{"id":204998,"date":"2025-05-29T13:41:32","date_gmt":"2025-05-29T05:41:32","guid":{"rendered":"https:\/\/server.hk\/cnblog\/204998\/"},"modified":"2025-05-29T13:41:32","modified_gmt":"2025-05-29T05:41:32","slug":"%e4%bd%bf%e7%94%a8-gemini-flash-%e6%9e%84%e5%bb%ba%e8%a7%86%e9%a2%91%e6%b4%9e%e5%af%9f%e7%94%9f%e6%88%90%e5%99%a8","status":"publish","type":"post","link":"https:\/\/server.hk\/cnblog\/204998\/","title":{"rendered":"\u4f7f\u7528 Gemini Flash \u6784\u5efa\u89c6\u9891\u6d1e\u5bdf\u751f\u6210\u5668"},"content":{"rendered":"<p><b><\/b>     <\/p>\n<h1>\u4f7f\u7528 Gemini Flash \u6784\u5efa\u89c6\u9891\u6d1e\u5bdf\u751f\u6210\u5668<\/h1>\n<p>\u4e00\u5206\u8015\u8018\uff0c\u4e00\u5206\u6536\u83b7\uff01\u65e2\u7136\u6253\u5f00\u4e86\u8fd9\u7bc7\u6587\u7ae0<span style=\"color: #FF6600;, Helvetica, Arial, sans-serif;font-size: 14px;background-color: #FFFFFF\">\u300a\u4f7f\u7528 Gemini Flash \u6784\u5efa\u89c6\u9891\u6d1e\u5bdf\u751f\u6210\u5668\u300b<\/span>\uff0c\u5c31\u575a\u6301\u770b\u4e0b\u53bb\u5427\uff01\u6587\u4e2d\u5185\u5bb9\u5305\u542b<span style=\"color: #FF6600;, Helvetica, Arial, sans-serif;font-size: 14px;background-color: #FFFFFF\"><\/span>\u7b49\u7b49\u77e5\u8bc6\u70b9&#8230;\u5e0c\u671b\u4f60\u80fd\u5728\u9605\u8bfb\u672c\u6587\u540e\uff0c\u80fd\u771f\u771f\u5b9e\u5b9e\u5b66\u5230\u77e5\u8bc6\u6216\u8005\u5e2e\u4f60\u89e3\u51b3\u5fc3\u4e2d\u7684\u7591\u60d1\uff0c\u4e5f\u6b22\u8fce\u5927\u4f6c\u6216\u8005\u65b0\u4eba\u670b\u53cb\u4eec\u591a\u7559\u8a00\u8bc4\u8bba\uff0c\u591a\u7ed9\u5efa\u8bae\uff01\u8c22\u8c22\uff01<\/p>\n<p>\u89c6\u9891\u7406\u89e3\u6216\u89c6\u9891\u6d1e\u5bdf\u7531\u4e8e\u5176\u591a\u65b9\u9762\u7684\u4f18\u52bf\u800c\u5728\u5404\u4e2a\u884c\u4e1a\u548c\u5e94\u7528\u4e2d\u81f3\u5173\u91cd\u8981\u3002\u5b83\u4eec\u901a\u8fc7\u81ea\u52a8\u751f\u6210\u5143\u6570\u636e\u3001\u5bf9\u5185\u5bb9\u8fdb\u884c\u5206\u7c7b\u5e76\u4f7f\u89c6\u9891\u66f4\u6613\u4e8e\u641c\u7d22\u6765\u589e\u5f3a\u5185\u5bb9\u5206\u6790\u548c\u7ba1\u7406\u3002\u6b64\u5916\uff0c\u89c6\u9891\u6d1e\u5bdf\u63d0\u4f9b\u4e86\u63a8\u52a8\u51b3\u7b56\u3001\u589e\u5f3a\u7528\u6237\u4f53\u9a8c\u5e76\u63d0\u9ad8\u4e0d\u540c\u884c\u4e1a\u8fd0\u8425\u6548\u7387\u7684\u5173\u952e\u6570\u636e\u3002<\/p>\n<p>google \u7684 gemini 1.5 \u6a21\u578b\u4e3a\u8be5\u9886\u57df\u5e26\u6765\u4e86\u91cd\u5927\u8fdb\u6b65\u3002\u9664\u4e86\u5728\u8bed\u8a00\u5904\u7406\u65b9\u9762\u4ee4\u4eba\u5370\u8c61\u6df1\u523b\u7684\u6539\u8fdb\u4e4b\u5916\uff0c\u8be5\u6a21\u578b\u8fd8\u53ef\u4ee5\u5904\u7406\u591a\u8fbe 100 \u4e07\u4e2a\u6807\u8bb0\u7684\u5de8\u5927\u8f93\u5165\u4e0a\u4e0b\u6587\u3002\u4e3a\u4e86\u8fdb\u4e00\u6b65\u589e\u5f3a\u5176\u529f\u80fd\uff0cgemini 1.5 \u88ab\u8bad\u7ec3\u4e3a\u591a\u6a21\u5f0f\u6a21\u578b\uff0c\u53ef\u4ee5\u672c\u5730\u5904\u7406\u6587\u672c\u3001\u56fe\u50cf\u3001\u97f3\u9891\u548c\u89c6\u9891\u3002\u5404\u79cd\u8f93\u5165\u7c7b\u578b\u548c\u5e7f\u6cdb\u7684\u4e0a\u4e0b\u6587\u5927\u5c0f\u7684\u5f3a\u5927\u7ec4\u5408\u4e3a\u6709\u6548\u5904\u7406\u957f\u89c6\u9891\u5f00\u8f9f\u4e86\u65b0\u7684\u53ef\u80fd\u6027\u3002<\/p>\n<p>\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u5229\u7528 gemini 1.5 \u751f\u6210\u6709\u4ef7\u503c\u7684\u89c6\u9891\u89c1\u89e3\uff0c\u6539\u53d8\u6211\u4eec\u8de8\u4e0d\u540c\u9886\u57df\u7406\u89e3\u548c\u5229\u7528\u89c6\u9891\u5185\u5bb9\u7684\u65b9\u5f0f\u3002<\/p>\n<ul>\n<li>\u4ec0\u4e48\u662f gemini 1.5<\/li>\n<li>\u5148\u51b3\u6761\u4ef6<\/li>\n<li>\u5b89\u88c5\u4f9d\u8d56\u9879<\/li>\n<li>\u8bbe\u7f6e gemini api \u5bc6\u94a5<\/li>\n<li>\u8bbe\u7f6e\u73af\u5883\u53d8\u91cf<\/li>\n<li>\u5bfc\u5165\u5e93<\/li>\n<li>\u521d\u59cb\u5316\u9879\u76ee<\/li>\n<li>\u4fdd\u5b58\u4e0a\u4f20\u7684\u6587\u4ef6<\/li>\n<li>\u4ece\u89c6\u9891\u4e2d\u751f\u6210\u89c1\u89e3<\/li>\n<li>\u5c06\u89c6\u9891\u4e0a\u4f20\u5230\u6587\u4ef6 api<\/li>\n<li>\u83b7\u53d6\u6587\u4ef6<\/li>\n<li>\u54cd\u5e94\u751f\u6210<\/li>\n<li>\u5220\u9664\u6587\u4ef6<\/li>\n<li>\u7ec4\u5408\u5404\u4e2a\u9636\u6bb5<\/li>\n<li>\u521b\u5efa\u754c\u9762<\/li>\n<li>\u521b\u5efa streamlit \u5e94\u7528\u7a0b\u5e8f<\/li>\n<\/ul>\n<p>google \u7684 gemini 1.5 \u4ee3\u8868\u4e86\u4eba\u5de5\u667a\u80fd\u6027\u80fd\u548c\u6548\u7387\u7684\u91cd\u5927\u98de\u8dc3\u3002\u8be5\u6a21\u578b\u5efa\u7acb\u5728\u5e7f\u6cdb\u7684\u7814\u7a76\u548c\u5de5\u7a0b\u521b\u65b0\u7684\u57fa\u7840\u4e0a\uff0c\u91c7\u7528\u65b0\u7684\u4e13\u5bb6\u6df7\u5408 (moe) \u67b6\u6784\uff0c\u63d0\u9ad8\u4e86\u57f9\u8bad\u548c\u670d\u52a1\u6548\u7387\u3002 gemini 1.5 pro \u548c 1.5 flash \u73b0\u5df2\u63a8\u51fa\u516c\u5171\u9884\u89c8\u7248\uff0c\u901a\u8fc7 google ai studio \u548c vertex ai \u63d0\u4f9b\u4e86\u4ee4\u4eba\u5370\u8c61\u6df1\u523b\u7684 100 \u4e07\u4e2a\u4ee3\u5e01\u4e0a\u4e0b\u6587\u7a97\u53e3\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.17golang.com\/uploads\/20241121\/1732161288673eaf08b5066.jpg\" class=\"aligncenter\"><\/p>\n<p>google gemini \u66f4\u65b0\uff1aflash 1.5\u3001gemma 2 \u548c project astra (blog.google)<br \/> 1.5 flash \u578b\u53f7\u662f gemini \u7cfb\u5217\u7684\u6700\u65b0\u6210\u5458\uff0c\u5bf9\u4e8e\u5927\u5bb9\u91cf\u3001\u9ad8\u9891\u4efb\u52a1\u6765\u8bf4\u901f\u5ea6\u6700\u5feb\u4e14\u6700\u4f18\u5316\u3002\u5b83\u4e13\u4e3a\u5b9e\u73b0\u6210\u672c\u6548\u76ca\u800c\u8bbe\u8ba1\uff0c\u5728\u6458\u8981\u3001\u804a\u5929\u3001\u56fe\u50cf\u548c\u89c6\u9891\u5b57\u5e55\u4ee5\u53ca\u4ece\u5927\u91cf\u6587\u6863\u548c\u8868\u683c\u4e2d\u63d0\u53d6\u6570\u636e\u7b49\u5e94\u7528\u4e2d\u8868\u73b0\u51fa\u8272\u3002\u51ed\u501f\u8fd9\u4e9b\u8fdb\u6b65\uff0cgemini 1.5 \u4e3a ai \u6a21\u578b\u7684\u6027\u80fd\u548c\u591a\u529f\u80fd\u6027\u6811\u7acb\u4e86\u65b0\u6807\u51c6\u3002<\/p>\n<ul>\n<li> python 3.9+ (https:\/\/www.python.org\/downloads)<\/li>\n<li>\u8c37\u6b4c\u751f\u6210ai<\/li>\n<li>\u6d41\u7ebf\u578b<\/li>\n<\/ul>\n<ul>\n<li>\u901a\u8fc7\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4\u521b\u5efa\u5e76\u6fc0\u6d3b\u865a\u62df\u73af\u5883\u3002 <\/li>\n<\/ul>\n<pre>python -m venv venv\nsource venv\/bin\/activate #for ubuntu\nvenv\/scripts\/activate #for windows\n<\/pre>\n<ul>\n<li>\u4f7f\u7528 pip \u5b89\u88c5 google-generativeai\u3001streamlit\u3001python-dotenv \u5e93\u3002\u8bf7\u6ce8\u610f\uff0cgenerativeai \u9700\u8981 python 3.9+ \u7248\u672c\u624d\u80fd\u5de5\u4f5c\u3002 <\/li>\n<\/ul>\n<pre>pip install google-generativeai streamlit python-dotenv\n<\/pre>\n<p>\u8981\u8bbf\u95ee gemini api \u5e76\u5f00\u59cb\u4f7f\u7528\u5176\u529f\u80fd\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u6ce8\u518c google ai studio \u6765\u83b7\u53d6\u514d\u8d39\u7684 google api \u5bc6\u94a5\u3002 google ai studio \u7531 google \u63d0\u4f9b\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u7528\u6237\u53cb\u597d\u7684\u3001\u57fa\u4e8e\u89c6\u89c9\u7684\u754c\u9762\uff0c\u7528\u4e8e\u4e0e gemini api \u8fdb\u884c\u4ea4\u4e92\u3002\u5728 google ai studio \u4e2d\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u5176\u76f4\u89c2\u7684 ui \u65e0\u7f1d\u5730\u4e0e\u751f\u6210\u6a21\u578b\u4ea4\u4e92\uff0c\u5982\u679c\u9700\u8981\uff0c\u8fd8\u53ef\u4ee5\u751f\u6210 api \u4ee4\u724c\u4ee5\u589e\u5f3a\u63a7\u5236\u548c\u81ea\u5b9a\u4e49\u3002<\/p>\n<p>\u6309\u7167\u4ee5\u4e0b\u6b65\u9aa4\u751f\u6210 gemini api \u5bc6\u94a5\uff1a<\/p>\n<ul>\n<li>\u8981\u542f\u52a8\u6b64\u8fc7\u7a0b\uff0c\u60a8\u53ef\u4ee5\u5355\u51fb\u94fe\u63a5 (https:\/\/aistudio.google.com\/app) \u4ee5\u91cd\u5b9a\u5411\u5230 google ai studio\uff0c\u6216\u8005\u5728 google \u4e0a\u6267\u884c\u5feb\u901f\u641c\u7d22\u4ee5\u627e\u5230\u5b83\u3002<\/li>\n<li>\u63a5\u53d7\u670d\u52a1\u6761\u6b3e\u5e76\u5355\u51fb\u7ee7\u7eed\u3002<\/li>\n<li>\u70b9\u51fb\u4fa7\u8fb9\u680f\u7684\u83b7\u53d6 api \u5bc6\u94a5\u94fe\u63a5\u548c\u5728\u65b0\u9879\u76ee\u4e2d\u521b\u5efa api \u5bc6\u94a5\u6309\u94ae\u6765\u751f\u6210\u5bc6\u94a5\u3002<\/li>\n<li>\u590d\u5236\u751f\u6210\u7684 api \u5bc6\u94a5\u3002<\/li>\n<\/ul>\n<p><img decoding=\"async\" src=\"https:\/\/www.17golang.com\/uploads\/20241121\/1732161288673eaf08b8687.jpg\" class=\"aligncenter\"><\/p>\n<p>\u9996\u5148\u4e3a\u60a8\u7684\u9879\u76ee\u521b\u5efa\u4e00\u4e2a\u65b0\u6587\u4ef6\u5939\u3002\u9009\u62e9\u4e00\u4e2a\u80fd\u591f\u53cd\u6620\u60a8\u9879\u76ee\u76ee\u7684\u7684\u540d\u79f0\u3002<br \/> \u5728\u65b0\u9879\u76ee\u6587\u4ef6\u5939\u4e2d\uff0c\u521b\u5efa\u4e00\u4e2a\u540d\u4e3a .env \u7684\u6587\u4ef6\u3002\u8be5\u6587\u4ef6\u5c06\u5b58\u50a8\u60a8\u7684\u73af\u5883\u53d8\u91cf\uff0c\u5305\u62ec\u60a8\u7684 gemini api \u5bc6\u94a5\u3002<br \/> \u6253\u5f00 .env \u6587\u4ef6\u5e76\u6dfb\u52a0\u4ee5\u4e0b\u4ee3\u7801\u6765\u6307\u5b9a\u60a8\u7684 gemini api \u5bc6\u94a5\uff1a<\/p>\n<pre>google_api_key=aizasy......\n<\/pre>\n<p>\u8981\u5f00\u59cb\u60a8\u7684\u9879\u76ee\u5e76\u786e\u4fdd\u60a8\u62e5\u6709\u6240\u6709\u5fc5\u8981\u7684\u5de5\u5177\uff0c\u60a8\u9700\u8981\u5bfc\u5165\u51e0\u4e2a\u5173\u952e\u5e93\uff0c\u5982\u4e0b\u6240\u793a\u3002<\/p>\n<pre>import os\nimport time\nimport google.generativeai as genai\nimport streamlit as st\nfrom dotenv import load_dotenv\n<\/pre>\n<ul>\n<li> google.generativeai as genai\uff1a\u5bfc\u5165 google generative ai \u5e93\u4ee5\u4e0e gemini api \u4ea4\u4e92\u3002<\/li>\n<li> streamlit as st\uff1a\u5bfc\u5165 streamlit \u7528\u4e8e\u521b\u5efa web \u5e94\u7528\u7a0b\u5e8f\u3002<\/li>\n<li> from dotenv import load_dotenv\uff1a\u4ece .env \u6587\u4ef6\u52a0\u8f7d\u73af\u5883\u53d8\u91cf\u3002<\/li>\n<\/ul>\n<p>\u8981\u8bbe\u7f6e\u60a8\u7684\u9879\u76ee\uff0c\u60a8\u9700\u8981\u914d\u7f6e api \u5bc6\u94a5\u5e76\u4e3a\u4e0a\u4f20\u7684\u6587\u4ef6\u521b\u5efa\u4e34\u65f6\u6587\u4ef6\u5b58\u50a8\u76ee\u5f55\u3002<\/p>\n<p>\u901a\u8fc7\u521d\u59cb\u5316\u5fc5\u8981\u7684\u8bbe\u7f6e\u6765\u5b9a\u4e49\u5a92\u4f53\u6587\u4ef6\u5939\u5e76\u914d\u7f6e gemini api \u5bc6\u94a5\u3002\u5c06\u4ee5\u4e0b\u4ee3\u7801\u6dfb\u52a0\u5230\u60a8\u7684\u811a\u672c\u4e2d\uff1a<\/p>\n<pre>media_folder = 'medias'\n\ndef __init__():\n    # create the media directory if it doesn't exist\n    if not os.path.exists(media_folder):\n        os.makedirs(media_folder)\n\n    # load environment variables from the .env file\n    load_dotenv()\n\n    # retrieve the api key from the environment variables\n    api_key = os.getenv(\"gemini_api_key\")\n\n    # configure the gemini api with your api key\n    genai.configure(api_key=api_key)\n<\/pre>\n<p>\u8981\u5c06\u4e0a\u4f20\u7684\u6587\u4ef6\u5b58\u50a8\u5728\u5a92\u4f53\u6587\u4ef6\u5939\u4e2d\u5e76\u8fd4\u56de\u5176\u8def\u5f84\uff0c\u8bf7\u5b9a\u4e49\u4e00\u4e2a\u540d\u4e3a save_uploaded_file \u7684\u65b9\u6cd5\u5e76\u5411\u5176\u4e2d\u6dfb\u52a0\u4ee5\u4e0b\u4ee3\u7801\u3002<\/p>\n<pre>def save_uploaded_file(uploaded_file):\n    \"\"\"save the uploaded file to the media folder and return the file path.\"\"\"\n    file_path = os.path.join(media_folder, uploaded_file.name)\n    with open(file_path, 'wb') as f:\n        f.write(uploaded_file.read())\n    return file_path\n<\/pre>\n<p>\u4ece\u89c6\u9891\u4e2d\u751f\u6210\u89c1\u89e3\u6d89\u53ca\u51e0\u4e2a\u5173\u952e\u9636\u6bb5\uff0c\u5305\u62ec\u4e0a\u4f20\u3001\u5904\u7406\u548c\u751f\u6210\u54cd\u5e94\u3002<\/p>\n<h4> 1. \u5c06\u89c6\u9891\u4e0a\u4f20\u5230files api <\/h4>\n<p>gemini api \u76f4\u63a5\u63a5\u53d7\u89c6\u9891\u6587\u4ef6\u683c\u5f0f\u3002\u6587\u4ef6 api \u652f\u6301\u6700\u5927 2gb \u7684\u6587\u4ef6\uff0c\u5e76\u5141\u8bb8\u6bcf\u4e2a\u9879\u76ee\u6700\u5927\u5b58\u50a8 20gb\u3002\u4e0a\u4f20\u7684\u6587\u4ef6\u4fdd\u7559 2 \u5929\uff0c\u5e76\u4e14\u65e0\u6cd5\u4ece api \u4e0b\u8f7d\u3002<\/p>\n<pre>video_file = genai.upload_file(path=video_path)\n<\/pre>\n<h4> 2. \u83b7\u53d6\u6587\u4ef6 <\/h4>\n<p>\u4e0a\u4f20\u6587\u4ef6\u540e\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528files.get\u65b9\u6cd5\u9a8c\u8bc1api\u662f\u5426\u5df2\u6210\u529f\u63a5\u6536\u6587\u4ef6\u3002\u6b64\u65b9\u6cd5\u5141\u8bb8\u60a8\u67e5\u770b\u4e0a\u4f20\u5230\u6587\u4ef6 api \u7684\u6587\u4ef6\uff0c\u8fd9\u4e9b\u6587\u4ef6\u4e0e\u94fe\u63a5\u5230\u60a8\u7684 api \u5bc6\u94a5\u7684\u4e91\u9879\u76ee\u5173\u8054\u3002\u53ea\u6709\u6587\u4ef6\u540d\u548c uri \u662f\u552f\u4e00\u6807\u8bc6\u7b26\u3002<\/p>\n<pre>import time\n\nwhile video_file.state.name == \"processing\":\n    print('waiting for video to be processed.')\n    time.sleep(10)\n    video_file = genai.get_file(video_file.name)\n\nif video_file.state.name == \"failed\":\n  raise valueerror(video_file.state.name)\n<\/pre>\n<h4> 3. \u54cd\u5e94\u751f\u6210 <\/h4>\n<p>\u89c6\u9891\u4e0a\u4f20\u540e\uff0c\u60a8\u53ef\u4ee5\u53d1\u51fa\u5f15\u7528\u6587\u4ef6 api uri \u7684generatecontent \u8bf7\u6c42\u3002<\/p>\n<pre># create the prompt.\nprompt = \"describe the video. provides the insights from the video.\"\n\n# set the model to gemini 1.5 flash.\nmodel = genai.generativemodel(model_name=\"models\/gemini-1.5-flash\")\n\n# make the llm request.\nprint(\"making llm inference request...\")\nresponse = model.generate_content([prompt, video_file],\n                                  request_options={\"timeout\": 600})\nprint(response.text)\n<\/pre>\n<h4> 4. \u5220\u9664\u6587\u4ef6 <\/h4>\n<p>\u6587\u4ef6\u4f1a\u5728 2 \u5929\u540e\u81ea\u52a8\u5220\u9664\uff0c\u6216\u8005\u60a8\u53ef\u4ee5\u4f7f\u7528 files.delete() \u624b\u52a8\u5220\u9664\u5b83\u4eec\u3002<\/p>\n<pre>genai.delete_file(video_file.name)\n<\/pre>\n<h4> 5. \u7ed3\u5408\u5404\u4e2a\u9636\u6bb5 <\/h4>\n<p>\u521b\u5efa\u4e00\u4e2a\u540d\u4e3a get_insights \u7684\u65b9\u6cd5\u5e76\u5411\u5176\u4e2d\u6dfb\u52a0\u4ee5\u4e0b\u4ee3\u7801\u3002\u4f7f\u7528 streamlit write() \u65b9\u6cd5\u4ee3\u66ff print() \u6765\u67e5\u770b\u7f51\u7ad9\u4e0a\u7684\u6d88\u606f\u3002<\/p>\n<pre>def get_insights(video_path):\n    \"\"\"extract insights from the video using gemini flash.\"\"\"\n    st.write(f\"processing video: {video_path}\")\n\n    st.write(f\"uploading file...\")\n    video_file = genai.upload_file(path=video_path)\n    st.write(f\"completed upload: {video_file.uri}\")\n\n    while video_file.state.name == \"processing\":\n        st.write('waiting for video to be processed.')\n        time.sleep(10)\n        video_file = genai.get_file(video_file.name)\n\n    if video_file.state.name == \"failed\":\n        raise valueerror(video_file.state.name)\n\n    prompt = \"describe the video. provides the insights from the video.\"\n\n    model = genai.generativemodel(model_name=\"models\/gemini-1.5-flash\")\n\n    st.write(\"making llm inference request...\")\n    response = model.generate_content([prompt, video_file],\n                                    request_options={\"timeout\": 600})\n    st.write(f'video processing complete')\n    st.subheader(\"insights\")\n    st.write(response.text)\n    genai.delete_file(video_file.name)\n<\/pre>\n<p>\u8981\u7b80\u5316\u5728 streamlit \u5e94\u7528\u7a0b\u5e8f\u4e2d\u4e0a\u4f20\u89c6\u9891\u548c\u751f\u6210\u89c1\u89e3\u7684\u8fc7\u7a0b\uff0c\u60a8\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u540d\u4e3a app \u7684\u65b9\u6cd5\u3002\u6b64\u65b9\u6cd5\u5c06\u63d0\u4f9b\u4e00\u4e2a\u4e0a\u4f20\u6309\u94ae\uff0c\u663e\u793a\u4e0a\u4f20\u7684\u89c6\u9891\uff0c\u5e76\u4ece\u4e2d\u751f\u6210\u89c1\u89e3\u3002<\/p>\n<pre>def app():\n    st.title(\"video insights generator\")\n\n    uploaded_file = st.file_uploader(\"upload a video file\", type=[\"mp4\", \"avi\", \"mov\", \"mkv\"])\n\n    if uploaded_file is not none:\n        file_path = save_uploaded_file(uploaded_file)\n        st.video(file_path)\n        get_insights(file_path)\n        if os.path.exists(file_path):  ## optional: removing uploaded files from the temporary location\n            os.remove(file_path)\n\n<\/pre>\n<p>\u8981\u521b\u5efa\u4e00\u4e2a\u5b8c\u6574\u4e14\u529f\u80fd\u9f50\u5168\u7684 streamlit \u5e94\u7528\u7a0b\u5e8f\uff0c\u5141\u8bb8\u7528\u6237\u4f7f\u7528 gemini 1.5 flash \u6a21\u578b\u4e0a\u4f20\u89c6\u9891\u5e76\u751f\u6210\u89c1\u89e3\uff0c\u8bf7\u5c06\u6240\u6709\u7ec4\u4ef6\u5408\u5e76\u5230\u4e00\u4e2a\u540d\u4e3a app.py \u7684\u6587\u4ef6\u4e2d\u3002<\/p>\n<p>\u8fd9\u662f\u6700\u7ec8\u4ee3\u7801\uff1a<\/p>\n<pre>import os\nimport time\nimport google.generativeai as genai\nimport streamlit as st\nfrom dotenv import load_dotenv\n\nmedia_folder = 'medias'\n\ndef __init__():\n    if not os.path.exists(media_folder):\n        os.makedirs(media_folder)\n\n    load_dotenv()  ## load all the environment variables\n    api_key = os.getenv(\"gemini_api_key\")\n    genai.configure(api_key=api_key)\n\ndef save_uploaded_file(uploaded_file):\n    \"\"\"save the uploaded file to the media folder and return the file path.\"\"\"\n    file_path = os.path.join(media_folder, uploaded_file.name)\n    with open(file_path, 'wb') as f:\n        f.write(uploaded_file.read())\n    return file_path\n\ndef get_insights(video_path):\n    \"\"\"extract insights from the video using gemini flash.\"\"\"\n    st.write(f\"processing video: {video_path}\")\n\n    st.write(f\"uploading file...\")\n    video_file = genai.upload_file(path=video_path)\n    st.write(f\"completed upload: {video_file.uri}\")\n\n    while video_file.state.name == \"processing\":\n        st.write('waiting for video to be processed.')\n        time.sleep(10)\n        video_file = genai.get_file(video_file.name)\n\n    if video_file.state.name == \"failed\":\n        raise valueerror(video_file.state.name)\n\n    prompt = \"describe the video. provides the insights from the video.\"\n\n    model = genai.generativemodel(model_name=\"models\/gemini-1.5-flash\")\n\n    st.write(\"making llm inference request...\")\n    response = model.generate_content([prompt, video_file],\n                                    request_options={\"timeout\": 600})\n    st.write(f'video processing complete')\n    st.subheader(\"insights\")\n    st.write(response.text)\n    genai.delete_file(video_file.name)\n\n\ndef app():\n    st.title(\"video insights generator\")\n\n    uploaded_file = st.file_uploader(\"upload a video file\", type=[\"mp4\", \"avi\", \"mov\", \"mkv\"])\n\n    if uploaded_file is not none:\n        file_path = save_uploaded_file(uploaded_file)\n        st.video(file_path)\n        get_insights(file_path)\n        if os.path.exists(file_path):  ## optional: removing uploaded files from the temporary location\n            os.remove(file_path)\n\n__init__()\napp()\n<\/pre>\n<p>\u6267\u884c\u4ee5\u4e0b\u4ee3\u7801\u6765\u8fd0\u884c\u5e94\u7528\u7a0b\u5e8f\u3002<\/p>\n<pre>streamlit run app.py\n<\/pre>\n<p>\u60a8\u53ef\u4ee5\u6253\u5f00\u63a7\u5236\u53f0\u4e2d\u63d0\u4f9b\u7684\u94fe\u63a5\u6765\u67e5\u770b\u8f93\u51fa\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.17golang.com\/uploads\/20241121\/1732161288673eaf08b9126.jpg\" class=\"aligncenter\"><\/p>\n<p>\u611f\u8c22\u60a8\u9605\u8bfb\u8fd9\u7bc7\u6587\u7ae0\uff01\uff01<\/p>\n<p>\u5982\u679c\u60a8\u559c\u6b22\u8fd9\u7bc7\u6587\u7ae0\uff0c\u8bf7\u70b9\u51fb\u5fc3\u5f62\u6309\u94ae\u5e76\u5206\u4eab\u4ee5\u5e2e\u52a9\u5176\u4ed6\u4eba\u627e\u5230\u5b83\uff01<\/p>\n<p>\u672c\u6559\u7a0b\u7684\u5b8c\u6574\u6e90\u4ee3\u7801\u53ef\u4ee5\u5728\u8fd9\u91cc\u627e\u5230\uff0c<\/p>\n<p>github &#8211; codemaker2015\/video-insights-generator<\/p>\n<p>\u4eca\u5929\u5173\u4e8e\u300a\u4f7f\u7528 Gemini Flash \u6784\u5efa\u89c6\u9891\u6d1e\u5bdf\u751f\u6210\u5668\u300b\u7684\u5185\u5bb9\u4ecb\u7ecd\u5c31\u5230\u6b64\u7ed3\u675f\uff0c\u5982\u679c\u6709\u4ec0\u4e48\u7591\u95ee\u6216\u8005\u5efa\u8bae\uff0c\u53ef\u4ee5\u5728\u516c\u4f17\u53f7\u4e0b\u591a\u591a\u56de\u590d\u4ea4\u6d41\uff1b\u6587\u4e2d\u82e5\u6709\u4e0d\u6b63\u4e4b\u5904\uff0c\u4e5f\u5e0c\u671b\u56de\u590d\u7559\u8a00\u4ee5\u544a\u77e5\uff01<\/p>\n<p>      \u7248\u672c\u58f0\u660e \u672c\u6587\u8f6c\u8f7d\u4e8e\uff1adev.to \u5982\u6709\u4fb5\u72af\uff0c\u8bf7\u8054\u7cfb\u5220\u9664<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4f7f\u7528 Gemini Flash &#46;&#46;&#46;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4925],"tags":[],"class_list":["post-204998","post","type-post","status-publish","format-standard","hentry","category-4925"],"_links":{"self":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/204998","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/comments?post=204998"}],"version-history":[{"count":0,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/204998\/revisions"}],"wp:attachment":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/media?parent=204998"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/categories?post=204998"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/tags?post=204998"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}