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feat: Add configurable LLM and Whisper models with user selection and API integration.

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This commit is contained in:
Tomi Eckert
2026-02-25 22:05:32 +01:00
parent 863063f124
commit c2f4cbbfb2
3 changed files with 40 additions and 9 deletions
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8
GroqApiClient.cs
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@@ -51,7 +51,7 @@ public class GroqApiClient
_httpClient.BaseAddress = new Uri("https://api.groq.com/openai/v1/");
}
public async Task<string> TranscribeAsync(string filePath, string language = "")
public async Task<string> TranscribeAsync(string filePath, string language = "", string model = "whisper-large-v3-turbo")
{
using var content = new MultipartFormDataContent();
using var fileStream = File.OpenRead(filePath);
@@ -60,7 +60,7 @@ public class GroqApiClient
streamContent.Headers.ContentType = new MediaTypeHeaderValue("audio/wav"); // or mpeg
content.Add(streamContent, "file", Path.GetFileName(filePath));
string modelToUse = "whisper-large-v3-turbo";
string modelToUse = string.IsNullOrWhiteSpace(model) ? "whisper-large-v3-turbo" : model;
// according to docs whisper-large-v3-turbo requires the language to be provided if it is to be translated later potentially or if we need the most accurate behavior
// Actually, if we want language param, we can pass it to either model
@@ -85,11 +85,11 @@ public class GroqApiClient
return result?.Text ?? string.Empty;
}
public async Task<string> RefineTextAsync(string rawTranscript, string systemPrompt)
public async Task<string> RefineTextAsync(string rawTranscript, string systemPrompt, string model = "openai/gpt-oss-20b")
{
var requestBody = new LlamaRequest
{
Model = "openai/gpt-oss-20b",
Model = string.IsNullOrWhiteSpace(model) ? "openai/gpt-oss-20b" : model,
Temperature = 0.0,
Messages = new[]
{