added openai models

OpenAi/ModerationResponse.cs

@@ -0,0 +1,27 @@
+public class ModerationResponse
+{
+    public string Id { get; set; }
+    public string Model { get; set; }
+    public List<ModerationResult> Results { get; set; }
+}
+
+public class ModerationResult
+{
+    public Categories Categories { get; set; }
+    public CategoryScores Category_Scores { get; set; }
+    public bool Flagged { get; set; }
+}
+
+public class Categories
+{
+    public bool Hate { get; set; }
+    public bool Self_Harm { get; set; }
+    public bool Violence { get; set; }
+}
+
+public class CategoryScores
+{
+    public float Hate { get; set; }
+    public float Self_Harm { get; set; }
+    public float Violence { get; set; }
+}

OpenAi/OpenAiClient.cs

@@ -0,0 +1,71 @@
+using System;
+using System.Net.Http;
+using System.Net.Http.Headers;
+using System.Text;
+using System.Text.Json;
+using System.Threading.Tasks;
+using System.Text.Json.Serialization;
+
+public class OpenAIClient
+{
+    private readonly string _apiKey;
+    private readonly HttpClient _httpClient;
+    private readonly string _dalleModel = "dall-e-2";
+    private readonly string _moderationModel = "omni-moderation-latest";
+
+    public OpenAIClient(string apiKey)
+    {
+        _apiKey = apiKey;
+        _httpClient = new HttpClient();
+        _httpClient.DefaultRequestHeaders.Authorization =
+            new AuthenticationHeaderValue("Bearer", _apiKey);
+    }
+
+    public async Task<string> GenerateImageAsync(string prompt)
+    {
+        var url = "https://api.openai.com/v1/images/generations";
+        var requestBody = new
+        {
+            model = _dalleModel,
+            prompt = prompt,
+            n = 1,
+            size = "1024x1024"
+        };
+        var json = JsonSerializer.Serialize(requestBody);
+        var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+        var response = await _httpClient.PostAsync(url, content);
+        response.EnsureSuccessStatusCode();
+
+        var responseJson = await response.Content.ReadAsStringAsync();
+        using var doc = JsonDocument.Parse(responseJson);
+        var imageUrl = doc.RootElement.GetProperty("data")[0].GetProperty("url").GetString();
+
+        return imageUrl;
+    }
+    public async Task<ModerationResponse> ModerateContentAsync(string input)
+    {
+        var url = "https://api.openai.com/v1/moderations";
+        var requestBody = new
+        {
+            model = _moderationModel,
+            input = input
+        };
+        var json = JsonSerializer.Serialize(requestBody);
+        var content = new StringContent(json, Encoding.UTF8, "application/json");
+
+        var response = await _httpClient.PostAsync(url, content);
+        response.EnsureSuccessStatusCode();
+
+        var responseJson = await response.Content.ReadAsStringAsync();
+
+        var options = new JsonSerializerOptions
+        {
+            PropertyNameCaseInsensitive = true
+        };
+
+        var moderationResponse = JsonSerializer.Deserialize<ModerationResponse>(responseJson, options);
+        return moderationResponse;
+    }
+
+}

OpenAi/OpenAiHandler.py

@@ -0,0 +1,37 @@
+import os
+import requests
+
+class OpenAIHandler:
+    def __init__(self, api_key):
+        self.headers = {
+            "Authorization": f"Bearer {api_key}",
+        }
+
+    def generate_code(self, prompt: str) -> str:
+        payload = {
+            "model": "gpt-4o-mini",
+            "messages": [{"role": "user", "content": prompt}],
+            "temperature": 0.2,  # lower temp for more focused code
+        }
+        headers = self.headers.copy()
+        headers["Content-Type"] = "application/json"
+
+        response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
+        response.raise_for_status()
+        data = response.json()
+        return data["choices"][0]["message"]["content"]
+
+    def transcribe_audio(self, audio_file_path: str) -> str:
+        headers = self.headers.copy()
+        with open(audio_file_path, "rb") as audio_file:
+            files = {
+                "file": (audio_file_path, audio_file, "audio/mpeg"),
+            }
+            data = {
+                "model": "whisper-1",
+                "language": "en"
+            }
+            response = requests.post("https://api.openai.com/v1/audio/transcriptions", headers=headers, data=data, files=files)
+            response.raise_for_status()
+        data = response.json()
+        return data["text"]