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
-// );

src/StreamShorts.Console/Usings.cs

@@ -15,6 +15,7 @@ global using Spectre.Console.Cli;
 
 global using StreamShorts.Console.Commands;
 global using StreamShorts.Console.Hosting;
+global using StreamShorts.Library.Analysis;
+global using StreamShorts.Library.Analysis.Gemini;
 global using StreamShorts.Library.Media.Audio;
 global using StreamShorts.Library.Transcription;
-global using StreamShorts.Library.Analysis;

src/StreamShorts.Library/Analysis/Gemini/Content.cs

@@ -0,0 +1,13 @@
+using System.Text.Json.Serialization;
+
+internal record Content(
+  [property: JsonPropertyName("role")]
+  string Role,
+  [property: JsonPropertyName("parts")]
+  Part[] Parts
+);
+
+internal record Part(
+  [property: JsonPropertyName("text")]
+  string Text
+);

src/StreamShorts.Library/Analysis/Gemini/GeminiAnalyzer.cs

@@ -1,88 +1,72 @@
 using System.Text;
 using System.Text.Json;
-using System.Text.Json.Serialization;
-
-using NAudio.CoreAudioApi;
 
+using StreamShorts.Library.Analysis.Prompts;
 using StreamShorts.Library.Transcription;
 
-namespace StreamShorts.Library.Analysis;
+namespace StreamShorts.Library.Analysis.Gemini;
 
+/// <summary>
+/// Represents an analyzer that uses Gemini to analyze transcript segments and generate short clips.
+/// </summary>
+/// <inheritdoc/>
 public sealed class GeminiAnalyzer(
   IHttpClientFactory httpClientFactory,
   string apiKey
-) : ITranscriptAnalyzer
+  ) : ITranscriptAnalyzer
 {
   private readonly IHttpClientFactory _httpClientFactory = httpClientFactory ?? throw new ArgumentNullException(nameof(httpClientFactory));
   private readonly string _apiKey = apiKey ?? throw new ArgumentNullException(nameof(apiKey));
+  private readonly IAnalysisPrompt _prompt = new DefaultAnalysisPrompt();
+
+  public GeminiAnalyzer(
+    IHttpClientFactory httpClientFactory,
+    string apiKey,
+    IAnalysisPrompt prompt
+  ) : this(httpClientFactory, apiKey)
+  {
+    _prompt = prompt ?? throw new ArgumentNullException(nameof(prompt));
+  }
 
   public async Task<TranscriptAnalysis> AnalyzeAsync(IEnumerable<TranscriptionSegment> segments)
   {
     using var client = _httpClientFactory.CreateClient();
     client.Timeout = TimeSpan.FromMinutes(5);
 
-    // TODO: Load prompt from resource file
     var requestUrl = $"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent?key={_apiKey}";
+    var generateContentRequest = new GenerateContentRequest(
+      [
+        new Content(
+          Role: "user",
+          Parts:[ new Part(Text: _prompt.GetPrompt(segments)) ]
+        )
+      ],
+      new GenerationConfig(ResponseMimeType: "application/json")
+    );
+    using var requestContent = new StringContent(
+      JsonSerializer.Serialize(generateContentRequest),
+      Encoding.UTF8,
+      "application/json"
+    );
     using var request = new HttpRequestMessage(HttpMethod.Post, requestUrl)
     {
-      Content = new StringContent(
+      Content = requestContent
-        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).ConfigureAwait(false);
     var responseContent = await response.Content.ReadAsStringAsync().ConfigureAwait(false);
-    var responseJson = JsonSerializer.Deserialize<LLMResponse>(responseContent);
+    var responseJson = JsonSerializer.Deserialize<GenerateContentResponse>(responseContent);
     var candidatesText = responseJson?
       .Candidates?
       .FirstOrDefault()?
       .Content
       .Parts?.FirstOrDefault()?
       .Text;
-    
+
     var clips = JsonSerializer.Deserialize<List<ShortClip>>(candidatesText ?? string.Empty);
     return new TranscriptAnalysis(clips ?? []);
   }
 }
 
-// TODO: Sort this shit out
-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
-);

src/StreamShorts.Library/Analysis/Gemini/GenerateContentRequest.cs

@@ -0,0 +1,15 @@
+using System.Text.Json.Serialization;
+
+namespace StreamShorts.Library.Analysis.Gemini;
+
+internal record GenerateContentRequest(
+  [property: JsonPropertyName("contents")]
+  Content[] Contents,
+  [property: JsonPropertyName("generationConfig")]
+  GenerationConfig GenerationConfig
+);
+
+internal record GenerationConfig(
+  [property: JsonPropertyName("responseMimeType")]
+  string ResponseMimeType
+);

src/StreamShorts.Library/Analysis/Gemini/GenerateContentResponse.cs

@@ -0,0 +1,14 @@
+using System.Text.Json.Serialization;
+
+namespace StreamShorts.Library.Analysis.Gemini;
+
+internal record GenerateContentResponse(
+  [property: JsonPropertyName("candidates")]
+  Candidate[] Candidates
+);
+
+internal record Candidate(
+  [property: JsonPropertyName("content")]
+  Content Content
+);
+

src/StreamShorts.Library/Analysis/ITranscriptAnalyzer.cs

@@ -2,7 +2,15 @@ using StreamShorts.Library.Transcription;
 
 namespace StreamShorts.Library.Analysis;
 
+/// <summary>
+/// Defines the contract for transcript analyzers that process segments of a transcript and produce an analysis result containing short clips.
+/// </summary>
 public interface ITranscriptAnalyzer
 {
+  /// <summary>
+  /// Analyzes the provided transcript segments and generates a transcript analysis result.
+  /// </summary>
+  /// <param name="segments">The transcript segments to analyze.</param>
+  /// <returns>A task that represents the asynchronous operation. The task result contains the <see cref="TranscriptAnalysis"/> containing the short clips derived from the transcript.</returns> 
   Task<TranscriptAnalysis> AnalyzeAsync(IEnumerable<TranscriptionSegment> segments);
 }

src/StreamShorts.Library/Analysis/Prompts/DefaultAnalysisPrompt.cs

@@ -0,0 +1,49 @@
+using System.Globalization;
+using System.Text;
+
+using StreamShorts.Library.Transcription;
+
+namespace StreamShorts.Library.Analysis.Prompts;
+
+/// <summary>
+/// Default implementation of the analysis prompt for generating YouTube Shorts.
+/// </summary>
+/// <inheritdoc/>
+internal sealed class DefaultAnalysisPrompt : IAnalysisPrompt
+{
+  private static readonly CompositeFormat Prompt = CompositeFormat.Parse(@"
+  I need your help to transform my YouTube live stream transcript into engaging YouTube Shorts. Act as my content editor and pinpoint **all potential candidate segments** that are perfect for short-form video. I'm looking for clips that are:
+  
+    - **Funny:** Moments that will make viewers laugh.
+    - **Informative:** Sections packed with valuable information or tips.
+    - **Insightful:** Portions offering unique perspectives or 'aha!' moments.
+
+  For each suggested short, please provide:
+
+    - The **start time** of the initial segment and the **end time** of the final segment. The duration of each short should be no longer than 3 minutes, but **aim for durations between 15 seconds and 60 seconds**. However, the short **must be as long as necessary to capture the complete thought or idea**, even if it means exceeding the target range or extending slightly to capture all necessary dialogue.
+    - A concise **title** that grabs attention.
+    - A brief **description** highlighting the short's content and its appeal.
+    - An **explanation** of why this particular segment is suitable for a YouTube Short, focusing on its potential for discoverability and engagement.
+
+  Please format your response as a JSON array of objects with the following structure:
+
+  ```json
+  {{
+    ""title"": ""string"",
+    ""start_time"": ""string"",
+    ""end_time"": ""string"",
+    ""description"": ""string"",
+    ""explanation"": ""string""
+  }}
+  ```
+
+  Here is the transcript of my YouTube live stream:
+
+  {0}
+  ");
+
+  public string GetPrompt(IEnumerable<TranscriptionSegment> transcript)
+  {
+    return string.Format(CultureInfo.InvariantCulture, Prompt, transcript);
+  }
+}

src/StreamShorts.Library/Analysis/Prompts/IAnalysisPrompt.cs

@@ -0,0 +1,16 @@
+using StreamShorts.Library.Transcription;
+
+namespace StreamShorts.Library.Analysis.Prompts;
+
+/// <summary>
+/// Defines the contract for analysis prompts used in transcript analysis.
+/// </summary>
+public interface IAnalysisPrompt
+{
+  /// <summary>
+  /// Generates a prompt based on the provided transcript segments.
+  /// </summary>
+  /// <param name="transcript">The transcript segments to analyze.</param>
+  /// <returns>A formatted prompt string for analysis.</returns>
+  string GetPrompt(IEnumerable<TranscriptionSegment> transcript);
+}

src/StreamShorts.Library/Analysis/ShortClip.cs

@@ -2,6 +2,9 @@ using System.Text.Json.Serialization;
 
 namespace StreamShorts.Library.Analysis;
 
+/// <summary>
+/// Represents a short clip derived from a transcript
+/// </summary>
 public record ShortClip(
   [property: JsonPropertyName("title")]
   string Title,

src/StreamShorts.Library/Analysis/TranscriptAnalysis.cs

@@ -1,6 +1,12 @@
 namespace StreamShorts.Library.Analysis;
 
-public class TranscriptAnalysis(IEnumerable<ShortClip> shortClips)
+/// <summary>
+/// Represents the analysis of a transcript, containing short clips derived from the transcript.
+/// </summary>
+public sealed class TranscriptAnalysis(IEnumerable<ShortClip> shortClips)
 {
+  /// <summary>
+  /// Gets the short clips derived from the transcript.
+  /// </summary>
   public IEnumerable<ShortClip> ShortClips { get; init; } = shortClips;
 }

src/StreamShorts.Library/Media/FFMpegService.cs

@@ -1,5 +1,3 @@
-using System.Diagnostics.CodeAnalysis;
-
 using FFMpegCore;
 using FFMpegCore.Enums;
 using FFMpegCore.Pipes;

src/StreamShorts.Library/Media/IAudioService.cs

@@ -1,4 +1,3 @@
-
 namespace StreamShorts.Library.Media;
 
 /// <summary>

src/StreamShorts.Library/Resources/DefaultAnalysisPrompt.md

@@ -1,28 +0,0 @@
-I need your help to transform my YouTube live stream transcript into engaging YouTube Shorts. Act as my content editor and pinpoint **all potential candidate segments** that are perfect for short-form video. I'm looking for clips that are:
-
-  - **Funny:** Moments that will make viewers laugh.
-  - **Informative:** Sections packed with valuable information or tips.
-  - **Insightful:** Portions offering unique perspectives or 'aha\!' moments.
-
-For each suggested short, please provide:
-
-  - The **start time** of the initial segment and the **end time** of the final segment. The duration of each short should be no longer than 3 minutes, but **aim for durations between 15 seconds and 60 seconds**. However, the short **must be as long as necessary to capture the complete thought or idea**, even if it means exceeding the target range or extending slightly to capture all necessary dialogue.
-  - A concise **title** that grabs attention.
-  - A brief **description** highlighting the short's content and its appeal.
-  - An **explanation** of why this particular segment is suitable for a YouTube Short, focusing on its potential for discoverability and engagement.
-
-Please format your response as a JSON array of objects with the following structure:
-
-```json
-{
-  "title": "string",
-  "start_time": "string",
-  "end_time": "string",
-  "description": "string",
-  "explanation": "string"
-}
-```
-
-Here is the transcript of my YouTube live stream:
-
-{0}

src/StreamShorts.Library/Transcription/ITranscriber.cs

@@ -1,5 +1,3 @@
-using System.Runtime.CompilerServices;
-
 namespace StreamShorts.Library.Transcription;
 
 /// <summary>