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* AI Engine for YapTrap\n * Handles LLM integration and response generation\n */\n\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport type { \n ConversationContext, \n AIResponse, \n AIProvider,\n NormalizedMessage \n} from '../../shared/types.ts';\nimport { SystemLogQueries, ConfigurationQueries } from '../database/queries.ts';\nimport { MetricsCollector } from '../monitoring/metrics.ts';\n\nexport class AIEngine {\n private providers: Map;\n \n constructor() {\n this.providers = new Map();\n this.initializeProviders();\n }\n \n /**\n * Initialize AI providers based on available API keys\n */\n private initializeProviders(): void {\n // OpenAI provider\n const openaiKey = Deno.env.get('OPENAI_API_KEY');\n if (openaiKey) {\n this.providers.set('openai', {\n name: 'openai',\n model: 'gpt-4o-mini',\n apiKey: openaiKey,\n maxTokens: 150,\n temperature: 0.8\n });\n }\n \n // xAI provider\n const xaiKey = Deno.env.get('XAI_API_KEY');\n if (xaiKey) {\n this.providers.set('xai', {\n name: 'xai',\n model: 'grok-beta',\n apiKey: xaiKey,\n baseUrl: 'https://api.x.ai/v1',\n maxTokens: 150,\n temperature: 0.8\n });\n }\n \n // Claude provider (Anthropic)\n const claudeKey = Deno.env.get('ANTHROPIC_API_KEY');\n if (claudeKey) {\n this.providers.set('claude', {\n name: 'claude',\n model: 'claude-3-haiku-20240307',\n apiKey: claudeKey,\n baseUrl: 'https://api.anthropic.com/v1',\n maxTokens: 150,\n temperature: 0.8\n });\n }\n }\n \n /**\n * Generate a contextual response based on conversation context\n */\n async generateResponse(context: ConversationContext): Promise {\n const startTime = Date.now();\n \n try {\n // Get the preferred AI provider\n const provider = await this.getPreferredProvider();\n \n if (!provider) {\n await SystemLogQueries.log(\n 'error',\n 'ai-engine',\n 'No AI providers available',\n {},\n context.conversationId\n );\n return null;\n }\n \n // Build the prompt\n const prompt = await this.buildPrompt(context);\n \n // Generate response using the selected provider\n const response = await this.callAIProvider(provider, prompt, context);\n \n const responseTime = Date.now() - startTime;\n \n await SystemLogQueries.log(\n 'info',\n 'ai-engine',\n 'AI response generated successfully',\n {\n provider: provider.name,\n model: provider.model,\n responseTime,\n tokensUsed: response.metadata.tokensUsed,\n confidence: response.confidence\n },\n context.conversationId\n );\n \n // Record metrics\n await MetricsCollector.recordAIResponse(\n provider.name,\n provider.model,\n response.metadata.tokensUsed,\n responseTime,\n true\n );\n \n return response;\n \n } catch (error) {\n const responseTime = Date.now() - startTime;\n \n await SystemLogQueries.log(\n 'error',\n 'ai-engine',\n `AI response generation failed: ${error.message}`,\n {\n error: error.message,\n stack: error.stack,\n responseTime\n },\n context.conversationId\n );\n \n // Record failed metrics\n await MetricsCollector.recordAIResponse('unknown', 'unknown', 0, responseTime, false);\n \n return null;\n }\n }\n \n /**\n * Get the preferred AI provider based on configuration\n */\n private async getPreferredProvider(): Promise {\n try {\n // Get provider preference from configuration\n const defaultProvider = await ConfigurationQueries.get('ai.default_provider');\n \n if (defaultProvider && this.providers.has(defaultProvider.name)) {\n const provider = this.providers.get(defaultProvider.name)!;\n return {\n ...provider,\n ...defaultProvider // Override with config values\n };\n }\n \n // Fall back to first available provider\n const availableProviders = Array.from(this.providers.values());\n return availableProviders.length > 0 ? availableProviders[0] : null;\n \n } catch (error) {\n await SystemLogQueries.log(\n 'warn',\n 'ai-engine',\n `Failed to get preferred provider: ${error.message}`\n );\n \n // Return first available provider as fallback\n const availableProviders = Array.from(this.providers.values());\n return availableProviders.length > 0 ? availableProviders[0] : null;\n }\n }\n \n /**\n * Build the AI prompt based on conversation context\n */\n private async buildPrompt(context: ConversationContext): Promise {\n const settings = context.yapTrapSettings;\n const recentMessages = context.recentMessages.slice(0, 10); // Last 10 messages\n \n // Build personality description\n const personalityDesc = this.buildPersonalityDescription(context);\n \n // Build conversation history\n const conversationHistory = recentMessages\n .map(msg => {\n const sender = msg.userId ? \n context.participants.find(p => p.id === msg.userId)?.displayName || 'User' :\n 'YapTrap';\n return `${sender}: ${msg.content}`;\n })\n .join('\\n');\n \n // Build the main prompt\n const prompt = `You are YapTrap, a witty and engaging chatbot that participates in group conversations. Your personality and behavior should match the following guidelines:\n\nPERSONALITY:\n${personalityDesc}\n\nCONVERSATION CONTEXT:\n- Platform: ${context.conversationId.split('_')[1]}\n- Participants: ${context.participants.map(p => p.displayName).join(', ')}\n- Current topic: ${context.currentTopic || 'General conversation'}\n- Group dynamics: Activity level ${(context.groupDynamics.activityLevel * 100).toFixed(0)}%, Humor level ${(context.groupDynamics.humorLevel * 100).toFixed(0)}%\n\nRECENT CONVERSATION:\n${conversationHistory}\n\nRESPONSE GUIDELINES:\n- Roast intensity: ${(settings.roastIntensity * 100).toFixed(0)}% (0% = gentle teasing, 100% = savage roasts)\n- Keep responses under 150 characters for most platforms\n- Be contextually relevant to the conversation\n- Match the group's energy and humor level\n- Don't be repetitive or predictable\n- Use emojis sparingly and appropriately\n- If someone seems upset, tone down the roasting\n\nGenerate a witty, contextual response that fits naturally into this conversation:`;\n\n return prompt;\n }\n \n /**\n * Build personality description based on group dynamics and settings\n */\n private buildPersonalityDescription(context: ConversationContext): string {\n const dynamics = context.groupDynamics;\n const settings = context.yapTrapSettings;\n \n let personality = \"You are witty, observant, and slightly sarcastic. \";\n \n if (dynamics.humorLevel > 0.7) {\n personality += \"The group loves humor, so be extra funny and playful. \";\n } else if (dynamics.humorLevel < 0.3) {\n personality += \"Keep things more serious and thoughtful. \";\n }\n \n if (settings.roastIntensity > 0.7) {\n personality += \"Don't hold back on the roasts - this group can handle spicy commentary. \";\n } else if (settings.roastIntensity < 0.3) {\n personality += \"Keep roasts gentle and friendly. \";\n }\n \n if (dynamics.conflictLevel > 0.5) {\n personality += \"There's some tension in the group, so be diplomatic and try to lighten the mood. \";\n }\n \n if (dynamics.activityLevel > 0.8) {\n personality += \"The conversation is very active, so jump in with quick, punchy responses. \";\n } else if (dynamics.activityLevel < 0.3) {\n personality += \"The conversation is quiet, so try to spark engagement. \";\n }\n \n return personality;\n }\n \n /**\n * Call the AI provider to generate a response\n */\n private async callAIProvider(\n provider: AIProvider, \n prompt: string, \n context: ConversationContext\n ): Promise {\n const startTime = Date.now();\n \n try {\n let response;\n let tokensUsed = 0;\n \n if (provider.name === 'openai') {\n response = await this.callOpenAI(provider, prompt);\n tokensUsed = response.usage?.total_tokens || 0;\n } else if (provider.name === 'xai') {\n response = await this.callXAI(provider, prompt);\n tokensUsed = response.usage?.total_tokens || 0;\n } else if (provider.name === 'claude') {\n response = await this.callClaude(provider, prompt);\n tokensUsed = response.usage?.input_tokens + response.usage?.output_tokens || 0;\n } else {\n throw new Error(`Unsupported AI provider: ${provider.name}`);\n }\n \n const responseTime = Date.now() - startTime;\n const content = this.extractContent(response, provider.name);\n \n if (!content || content.trim() === '') {\n throw new Error('AI provider returned empty response');\n }\n \n return {\n content: content.trim(),\n confidence: this.calculateConfidence(response, provider.name),\n reasoning: this.extractReasoning(response, provider.name),\n metadata: {\n provider: provider.name,\n model: provider.model,\n tokensUsed,\n responseTime\n }\n };\n \n } catch (error) {\n throw new Error(`AI provider call failed: ${error.message}`);\n }\n }\n \n /**\n * Call OpenAI API\n */\n private async callOpenAI(provider: AIProvider, prompt: string): Promise {\n const openai = new OpenAI({ apiKey: provider.apiKey });\n \n const completion = await openai.chat.completions.create({\n model: provider.model,\n messages: [\n { role: \"system\", content: \"You are YapTrap, a witty chatbot.\" },\n { role: \"user\", content: prompt }\n ],\n max_tokens: provider.maxTokens,\n temperature: provider.temperature\n });\n \n return completion;\n }\n \n /**\n * Call xAI API (similar to OpenAI format)\n */\n private async callXAI(provider: AIProvider, prompt: string): Promise {\n const response = await fetch(`${provider.baseUrl}/chat/completions`, {\n method: 'POST',\n headers: {\n 'Authorization': `Bearer ${provider.apiKey}`,\n 'Content-Type': 'application/json'\n },\n body: JSON.stringify({\n model: provider.model,\n messages: [\n { role: \"system\", content: \"You are YapTrap, a witty chatbot.\" },\n { role: \"user\", content: prompt }\n ],\n max_tokens: provider.maxTokens,\n temperature: provider.temperature\n })\n });\n \n if (!response.ok) {\n throw new Error(`xAI API error: ${response.status} ${response.statusText}`);\n }\n \n return await response.json();\n }\n \n /**\n * Call Claude API\n */\n private async callClaude(provider: AIProvider, prompt: string): Promise {\n const response = await fetch(`${provider.baseUrl}/messages`, {\n method: 'POST',\n headers: {\n 'Authorization': `Bearer ${provider.apiKey}`,\n 'Content-Type': 'application/json',\n 'anthropic-version': '2023-06-01'\n },\n body: JSON.stringify({\n model: provider.model,\n max_tokens: provider.maxTokens,\n temperature: provider.temperature,\n messages: [\n { role: \"user\", content: prompt }\n ]\n })\n });\n \n if (!response.ok) {\n throw new Error(`Claude API error: ${response.status} ${response.statusText}`);\n }\n \n return await response.json();\n }\n \n /**\n * Extract content from AI provider response\n */\n private extractContent(response: any, providerName: string): string {\n switch (providerName) {\n case 'openai':\n case 'xai':\n return response.choices?.[0]?.message?.content || '';\n case 'claude':\n return response.content?.[0]?.text || '';\n default:\n return '';\n }\n }\n \n /**\n * Calculate confidence score based on response\n */\n private calculateConfidence(response: any, providerName: string): number {\n // Simple confidence calculation based on response structure\n // In practice, this could be more sophisticated\n \n const content = this.extractContent(response, providerName);\n \n if (!content || content.length < 10) {\n return 0.1;\n }\n \n if (content.length > 100) {\n return 0.9;\n }\n \n return 0.7;\n }\n \n /**\n * Extract reasoning from AI response (if available)\n */\n private extractReasoning(response: any, providerName: string): string | undefined {\n // Most providers don't return reasoning by default\n // This could be enhanced with chain-of-thought prompting\n return undefined;\n }\n}","deleted","label",[167,168,149],"backend","ai","permalink","https://www.val.town/x/lantholin/YapTrap/code/backend/ai/engine.ts","extension","actionData","errors"]