feat: implement default prompt for analysis

src/StreamShorts.Console/Program.cs

@@ -22,6 +22,7 @@ try
       services.AddSingleton<IFileSystem, FileSystem>();
       services.AddSingleton<IAudioExtractor, AudioExtractor>();
       services.AddSingleton<ITranscriber, WhisperTranscriber>();
+      services.AddSingleton<ITranscriptAnalyzer, GeminiAnalyzer>();
     })
     .BuildApp()
     .RunAsync(args);
@@ -37,105 +38,3 @@ finally
 {
   await Log.CloseAndFlushAsync();
 }
-
-// if (string.IsNullOrWhiteSpace(apiKey))
-// {
-//   throw new InvalidOperationException("GeminiApiKey is not configured in appsettings.json.");
-// }
-
-// using var client = new HttpClient()
-// {
-//   Timeout = TimeSpan.FromMinutes(30)
-// };
-
-// var requestUrl = $"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent?key={apiKey}";
-// using var request = new HttpRequestMessage(HttpMethod.Post, requestUrl)
-// {
-//   Content = new StringContent(
-//     JsonSerializer.Serialize(new
-//     {
-//       contents = new[]
-//       {
-//         new
-//         {
-//           role = "user",
-//           parts = new[]
-//           {
-//             new
-//             {
-//               text = prompt
-//             }
-//           },
-//         }
-//       },
-//       generationConfig = new
-//       {
-//         responseMimeType = "application/json",
-//       }
-//     }),
-//     Encoding.UTF8,
-//     "application/json"
-//   )
-// };
-// var response = await client.SendAsync(request);
-// var responseContent = await response.Content.ReadAsStringAsync();
-// var responseJson = JsonSerializer.Deserialize<LLMResponse>(responseContent);
-// var candidatesText = responseJson?
-//   .Candidates?
-//   .FirstOrDefault()?
-//   .Content
-//   .Parts?.FirstOrDefault()?
-//   .Text;
-// var analysis = JsonSerializer.Deserialize<List<LLMAnalysis>>(candidatesText ?? string.Empty);
-
-// if (analysis is null)
-// {
-//   Console.WriteLine(resourceManager.GetString("LLMAnalysisFailed", CultureInfo.CurrentCulture));
-//   return;
-// }
-
-// foreach (var result in analysis)
-// {
-//   var fileName = string.Concat(result.Title.Split(Path.GetInvalidFileNameChars()));
-//   await FFMpeg.SubVideoAsync(
-//     args[0],
-//     $"{fileName}.mp4",
-//     result.StartTime,
-//     result.EndTime
-//   );
-// }
-
-// // Step 6: Use analysis to generate a short video
-
-// record LLMAnalysis(
-//   [property: JsonPropertyName("title")]
-//   string Title,
-//   [property: JsonPropertyName("description")]
-//   string Description,
-//   [property: JsonPropertyName("explanation")]
-//   string Explanation,
-//   [property: JsonPropertyName("start_time")]
-//   TimeSpan StartTime,
-//   [property: JsonPropertyName("end_time")]
-//   TimeSpan EndTime
-// );
-
-// record LLMResponse(
-//   [property: JsonPropertyName("candidates")]
-//   Candidate[] Candidates
-// );
-
-// record Candidate(
-//   [property: JsonPropertyName("content")]
-//   Content Content
-// );
-
-// record Content(
-//   [property: JsonPropertyName("parts")]
-//   Part[] Parts
-// );
-
-// record Part(
-//   [property: JsonPropertyName("text")]
-//   string Text
-// );