update flow and auth model

src/services/ai.service.ts

@@ -0,0 +1,243 @@
+/**
+ * AI Service
+ * 
+ * Handles communication with the AI proxy endpoint for chat completions.
+ */
+
+import {
+  NO_BACKEND_MODE,
+  API_ENDPOINTS,
+  AI_CONFIG,
+  buildApiUrl,
+  getApiHeaders,
+  logApiDebug,
+} from '../config';
+
+// =============================================================================
+// Type Definitions
+// =============================================================================
+
+export interface AIMessage {
+  role: 'system' | 'user' | 'assistant';
+  content: string;
+}
+
+export interface AIRequest {
+  messages: AIMessage[];
+  model?: string;
+}
+
+export interface AIResponse {
+  id: string;
+  object: string;
+  created: number;
+  model: string;
+  choices: Array<{
+    index: number;
+    message: AIMessage;
+    finish_reason: string;
+  }>;
+  usage: {
+    prompt_tokens: number;
+    completion_tokens: number;
+    total_tokens: number;
+  };
+}
+
+// =============================================================================
+// Mock Response Generator
+// =============================================================================
+
+const createMockResponse = (userMessage: string): AIResponse => {
+  return {
+    id: `mock-${Date.now()}`,
+    object: 'chat.completion',
+    created: Math.floor(Date.now() / 1000),
+    model: 'mock-model',
+    choices: [
+      {
+        index: 0,
+        message: {
+          role: 'assistant',
+          content: `I received your message: "${userMessage}". This is a mock response since the backend is not connected.`,
+        },
+        finish_reason: 'stop',
+      },
+    ],
+    usage: {
+      prompt_tokens: 10,
+      completion_tokens: 20,
+      total_tokens: 30,
+    },
+  };
+};
+
+// =============================================================================
+// AI Service
+// =============================================================================
+
+export const aiService = {
+  /**
+   * Send chat messages to the AI proxy
+   * @param messages - Array of chat messages
+   * @param token - JWT token for authentication
+   * @returns AI response
+   */
+  async chat(messages: AIMessage[], token?: string): Promise<AIResponse> {
+    if (NO_BACKEND_MODE) {
+      logApiDebug('AI Chat', 'Using mock mode');
+      return new Promise((resolve) => {
+        setTimeout(() => {
+          const lastUserMessage = messages.filter((m) => m.role === 'user').pop();
+          resolve(createMockResponse(lastUserMessage?.content || 'Hello'));
+        }, AI_CONFIG.MOCK_RESPONSE_DELAY);
+      });
+    }
+
+    const url = buildApiUrl(API_ENDPOINTS.AI.PROXY);
+    
+    logApiDebug('AI Request', {
+      url,
+      hasToken: !!token,
+      messageCount: messages.length,
+    });
+
+    try {
+      const response = await fetch(url, {
+        method: 'POST',
+        headers: getApiHeaders(token),
+        body: JSON.stringify({ messages } as AIRequest),
+      });
+
+      logApiDebug('AI Response Status', response.status);
+
+      if (!response.ok) {
+        const errorText = await response.text();
+        logApiDebug('AI Error Response', errorText);
+        
+        let errorDetail = 'AI request failed';
+        try {
+          const errorData = JSON.parse(errorText);
+          errorDetail = errorData.detail || errorDetail;
+        } catch {
+          errorDetail = errorText || errorDetail;
+        }
+        throw new Error(`${response.status}: ${errorDetail}`);
+      }
+
+      const data = await response.json();
+      logApiDebug('AI Success', {
+        id: data.id,
+        model: data.model,
+        choicesCount: data.choices?.length,
+      });
+      
+      return data;
+    } catch (error) {
+      console.error('AI proxy error:', error);
+      throw error;
+    }
+  },
+
+  /**
+   * Simple helper for single message chat
+   * @param content - User message content
+   * @param token - JWT token for authentication
+   * @returns AI response text
+   */
+  async sendMessage(content: string, token?: string): Promise<string> {
+    const messages: AIMessage[] = [
+      {
+        role: 'system',
+        content: AI_CONFIG.DEFAULT_SYSTEM_PROMPT,
+      },
+      {
+        role: 'user',
+        content,
+      },
+    ];
+
+    const response = await this.chat(messages, token);
+    return response.choices[0]?.message?.content || 'No response';
+  },
+
+  /**
+   * Send a message with an image to AI for analysis
+   * @param content - User message content
+   * @param imageBase64 - Base64 encoded image data
+   * @param token - JWT token for authentication
+   * @returns AI response text
+   */
+  async sendMessageWithImage(content: string, imageBase64: string, token?: string): Promise<string> {
+    if (NO_BACKEND_MODE) {
+      logApiDebug('AI Image Analysis', 'Using mock mode');
+      return new Promise((resolve) => {
+        setTimeout(() => {
+          resolve('This is a mock image analysis response. The image appears to show an interesting scene. In production, this would be analyzed by Gemini AI.');
+        }, AI_CONFIG.MOCK_RESPONSE_DELAY);
+      });
+    }
+
+    const url = buildApiUrl(API_ENDPOINTS.AI.PROXY);
+    
+    logApiDebug('AI Image Request', {
+      url,
+      hasToken: !!token,
+      hasImage: !!imageBase64,
+    });
+
+    // Gemini vision format - using multimodal content
+    const messages = [
+      {
+        role: 'user',
+        content: [
+          {
+            type: 'text',
+            text: content,
+          },
+          {
+            type: 'image_url',
+            image_url: {
+              url: `data:image/jpeg;base64,${imageBase64}`,
+            },
+          },
+        ],
+      },
+    ];
+
+    try {
+      const response = await fetch(url, {
+        method: 'POST',
+        headers: getApiHeaders(token),
+        body: JSON.stringify({ messages }),
+      });
+
+      logApiDebug('AI Image Response Status', response.status);
+
+      if (!response.ok) {
+        const errorText = await response.text();
+        logApiDebug('AI Image Error Response', errorText);
+        
+        let errorDetail = 'AI image request failed';
+        try {
+          const errorData = JSON.parse(errorText);
+          errorDetail = errorData.detail || errorDetail;
+        } catch {
+          errorDetail = errorText || errorDetail;
+        }
+        throw new Error(`${response.status}: ${errorDetail}`);
+      }
+
+      const data = await response.json();
+      logApiDebug('AI Image Success', {
+        id: data.id,
+        model: data.model,
+      });
+      
+      return data.choices[0]?.message?.content || 'No response';
+    } catch (error) {
+      console.error('AI image proxy error:', error);
+      throw error;
+    }
+  },
+};