48) if os.path.exists(self.font_path) else ImageFont.load_default()
+        images = []
+
+        for path in image_paths:
+            img = Image.open(path).convert("RGB").resize((self.unit_width, self.unit_height), Image.Resampling.LANCZOS)
+            timestamp = re.search(r"frame_(\d{2})_(\d{2})\.jpg", os.path.basename(path))
+            time_text = f"{timestamp.group(1)}:{timestamp.group(2)}" if timestamp else ""
+            draw = ImageDraw.Draw(img)
+            draw.text((10, 10), time_text, fill="yellow", font=font, stroke_width=1, stroke_fill="black")
+            images.append(img)
+
+        cols, rows = self.grid_size
+        grid_img = Image.new("RGB", (self.unit_width * cols, self.unit_height * rows), (255, 255, 255))
+
+        for i, img in enumerate(images):
+            x = (i % cols) * self.unit_width
+            y = (i // cols) * self.unit_height
+            grid_img.paste(img, (x, y))
+
+        save_path = os.path.join(self.grid_dir, f"{name}.jpg")
+        grid_img.save(save_path, quality=self.save_quality)
+        return save_path
+
+    def encode_images_to_base64(self, image_paths: list[str]) -> list[str]:
+        base64_images = []
+        for path in image_paths:
+            with open(path, "rb") as img_file:
+                encoded_string = base64.b64encode(img_file.read()).decode("utf-8")
+                base64_images.append(f"data:image/jpeg;base64,{encoded_string}")
+        return base64_images
+
+    def run(self)->list[str]:
+        logger.info("🚀 开始提取视频帧...")
+        try:
+            #清空帧文件夹
+            for file in os.listdir(self.frame_dir):
+                if file.startswith("frame_"):
+                    os.remove(os.path.join(self.frame_dir, file))
+            #清空网格文件夹
+            for file in os.listdir(self.grid_dir):
+                if file.startswith("grid_"):
+                    os.remove(os.path.join(self.grid_dir, file))
+            self.extract_frames()
+
+            logger.info("🧩 开始拼接网格图...")
+            image_paths = []
+            groups = self.group_images()
+            for idx, group in enumerate(groups, start=1):
+                if len(group) < self.grid_size[0] * self.grid_size[1]:
+                    logger.warning(f"⚠️ 跳过第 {idx} 组，图片不足 {self.grid_size[0] * self.grid_size[1]} 张")
+                    continue
+                out_path = self.concat_images(group, f"grid_{idx}")
+                image_paths.append(out_path)
+
+            logger.info("📤 开始编码图像...")
+            urls = self.encode_images_to_base64(image_paths)
+            return urls
+        except Exception as e:
+            logger.error(f"发生错误：{str(e)}")
+            raise ValueError("视频处理失败")
+
+