[{"_1":2,"_171":-5,"_172":-5},"loaderData",{"_3":4,"_91":92},"root",{"_5":6,"_34":35,"_64":65},"ctx",{"_7":8,"_23":-5,"_24":25,"_26":27,"_28":20,"_29":20,"_30":20,"_31":32,"_33":20},"auth",{"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5,"_19":20,"_21":22},"sessionClaims","sessionId","sessionStatus","userId","actor","orgId","orgRole","orgSlug","orgPermissions","factorVerificationAge","isAuthenticated",false,"tokenType","session_token","user","preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","notificationCount",0,"flagDenols","ENV",{"_36":37,"_38":39,"_40":41,"_42":43,"_44":45,"_46":47,"_48":49,"_50":51,"_52":53,"_54":55,"_56":57,"_58":59,"_60":61,"_62":63},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","VAL_RUNTIME_NAME","prod","RENDER_GIT_COMMIT","73d011c55f6ff6e543547a2f801bf2081197a5a4","RENDER_GIT_BRANCH","main","CLERK_PUBLISHABLE_KEY","pk_live_Y2xlcmsudmFsLnRvd24k","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","API_URL","https://api.val.town","clerkState",{"_66":67},"__internal_clerk_state",{"_68":69,"_70":45,"_71":72,"_73":72,"_74":20,"_75":72,"_76":72,"_77":72,"_78":72,"_79":80,"_89":20,"_90":20},"__clerk_ssr_state",{"_21":22,"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5,"_19":20},"__publishableKey","__proxyUrl","","__domain","__isSatellite","__signInUrl","__signUpUrl","__afterSignInUrl","__afterSignUpUrl","__clerk_debug",{"_81":20,"_19":20,"_82":72,"_83":84,"_85":72,"_86":45,"_87":20,"_88":72},"isSignedIn","proxyUrl","reason","session-token-and-uat-missing","message","publishableKey","isSatellite","domain","__telemetryDisabled","__telemetryDebug","routes/embed.x.$handle.$name.$",{"_93":94,"_95":96,"_97":98,"_99":100,"_146":147,"_168":169,"_170":-5},"handle","Venny","name","Chatbrain","path","backend/auto-responder.ts","project",{"_101":102,"_95":96,"_103":104,"_105":-5,"_106":20,"_107":108,"_109":-5,"_110":-5,"_12":111,"_112":-5,"_113":20,"_114":-5,"_115":32,"_14":116,"_117":118,"_119":118,"_120":121,"_122":121,"_123":121,"_124":118,"_125":118,"_23":126,"_129":130,"_132":133,"_145":20},"id","603f6164-3942-11f0-9efb-9e149126039e","createdAt",["D",1748161769385],"deletedAt","legacyEnvVars","privacy","public","description","imageUrl","c85aa4a0-2ce2-11f0-b24f-c19e9e5d59f9","pinnedFileId","pinPreview","screenshotVersion","likeCount","e6bfacf1-dff1-46eb-81c1-70adc05fbd3f","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm",{"_93":94,"_127":128},"profileImageUrl","https://img.clerk.com/eyJ0eXBlIjoiZGVmYXVsdCIsImlpZCI6Imluc18yTm10cGhQUklwU0tqZHNiOHNnNGd2ZjJURFUiLCJyaWQiOiJ1c2VyXzJ3cllnS2RUMGV4Z2pMRHQ1bEs4MVYwYW5sVyJ9","org",{"_93":94,"_131":128},"avatar","branch",{"_134":135,"_95":43,"_101":136,"_137":102,"_138":-5,"_139":-5,"_140":-5,"_141":-5,"_142":-5,"_143":96,"_144":94},"version",18,"603fa124-3942-11f0-9efb-9e149126039e","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","isOwned","file",{"_101":148,"_95":149,"_150":151,"_152":153,"_154":136,"_155":156,"_157":158,"_103":159,"_134":32,"_160":161,"_162":163,"_164":20,"_165":-5,"_97":166},"122a69c6-3945-11f0-926e-9e149126039e","auto-responder.ts","fileId","122a6a7a-3945-11f0-926e-9e149126039e","parentId","725d83d2-4fe8-4087-9378-ddcc192d84ba","branchId","branchVersion",15,"latest",true,["D",1748162926874],"fileType","script","content","// Automated response system for social media interactions\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport { TwitterAPI } from \"./twitter-api.ts\";\nimport type { SocialPlatform } from \"../shared/types.ts\";\n\nconst INTERACTIONS_TABLE = 'social_interactions_v1';\n\ninterface Interaction {\n id: string;\n platform: SocialPlatform;\n type: 'mention' | 'reply' | 'dm';\n authorId: string;\n authorUsername: string;\n content: string;\n originalPostId?: string;\n createdAt: string;\n responded: boolean;\n responseId?: string;\n responseContent?: string;\n}\n\nexport class AutoResponder {\n private openai: OpenAI;\n private twitterAPI: TwitterAPI;\n\n constructor() {\n this.openai = new OpenAI();\n this.twitterAPI = new TwitterAPI();\n this.initDatabase();\n }\n\n private async initDatabase() {\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS ${INTERACTIONS_TABLE} (\n id TEXT PRIMARY KEY,\n platform TEXT NOT NULL,\n type TEXT NOT NULL,\n author_id TEXT NOT NULL,\n author_username TEXT NOT NULL,\n content TEXT NOT NULL,\n original_post_id TEXT,\n created_at TEXT NOT NULL,\n responded BOOLEAN DEFAULT FALSE,\n response_id TEXT,\n response_content TEXT,\n processed_at TEXT\n )`);\n }\n\n async processNewMentions(): Promise<{\n success: boolean;\n processed?: number;\n responses?: number;\n error?: string;\n }> {\n try {\n // Get the last processed mention ID to avoid duplicates\n const lastProcessed = await sqlite.execute(\n `SELECT MAX(id) as last_id FROM ${INTERACTIONS_TABLE} WHERE platform = 'twitter' AND type = 'mention'`\n );\n \n const sinceId = lastProcessed.rows?.[0]?.last_id;\n\n // Fetch new mentions from Twitter\n const mentionsResult = await this.twitterAPI.getMentions(sinceId);\n if (!mentionsResult.success || !mentionsResult.mentions) {\n return { success: false, error: mentionsResult.error };\n }\n\n let processed = 0;\n let responses = 0;\n\n for (const mention of mentionsResult.mentions) {\n // Store the interaction\n await this.storeInteraction({\n id: mention.id,\n platform: 'twitter',\n type: 'mention',\n authorId: mention.authorId,\n authorUsername: mention.authorUsername,\n content: mention.text,\n createdAt: mention.createdAt,\n responded: false,\n });\n\n // Generate and send response if appropriate\n const shouldRespond = await this.shouldRespondToMention(mention.text, mention.authorUsername);\n if (shouldRespond) {\n const response = await this.generateResponse(mention.text, 'mention');\n if (response.success && response.content) {\n const replyResult = await this.twitterAPI.replyToTweet(response.content, mention.id);\n \n if (replyResult.success) {\n await this.markAsResponded(mention.id, replyResult.tweetId!, response.content);\n responses++;\n }\n }\n }\n\n processed++;\n }\n\n return { success: true, processed, responses };\n } catch (error) {\n return { success: false, error: error.message };\n }\n }\n\n private async storeInteraction(interaction: Omit): Promise {\n await sqlite.execute(\n `INSERT OR REPLACE INTO ${INTERACTIONS_TABLE} \n (id, platform, type, author_id, author_username, content, original_post_id, created_at, responded) \n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n [\n interaction.id,\n interaction.platform,\n interaction.type,\n interaction.authorId,\n interaction.authorUsername,\n interaction.content,\n interaction.originalPostId || null,\n interaction.createdAt,\n interaction.responded\n ]\n );\n }\n\n private async markAsResponded(interactionId: string, responseId: string, responseContent: string): Promise {\n await sqlite.execute(\n `UPDATE ${INTERACTIONS_TABLE} \n SET responded = TRUE, response_id = ?, response_content = ?, processed_at = ?\n WHERE id = ?`,\n [responseId, responseContent, new Date().toISOString(), interactionId]\n );\n }\n\n private async shouldRespondToMention(content: string, authorUsername: string): Promise {\n // Don't respond to our own mentions\n if (authorUsername.toLowerCase() === 'your_bot_username') {\n return false;\n }\n\n // Check if we've already responded to this user recently\n const recentResponse = await sqlite.execute(\n `SELECT COUNT(*) as count FROM ${INTERACTIONS_TABLE} \n WHERE author_username = ? \n AND responded = TRUE \n AND processed_at >= datetime('now', '-1 hour')`,\n [authorUsername]\n );\n\n if ((recentResponse.rows?.[0]?.count || 0) > 0) {\n return false; // Don't spam the same user\n }\n\n // Check for spam indicators\n const spamIndicators = [\n 'follow me', 'check out my', 'buy now', 'click here',\n 'free money', 'get rich', 'make money fast'\n ];\n\n const lowerContent = content.toLowerCase();\n if (spamIndicators.some(indicator => lowerContent.includes(indicator))) {\n return false;\n }\n\n // Check if it's a genuine question or interaction\n const interactionIndicators = [\n '?', 'how', 'what', 'why', 'when', 'where', 'help',\n 'thanks', 'thank you', 'great', 'awesome', 'love'\n ];\n\n return interactionIndicators.some(indicator => lowerContent.includes(indicator));\n }\n\n private async generateResponse(originalContent: string, type: 'mention' | 'reply'): Promise<{\n success: boolean;\n content?: string;\n error?: string;\n }> {\n try {\n const prompt = `You are a helpful and friendly social media bot. Someone has ${type === 'mention' ? 'mentioned' : 'replied to'} you with this message:\n\n\"${originalContent}\"\n\nGenerate a helpful, engaging, and authentic response. Keep it:\n- Under 280 characters (Twitter limit)\n- Friendly and professional\n- Helpful if they're asking a question\n- Grateful if they're giving positive feedback\n- Brief but meaningful\n\nDo not include hashtags in the response. Return only the response text.`;\n\n const completion = await this.openai.chat.completions.create({\n messages: [\n {\n role: \"system\",\n content: \"You are a helpful social media assistant that generates authentic, engaging responses to user interactions.\"\n },\n {\n role: \"user\",\n content: prompt\n }\n ],\n model: \"gpt-4o-mini\",\n max_tokens: 100,\n temperature: 0.7\n });\n\n const content = completion.choices[0]?.message?.content?.trim();\n \n if (!content) {\n return { success: false, error: 'No response generated' };\n }\n\n return { success: true, content };\n } catch (error) {\n return { success: false, error: error.message };\n }\n }\n\n async getInteractionStats(): Promise<{\n success: boolean;\n stats?: {\n totalInteractions: number;\n responsesGenerated: number;\n responseRate: number;\n interactionsToday: number;\n topInteractors: Array<{ username: string; count: number }>;\n };\n error?: string;\n }> {\n try {\n // Total interactions\n const totalResult = await sqlite.execute(\n `SELECT COUNT(*) as count FROM ${INTERACTIONS_TABLE}`\n );\n const totalInteractions = totalResult.rows?.[0]?.count || 0;\n\n // Responses generated\n const responsesResult = await sqlite.execute(\n `SELECT COUNT(*) as count FROM ${INTERACTIONS_TABLE} WHERE responded = TRUE`\n );\n const responsesGenerated = responsesResult.rows?.[0]?.count || 0;\n\n // Interactions today\n const todayResult = await sqlite.execute(\n `SELECT COUNT(*) as count FROM ${INTERACTIONS_TABLE} \n WHERE date(created_at) = date('now')`\n );\n const interactionsToday = todayResult.rows?.[0]?.count || 0;\n\n // Top interactors\n const topResult = await sqlite.execute(\n `SELECT author_username, COUNT(*) as count \n FROM ${INTERACTIONS_TABLE} \n GROUP BY author_username \n ORDER BY count DESC \n LIMIT 5`\n );\n const topInteractors = topResult.rows?.map(row => ({\n username: row.author_username,\n count: row.count\n })) || [];\n\n const responseRate = totalInteractions > 0 ? (responsesGenerated / totalInteractions) * 100 : 0;\n\n return {\n success: true,\n stats: {\n totalInteractions,\n responsesGenerated,\n responseRate: Math.round(responseRate * 100) / 100,\n interactionsToday,\n topInteractors\n }\n };\n } catch (error) {\n return { success: false, error: error.message };\n }\n }\n\n async getRecentInteractions(limit: number = 20): Promise<{\n success: boolean;\n interactions?: Array<{\n id: string;\n platform: string;\n type: string;\n authorUsername: string;\n content: string;\n createdAt: string;\n responded: boolean;\n responseContent?: string;\n }>;\n error?: string;\n }> {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${INTERACTIONS_TABLE} \n ORDER BY created_at DESC \n LIMIT ?`,\n [limit]\n );\n\n const interactions = result.rows?.map(row => ({\n id: row.id,\n platform: row.platform,\n type: row.type,\n authorUsername: row.author_username,\n content: row.content,\n createdAt: row.created_at,\n responded: row.responded,\n responseContent: row.response_content\n })) || [];\n\n return { success: true, interactions };\n } catch (error) {\n return { success: false, error: error.message };\n }\n }\n\n // Manual response generation for specific interactions\n async generateManualResponse(interactionId: string, customPrompt?: string): Promise<{\n success: boolean;\n content?: string;\n error?: string;\n }> {\n try {\n const interaction = await sqlite.execute(\n `SELECT * FROM ${INTERACTIONS_TABLE} WHERE id = ?`,\n [interactionId]\n );\n\n if (!interaction.rows?.length) {\n return { success: false, error: 'Interaction not found' };\n }\n\n const row = interaction.rows[0];\n const prompt = customPrompt || `Generate a response to: \"${row.content}\"`;\n\n return await this.generateResponse(prompt, row.type as 'mention' | 'reply');\n } catch (error) {\n return { success: false, error: error.message };\n }\n }\n}","deleted","label",[167,149],"backend","permalink","https://www.val.town/x/Venny/Chatbrain/code/backend/auto-responder.ts","extension","actionData","errors"]