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* Slack-GitHub Bug Connector\n *\n * This Val listens for new bug reports in a Slack channel and automatically\n * comments with related open bugs from GitHub.\n */\n\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { Octokit } from \"https://esm.sh/@octokit/rest@20.0.2\";\nimport { WebClient } from \"https://esm.sh/@slack/web-api@7.0.2\";\n\n// Dedupe events\n// https://api.slack.com/apis/events-api#responding-to-events\nconst processedEvents = new Set();\n\n// Initialize Slack client\nfunction getSlackClient(): WebClient | null {\n const slackToken = Deno.env.get(\"SLACK_BOT_TOKEN\");\n if (!slackToken) {\n console.error(\"SLACK_BOT_TOKEN not found\");\n return null;\n }\n return new WebClient(slackToken);\n}\n\n// Main handler for HTTP requests\nexport default async function(req: Request): Promise {\n try {\n // Handle Slack URL verification challenge\n if (req.method === \"POST\") {\n const body = await req.json() as any;\n\n // Slack sends a challenge parameter when setting up the webhook\n if (body.challenge) {\n return new Response(body.challenge, {\n headers: { \"Content-Type\": \"text/plain\" },\n });\n }\n\n // Process the Slack event\n if (body.event && body.event.type === \"message\") {\n // Check for duplicate events using event_id\n if (body.event_id && processedEvents.has(body.event_id)) {\n console.log(`Skipping duplicate event: ${body.event_id}`);\n return new Response(\"OK\");\n }\n\n // Add event to processed set\n if (body.event_id) {\n processedEvents.add(body.event_id);\n \n // Clean up old events (keep only last 500 to prevent memory leaks)\n if (processedEvents.size > 1000) {\n const eventsArray = Array.from(processedEvents);\n processedEvents.clear();\n eventsArray.slice(-500).forEach(id => processedEvents.add(id));\n }\n }\n\n // Process the event asynchronously to avoid Slack timeouts\n processSlackMessage(body.event).catch(error => {\n console.error(\"Error in async message processing:\", error);\n });\n }\n\n // Always respond with 200 OK to acknowledge receipt\n return new Response(\"OK\");\n }\n\n // For GET requests, show a simple status page\n return new Response(\"Slack GitHub Bug Connector is running\", {\n status: 200,\n headers: { \"Content-Type\": \"text/plain\" },\n });\n } catch (error) {\n console.error(\"Unhandled error in HTTP handler:\", error);\n return new Response(`Error: ${error.message}`, { status: 500 });\n }\n}\n\n/**\n * Process a message from Slack and check if it's a bug report\n */\nasync function processSlackMessage(event: any): Promise {\n // Skip messages in threads (we only want to process new messages)\n if (event.thread_ts && event.thread_ts !== event.ts) {\n return;\n }\n\n // Ensure event.text exists before processing\n if (!event.text) {\n return;\n }\n\n // Skip bot messages (including our own messages) to prevent loops\n if (event.bot_id || event.subtype === \"bot_message\") {\n return;\n }\n\n // Check if this looks like a bug report\n if (await isBugReport(event.text)) {\n try {\n // Get open issues from GitHub\n const openIssues = await fetchOpenIssues();\n\n // Use LLM to find semantically related issues\n const relatedIssues = await findRelatedIssues(event.text, openIssues);\n\n // Post the results back to Slack\n await postToSlackThread(event.channel, event.ts, formatRelatedIssues(relatedIssues));\n } catch (error) {\n console.error(\"Error processing bug report:\", error);\n try {\n await postToSlackThread(\n event.channel,\n event.ts,\n \":warning: I encountered an error while searching for related issues. Please check the GitHub repository configuration and permissions.\",\n );\n } catch (slackError) {\n console.error(\"Error posting to Slack:\", slackError);\n }\n }\n }\n}\n\n/**\n * Use LLM to detect if a message is a bug report\n */\nasync function isBugReportLLM(text: string): Promise {\n try {\n // Check if OpenAI API key is available\n if (!Deno.env.get(\"OPENAI_API_KEY\")) {\n console.warn(\"OpenAI API key not found - bug detection disabled\");\n return false;\n }\n\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n messages: [\n {\n role: \"system\",\n content: `You are an expert at analyzing messages to determine if they describe a bug, issue, or problem that needs technical attention.\n\nAnalyze the following message and determine if it's reporting a bug, technical issue, or problem. Consider:\n- Technical problems (crashes, errors, performance issues)\n- User experience issues (confusing UI, broken functionality)\n- Data problems (incorrect results, missing information)\n- Regression issues (something that used to work)\n- User complaints about functionality not working as expected\n\nDO NOT classify as bug reports:\n- Feature requests or suggestions\n- General questions or discussions\n- Positive feedback or compliments\n- Non-technical conversations\n- Casual mentions of words like \"issue\" in other contexts\n\nRespond with ONLY \"true\" or \"false\" - no explanation needed.`,\n },\n {\n role: \"user\",\n content: text,\n },\n ],\n model: \"gpt-4o-mini\", \n max_tokens: 10,\n temperature: 0,\n });\n\n const response = completion.choices[0].message.content?.toLowerCase().trim();\n return response === \"true\";\n } catch (error) {\n console.error(\"Error in LLM bug detection:\", error);\n return false;\n }\n}\n\n/**\n * Detect if a message is a bug report using LLM\n */\nasync function isBugReport(text: string | undefined): Promise {\n if (!text) {\n return false;\n }\n\n return await isBugReportLLM(text);\n}\n\n/**\n * Fetch all open issues from GitHub repository using Octokit\n */\nasync function fetchOpenIssues(): Promise {\n const githubToken = Deno.env.get(\"GITHUB_TOKEN\");\n const githubRepo = Deno.env.get(\"GITHUB_REPO\");\n\n if (!githubToken || !githubRepo) {\n return [];\n }\n\n try {\n // Parse owner and repo from the format \"owner/repo\"\n const [owner, repo] = githubRepo.split(\"/\");\n if (!owner || !repo) {\n console.error(\"GITHUB_REPO must be in format 'owner/repo'\");\n return [];\n }\n\n // Initialize Octokit \n const octokit = new Octokit({\n auth: githubToken,\n });\n\n let allIssues: any[] = [];\n let page = 1;\n const perPage = 100;\n\n // Fetch all open issues using Octokit\n while (true) {\n const response = await octokit.rest.issues.listForRepo({\n owner,\n repo,\n state: \"open\",\n per_page: perPage,\n page: page,\n });\n\n // Filter out pull requests (GitHub API includes PRs in issues endpoint)\n const actualIssues = response.data.filter(issue => !issue.html_url.includes(\"/pull/\"));\n\n allIssues = [...allIssues, ...actualIssues];\n\n if (response.data.length < perPage) {\n break;\n }\n\n page++;\n }\n\n return allIssues;\n } catch (error) {\n console.error(\"Error fetching issues with Octokit:\", error);\n return [];\n }\n}\n\n/**\n * Use LLM to find semantically related issues\n */\nasync function findRelatedIssues(slackMessage: string, issues: any[]): Promise {\n try {\n // Check if OpenAI API key is available\n if (!Deno.env.get(\"OPENAI_API_KEY\")) {\n return [];\n }\n\n if (issues.length === 0) {\n return [];\n }\n\n // Prepare issue data for the LLM (limit to avoid token limits)\n const issuesToAnalyze = issues.slice(0, 50); // Analyze most recent 50 issues\n const issueSummaries = issuesToAnalyze.map((issue, index) => {\n const updatedDate = new Date(issue.updated_at).toLocaleDateString();\n // Truncate body to keep within token limits\n const bodyPreview = issue.body\n ? issue.body.substring(0, 200) + (issue.body.length > 200 ? \"...\" : \"\")\n : \"No description\";\n\n return `${index}: #${issue.number} \"${issue.title}\" (updated ${updatedDate})\nDescription: ${bodyPreview}`;\n }).join(\"\\n\\n\");\n\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n messages: [\n {\n role: \"system\",\n content: `You are an expert at analyzing bug reports and matching them to existing GitHub issues. \n\nGiven a Slack message about a bug/issue and a list of open GitHub issues (with titles and descriptions), your job is to:\n1. Analyze the semantic meaning of the bug report\n2. Compare it against the issue titles and descriptions to find potentially related existing issues\n3. Only return issues that are genuinely relevant (not just keyword matches)\n4. Score relevance from 1-10 (only return issues scoring 6 or higher)\n5. Provide brief reasoning for each match\n\nReturn your response as a JSON array of objects with this structure (no markdown formatting, just pure JSON):\n[\n {\n \"issueIndex\": 0,\n \"relevanceScore\": 8,\n \"reasoning\": \"Brief explanation of why this issue might be related\"\n }\n]\n\nIf no issues are genuinely relevant, return an empty array []\n\nIMPORTANT: Return only pure JSON, no markdown code blocks or additional formatting.`,\n },\n {\n role: \"user\",\n content: `Bug Report from Slack:\n\"${slackMessage}\"\n\nOpen GitHub Issues:\n${issueSummaries}`,\n },\n ],\n model: \"gpt-4o\",\n max_tokens: 1000,\n temperature: 0.1,\n });\n\n const responseText = completion.choices[0].message.content;\n if (!responseText) {\n return [];\n }\n\n // Parse the JSON response\n let matches: { issueIndex: number; relevanceScore: number; reasoning: string }[] = [];\n try {\n // Clean the response text by removing markdown code blocks if present\n let cleanedResponse = responseText.trim();\n \n // Remove ```json and ```\n if (cleanedResponse.startsWith('```json')) {\n cleanedResponse = cleanedResponse.replace(/^```json\\s*/, '').replace(/\\s*```$/, '');\n } else if (cleanedResponse.startsWith('```')) {\n cleanedResponse = cleanedResponse.replace(/^```\\s*/, '').replace(/\\s*```$/, '');\n }\n \n matches = JSON.parse(cleanedResponse);\n } catch (parseError) {\n console.error(\"Error parsing LLM response:\", parseError);\n console.error(\"Raw response:\", responseText);\n return [];\n }\n\n // Convert to issue match objects with the structure we need\n const issueMatches = matches\n .filter(match => match.relevanceScore >= 6) // Only high-confidence matches\n .map(match => ({\n issue: issuesToAnalyze[match.issueIndex],\n relevanceScore: match.relevanceScore,\n reasoning: match.reasoning,\n }))\n .sort((a, b) => b.relevanceScore - a.relevanceScore); // Sort by relevance\n\n return issueMatches;\n } catch (error) {\n console.error(\"Error finding related issues:\", error);\n return [];\n }\n}\n\n/**\n * Format the related issues into final Slack message\n */\nfunction formatRelatedIssues(issueMatches: any[]): string {\n if (issueMatches.length === 0) {\n return \"No related open issues found. 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