[{"_1":2,"_361":-5,"_362":-5},"loaderData",{"_3":4,"_91":92,"_303":304},"root",{"_5":6,"_34":35,"_64":65},"ctx",{"_7":8,"_23":-5,"_24":25,"_26":27,"_28":22,"_29":22,"_30":22,"_31":32,"_33":22},"auth",{"_9":10,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5,"_19":-5,"_20":-5,"_21":22},"tokenType","session_token","sessionClaims","sessionId","sessionStatus","userId","actor","orgId","orgRole","orgSlug","orgPermissions","factorVerificationAge","isAuthenticated",false,"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","e3ca0a77ab07ff2ce3097208ffd6aa0e378d3c47","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":22,"_75":72,"_76":72,"_77":72,"_78":72,"_79":80,"_89":22,"_90":22},"__clerk_ssr_state",{"_9":10,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5,"_19":-5,"_20":-5,"_21":22},"__publishableKey","__proxyUrl","","__domain","__isSatellite","__signInUrl","__signUpUrl","__afterSignInUrl","__afterSignUpUrl","__clerk_debug",{"_81":22,"_21":22,"_82":72,"_83":84,"_85":72,"_86":45,"_87":22,"_88":72},"isSignedIn","proxyUrl","reason","session-token-and-uat-missing","message","publishableKey","isSatellite","domain","__telemetryDisabled","__telemetryDebug","routes/_app.x.$handle.$name",{"_93":94,"_95":96,"_97":43,"_98":99,"_100":101,"_102":103,"_148":149,"_283":284,"_285":286,"_292":293,"_163":294,"_297":-5,"_298":-5,"_299":22,"_300":22,"_301":302},"handle","dinavinter","name","os","branchName","path","accounts-schema.ts","version",67,"project",{"_104":105,"_95":96,"_106":107,"_108":-5,"_109":22,"_110":111,"_112":-5,"_113":-5,"_14":114,"_115":-5,"_116":22,"_117":-5,"_118":32,"_16":119,"_120":121,"_122":121,"_123":124,"_125":124,"_126":124,"_127":121,"_128":121,"_23":129,"_132":133,"_135":136,"_147":22},"id","e15ca240-4214-11f0-b519-76b3cceeab13","createdAt",["D",1749131789618],"deletedAt","legacyEnvVars","privacy","public","description","imageUrl","6d45e71e-9df4-45e8-82ab-e09c45bfc5a1","pinnedFileId","pinPreview","screenshotVersion","likeCount","b636164b-34c9-4e0c-9d39-dd3dc6f25436","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm",{"_93":94,"_130":131},"profileImageUrl","https://img.clerk.com/eyJ0eXBlIjoicHJveHkiLCJzcmMiOiJodHRwczovL2ltYWdlcy5jbGVyay5kZXYvb2F1dGhfZ2l0aHViL2ltZ18ycVgxSUNRd1V1VDlqTnNmYUh6MDA0VW1ldlMifQ","org",{"_93":94,"_134":131},"avatar","branch",{"_100":137,"_95":43,"_104":138,"_139":105,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":-5,"_145":96,"_146":94},167,"e15cf164-4214-11f0-b519-76b3cceeab13","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","isOwned","tree",[150,171,179,189,199,209,219,228,237,247,255,264,273],{"_104":151,"_95":152,"_153":154,"_155":-5,"_156":138,"_157":158,"_159":160,"_106":161,"_100":32,"_162":163,"_164":165,"_166":22,"_167":-5,"_168":169,"_98":170},"2086ef42-42de-11f0-8fb7-76b3cceeab13","README-author-update.md","fileId","2086f014-42de-11f0-8fb7-76b3cceeab13","parentId","branchId","branchVersion",63,"latest",true,["D",1749218224426],"fileType","file","content","# Project Author Update Scripts\n\nThis directory contains scripts to update existing projects in Gigya DS with proper author names where they are missing or set to \"Unknown\".\n\n## Scripts\n\n### 1. `update-project-authors.ts` (Basic Version)\nA straightforward script that updates projects with missing or \"Unknown\" authors.\n\n**Features:**\n- Fetches all projects from Gigya DS\n- Identifies projects needing author updates\n- Updates them with author data from `data.json`\n- Provides summary statistics\n\n### 2. `update-authors-advanced.ts` (Advanced Version)\nA comprehensive script with additional features and configuration options.\n\n**Features:**\n- Dry run mode to preview changes\n- Batch processing with rate limiting\n- Detailed analysis and reporting\n- Configurable update criteria\n- Better error handling and logging\n- Author name cleanup and formatting\n\n## Prerequisites\n\n1. **Environment Variables:**\n ```bash\n export GIGYA_API_KEY=\"your_api_key\"\n export GIGYA_APP_KEY=\"your_app_key\"\n export GIGYA_APP_SECRET=\"your_app_secret\"\n export GIGYA_DOMAIN=\"accounts.eu1.gigya.com\" # Optional, defaults to EU1\n ```\n\n2. **Data Source:**\n - Ensure `data.json` exists in the same directory\n - The file should contain project data with author information\n\n## Usage\n\n### Basic Script\n```bash\n# Run the basic update script\nnpx tsx update-project-authors.ts\n```\n\n### Advanced Script\n\n#### Preview Changes (Dry Run)\n```bash\n# Preview what would be updated without making changes\nDRY_RUN=true npx tsx update-authors-advanced.ts\n```\n\n#### Update All Missing Authors\n```bash\n# Update both missing and \"Unknown\" authors\nnpx tsx update-authors-advanced.ts\n```\n\n#### Update Only \"Unknown\" Authors\n```bash\n# Only update projects where author is specifically \"Unknown\"\nUPDATE_UNKNOWN_ONLY=true npx tsx update-authors-advanced.ts\n```\n\n## Configuration Options (Advanced Script)\n\n| Environment Variable | Default | Description |\n|---------------------|---------|-------------|\n| `DRY_RUN` | `false` | Preview changes without applying them |\n| `UPDATE_UNKNOWN_ONLY` | `false` | Only update \"Unknown\" authors, not missing ones |\n| `GIGYA_DOMAIN` | `accounts.eu1.gigya.com` | Gigya domain to use |\n\n## What Gets Updated\n\nThe scripts will update projects where the author field is:\n- `undefined` or `null`\n- Empty string (`\"\"`)\n- Set to `\"Unknown\"`\n- Set to `\"undefined\"` or `\"null\"` (string values)\n\n**Note:** If `UPDATE_UNKNOWN_ONLY=true`, only projects with author exactly equal to `\"Unknown\"` will be updated.\n\n## Author Name Processing\n\nThe advanced script includes author name cleanup:\n- User IDs like `I123456` become `User I123456`\n- Bot names like `osvote[bot]` become `osvote (Bot)`\n- Other names are used as-is\n\n## Output\n\nBoth scripts provide detailed logging including:\n- Projects being processed\n- Update success/failure status\n- Summary statistics\n- Verification of changes\n\n### Example Output\n```\n🔍 Starting author update process...\n📥 Found 25 existing projects\n📝 Created lookup for 20 projects with author data\n\n🔄 Updating \"bolt.diy\" with author: \"I347305\"\n✅ Successfully updated \"bolt.diy\"\n\n📊 Update Summary:\n✅ Successfully updated: 15 projects\n⏭️ Skipped: 8 projects\n❌ Errors: 0 projects\n📁 Total processed: 23 projects\n```\n\n## Error Handling\n\n- Network errors are caught and reported\n- Individual project failures don't stop the entire process\n- Rate limiting prevents API overload\n- Detailed error messages help with troubleshooting\n\n## Safety Features\n\n- **Dry run mode** allows previewing changes\n- **Batch processing** with delays prevents rate limiting\n- **Verification step** confirms updates were applied\n- **Backup consideration**: The scripts update existing records, so consider backing up your data first\n\n## Troubleshooting\n\n1. **Missing Environment Variables:**\n - Ensure all required Gigya credentials are set\n - Check that the domain is correct for your region\n\n2. **No Projects Updated:**\n - Verify `data.json` contains author information\n - Check that project titles match between DS and data.json\n - Use dry run mode to see what would be updated\n\n3. **API Errors:**\n - Check your Gigya credentials and permissions\n - Verify the DS schema exists and is accessible\n - Ensure rate limits aren't being exceeded\n\n4. **Author Data Not Found:**\n - Verify the project exists in `data.json`\n - Check that the title normalization (cabbabCase) matches\n - Some projects may not have author data in the source\n\n## Next Steps\n\nAfter running the update scripts:\n\n1. **Verify Results:** Check the application to ensure author names display correctly\n2. **Manual Review:** Review any projects that still need author assignment\n3. **Data Quality:** Consider implementing validation to prevent future author data issues\n4. **Monitoring:** Set up processes to ensure new projects include proper author information","deleted","label","children",[],[152],{"_104":172,"_95":173,"_153":174,"_155":-5,"_156":138,"_157":101,"_159":160,"_106":175,"_100":32,"_162":163,"_164":176,"_166":22,"_167":-5,"_168":177,"_98":178},"cbbc1bc4-42e5-11f0-ba72-76b3cceeab13","README-delete-test-projects.md","cbbc1c8c-42e5-11f0-ba72-76b3cceeab13",["D",1749221518146],"# Test Project Deletion Scripts\n\nThis directory contains scripts to safely delete projects with titles that are \"test\" or start with \"test\" from Gigya DS.\n\n## Scripts\n\n### 1. `delete-test-projects.ts` (Basic Version)\nA straightforward script that deletes test projects with minimal configuration.\n\n**Features:**\n- Identifies projects with titles matching \"test\" patterns\n- Soft deletes projects (marks as deleted rather than permanent removal)\n- Provides summary statistics and verification\n\n### 2. `delete-test-projects-advanced.ts` (Advanced Version)\nA comprehensive script with extensive safety features and configuration options.\n\n**Features:**\n- **Dry run mode** to preview deletions\n- **Confirmation prompts** for safety\n- **Flexible matching patterns** (exact match, starts with, custom patterns)\n- **Case sensitivity options**\n- **Batch processing** with rate limiting\n- **Detailed analysis and reporting**\n- **Comprehensive verification**\n\n## ⚠️ Safety Notice\n\n**IMPORTANT:** These scripts perform **soft deletes** by marking projects as `deleted: true` rather than permanently removing them from the database. This allows for potential recovery if needed.\n\n## Prerequisites\n\n1. **Environment Variables:**\n ```bash\n export GIGYA_API_KEY=\"your_api_key\"\n export GIGYA_APP_KEY=\"your_app_key\"\n export GIGYA_APP_SECRET=\"your_app_secret\"\n export GIGYA_DOMAIN=\"accounts.eu1.gigya.com\" # Optional, defaults to EU1\n ```\n\n2. **Permissions:**\n - Ensure your Gigya credentials have write access to the `oss_projects` data store\n\n## Usage\n\n### Basic Script\n```bash\n# Delete all test projects (basic version)\nnpx tsx delete-test-projects.ts\n```\n\n### Advanced Script\n\n#### Preview Deletions (Recommended First Step)\n```bash\n# Preview what would be deleted without making changes\nDRY_RUN=true npx tsx delete-test-projects-advanced.ts\n```\n\n#### Delete with Confirmation\n```bash\n# Delete test projects with confirmation prompt\nCONFIRM_DELETE=DELETE npx tsx delete-test-projects-advanced.ts\n```\n\n#### Delete Without Confirmation\n```bash\n# Delete test projects without confirmation (use with caution!)\nREQUIRE_CONFIRMATION=false npx tsx delete-test-projects-advanced.ts\n```\n\n#### Case Sensitive Matching\n```bash\n# Only match \"Test\" with exact case\nCASE_SENSITIVE=true npx tsx delete-test-projects-advanced.ts\n```\n\n#### Exact Match Only\n```bash\n# Only delete projects with title exactly \"test\"\nEXACT_MATCH_ONLY=true npx tsx delete-test-projects-advanced.ts\n```\n\n#### Custom Patterns\n```bash\n# Delete projects matching custom patterns\nCUSTOM_PATTERNS=\"demo,sample,temp\" npx tsx delete-test-projects-advanced.ts\n```\n\n## Configuration Options (Advanced Script)\n\n| Environment Variable | Default | Description |\n|---------------------|---------|-------------|\n| `DRY_RUN` | `false` | Preview deletions without executing them |\n| `REQUIRE_CONFIRMATION` | `true` | Require manual confirmation before deletion |\n| `CASE_SENSITIVE` | `false` | Use case-sensitive title matching |\n| `EXACT_MATCH_ONLY` | `false` | Only delete exact \"test\" matches, not \"test*\" |\n| `CUSTOM_PATTERNS` | `\"\"` | Comma-separated additional patterns to match |\n| `CONFIRM_DELETE` | `\"\"` | Set to \"DELETE\" to confirm deletion |\n\n## Matching Patterns\n\n### Default Behavior (Case Insensitive)\nThe scripts will delete projects with titles that:\n- Are exactly \"test\" (case insensitive)\n- Start with \"test\" (case insensitive)\n\n**Examples of matched titles:**\n- `test`\n- `Test`\n- `TEST`\n- `test project`\n- `Test Application`\n- `testing something`\n\n### Exact Match Only\nWith `EXACT_MATCH_ONLY=true`, only projects with title exactly \"test\" will be deleted.\n\n### Custom Patterns\nYou can specify additional patterns to match:\n```bash\nCUSTOM_PATTERNS=\"demo,sample,temp,prototype\"\n```\n\nThis will also delete projects containing these words in their titles.\n\n## Output Examples\n\n### Analysis Phase\n```\n🔍 Analyzing projects for test patterns...\n\n📊 Project Analysis:\n 📁 Total active projects: 25\n 🧪 Test projects found: 3\n 🎯 Exact 'test' matches: 1\n 🔤 Starts with 'test': 2\n 🔧 Custom pattern matches: 0\n\n📋 Projects that will be deleted:\n 1. \"test\" - Exact match: 'test'\n 👤 Author: User I123456\n 📅 Created: 12/3/2024\n 2. \"test project\" - Starts with 'test'\n 👤 Author: Developer\n 📅 Created: 12/2/2024\n```\n\n### Deletion Phase\n```\n🗑️ Starting test project deletion...\n\n📦 Processing batch 1/1\n\n🔄 Deleting \"test\"\n 📝 Reason: Exact match: 'test'\n ✅ Successfully deleted\n\n📊 Final Deletion Report:\n✅ Successfully deleted: 3 projects\n❌ Errors: 0 projects\n📈 Success rate: 100.0%\n```\n\n## Safety Features\n\n### 1. Dry Run Mode\n- Preview all changes before execution\n- See exactly which projects would be deleted\n- No actual modifications made\n\n### 2. Confirmation Prompts\n- Manual confirmation required by default\n- Must type \"DELETE\" exactly to proceed\n- Can be disabled for automation\n\n### 3. Soft Deletion\n- Projects marked as `deleted: true`\n- Original data preserved\n- Can potentially be recovered\n\n### 4. Batch Processing\n- Processes projects in small batches\n- Rate limiting to prevent API overload\n- Graceful error handling\n\n### 5. Comprehensive Verification\n- Confirms deletions were successful\n- Reports any remaining test projects\n- Shows before/after statistics\n\n## Recovery\n\nIf you need to recover deleted projects:\n\n```bash\n# Find deleted test projects\n# You would need to create a recovery script that:\n# 1. Searches for projects with deleted=true\n# 2. Filters for test projects\n# 3. Sets deleted=false to restore them\n```\n\n## Troubleshooting\n\n### 1. No Projects Found\n```\n✅ No test projects found to delete.\n```\n- Verify projects exist with test-like titles\n- Check case sensitivity settings\n- Ensure projects aren't already deleted\n\n### 2. Permission Errors\n```\n❌ Failed to delete: Access denied\n```\n- Verify Gigya credentials have write permissions\n- Check API key, app key, and secret are correct\n- Ensure you have access to the oss_projects data store\n\n### 3. Confirmation Issues\n```\n❌ Deletion not confirmed. Exiting.\n```\n- Set `CONFIRM_DELETE=DELETE` environment variable\n- Or use `REQUIRE_CONFIRMATION=false` to skip confirmation\n\n### 4. Rate Limiting\n```\n❌ Error: Too many requests\n```\n- The script includes built-in rate limiting\n- If issues persist, increase delay between requests\n- Process smaller batches\n\n## Best Practices\n\n1. **Always start with dry run:**\n ```bash\n DRY_RUN=true npx tsx delete-test-projects-advanced.ts\n ```\n\n2. **Review the analysis carefully:**\n - Check the list of projects to be deleted\n - Verify no legitimate projects are included\n - Pay attention to author and creation date\n\n3. **Use confirmation for safety:**\n - Keep `REQUIRE_CONFIRMATION=true` for manual operations\n - Only disable for trusted automated processes\n\n4. **Test with exact match first:**\n ```bash\n EXACT_MATCH_ONLY=true DRY_RUN=true npx tsx delete-test-projects-advanced.ts\n ```\n\n5. **Backup considerations:**\n - Consider exporting project data before deletion\n - Soft deletes allow recovery, but backup is safer\n\n## Integration with Other Scripts\n\nThese deletion scripts work well with other project management scripts:\n\n1. **After data imports:** Clean up test projects created during development\n2. **Before production:** Remove test data before going live\n3. **Regular maintenance:** Periodic cleanup of test projects\n\n## Example Workflows\n\n### Development Cleanup\n```bash\n# 1. Preview what would be deleted\nDRY_RUN=true npx tsx delete-test-projects-advanced.ts\n\n# 2. Delete exact \"test\" matches only\nEXACT_MATCH_ONLY=true CONFIRM_DELETE=DELETE npx tsx delete-test-projects-advanced.ts\n\n# 3. Delete all test projects\nCONFIRM_DELETE=DELETE npx tsx delete-test-projects-advanced.ts\n```\n\n### Automated Cleanup\n```bash\n# For CI/CD or automated environments\nREQUIRE_CONFIRMATION=false CUSTOM_PATTERNS=\"temp,demo\" npx tsx delete-test-projects-advanced.ts\n```\n\n### Conservative Cleanup\n```bash\n# Very careful deletion - exact matches only, case sensitive\nEXACT_MATCH_ONLY=true CASE_SENSITIVE=true CONFIRM_DELETE=DELETE npx tsx delete-test-projects-advanced.ts\n```",[],[173],{"_104":180,"_95":99,"_153":181,"_155":-5,"_156":138,"_157":182,"_159":160,"_106":183,"_100":184,"_162":185,"_164":186,"_166":22,"_167":-5,"_168":187,"_98":188},"d4a99f32-4253-11f0-a423-76b3cceeab13","7efb4cca-4253-11f0-ad15-76b3cceeab13",50,["D",1749158826598],7,"script","// Script to update Gigya Accounts schema for the OSS Contribution project\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n process.exit(1);\n}\n\nasync function makeGigyaRequest(endpoint, params) {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY,\n userKey: GIGYA_APP_KEY,\n secret: GIGYA_APP_SECRET,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\nasync function updateAccountsSchema() {\n console.log(\"Updating Gigya Accounts schema for OSS Contribution project...\");\n\n // Define the data schema fields to add/update\n const dataSchema = {\n dynamicSchema: true,\n fields: {\n \"vote\": {\n type: \"basic-string\",\n writeAccess: \"clientModify\",\n },\n \"assign\": {\n type: \"basic-string\",\n writeAccess: \"serverOnly\",\n },\n },\n };\n\n try {\n // Get current schema first\n console.log(\"Getting current accounts schema...\");\n const currentSchemaResponse = await makeGigyaRequest(\"accounts.getSchema\", {});\n\n if (currentSchemaResponse.errorCode !== 0) {\n console.error(\"❌ Failed to get current schema:\", currentSchemaResponse.errorMessage);\n return false;\n }\n\n console.log(\"✅ Current schema retrieved successfully\");\n\n // Update the schema with new fields\n console.log(\"Updating accounts schema with vote field...\");\n\n const response = await makeGigyaRequest(\"accounts.setSchema\", {\n dataSchema: JSON.stringify(dataSchema),\n });\n\n if (response.errorCode === 0) {\n console.log(\"✅ Accounts schema updated successfully\");\n } else {\n console.error(\"❌ Failed to update accounts schema:\", response.errorMessage);\n return false;\n }\n\n // Verify the schema was updated\n console.log(\"Verifying updated schema...\");\n const verifyResponse = await makeGigyaRequest(\"accounts.getSchema\", {});\n\n if (verifyResponse.errorCode === 0) {\n console.log(\"✅ Schema verification successful\");\n\n // Check if our new field is present\n if (verifyResponse.dataSchema && verifyResponse.dataSchema.vote) {\n const voteField = verifyResponse.dataSchema.vote;\n console.log(\n `✅ Vote field added: type=${voteField.type}, writeAccess=${voteField.writeAccess || \"serverOnly\"}`,\n );\n } else {\n console.log(\"⚠️ Vote field not found in schema response\");\n }\n\n // Show all data schema fields\n if (verifyResponse.dataSchema) {\n const fields = Object.keys(verifyResponse.dataSchema);\n console.log(\"Data schema fields:\", fields.join(\", \"));\n }\n } else {\n console.error(\"❌ Schema verification failed:\", verifyResponse.errorMessage);\n }\n\n return true;\n } catch (error) {\n console.error(\"❌ Error updating accounts schema:\", error.message);\n return false;\n }\n}\n\n// Run the script\nupdateAccountsSchema()\n .then((success) => {\n if (success) {\n console.log(\"\\n🎉 Accounts schema update completed successfully!\");\n console.log(\"\\nNext steps:\");\n console.log(\"1. Test voting functionality with the new schema\");\n console.log(\"2. Verify client-side vote updates work correctly\");\n } else {\n console.log(\"\\n❌ Accounts schema update failed!\");\n process.exit(1);\n }\n })\n .catch((error) => {\n console.error(\"❌ Script execution failed:\", error);\n process.exit(1);\n });",[],[99],{"_104":190,"_95":191,"_153":192,"_155":-5,"_156":138,"_157":193,"_159":160,"_106":194,"_100":195,"_162":185,"_164":196,"_166":22,"_167":-5,"_168":197,"_98":198},"b74e1a96-426f-11f0-89c8-76b3cceeab13","cleanup.tsx","0a13e63e-4225-11f0-9f81-76b3cceeab13",55,["D",1749170803254],6,"// Script to cleanup and reset Gigya DS data (use with caution!)\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n process.exit(1);\n}\n\nasync function makeGigyaRequest(endpoint, params) {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY,\n userKey: GIGYA_APP_KEY,\n secret: GIGYA_APP_SECRET,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\nasync function confirmCleanup() {\n console.log(\"⚠️ WARNING: This script will delete ALL data from Gigya DS!\");\n console.log(\"This action cannot be undone.\");\n console.log(\"\\nTo proceed, you must set the environment variable CONFIRM_CLEANUP=true\");\n\n if (process.env.CONFIRM_CLEANUP !== \"true\") {\n console.log(\"❌ Cleanup not confirmed. Exiting for safety.\");\n process.exit(0);\n }\n\n console.log(\"✅ Cleanup confirmed. Proceeding...\");\n return true;\n}\n\nasync function cleanupDSData() {\n await confirmCleanup();\n\n console.log(\"🧹 Starting Gigya DS data cleanup...\\n\");\n\n try {\n // 1. Get all projects\n console.log(\"1. Fetching all projects...\");\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects\",\n });\n\n if (searchResponse.errorCode !== 0) {\n console.log(\"❌ Failed to fetch projects:\", searchResponse.errorMessage);\n return false;\n }\n\n const projects = searchResponse.results || [];\n console.log(`Found ${projects.length} projects to cleanup`);\n\n if (projects.length === 0) {\n console.log(\"✅ No projects found. Nothing to cleanup.\");\n return true;\n }\n\n // 2. Mark all projects as deleted\n console.log(\"\\n2. Marking projects as deleted...\");\n let deletedCount = 0;\n let errorCount = 0;\n\n for (const project of projects) {\n try {\n const deleteResponse = await makeGigyaRequest(\"ds.delete\", {\n type: \"oss_projects\",\n oid: project.oid,\n });\n\n if (deleteResponse.errorCode === 0) {\n console.log(`✅ Deleted: ${project.data.title}`);\n deletedCount++;\n } else {\n console.log(`❌ Failed to delete ${project.data.title}:`, deleteResponse.errorMessage);\n errorCount++;\n }\n\n // Add delay to avoid rate limiting\n await new Promise((resolve) => setTimeout(resolve, 100));\n } catch (error) {\n console.error(`❌ Error deleting project ${project.data.title}:`, error.message);\n errorCount++;\n }\n }\n\n console.log(`\\n📊 Cleanup Summary:`);\n console.log(`✅ Successfully deleted: ${deletedCount} projects`);\n console.log(`❌ Errors: ${errorCount} projects`);\n\n // 3. Verify cleanup\n console.log(\"\\n3. Verifying cleanup...\");\n const verifyResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT COUNT(*) FROM oss_projects WHERE deleted != true\",\n });\n\n if (verifyResponse.errorCode === 0) {\n const remainingCount = verifyResponse.totalCount || 0;\n if (remainingCount === 0) {\n console.log(\"✅ Cleanup verification successful: No active projects remaining\");\n } else {\n console.log(`⚠️ Warning: ${remainingCount} active projects still found`);\n }\n }\n\n return true;\n } catch (error) {\n console.error(\"❌ Error during cleanup:\", error.message);\n return false;\n }\n}\n\n// Run the cleanup\ncleanupDSData()\n .then((success) => {\n if (success) {\n console.log(\"\\n🎉 DS data cleanup completed!\");\n console.log(\"\\nNext steps:\");\n console.log(\"1. Run load-projects-to-ds.js to reload fresh data\");\n console.log(\"2. Verify the application works correctly\");\n } else {\n console.log(\"\\n❌ Cleanup failed!\");\n process.exit(1);\n }\n })\n .catch((error) => {\n console.error(\"❌ Cleanup script failed:\", error);\n process.exit(1);\n });",[],[191],{"_104":200,"_95":201,"_153":202,"_155":-5,"_156":138,"_157":203,"_159":160,"_106":204,"_100":205,"_162":185,"_164":206,"_166":22,"_167":-5,"_168":207,"_98":208},"b22b53bc-42dd-11f0-bea7-76b3cceeab13","copy-projects-tods.ts","59080d84-4215-11f0-931e-76b3cceeab13",60,["D",1749218039278],17,"// Script to load projects from data.json into Gigya DS\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n process.exit(1);\n}\n\nasync function makeGigyaRequest(endpoint, params) {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY,\n userKey: GIGYA_APP_KEY,\n secret: GIGYA_APP_SECRET,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\n// Helper function to safely ensure a value is an array\nfunction ensureArray(value) {\n if (Array.isArray(value)) {\n return value;\n }\n if (value === null || value === undefined) {\n return [];\n }\n if (typeof value === \"string\") {\n try {\n const parsed = JSON.parse(value);\n return Array.isArray(parsed) ? parsed : [];\n } catch {\n return value\n .split(\",\")\n .map((item) => item.trim())\n .filter(Boolean);\n }\n }\n return [value].filter(Boolean);\n}\n\n// Helper function to normalize project data\nfunction normalizeProjectData(rawProject) {\n if (!rawProject || typeof rawProject !== \"object\") {\n return null;\n }\n\n try {\n const normalized = {\n title: String(rawProject.title || rawProject.projectName || \"Untitled Project\"),\n description: String(rawProject.description || \"No description available\"),\n repositoryUrl: String(rawProject.repositoryUrl || \"#\"),\n votes: Number(rawProject.reactions?.[\"+1\"] || 0) + Number(rawProject.reactions?.[\"heart\"] || 0),\n comments: Number(rawProject.comments) || 0,\n cmmitment: rawProject.timeCommitment && String(rawProject.timeCommitment),\n skills: rawProject.skills && ensureArray(rawProject.skills),\n contribution: rawProject.contribution && String(rawProject.contribution),\n author: rawProject.author?.name ?? String(rawProject.author?.name),\n enabled: Boolean(true),\n createdAt: rawProject.createdAt,\n updatedAt: rawProject.updatedAt,\n };\n\n return normalized;\n } catch (error) {\n console.error(\"Error normalizing project data:\", error);\n return null;\n }\n}\nimport data from \"./data.json\" with { \"type\": \"json\" };\nconsole.log(data);\n\nfunction cabbabCase(str: string): string {\n return str.replaceAll(/[\\W_]+/g, \"-\").toLowerCase();\n}\nconst { projects } = data;\nasync function loadProjectsToDS() {\n console.log(\"Loading projects from data.json to Gigya DS...\");\n\n try {\n // Read the data.json file\n\n if (!projects || !Array.isArray(projects)) {\n throw new Error(\"Invalid data.json format - projects array not found\");\n }\n\n console.log(`Found ${projects.length} projects in data.json`);\n\n let successCount = 0;\n let skipCount = 0;\n let errorCount = 0;\n\n for (const rawProject of projects) {\n try {\n // Skip archived projects\n if (rawProject.labels?.includes(\"os:archive\")) {\n console.log(`⏭️ Skipping archived project: ${rawProject.title}`);\n skipCount++;\n continue;\n }\n\n // Normalize the project data\n const projectData = normalizeProjectData(rawProject);\n\n if (!projectData) {\n console.error(`❌ Failed to normalize project: ${rawProject.title || rawProject.id}`);\n errorCount++;\n continue;\n }\n\n // Check if project already exists\n const oid = cabbabCase(projectData.title);\n\n try {\n const existingResponse = await makeGigyaRequest(\"ds.get\", {\n type: \"oss_projects\",\n oid: oid,\n });\n\n if (\n existingResponse.errorCode === 0\n && existingResponse.object?.data\n && !existingResponse.object.data.deleted\n ) {\n console.log(`⏭️ Project already exists: ${projectData.title}`);\n skipCount++;\n continue;\n }\n } catch (error) {\n // Project doesn't exist, continue with creation\n }\n\n // Store the project in Gigya DS\n const storeResponse = await makeGigyaRequest(\"ds.store\", {\n type: \"oss_projects\",\n data: JSON.stringify(projectData),\n oid: oid,\n });\n\n if (storeResponse.errorCode === 0) {\n console.log(`✅ Successfully loaded: ${projectData.title}`);\n successCount++;\n } else {\n console.error(`❌ Failed to store project ${projectData.title}:`, storeResponse.errorMessage);\n errorCount++;\n }\n\n // Add a small delay to avoid rate limiting\n await new Promise((resolve) => setTimeout(resolve, 100));\n } catch (error) {\n console.error(`❌ Error processing project ${rawProject.title || rawProject.id}:`, error.message);\n errorCount++;\n }\n }\n\n console.log(\"\\n📊 Loading Summary:\");\n console.log(`✅ Successfully loaded: ${successCount} projects`);\n console.log(`⏭️ Skipped: ${skipCount} projects`);\n console.log(`❌ Errors: ${errorCount} projects`);\n console.log(`📁 Total processed: ${successCount + skipCount + errorCount} projects`);\n\n return { successCount, skipCount, errorCount };\n } catch (error) {\n console.error(\"❌ Error loading projects to DS:\", error.message);\n throw error;\n }\n}\n\nasync function verifyLoadedData() {\n console.log(\"\\n🔍 Verifying loaded data...\");\n\n try {\n const response = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (response.errorCode === 0) {\n const count = response.results?.length || 0;\n console.log(`✅ Verification successful: Found ${count} projects in DS`);\n\n if (response.results && response.results.length > 0) {\n console.log(\"\\n📋 Sample projects:\");\n response.results.slice(0, 3).forEach((result, index) => {\n const project = result.data;\n console.log(`${index + 1}. ${project.title} (ID: ${project.id})`);\n });\n }\n } else {\n console.error(\"❌ Verification failed:\", response.errorMessage);\n }\n } catch (error) {\n console.error(\"❌ Error during verification:\", error.message);\n }\n}\n\n// Run the script\nloadProjectsToDS()\n .then(async (result) => {\n if (result.successCount > 0) {\n await verifyLoadedData();\n console.log(\"\\n🎉 Project loading completed successfully!\");\n console.log(\"\\nNext steps:\");\n console.log(\"1. Test the application to ensure projects are loading correctly\");\n console.log(\"2. Verify user voting and assignment functionality\");\n } else {\n console.log(\"\\n⚠️ No projects were loaded successfully!\");\n }\n })\n .catch((error) => {\n console.error(\"❌ Script execution failed:\", error);\n process.exit(1);\n });",[],[201],{"_104":210,"_95":211,"_153":212,"_155":-5,"_156":138,"_157":213,"_159":160,"_106":214,"_100":215,"_162":163,"_164":216,"_166":22,"_167":-5,"_168":217,"_98":218},"8834f28a-425f-11f0-b846-76b3cceeab13","data.json","92f50704-4215-11f0-b622-76b3cceeab13",51,["D",1749163852288],8,"{\n\n \n \"projects\": [\n {\n \"raw\": \"# bolt.diy\\r\\n\\r\\n### Repository URL\\r\\n\\r\\nhttps://github.com/stackblitz-labs/bolt.diy\\r\\n\\r\\n### Project Description\\r\\n\\r\\nbolt.diy is an open-source platform that enables users to prompt, run, edit, and deploy full-stack web applications directly in the browser using various Large Language Models (LLMs). It supports integration with multiple LLM providers, including OpenAI, Anthropic, HuggingFace, and more. The platform offers features like an integrated terminal, code versioning, and the ability to attach images to prompts, facilitating a seamless AI-powered development experience. \\r\\n\\r\\n\\r\\n### Potential Contribution Areas\\r\\n\\r\\nAgent Collaboration: Enhance bolt.diy to support MCP tool access and A2A-based agent collaboration, fostering better interoperability between SAP agents and bolt.diy projects.\\r\\nSAP Integration: Develop adapters or plugins to integrate bolt.diy with SAP's App Router or Cloud Foundry, enabling seamless deployment of applications within the SAP ecosystem.\\r\\n\\r\\n### Estimated Time Commitment\\r\\n\\r\\nMedium (4-8 hours/week)\\r\\n\\r\\n### Required Skills\\r\\n\\r\\nTypeScript\\r\\n\\r\\n### License\\r\\n\\r\\nMIT\\r\\n\\r\\n### Additional Information\\r\\n\\r\\n_No response_\",\n \"id\": 22,\n \"title\": \"bolt.diy\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/22/reactions\",\n \"total_count\": 1,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 1,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"os:app-builder\"\n ],\n \"votes\": 1,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"I347305\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-06-03T12:14:23Z\",\n \"updatedAt\": \"2025-06-03T13:06:02Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"https://github.com/stackblitz-labs/bolt.diy\",\n \"description\": \"bolt.diy is an open-source platform that enables users to prompt, run, edit, and deploy full-stack web applications directly in the browser using various Large Language Models (LLMs). It supports integration with multiple LLM providers, including OpenAI, Anthropic, HuggingFace, and more. The platform offers features like an integrated terminal, code versioning, and the ability to attach images to prompts, facilitating a seamless AI-powered development experience.\",\n \"contribution\": \"Agent Collaboration: Enhance bolt.diy to support MCP tool access and A2A-based agent collaboration, fostering better interoperability between SAP agents and bolt.diy projects.\\r\\nSAP Integration: Develop adapters or plugins to integrate bolt.diy with SAP's App Router or Cloud Foundry, enabling seamless deployment of applications within the SAP ecosystem.\",\n \"timeCommitment\": \"Medium (4-8 hours/week)\",\n \"skills\": [\n \"TypeScript\"\n ],\n \"license\": \"MIT\",\n \"additionalInfo\": \"_No response_\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"### Project Name\\n\\nDevstral_FT\\n\\n### Repository URL\\n\\nhttps://github.TBD/org-name/sap-tuned-devstral\\n\\n### Project Description\\n\\nProblem Statement/Motivation: 🎯\\r\\nCurrently, leveraging Large Language Models (LLMs) for code assistance, generation, and understanding often involves sending proprietary code to third-party services. This presents potential privacy and security concerns. Additionally, reliance on external services can introduce latency and lacks offline capabilities.\\r\\n\\r\\nOur services extensive codebase, contained within our Git repositories, represents a valuable dataset. Fine-tuning a capable open-source model like Devstral specifically on our code could provide a highly contextualized, fast, and private LLM assistant. This would empower developers with tailored code suggestions, explanations, and generation capabilities directly within their local development environment.\\r\\n\\r\\nGoals/Acceptance Criteria: ✅\\r\\n\\r\\nSuccessfully fine-tune a version of the Devstral model on a selected subset of our team's Git repositories.\\r\\nThe fine-tuned model can be run locally using Ollama on a typical developer machine with acceptable performance (e.g., response time for suggestions < 1-2 seconds).\\r\\nDevelopers can query the local model from VS Code (e.g., via a compatible extension like Continue or a similar tool) for:\\r\\nCode completion/suggestion relevant to our codebase.\\r\\nExplaining snippets of our proprietary code.\\r\\nGenerating boilerplate or utility functions based on our coding patterns.\\r\\nThe entire process maintains data privacy by keeping our codebase and the fine-tuned model strictly within our local/private infrastructure.\\r\\nDocumentation is created for setting up and using the local LLM.\\r\\n\\r\\n\\r\\nHigh-Level Tasks: 🛠️\\r\\n\\r\\n[ ] Research & Planning:\\r\\n[ ] Identify suitable Git repositories and branches for the training dataset.\\r\\n[ ] Research best practices for preparing code data for fine-tuning (e.g., filtering, formatting, anonymization if needed).\\r\\n[ ] Evaluate hardware requirements for fine-tuning and local inference.\\r\\n[ ] Investigate and select the most appropriate VS Code plugin(s) for Ollama integration.\\r\\n\\r\\n[ ] Data Preparation:\\r\\n[ ] Clone selected repositories.\\r\\n[ ] Implement scripts to clean, preprocess, and format the code data.\\r\\n\\r\\n[ ] Model Fine-Tuning:\\r\\n[ ] Set up the fine-tuning environment for Devstral.\\r\\n[ ] Perform initial fine-tuning runs and iterate on parameters.\\r\\n[ ] Evaluate the performance and quality of the fine-tuned model.\\r\\n\\r\\n[ ] Deployment & Integration:\\r\\n[ ] Package the fine-tuned model for Ollama.\\r\\n[ ] Develop instructions for team members to install Ollama and the custom model.\\r\\n[ ] Configure VS Code plugin(s) to connect to the local Ollama instance.\\r\\n\\r\\n[ ] Testing & Feedback:\\r\\n[ ] Conduct internal testing with the development team.\\r\\n[ ] Gather feedback and iterate on the model/setup.\\r\\n\\r\\n[ ] Documentation:\\r\\n[ ] Create user guides for setup and usage.\\r\\n[ ] Document the fine-tuning process for future reference.\\r\\n\\r\\n\\r\\nConsiderations/Potential Challenges: 🤔\\r\\nData Volume & Quality: Ensuring enough high-quality, representative code is used for effective fine-tuning.\\r\\nComputational Resources: Fine-tuning can be resource-intensive. We need to assess if local machines are sufficient or if a dedicated training server is needed.\\r\\nModel Performance: Achieving a good balance between model size, inference speed, and the quality of assistance.\\r\\nMaintenance: The model may need to be periodically retrained as the codebase evolves.\\n\\n### Potential Contribution Areas\\n\\n_No response_\\n\\n### Estimated Time Commitment\\n\\nMedium (4-8 hours/week)\\n\\n### Required Skills\\n\\n_No response_\\n\\n### License\\n\\n_No response_\\n\\n### Additional Information\\n\\n_No response_\",\n \"id\": 27,\n \"title\": \"🚀 Project: Fine-tune Devstral for Local, Private Code Assistance via Ollama & VS Code\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/27/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"I500695\",\n \"avatar\": \"https://avatars.github.tools.sap/u/19453?\"\n },\n \"createdAt\": \"2025-06-03T15:03:49Z\",\n \"updatedAt\": \"2025-06-03T15:03:49Z\",\n \"languages\": [],\n \"projectName\": \"Devstral_FT\",\n \"repositoryUrl\": \"https://github.TBD/org-name/sap-tuned-devstral\",\n \"description\": \"Problem Statement/Motivation: 🎯\\r\\nCurrently, leveraging Large Language Models (LLMs) for code assistance, generation, and understanding often involves sending proprietary code to third-party services. This presents potential privacy and security concerns. Additionally, reliance on external services can introduce latency and lacks offline capabilities.\\r\\n\\r\\nOur services extensive codebase, contained within our Git repositories, represents a valuable dataset. Fine-tuning a capable open-source model like Devstral specifically on our code could provide a highly contextualized, fast, and private LLM assistant. This would empower developers with tailored code suggestions, explanations, and generation capabilities directly within their local development environment.\\r\\n\\r\\nGoals/Acceptance Criteria: ✅\\r\\n\\r\\nSuccessfully fine-tune a version of the Devstral model on a selected subset of our team's Git repositories.\\r\\nThe fine-tuned model can be run locally using Ollama on a typical developer machine with acceptable performance (e.g., response time for suggestions < 1-2 seconds).\\r\\nDevelopers can query the local model from VS Code (e.g., via a compatible extension like Continue or a similar tool) for:\\r\\nCode completion/suggestion relevant to our codebase.\\r\\nExplaining snippets of our proprietary code.\\r\\nGenerating boilerplate or utility functions based on our coding patterns.\\r\\nThe entire process maintains data privacy by keeping our codebase and the fine-tuned model strictly within our local/private infrastructure.\\r\\nDocumentation is created for setting up and using the local LLM.\\r\\n\\r\\n\\r\\nHigh-Level Tasks: 🛠️\\r\\n\\r\\n[ ] Research & Planning:\\r\\n[ ] Identify suitable Git repositories and branches for the training dataset.\\r\\n[ ] Research best practices for preparing code data for fine-tuning (e.g., filtering, formatting, anonymization if needed).\\r\\n[ ] Evaluate hardware requirements for fine-tuning and local inference.\\r\\n[ ] Investigate and select the most appropriate VS Code plugin(s) for Ollama integration.\\r\\n\\r\\n[ ] Data Preparation:\\r\\n[ ] Clone selected repositories.\\r\\n[ ] Implement scripts to clean, preprocess, and format the code data.\\r\\n\\r\\n[ ] Model Fine-Tuning:\\r\\n[ ] Set up the fine-tuning environment for Devstral.\\r\\n[ ] Perform initial fine-tuning runs and iterate on parameters.\\r\\n[ ] Evaluate the performance and quality of the fine-tuned model.\\r\\n\\r\\n[ ] Deployment & Integration:\\r\\n[ ] Package the fine-tuned model for Ollama.\\r\\n[ ] Develop instructions for team members to install Ollama and the custom model.\\r\\n[ ] Configure VS Code plugin(s) to connect to the local Ollama instance.\\r\\n\\r\\n[ ] Testing & Feedback:\\r\\n[ ] Conduct internal testing with the development team.\\r\\n[ ] Gather feedback and iterate on the model/setup.\\r\\n\\r\\n[ ] Documentation:\\r\\n[ ] Create user guides for setup and usage.\\r\\n[ ] Document the fine-tuning process for future reference.\\r\\n\\r\\n\\r\\nConsiderations/Potential Challenges: 🤔\\r\\nData Volume & Quality: Ensuring enough high-quality, representative code is used for effective fine-tuning.\\r\\nComputational Resources: Fine-tuning can be resource-intensive. We need to assess if local machines are sufficient or if a dedicated training server is needed.\\r\\nModel Performance: Achieving a good balance between model size, inference speed, and the quality of assistance.\\r\\nMaintenance: The model may need to be periodically retrained as the codebase evolves.\",\n \"contribution\": \"_No response_\",\n \"timeCommitment\": \"Medium (4-8 hours/week)\",\n \"skills\": [],\n \"license\": \"_No response_\",\n \"additionalInfo\": \"_No response_\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"### Project Name\\n\\nCVE Mitigator\\n\\n### Repository URL\\n\\nhttps://github.com/sap-samples/cve-mitigator\\n\\n### Project Description\\n\\nCVE Mitigator is a developer-focused tool designed to automate the mitigation workflow for Common Vulnerabilities and Exposures (CVEs) detected in SAP development environments. It connects to SAP’s security scanning tools (e.g. Whitesource), fetches detected vulnerabilities, and intelligently maps them to affected source code in Git-based repositories. Leveraging AI-assisted suggestions, the tool proposes relevant code changes, library upgrades, or configuration fixes. This dramatically reduces mean-time-to-remediate (MTTR) and enhances security response efficiency across SAP projects. The tool can be used as a CLI utility, GitHub bot, or CI pipeline integration.\\n\\n### Potential Contribution Areas\\n\\n_No response_\\n\\n### Estimated Time Commitment\\n\\nMedium (4-8 hours/week)\\n\\n### Required Skills\\n\\n_No response_\\n\\n### License\\n\\n_No response_\\n\\n### Additional Information\\n\\n_No response_\",\n \"id\": 26,\n \"title\": \"CVE Mitigator\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/26/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"I074921\",\n \"avatar\": \"https://avatars.github.tools.sap/u/6395?\"\n },\n \"createdAt\": \"2025-06-03T14:40:59Z\",\n \"updatedAt\": \"2025-06-03T14:41:00Z\",\n \"languages\": [],\n \"projectName\": \"CVE Mitigator\",\n \"repositoryUrl\": \"https://github.com/sap-samples/cve-mitigator\",\n \"description\": \"CVE Mitigator is a developer-focused tool designed to automate the mitigation workflow for Common Vulnerabilities and Exposures (CVEs) detected in SAP development environments. It connects to SAP’s security scanning tools (e.g. Whitesource), fetches detected vulnerabilities, and intelligently maps them to affected source code in Git-based repositories. Leveraging AI-assisted suggestions, the tool proposes relevant code changes, library upgrades, or configuration fixes. This dramatically reduces mean-time-to-remediate (MTTR) and enhances security response efficiency across SAP projects. The tool can be used as a CLI utility, GitHub bot, or CI pipeline integration.\",\n \"contribution\": \"_No response_\",\n \"timeCommitment\": \"Medium (4-8 hours/week)\",\n \"skills\": [],\n \"license\": \"_No response_\",\n \"additionalInfo\": \"_No response_\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"### Project Name\\n\\nJira Support Agent\\n\\n### Repository URL\\n\\nhttps://github.TBD/org-name/support-agent-jira\\n\\n### Project Description\\n\\nThe Support Agent (Jira) is an AI-powered automation tool that enhances support ticket triaging and stakeholder communication within Jira. It intelligently analyzes incoming tickets to assign them to the correct teams, apply relevant tags and labels, and post contextual comments when information is missing. The agent is designed to improve operational efficiency, reduce human error, and ensure faster turnaround times by streamlining the first-touch resolution process in enterprise support workflows.\\n\\n### Potential Contribution Areas\\n\\n- NLP Integration: Improve natural language understanding to better classify and route tickets based on intent and content.\\r\\n- Custom Workflows: Develop rule-based or LLM-based flows for specific Jira projects or support queues.\\r\\n- Stakeholder Interaction: Enhance the agent’s comment generation to ask for missing information in a context-aware, human-like manner.\\r\\n- Jira API Enhancements: Extend the agent’s capabilities to support bulk operations, custom fields, and integration with other Atlassian tools (e.g., Confluence, Opsgenie).\\n\\n### Estimated Time Commitment\\n\\nLow (1-3 hours/week)\\n\\n### Required Skills\\n\\n_No response_\\n\\n### License\\n\\n_No response_\\n\\n### Additional Information\\n\\n_No response_\",\n \"id\": 25,\n \"title\": \"Jira Support Agent\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/25/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"I355895\",\n \"avatar\": \"https://avatars.github.tools.sap/u/8901?\"\n },\n \"createdAt\": \"2025-06-03T14:28:06Z\",\n \"updatedAt\": \"2025-06-03T14:28:06Z\",\n \"languages\": [],\n \"projectName\": \"Jira Support Agent\",\n \"repositoryUrl\": \"https://github.TBD/org-name/support-agent-jira\",\n \"description\": \"The Support Agent (Jira) is an AI-powered automation tool that enhances support ticket triaging and stakeholder communication within Jira. It intelligently analyzes incoming tickets to assign them to the correct teams, apply relevant tags and labels, and post contextual comments when information is missing. The agent is designed to improve operational efficiency, reduce human error, and ensure faster turnaround times by streamlining the first-touch resolution process in enterprise support workflows.\",\n \"contribution\": \"- NLP Integration: Improve natural language understanding to better classify and route tickets based on intent and content.\\r\\n- Custom Workflows: Develop rule-based or LLM-based flows for specific Jira projects or support queues.\\r\\n- Stakeholder Interaction: Enhance the agent’s comment generation to ask for missing information in a context-aware, human-like manner.\\r\\n- Jira API Enhancements: Extend the agent’s capabilities to support bulk operations, custom fields, and integration with other Atlassian tools (e.g., Confluence, Opsgenie).\",\n \"timeCommitment\": \"Low (1-3 hours/week)\",\n \"skills\": [],\n \"license\": \"_No response_\",\n \"additionalInfo\": \"_No response_\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"### Project Name\\n\\nSoftware Dependency Upgrade Agent\\n\\n### Repository URL\\n\\nhttps://githubTBD/org-name/dependency-upgrade-agent\\n\\n### Project Description\\n\\nThe Software Dependency Upgrade Agent is an intelligent automation tool designed to monitor and upgrade outdated dependencies in internal codebases. It works across various project types (Node.js, Python, Java, etc.), detecting outdated libraries, proposing or applying version upgrades, validating compatibility, and optionally opening merge requests. Integrated with Git and CI pipelines, the agent reduces tech debt and security risks while saving developer time. Its pluggable design allows easy adaptation to organizational policies and internal registries.\\n\\n### Potential Contribution Areas\\n\\n- Language Support: Extend support for additional languages and package managers (e.g., Maven, pip, Cargo).\\r\\n- Smart Upgrade Logic: Implement AI-based changelog analysis to flag breaking changes or suggest semantic versioning strategies.\\r\\n- CI/CD Integration: Build adapters for CI tools like GitHub Actions, GitLab CI, or SAP CI/CD service to run upgrades and tests automatically.\\r\\n- Custom Policies: Enable configuration of internal upgrade policies (e.g., allow minor upgrades only, require code owners' review).\\n\\n### Estimated Time Commitment\\n\\nLow (1-3 hours/week)\\n\\n### Required Skills\\n\\n_No response_\\n\\n### License\\n\\n_No response_\\n\\n### Additional Information\\n\\n_No response_\",\n \"id\": 24,\n \"title\": \"Software Dependency Upgrade Agent\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/24/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"I355895\",\n \"avatar\": \"https://avatars.github.tools.sap/u/8901?\"\n },\n \"createdAt\": \"2025-06-03T14:26:31Z\",\n \"updatedAt\": \"2025-06-03T14:26:31Z\",\n \"languages\": [],\n \"projectName\": \"Software Dependency Upgrade Agent\",\n \"repositoryUrl\": \"https://githubTBD/org-name/dependency-upgrade-agent\",\n \"description\": \"The Software Dependency Upgrade Agent is an intelligent automation tool designed to monitor and upgrade outdated dependencies in internal codebases. It works across various project types (Node.js, Python, Java, etc.), detecting outdated libraries, proposing or applying version upgrades, validating compatibility, and optionally opening merge requests. Integrated with Git and CI pipelines, the agent reduces tech debt and security risks while saving developer time. Its pluggable design allows easy adaptation to organizational policies and internal registries.\",\n \"contribution\": \"- Language Support: Extend support for additional languages and package managers (e.g., Maven, pip, Cargo).\\r\\n- Smart Upgrade Logic: Implement AI-based changelog analysis to flag breaking changes or suggest semantic versioning strategies.\\r\\n- CI/CD Integration: Build adapters for CI tools like GitHub Actions, GitLab CI, or SAP CI/CD service to run upgrades and tests automatically.\\r\\n- Custom Policies: Enable configuration of internal upgrade policies (e.g., allow minor upgrades only, require code owners' review).\",\n \"timeCommitment\": \"Low (1-3 hours/week)\",\n \"skills\": [],\n \"license\": \"_No response_\",\n \"additionalInfo\": \"_No response_\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"### Project Name\\n\\nLLM Proxy Server for SAP AI Core\\n\\n### Repository URL\\n\\nhttps://github.com/sap-samples/llm-proxy-sap-ai-core\\n\\n### Project Description\\n\\nThe LLM Proxy Server for SAP AI Core is an open-source project designed to serve as a lightweight, performant, and extensible intermediary between SAP AI Core and a variety of large language model (LLM) backends. Inspired by solutions like LightLLM, this proxy server standardizes interactions with different model providers (OpenAI, Anthropic, HuggingFace, etc.), handles rate limiting and caching, and simplifies integration for enterprise use cases. Its purpose is to provide a scalable, multi-tenant LLM gateway that plugs seamlessly into the SAP AI Core inference pipeline.\\n\\n### Potential Contribution Areas\\n\\n- Model Adapter Layer: Implement new adapters to support additional LLM providers or fine-tuned models hosted on SAP AI Core.\\r\\n- Request Routing & Optimization: Improve routing logic, caching strategies, and load balancing between LLM providers.\\r\\n- Security & Multi-Tenancy: Enhance authentication, logging, and quota management to support secure, tenant-aware deployments.\\r\\n- SAP Integration: Develop SDK components or API contracts to enable easy consumption of the proxy within SAP BTP-based applications.\\n\\n### Estimated Time Commitment\\n\\nMedium (4-8 hours/week)\\n\\n### Required Skills\\n\\n_No response_\\n\\n### License\\n\\n_No response_\\n\\n### Additional Information\\n\\n_No response_\",\n \"id\": 23,\n \"title\": \"LLM Proxy Server for SAP AI Core\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/23/reactions\",\n \"total_count\": 1,\n \"+1\": 1,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 1,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"I355895\",\n \"avatar\": \"https://avatars.github.tools.sap/u/8901?\"\n },\n \"createdAt\": \"2025-06-03T14:25:01Z\",\n \"updatedAt\": \"2025-06-03T14:25:01Z\",\n \"languages\": [],\n \"projectName\": \"LLM Proxy Server for SAP AI Core\",\n \"repositoryUrl\": \"https://github.com/sap-samples/llm-proxy-sap-ai-core\",\n \"description\": \"The LLM Proxy Server for SAP AI Core is an open-source project designed to serve as a lightweight, performant, and extensible intermediary between SAP AI Core and a variety of large language model (LLM) backends. Inspired by solutions like LightLLM, this proxy server standardizes interactions with different model providers (OpenAI, Anthropic, HuggingFace, etc.), handles rate limiting and caching, and simplifies integration for enterprise use cases. Its purpose is to provide a scalable, multi-tenant LLM gateway that plugs seamlessly into the SAP AI Core inference pipeline.\",\n \"contribution\": \"- Model Adapter Layer: Implement new adapters to support additional LLM providers or fine-tuned models hosted on SAP AI Core.\\r\\n- Request Routing & Optimization: Improve routing logic, caching strategies, and load balancing between LLM providers.\\r\\n- Security & Multi-Tenancy: Enhance authentication, logging, and quota management to support secure, tenant-aware deployments.\\r\\n- SAP Integration: Develop SDK components or API contracts to enable easy consumption of the proxy within SAP BTP-based applications.\",\n \"timeCommitment\": \"Medium (4-8 hours/week)\",\n \"skills\": [],\n \"license\": \"_No response_\",\n \"additionalInfo\": \"_No response_\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"### Project Name\\n\\n_No response_\\n\\n### Repository URL\\n\\nhttps://github.com/BerriAI/litellm\\n\\n### Project Description\\n\\nknown proxy for several tools (used by high volume projects such as aidr/claude code/cline/etc)\\n\\n### Potential Contribution Areas\\n\\nsupport sap core ai in lite llm which can be generic solution for all the tools that we want to support core ai\\r\\n\\r\\nnote: someone from sap already started to work on it: https://github.com/mbrner/litellm/tree/main/litellm/llms/sap/chat\\n\\n### Estimated Time Commitment\\n\\nMedium (4-8 hours/week)\\n\\n### Required Skills\\n\\nPython, Prompt Engineering\\n\\n### License\\n\\n_No response_\\n\\n### Additional Information\\n\\n_No response_\",\n \"id\": 21,\n \"title\": \"litellm\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/21/reactions\",\n \"total_count\": 1,\n \"+1\": 1,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 1,\n \"comments\": 1,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"I538157\",\n \"avatar\": \"https://avatars.github.tools.sap/u/22102?\"\n },\n \"createdAt\": \"2025-05-26T15:41:06Z\",\n \"updatedAt\": \"2025-05-26T15:41:16Z\",\n \"languages\": [],\n \"projectName\": \"_No response_\",\n \"repositoryUrl\": \"https://github.com/BerriAI/litellm\",\n \"description\": \"known proxy for several tools (used by high volume projects such as aidr/claude code/cline/etc)\",\n \"contribution\": \"support sap core ai in lite llm which can be generic solution for all the tools that we want to support core ai\\r\\n\\r\\nnote: someone from sap already started to work on it: https://github.com/mbrner/litellm/tree/main/litellm/llms/sap/chat\",\n \"timeCommitment\": \"Medium (4-8 hours/week)\",\n \"skills\": [\n \"Python\",\n \"Prompt Engineering\"\n ],\n \"license\": \"_No response_\",\n \"additionalInfo\": \"_No response_\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# 📌 OpenDevin\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/OpenDevin/OpenDevin\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Open-source autonomous software engineer focused on building full dev environments and tasks.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Ideal candidate for MCP to unify tooling access (e.g. terminals, file systems) and A2A to interoperate with external agents (e.g. testers, reviewers).\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Modularize tasks using A2A to break software dev flow into subprocesses\\r\\n - Create devops MCP tool for CF deployment automation\\r\\n - Align agents with SAP’s internal CLI tools (btp CLI)\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, TypeScript, DevOps Automation, LLMs\\r\\n\\r\\n ## 🔑 SAP Relevance \\r\\n - Modularize tasks using A2A to break software dev flow into subprocesses\\r\\n- Create devops MCP tool for CF deployment automation\\r\\n- Align agents with SAP’s internal CLI tools (btp CLI)\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `OpenDevin.json`\\r\\n \",\n \"id\": 20,\n \"title\": \"OpenDevin\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/20/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:06Z\",\n \"updatedAt\": \"2025-05-26T16:15:59Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# Continue\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/continuedev/continue\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Open-source VS Code/JetBrains extension for AI pair programming and agentic editing.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Could benefit from A2A to collaborate with remote agents (e.g. testers, doc agents) and MCP to fetch standardized tool or context data (e.g. bug reports, CI results).\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Add SAP authorization to Continue editor agent\\r\\n - Write MCP plugin to fetch dev logs or issues from SAP ecosystem\\r\\n - Integrate with SAP application studio\\r\\n - Add diffrent SAP context providers\\r\\n - Build AI reviewer that uses A2A to consult SAP coding guidelines\\r\\n\\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, VS Code Extensions, Python, LLM Integration\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `Continue.json`\\r\\n \",\n \"id\": 19,\n \"title\": \"Continue\",\n \"description\": \"Continue is an IDE Assistant designed to enhance the coding experience by providing support and suggestions directly within the integrated development environment. It aims to streamline the coding process, making it easier for developers to write, debug, and optimize their code without switching contexts. This tool is open source, allowing for community contributions and improvements, and it is not a no-code solution, indicating that it is intended for users who are comfortable with coding.\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/19/reactions\",\n \"total_count\": 1,\n \"+1\": 1,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"os:smart-ide\"\n ],\n \"votes\": 1,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:05Z\",\n \"updatedAt\": \"2025-06-03T13:10:38Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# code-sandbox-mcp\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/Automata-Labs-team/code-sandbox-mcp\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Code sandbox tool server implementing MCP, built for AI agents to execute code in a safe environment.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Implements MCP directly; useful as a tool server for any agent using MCP. Could benefit from hardening, tests, extensions.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Integrate with CloudFundry/ Kyma runtime\\r\\n - Secure sandbox with SA identity in multi-agent flows\\r\\n\\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, Docker, MCP, Security\\r\\n\\r\\n ## 🔑 SAP Relevance \\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `code-sandbox-mcp.json`\\r\\n \",\n \"id\": 18,\n \"title\": \"code-sandbox-mcp\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/18/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:05Z\",\n \"updatedAt\": \"2025-05-26T16:19:31Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \" **Semantic Kernel**\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/microsoft/semantic-kernel\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Lightweight orchestration SDK to build agents combining LLMs with tools, memory, and plans.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Supports MCP concepts via tool plugins; could benefit from A2A for cross-agent coordination.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Plug kernel plugins into A2A so that orchestration spans agents\\r\\n - Use SAP Gateway (OData) as agentized tool set via MCP\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n C#, Python, AI Orchestration, LLM Integration\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `Semantic Kernel.json`\\r\\n \",\n \"id\": 16,\n \"title\": \"Semantic Kernel\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/16/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"microsoft\",\n \"os:agent-builder\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:04Z\",\n \"updatedAt\": \"2025-06-03T13:08:50Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# OpenGPTs \\r\\n \\r\\n ---\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/langchain-ai/opengpts\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Multi-agent interface with LangChain to create and interact with autonomous GPTs via UI.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Could expose agents as A2A endpoints and add MCP-based tools into LangChain tools list.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Add UI for registering tools into SAP Launchpad via MCP schema\\r\\n - Wire agent config into SAP IAS and provisioning interface\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, LangChain, TypeScript, LLM Agents\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `OpenGPTs.json`\\r\\n \",\n \"id\": 15,\n \"title\": \"OpenGPTs\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/15/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:archive\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:03Z\",\n \"updatedAt\": \"2025-06-03T13:02:25Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# smol-developer\\r\\n ---\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/smol-ai/developer\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Smol AI’s autonomous developer – plans and executes entire software tasks with LLMs.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Could be modularized with A2A for coordination and enhanced via MCP tool integrations (debuggers, browsers, docs).\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Provide SAP GitOps overlay on agent-generated names\\r\\n - Auto-gen build + deploy workflows for BTP or CAP from A2A agent intents\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, Autonomous Agents, Software Engineering, LLMs\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `smol-developer.json`\\r\\n \",\n \"id\": 14,\n \"title\": \"smol-developer\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/14/reactions\",\n \"total_count\": 1,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 1,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 1,\n \"comments\": 1,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:03Z\",\n \"updatedAt\": \"2025-05-26T16:28:11Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# Aider \\r\\n ---\\r\\n ## 🔗 Repository URL \\r\\n https://github.com/Aider-AI/aider\\r\\n \\r\\n ## 🧠 Project Description \\r\\n CLI tool for AI pair programming with Git integration.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n No current MCP/A2A use; could benefit from MCP tool access and A2A-based agent collaboration.\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, Git, LLMs, CLI Tools\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `Aider.json`\\r\\n \",\n \"id\": 13,\n \"title\": \"Aider\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/13/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 1,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:02Z\",\n \"updatedAt\": \"2025-05-26T16:29:39Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# Helicone \\r\\n ---\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/Helicone/helicone\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Observability and analytics layer for LLM usage, focused on prompt tracing and cost tracking.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Could benefit from A2A for distributed agent monitoring and from MCP to standardize tool usage across tracked models.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Add A2A hooks for remote tool feedback to prompt monitors\\r\\n - Expose telemetry as MCP service for dynamic model adjustments\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, Go, Python, LLM Observability\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `Helicone.json`\\r\\n \",\n \"id\": 12,\n \"title\": \"Helicone\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/12/reactions\",\n \"total_count\": 1,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 1,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 1,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:01Z\",\n \"updatedAt\": \"2025-05-26T16:30:57Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \" ## 🔗 Repository URL \\r\\n https://github.com/lastmile-ai/mcp-agent\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Framework for building agents using the Model Context Protocol.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Built on MCP; could be extended with A2A support for inter-agent communication.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Build SAP-specific tool servers (e.g., SAP Help Search, DB Query)\\r\\n - Add A2A protocol endpoints for inter-agent federation on BTP (?)\\r\\n\\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, Model Context Protocol (MCP), Agent Orchestration\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `MCP Agent.json`\\r\\n \",\n \"id\": 11,\n \"title\": \"MCP Agent\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/11/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"os:agent-builder\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:01Z\",\n \"updatedAt\": \"2025-06-03T13:10:06Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# MCP Inspector \\r\\n ---\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/modelcontextprotocol/inspector\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Inspector tool for MCP messages—monitors and visualizes requests/responses between clients and servers.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Built to debug MCP; could be enhanced with better visualizations or support for A2A traffic in future extensions.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Extend to support multi servers \\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Small (1-3 hours/week)\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, React, MCP, Debugging Tools\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `inspector.json`\\r\\n \",\n \"id\": 10,\n \"title\": \"MCP Inspector\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/10/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:10:00Z\",\n \"updatedAt\": \"2025-06-03T13:04:40Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# Open WebUI \\r\\n ---\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/open-webui/open-webui\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Local web UI for interacting with LLMs like OpenAI, Ollama, LM Studio, and others.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Could integrate MCP to allow access to external tool APIs and A2A for backend AI agent interaction.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Add SAP API Hub wrapper as MCP server\\r\\n - Build agent-to-agent pipeline that connects support tooling to dev tools\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, Python, LLM APIs, Web UI Development\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `Open WebUI.json`\\r\\n \",\n \"id\": 9,\n \"title\": \"Open WebUI\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/9/reactions\",\n \"total_count\": 2,\n \"+1\": 2,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"os:chat-app\"\n ],\n \"votes\": 2,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:59Z\",\n \"updatedAt\": \"2025-06-03T13:09:13Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# GPT Pilot\\r\\nAI software engineer that generates full-stack apps from specifications and user feedback.\\r\\n\\r\\n ---\\r\\n\\r\\n ## 🔗 Repository URL \\r\\n https://github.com/Pythagora-io/gpt-pilot\\r\\n \\r\\n ## 🧠 Project Description \\r\\nGPT Pilot demonstrates high autonomy by employing a multi-agent system (Product Owner Agent, Software Architect Agent, DevOps Agent) to handle requirement analysis, technical planning, environment setup, and TDD-based code generation\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Could be modularized with A2A for task delegation to specialized agents (e.g. UX, backend, infra) and integrate MCP for tool access during code generation.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Extend the pilot capabilities with SAP diffrent applications (CDS, App Router, Worzone, Identity, AMS etc) \\r\\n - Implement design-to-code toolchain with SAP Fiori assets as MCP service\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, Python, Full-Stack Development, LLMs\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `GPT Pilot.json`\\r\\n \",\n \"id\": 8,\n \"title\": \"GPT Pilot\",\n \"description\": \"GPT Pilot is an AI-driven assistant for building full-fledged applications autonomously from natural language prompts. GPT Pilot demonstrates high autonomy by employing a multi-agent system (Product Owner Agent, Software Architect Agent, DevOps Agent) to handle requirement analysis, technical planning, environment setup, and TDD-based code generation.\",\n\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/8/reactions\",\n \"total_count\": 1,\n \"+1\": 1,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"os:app-builder\"\n ],\n \"votes\": 1,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:59Z\",\n \"updatedAt\": \"2025-06-03T13:09:04Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"\\r\\n ## 🔗 Repository URL \\r\\n https://github.com/plastic-labs/tutor-gpt\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Personalized AI tutor with theory-of-mind capabilities.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Not currently using MCP/A2A; potential for multi-agent tutoring with A2A and dynamic tool access via MCP.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Create multi-agent tutoring model with A2A (lesson agent, quiz agent)\\r\\n - Add MCP integration for retrieving learning content from SAP Learning Hub\\r\\n - Develop context manager that tailors response via SAP profile extensions\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, Next.js, Python, LLMs\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `Tutor-GPT.json`\\r\\n \",\n \"id\": 7,\n \"title\": \"Tutor-GPT\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/7/reactions\",\n \"total_count\": 1,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 1,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:archive\"\n ],\n \"votes\": 1,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:58Z\",\n \"updatedAt\": \"2025-06-03T13:03:30Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# 📌 Big-AGI\\r\\n---\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/enricoros/big-AGI\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Open AGI interface and agentic framework with extensible toolset and local-first model options.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Framework is ready for MCP/A2A plugins—excellent candidate to embed protocol support for agent interoperability and external tool usage.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Enable App Router extensions for multi-agent interface\\r\\n - Use MCP to pull service info from SAP HANA Cloud metadata layer\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, Python, AI Orchestration, Tools Integration\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `big-AGI.json`\\r\\n \",\n \"id\": 6,\n \"title\": \"big-AGI\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/6/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:58Z\",\n \"updatedAt\": \"2025-05-26T16:45:59Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# Zed\\r\\n \\r\\n--- \\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/zed-industries/zed\\r\\n \\r\\n ## 🧠 Project Description \\r\\n High-performance code editor built in Rust with collaborative features.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Though primarily Rust, could be extended with A2A for agent co-editing, or embed MCP clients for tooling support in AI-assisted workflows.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - \\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Rust, TypeScript, Real-time Collaboration, Editor Development\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `Zed.json`\\r\\n \",\n \"id\": 5,\n \"title\": \"Zed\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/5/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"os:smart-ide\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:57Z\",\n \"updatedAt\": \"2025-06-03T13:09:26Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# 📌 XState Agent\\r\\n---\\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/statelyai/agent\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Agent framework built on top of XState to manage reasoning and actions via finite state machines.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n A strong fit for both protocols — could expose agents as A2A services and leverage MCP to connect tools declaratively inside the state machine logic.\\r\\n \\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Integrate Agent tools with MCP servers\\r\\n - Integration with SAP agent builder\\r\\n - Add agent visualization\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n TypeScript, XState, State Machines, LLM Integration\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `XState Agent.json`\\r\\n \",\n \"id\": 4,\n \"title\": \"XState Agent\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/4/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\",\n \"os:smart-ide\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:57Z\",\n \"updatedAt\": \"2025-06-03T13:09:42Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# AutoGen Studio\\r\\n---\\r\\n \\r\\n## 🔗 Repository URL \\r\\nhttps://github.com/microsoft/autogen\\r\\n\\r\\n## 🧠 Project Description \\r\\nVisual drag-and-drop interface for building multi-agent workflows using AutoGen.\\r\\n\\r\\n## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\nAlthough initiated by Microsoft, many forks/extensions are open. Guild could fork and add MCP/A2A compatibility to let agents talk across frameworks or use MCP-based tools.\\r\\n\\r\\n ## 🛠️ How AI Guild Can Contribute \\r\\n - Fork and integrate MCP into agent graph visualizer\\r\\n- Embed SAP BTP tool server templates for LLM workflows\\r\\n- Allow App Router to proxy agent tool execution\\r\\n \\r\\n## 🕒 Estimated Time Commitment \\r\\nMedium (4-8 hours/week)\\r\\n\\r\\n\\r\\n## 🧪 Required Skills \\r\\nPython, TypeScript, Multi-Agent Systems, Low-Code Tools\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n Creative Commons Attribution 4.0 International\\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `AutoGen Studio.json`\\r\\n \",\n \"id\": 3,\n \"title\": \"AutoGen Studio\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/3/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:suggestion\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:56Z\",\n \"updatedAt\": \"2025-06-03T13:06:39Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# LlamaIndex \\r\\n ---\\r\\n \\r\\n \\r\\n ## 🔗 Repository URL \\r\\n https://github.com/jerryjliu/llama_index\\r\\n \\r\\n ## 🧠 Project Description \\r\\n Framework for connecting LLMs to external data using custom indexes, tools, and retrieval.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Ideal fit for MCP to standardize tool access and for A2A to interact as a specialized knowledge agent.\\r\\n \\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, Data Indexing, Knowledge Retrieval, LLMs\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `LlamaIndex.json`\\r\\n \",\n \"id\": 2,\n \"title\": \"LlamaIndex\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/2/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:archive\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:55Z\",\n \"updatedAt\": \"2025-06-03T13:01:04Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n },\n {\n \"raw\": \"# 📜 DocETL: Powering Complex Document Processing Pipelines\\r\\n \\r\\n---\\r\\n ## 🔗 Repository URL \\r\\n https://github.com/ucbepic/docetl\\r\\n \\r\\n ## 🧠 Project Description \\r\\n LLM-powered document-centric data pipeline builder.\\r\\n \\r\\n ## 🧩 Interoperability: Agent & Tool Protocol Fit \\r\\n Does not use MCP/A2A; could benefit by using A2A to delegate tasks and MCP for standardized tool access.\\r\\n \\r\\n ## 🕒 Estimated Time Commitment \\r\\n Medium (4-8 hours/week)\\r\\n\\r\\n \\r\\n ## 🧪 Required Skills \\r\\n Python, Data Pipelines, Document AI, LLM Integration\\r\\n\\r\\n \\r\\n ## ⚖️ License \\r\\n \\r\\n \\r\\n ---\\r\\n \\r\\n ## 💬 Additional Information \\r\\n \\r\\n \\r\\n 📎 Linked source: `DocETL.json`\\r\\n \",\n \"id\": 1,\n \"title\": \"DocETL\",\n \"reactions\": {\n \"url\": \"https://github.tools.sap/api/v3/repos/AI-GUILD-IL/os-contribution/issues/1/reactions\",\n \"total_count\": 0,\n \"+1\": 0,\n \"-1\": 0,\n \"laugh\": 0,\n \"hooray\": 0,\n \"confused\": 0,\n \"heart\": 0,\n \"rocket\": 0,\n \"eyes\": 0\n },\n \"labels\": [\n \"os:archive\"\n ],\n \"votes\": 0,\n \"comments\": 0,\n \"prerequisites\": {\n \"notDuplicate\": false,\n \"hasLicense\": false,\n \"isActive\": false\n },\n \"author\": {\n \"name\": \"osvote[bot]\",\n \"avatar\": \"https://avatars.github.tools.sap/u/39522?\"\n },\n \"createdAt\": \"2025-05-15T20:09:55Z\",\n \"updatedAt\": \"2025-06-03T13:03:06Z\",\n \"languages\": [],\n \"projectName\": \"\",\n \"repositoryUrl\": \"\",\n \"description\": \"\",\n \"contribution\": \"\",\n \"timeCommitment\": \"\",\n \"skills\": [],\n \"license\": \"\",\n \"additionalInfo\": \"\",\n \"highlights\": \"\"\n }\n ]\n}",[],[211],{"_104":220,"_95":221,"_153":222,"_155":-5,"_156":138,"_157":223,"_159":22,"_106":224,"_100":32,"_162":185,"_164":225,"_166":22,"_167":-5,"_168":226,"_98":227},"b31e30e8-42e5-11f0-a397-76b3cceeab13","delete-test-projects-advanced.ts","b31e31b0-42e5-11f0-a397-76b3cceeab13",66,["D",1749221476845],"// Advanced script to delete projects with titles that are \"test\" or start with \"test\"\n// Includes safety features, dry run mode, and comprehensive reporting\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\n// Configuration options\nconst CONFIG = {\n dryRun: process.env.DRY_RUN === \"true\", // Set to true to preview deletions without executing them\n requireConfirmation: process.env.REQUIRE_CONFIRMATION !== \"false\", // Require manual confirmation\n batchSize: 5, // Number of projects to delete in each batch\n delayBetweenRequests: 200, // Milliseconds to wait between API calls\n caseSensitive: process.env.CASE_SENSITIVE === \"true\", // Case sensitive matching\n exactMatchOnly: process.env.EXACT_MATCH_ONLY === \"true\", // Only delete exact \"test\" matches\n customPatterns: process.env.CUSTOM_PATTERNS?.split(\",\") || [], // Additional patterns to match\n};\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n console.log(\"\\nOptional environment variables:\");\n console.log(\"- DRY_RUN=true (preview deletions without executing)\");\n console.log(\"- REQUIRE_CONFIRMATION=false (skip confirmation prompt)\");\n console.log(\"- CASE_SENSITIVE=true (case sensitive title matching)\");\n console.log(\"- EXACT_MATCH_ONLY=true (only delete exact 'test' matches)\");\n console.log(\"- CUSTOM_PATTERNS=pattern1,pattern2 (additional patterns to match)\");\n process.exit(1);\n}\n\ninterface ProjectData {\n id?: number;\n title: string;\n description: string;\n repositoryUrl: string;\n votes: number;\n comments: number;\n commitment?: string;\n skills?: string[];\n contribution?: string;\n author?: string;\n enabled: boolean;\n createdAt?: string;\n updatedAt?: string;\n deleted?: boolean;\n deletedAt?: string;\n}\n\ninterface GigyaResponse {\n errorCode: number;\n errorMessage?: string;\n results?: Array<{\n oid: string;\n data: ProjectData;\n }>;\n object?: {\n data: ProjectData;\n };\n}\n\ninterface DeletionStats {\n total: number;\n matched: number;\n deleted: number;\n errors: number;\n skipped: number;\n}\n\nasync function makeGigyaRequest(endpoint: string, params: Record): Promise {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY!,\n userKey: GIGYA_APP_KEY!,\n secret: GIGYA_APP_SECRET!,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\nfunction isTestProject(title: string): { isMatch: boolean; reason: string } {\n const originalTitle = title.trim();\n const checkTitle = CONFIG.caseSensitive ? originalTitle : originalTitle.toLowerCase();\n \n // Check exact match for \"test\"\n if (checkTitle === \"test\") {\n return { isMatch: true, reason: \"Exact match: 'test'\" };\n }\n \n // If exact match only, stop here\n if (CONFIG.exactMatchOnly) {\n return { isMatch: false, reason: \"Not exact match\" };\n }\n \n // Check if starts with \"test\"\n if (checkTitle.startsWith(\"test\")) {\n return { isMatch: true, reason: \"Starts with 'test'\" };\n }\n \n // Check custom patterns\n for (const pattern of CONFIG.customPatterns) {\n if (pattern.trim()) {\n const checkPattern = CONFIG.caseSensitive ? pattern.trim() : pattern.trim().toLowerCase();\n if (checkTitle.includes(checkPattern)) {\n return { isMatch: true, reason: `Matches custom pattern: '${pattern}'` };\n }\n }\n }\n \n return { isMatch: false, reason: \"No match\" };\n}\n\nasync function analyzeProjects(): Promise {\n console.log(\"🔍 Analyzing projects for test patterns...\");\n \n try {\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (searchResponse.errorCode !== 0) {\n throw new Error(`Failed to fetch projects: ${searchResponse.errorMessage}`);\n }\n\n const projects = searchResponse.results || [];\n \n const analysis = {\n total: projects.length,\n testProjects: 0,\n exactMatches: 0,\n startsWithTest: 0,\n customPatternMatches: 0,\n };\n\n const matchedProjects: Array<{ project: any; reason: string }> = [];\n\n for (const project of projects) {\n const { isMatch, reason } = isTestProject(project.data.title);\n \n if (isMatch) {\n analysis.testProjects++;\n matchedProjects.push({ project, reason });\n \n if (reason.includes(\"Exact match\")) {\n analysis.exactMatches++;\n } else if (reason.includes(\"Starts with\")) {\n analysis.startsWithTest++;\n } else if (reason.includes(\"custom pattern\")) {\n analysis.customPatternMatches++;\n }\n }\n }\n\n console.log(\"\\n📊 Project Analysis:\");\n console.log(` 📁 Total active projects: ${analysis.total}`);\n console.log(` 🧪 Test projects found: ${analysis.testProjects}`);\n console.log(` 🎯 Exact 'test' matches: ${analysis.exactMatches}`);\n console.log(` 🔤 Starts with 'test': ${analysis.startsWithTest}`);\n console.log(` 🔧 Custom pattern matches: ${analysis.customPatternMatches}`);\n\n if (matchedProjects.length > 0) {\n console.log(\"\\n📋 Projects that will be deleted:\");\n matchedProjects.forEach((item, index) => {\n const { project, reason } = item;\n console.log(` ${index + 1}. \"${project.data.title}\" - ${reason}`);\n if (project.data.author) {\n console.log(` 👤 Author: ${project.data.author}`);\n }\n if (project.data.createdAt) {\n console.log(` 📅 Created: ${new Date(project.data.createdAt).toLocaleDateString()}`);\n }\n });\n }\n\n } catch (error) {\n console.error(\"❌ Error during analysis:\", error);\n throw error;\n }\n}\n\nasync function confirmDeletion(projectCount: number): Promise {\n if (!CONFIG.requireConfirmation) {\n console.log(\"⚠️ Confirmation skipped (REQUIRE_CONFIRMATION=false)\");\n return true;\n }\n\n console.log(`\\n⚠️ WARNING: About to delete ${projectCount} test projects!`);\n console.log(\"This action cannot be undone.\");\n console.log(\"\\nTo proceed, type 'DELETE' (case sensitive):\");\n \n // In a real interactive environment, you would use readline\n // For this script, we'll check an environment variable\n const confirmation = process.env.CONFIRM_DELETE;\n \n if (confirmation === \"DELETE\") {\n console.log(\"✅ Deletion confirmed.\");\n return true;\n } else {\n console.log(\"❌ Deletion not confirmed. Exiting.\");\n console.log(\"To confirm deletion, set: CONFIRM_DELETE=DELETE\");\n return false;\n }\n}\n\nasync function deleteTestProjects(): Promise {\n console.log(`\\n🗑️ Starting test project deletion... ${CONFIG.dryRun ? \"(DRY RUN)\" : \"\"}`);\n \n const stats: DeletionStats = {\n total: 0,\n matched: 0,\n deleted: 0,\n errors: 0,\n skipped: 0,\n };\n\n try {\n // Fetch all projects\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (searchResponse.errorCode !== 0) {\n throw new Error(`Failed to fetch projects: ${searchResponse.errorMessage}`);\n }\n\n const allProjects = searchResponse.results || [];\n stats.total = allProjects.length;\n\n // Identify test projects\n const testProjects = allProjects.filter(project => {\n const { isMatch } = isTestProject(project.data.title);\n return isMatch;\n });\n\n stats.matched = testProjects.length;\n\n if (testProjects.length === 0) {\n console.log(\"✅ No test projects found to delete.\");\n return stats;\n }\n\n // Confirm deletion\n if (!CONFIG.dryRun) {\n const confirmed = await confirmDeletion(testProjects.length);\n if (!confirmed) {\n stats.skipped = testProjects.length;\n return stats;\n }\n }\n\n // Process deletions in batches\n for (let i = 0; i < testProjects.length; i += CONFIG.batchSize) {\n const batch = testProjects.slice(i, i + CONFIG.batchSize);\n console.log(`\\n📦 Processing batch ${Math.floor(i / CONFIG.batchSize) + 1}/${Math.ceil(testProjects.length / CONFIG.batchSize)}`);\n\n for (const project of batch) {\n try {\n const { reason } = isTestProject(project.data.title);\n console.log(`🔄 ${CONFIG.dryRun ? \"[DRY RUN] \" : \"\"}Deleting \"${project.data.title}\"`);\n console.log(` 📝 Reason: ${reason}`);\n\n if (!CONFIG.dryRun) {\n // Mark project as deleted (soft delete)\n const updatedProjectData = {\n ...project.data,\n deleted: true,\n deletedAt: new Date().toISOString(),\n updatedAt: new Date().toISOString(),\n };\n\n const deleteResponse = await makeGigyaRequest(\"ds.store\", {\n type: \"oss_projects\",\n data: JSON.stringify(updatedProjectData),\n oid: project.oid,\n });\n\n if (deleteResponse.errorCode === 0) {\n console.log(` ✅ Successfully deleted`);\n stats.deleted++;\n } else {\n console.error(` ❌ Failed to delete: ${deleteResponse.errorMessage}`);\n stats.errors++;\n }\n\n // Rate limiting delay\n await new Promise((resolve) => setTimeout(resolve, CONFIG.delayBetweenRequests));\n } else {\n stats.deleted++; // Count as deleted for dry run stats\n }\n\n } catch (error) {\n console.error(`❌ Error deleting \"${project.data.title}\":`, error);\n stats.errors++;\n }\n }\n }\n\n return stats;\n\n } catch (error) {\n console.error(\"❌ Error during deletion process:\", error);\n throw error;\n }\n}\n\nasync function generateReport(stats: DeletionStats): Promise {\n console.log(\"\\n📊 Final Deletion Report:\");\n console.log(\"=\" .repeat(50));\n console.log(`📁 Total projects analyzed: ${stats.total}`);\n console.log(`🎯 Test projects found: ${stats.matched}`);\n console.log(`🗑️ Successfully deleted: ${stats.deleted}`);\n console.log(`⏭️ Skipped: ${stats.skipped}`);\n console.log(`❌ Errors: ${stats.errors}`);\n \n if (stats.matched > 0) {\n const successRate = (stats.deleted / stats.matched * 100).toFixed(1);\n console.log(`📈 Success rate: ${successRate}%`);\n }\n\n if (CONFIG.dryRun) {\n console.log(\"\\n⚠️ This was a DRY RUN - no projects were actually deleted\");\n console.log(\" Set DRY_RUN=false and CONFIRM_DELETE=DELETE to execute deletions\");\n }\n}\n\nasync function verifyDeletion(): Promise {\n if (CONFIG.dryRun) return;\n \n console.log(\"\\n🔍 Verifying deletions...\");\n \n try {\n // Check active projects\n const activeResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n // Check deleted projects\n const deletedResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted = true\",\n });\n\n if (activeResponse.errorCode === 0 && deletedResponse.errorCode === 0) {\n const activeProjects = activeResponse.results || [];\n const deletedProjects = deletedResponse.results || [];\n \n const remainingTestProjects = activeProjects.filter(project => {\n const { isMatch } = isTestProject(project.data.title);\n return isMatch;\n });\n \n const deletedTestProjects = deletedProjects.filter(project => {\n const { isMatch } = isTestProject(project.data.title);\n return isMatch;\n });\n \n console.log(`✅ Verification complete:`);\n console.log(` 📝 Total active projects: ${activeProjects.length}`);\n console.log(` 🧪 Remaining test projects: ${remainingTestProjects.length}`);\n console.log(` 🗑️ Deleted test projects: ${deletedTestProjects.length}`);\n \n if (remainingTestProjects.length > 0) {\n console.log(\"\\n⚠️ Test projects still active:\");\n remainingTestProjects.forEach((project, index) => {\n const { reason } = isTestProject(project.data.title);\n console.log(` ${index + 1}. \"${project.data.title}\" - ${reason}`);\n });\n } else {\n console.log(\"🎉 All matching test projects have been successfully deleted!\");\n }\n\n } else {\n console.error(\"❌ Verification failed\");\n }\n } catch (error) {\n console.error(\"❌ Error during verification:\", error);\n }\n}\n\n// Main execution\nasync function main() {\n console.log(\"🚀 Advanced Test Project Deletion Script\");\n console.log(\"=\" .repeat(50));\n \n console.log(\"🔧 Configuration:\");\n console.log(` Dry Run: ${CONFIG.dryRun}`);\n console.log(` Require Confirmation: ${CONFIG.requireConfirmation}`);\n console.log(` Case Sensitive: ${CONFIG.caseSensitive}`);\n console.log(` Exact Match Only: ${CONFIG.exactMatchOnly}`);\n console.log(` Custom Patterns: ${CONFIG.customPatterns.length > 0 ? CONFIG.customPatterns.join(\", \") : \"None\"}`);\n \n try {\n await analyzeProjects();\n const stats = await deleteTestProjects();\n await generateReport(stats);\n await verifyDeletion();\n \n console.log(\"\\n🎉 Script completed successfully!\");\n \n } catch (error) {\n console.error(\"❌ Script execution failed:\", error);\n process.exit(1);\n }\n}\n\n// Run the script\nmain();",[],[221],{"_104":229,"_95":230,"_153":231,"_155":-5,"_156":138,"_157":232,"_159":160,"_106":233,"_100":32,"_162":185,"_164":234,"_166":22,"_167":-5,"_168":235,"_98":236},"928a9920-42e5-11f0-b5b9-76b3cceeab13","delete-test-projects.ts","928a9a06-42e5-11f0-b5b9-76b3cceeab13",65,["D",1749221422191],"// Script to delete projects with titles that are \"test\" or start with \"test\"\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n process.exit(1);\n}\n\ninterface ProjectData {\n id?: number;\n title: string;\n description: string;\n repositoryUrl: string;\n votes: number;\n comments: number;\n commitment?: string;\n skills?: string[];\n contribution?: string;\n author?: string;\n enabled: boolean;\n createdAt?: string;\n updatedAt?: string;\n deleted?: boolean;\n}\n\ninterface GigyaResponse {\n errorCode: number;\n errorMessage?: string;\n results?: Array<{\n oid: string;\n data: ProjectData;\n }>;\n object?: {\n data: ProjectData;\n };\n}\n\nasync function makeGigyaRequest(endpoint: string, params: Record): Promise {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY!,\n userKey: GIGYA_APP_KEY!,\n secret: GIGYA_APP_SECRET!,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\nfunction isTestProject(title: string): boolean {\n const normalizedTitle = title.toLowerCase().trim();\n return normalizedTitle === \"test\" || normalizedTitle.startsWith(\"test\");\n}\n\nasync function deleteTestProjects() {\n console.log(\"🔍 Starting test project deletion process...\");\n \n try {\n // Step 1: Fetch all existing projects\n console.log(\"📥 Fetching all projects from Gigya DS...\");\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (searchResponse.errorCode !== 0) {\n throw new Error(`Failed to fetch projects: ${searchResponse.errorMessage}`);\n }\n\n const allProjects = searchResponse.results || [];\n console.log(`📊 Found ${allProjects.length} total projects`);\n\n // Step 2: Identify test projects\n const testProjects = allProjects.filter(project => \n isTestProject(project.data.title)\n );\n\n console.log(`🎯 Found ${testProjects.length} test projects to delete:`);\n \n if (testProjects.length === 0) {\n console.log(\"✅ No test projects found. Nothing to delete.\");\n return { deletedCount: 0, errorCount: 0 };\n }\n\n // List the projects that will be deleted\n testProjects.forEach((project, index) => {\n console.log(` ${index + 1}. \"${project.data.title}\" (oid: ${project.oid})`);\n });\n\n // Step 3: Confirm deletion\n console.log(`\\n⚠️ About to delete ${testProjects.length} test projects!`);\n console.log(\"This action cannot be undone.\");\n \n // In a real environment, you might want to add a confirmation prompt\n // For automation, we'll proceed directly\n \n // Step 4: Delete projects\n let deletedCount = 0;\n let errorCount = 0;\n\n console.log(\"\\n🗑️ Starting deletion process...\");\n\n for (const project of testProjects) {\n try {\n console.log(`🔄 Deleting \"${project.data.title}\"...`);\n\n // Mark project as deleted\n const updatedProjectData = {\n ...project.data,\n deleted: true,\n deletedAt: new Date().toISOString(),\n updatedAt: new Date().toISOString(),\n };\n\n const deleteResponse = await makeGigyaRequest(\"ds.store\", {\n type: \"oss_projects\",\n data: JSON.stringify(updatedProjectData),\n oid: project.oid,\n });\n\n if (deleteResponse.errorCode === 0) {\n console.log(`✅ Successfully deleted \"${project.data.title}\"`);\n deletedCount++;\n } else {\n console.error(`❌ Failed to delete \"${project.data.title}\": ${deleteResponse.errorMessage}`);\n errorCount++;\n }\n\n // Add delay to avoid rate limiting\n await new Promise((resolve) => setTimeout(resolve, 100));\n\n } catch (error) {\n console.error(`❌ Error deleting project \"${project.data.title}\":`, error);\n errorCount++;\n }\n }\n\n console.log(\"\\n📊 Deletion Summary:\");\n console.log(`✅ Successfully deleted: ${deletedCount} projects`);\n console.log(`❌ Errors: ${errorCount} projects`);\n console.log(`📁 Total processed: ${deletedCount + errorCount} projects`);\n\n return { deletedCount, errorCount };\n\n } catch (error) {\n console.error(\"❌ Error during deletion process:\", error);\n throw error;\n }\n}\n\nasync function verifyDeletion() {\n console.log(\"\\n🔍 Verifying deletion...\");\n \n try {\n // Check for remaining test projects\n const response = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (response.errorCode === 0) {\n const remainingProjects = response.results || [];\n const remainingTestProjects = remainingProjects.filter(project => \n isTestProject(project.data.title)\n );\n \n console.log(`✅ Verification complete:`);\n console.log(` 📝 Total active projects: ${remainingProjects.length}`);\n console.log(` 🧪 Remaining test projects: ${remainingTestProjects.length}`);\n \n if (remainingTestProjects.length > 0) {\n console.log(\"\\n⚠️ Test projects still found:\");\n remainingTestProjects.forEach((project, index) => {\n console.log(` ${index + 1}. \"${project.data.title}\" (oid: ${project.oid})`);\n });\n } else {\n console.log(\"🎉 All test projects have been successfully deleted!\");\n }\n\n // Also check deleted projects\n const deletedResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted = true\",\n });\n\n if (deletedResponse.errorCode === 0) {\n const deletedProjects = deletedResponse.results || [];\n const deletedTestProjects = deletedProjects.filter(project => \n isTestProject(project.data.title)\n );\n console.log(`🗑️ Deleted test projects: ${deletedTestProjects.length}`);\n }\n\n } else {\n console.error(\"❌ Verification failed:\", response.errorMessage);\n }\n } catch (error) {\n console.error(\"❌ Error during verification:\", error);\n }\n}\n\n// Run the script\ndeleteTestProjects()\n .then(async (result) => {\n await verifyDeletion();\n \n if (result.deletedCount > 0) {\n console.log(\"\\n🎉 Test project deletion completed successfully!\");\n console.log(\"\\nNext steps:\");\n console.log(\"1. Verify the application no longer shows the deleted test projects\");\n console.log(\"2. Check that legitimate projects remain unaffected\");\n } else if (result.errorCount > 0) {\n console.log(\"\\n⚠️ Some deletions failed. Check the errors above.\");\n } else {\n console.log(\"\\n✅ No test projects were found to delete.\");\n }\n })\n .catch((error) => {\n console.error(\"❌ Script execution failed:\", error);\n process.exit(1);\n });",[],[230],{"_104":238,"_95":239,"_153":240,"_155":-5,"_156":138,"_157":241,"_159":160,"_106":242,"_100":243,"_162":185,"_164":244,"_166":22,"_167":-5,"_168":245,"_98":246},"cfe1306a-4216-11f0-98c9-76b3cceeab13","ds-schema.ts","e4ab55a4-4214-11f0-997e-76b3cceeab13",26,["D",1749132619268],12,"// Script to create Gigya DS schema for the OSS Contribution project\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n process.exit(1);\n}\n\nasync function makeGigyaRequest(endpoint, params) {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY,\n userKey: GIGYA_APP_KEY,\n secret: GIGYA_APP_SECRET,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\nasync function createDSSchema() {\n console.log(\"Creating Gigya DS schema for OSS Contribution project...\");\n\n // Define the schema for projects\n const projectSchema = {\n dynamicSchema: true,\n fields: {\n \"id\": {\n type: \"long\",\n writeAccess: \"clientModify\",\n },\n \"title\": {\n type: \"text\",\n writeAccess: \"clientModify\",\n },\n \"description\": {\n type: \"text\",\n writeAccess: \"clientModify\",\n },\n \"repositoryUrl\": {\n type: \"text\",\n writeAccess: \"clientModify\",\n },\n \"votes\": {\n type: \"long\",\n writeAccess: \"serverOnly\",\n },\n \"comments\": {\n type: \"long\",\n writeAccess: \"clientModify\",\n },\n \"commitment\": {\n type: \"text\",\n writeAccess: \"clientModify\",\n },\n \"skills\": {\n type: \"text\",\n writeAccess: \"clientModify\",\n },\n \"contribution\": {\n type: \"text\",\n writeAccess: \"clientModify\",\n },\n \"author\": {\n type: \"text\",\n writeAccess: \"clientModify\",\n },\n \"enabled\": {\n type: \"boolean\",\n writeAccess: \"clientModify\",\n },\n \"createdAt\": {\n type: \"date\",\n writeAccess: \"clientModify\",\n },\n \"updatedAt\": {\n type: \"date\",\n writeAccess: \"clientModify\",\n },\n \"deleted\": {\n type: \"boolean\",\n writeAccess: \"clientModify\",\n },\n \"deletedAt\": {\n type: \"date\",\n writeAccess: \"serverOnly\",\n },\n },\n };\n\n try {\n // Create the schema\n console.log(\"Creating schema for type: oss_projects\");\n\n const response = await makeGigyaRequest(\"ds.setSchema\", {\n type: projectSchema.type,\n dynamicSchema: true,\n dataSchema: JSON.stringify(projectSchema),\n });\n\n if (response.errorCode === 0) {\n console.log(\"✅ Schema created successfully for oss_projects\");\n } else {\n console.error(\"❌ Failed to create schema:\", response.errorMessage);\n return false;\n }\n\n // Verify the schema was created\n console.log(\"Verifying schema...\");\n const verifyResponse = await makeGigyaRequest(\"ds.getSchema\", {\n type: projectSchema.type,\n });\n\n if (verifyResponse.errorCode === 0) {\n console.log(\"✅ Schema verification successful\");\n console.log(\n \"Schema fields:\",\n Object.keys(verifyResponse.schema).map((fieldName) => {\n const field = verifyResponse.schema[fieldName];\n return `${fieldName} (${field.type || \"unknown\"}, ${field.writeAccess || \"serverOnly\"})`;\n }).join(\", \"),\n );\n } else {\n console.error(\"❌ Schema verification failed:\", verifyResponse.errorMessage);\n }\n\n return true;\n } catch (error) {\n console.error(\"❌ Error creating DS schema:\", error.message);\n return false;\n }\n}\n\n// Run the script\ncreateDSSchema()\n .then((success) => {\n if (success) {\n console.log(\"\\n🎉 DS Schema creation completed successfully!\");\n console.log(\"\\nNext steps:\");\n console.log(\"1. Run the data loading script to populate projects\");\n console.log(\"2. Test the application with the new schema\");\n } else {\n console.log(\"\\n❌ DS Schema creation failed!\");\n process.exit(1);\n }\n })\n .catch((error) => {\n console.error(\"❌ Script execution failed:\", error);\n process.exit(1);\n });",[],[239],{"_104":248,"_95":249,"_153":250,"_155":-5,"_156":138,"_157":251,"_159":160,"_106":252,"_100":32,"_162":185,"_164":72,"_166":22,"_167":-5,"_168":253,"_98":254},"e15ed218-4214-11f0-b519-76b3cceeab13","main.tsx","e15ed2ae-4214-11f0-b519-76b3cceeab13",1,["D",1749131789629],[],[249],{"_104":256,"_95":257,"_153":258,"_155":-5,"_156":138,"_157":259,"_159":160,"_106":260,"_100":32,"_162":185,"_164":261,"_166":22,"_167":-5,"_168":262,"_98":263},"0ee72e32-42de-11f0-800c-76b3cceeab13","update-authors-advanced.ts","0ee72f04-42de-11f0-800c-76b3cceeab13",62,["D",1749218194863],"// Advanced script to update existing projects with author names\n// Handles multiple scenarios: missing authors, \"Unknown\" authors, and provides detailed reporting\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\n// Configuration options\nconst CONFIG = {\n dryRun: process.env.DRY_RUN === \"true\", // Set to true to preview changes without applying them\n batchSize: 10, // Number of projects to process in each batch\n delayBetweenRequests: 150, // Milliseconds to wait between API calls\n updateUnknownOnly: process.env.UPDATE_UNKNOWN_ONLY === \"true\", // Only update \"Unknown\" authors, not missing ones\n};\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n console.log(\"\\nOptional environment variables:\");\n console.log(\"- DRY_RUN=true (preview changes without applying)\");\n console.log(\"- UPDATE_UNKNOWN_ONLY=true (only update 'Unknown' authors)\");\n process.exit(1);\n}\n\ninterface ProjectData {\n id?: number;\n title: string;\n description: string;\n repositoryUrl: string;\n votes: number;\n comments: number;\n commitment?: string;\n skills?: string[];\n contribution?: string;\n author?: string;\n enabled: boolean;\n createdAt?: string;\n updatedAt?: string;\n deleted?: boolean;\n}\n\ninterface GigyaResponse {\n errorCode: number;\n errorMessage?: string;\n results?: Array<{\n oid: string;\n data: ProjectData;\n }>;\n object?: {\n data: ProjectData;\n };\n}\n\ninterface UpdateStats {\n total: number;\n needsUpdate: number;\n updated: number;\n skipped: number;\n errors: number;\n authorFound: number;\n authorNotFound: number;\n}\n\nasync function makeGigyaRequest(endpoint: string, params: Record): Promise {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY!,\n userKey: GIGYA_APP_KEY!,\n secret: GIGYA_APP_SECRET!,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\nfunction cabbabCase(str: string): string {\n return str.replaceAll(/[\\W_]+/g, \"-\").toLowerCase();\n}\n\nfunction shouldUpdateAuthor(currentAuthor: string | undefined): boolean {\n if (CONFIG.updateUnknownOnly) {\n return currentAuthor === \"Unknown\";\n }\n \n return !currentAuthor || \n currentAuthor === \"Unknown\" || \n currentAuthor.trim() === \"\" ||\n currentAuthor === \"undefined\" ||\n currentAuthor === \"null\";\n}\n\nfunction getAuthorDisplayName(authorName: string): string {\n // Clean up author names that might be user IDs\n if (authorName.startsWith(\"I\") && /^I\\d+$/.test(authorName)) {\n return `User ${authorName}`;\n }\n \n if (authorName.includes(\"[bot]\")) {\n return authorName.replace(\"[bot]\", \" (Bot)\");\n }\n \n return authorName;\n}\n\n// Import the data.json to get author information\nimport data from \"./data.json\" with { \"type\": \"json\" };\n\nasync function analyzeProjects(): Promise {\n console.log(\"🔍 Analyzing current project author status...\");\n \n try {\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (searchResponse.errorCode !== 0) {\n throw new Error(`Failed to fetch projects: ${searchResponse.errorMessage}`);\n }\n\n const projects = searchResponse.results || [];\n \n const analysis = {\n total: projects.length,\n withAuthor: 0,\n withoutAuthor: 0,\n unknownAuthor: 0,\n emptyAuthor: 0,\n };\n\n const authorCounts = new Map();\n\n for (const project of projects) {\n const author = project.data.author;\n \n if (!author || author.trim() === \"\") {\n analysis.withoutAuthor++;\n } else if (author === \"Unknown\") {\n analysis.unknownAuthor++;\n } else {\n analysis.withAuthor++;\n authorCounts.set(author, (authorCounts.get(author) || 0) + 1);\n }\n }\n\n console.log(\"\\n📊 Current Author Analysis:\");\n console.log(` 📁 Total projects: ${analysis.total}`);\n console.log(` ✅ With author: ${analysis.withAuthor}`);\n console.log(` ❓ Without author: ${analysis.withoutAuthor}`);\n console.log(` 🤷 Unknown author: ${analysis.unknownAuthor}`);\n console.log(` 📝 Need updating: ${analysis.withoutAuthor + analysis.unknownAuthor}`);\n\n if (authorCounts.size > 0) {\n console.log(\"\\n👥 Top Authors:\");\n const sortedAuthors = Array.from(authorCounts.entries())\n .sort((a, b) => b[1] - a[1])\n .slice(0, 5);\n \n for (const [author, count] of sortedAuthors) {\n console.log(` ${author}: ${count} project${count > 1 ? 's' : ''}`);\n }\n }\n\n } catch (error) {\n console.error(\"❌ Error during analysis:\", error);\n throw error;\n }\n}\n\nasync function updateProjectAuthors(): Promise {\n console.log(`\\n🔄 Starting author update process... ${CONFIG.dryRun ? \"(DRY RUN)\" : \"\"}`);\n \n const stats: UpdateStats = {\n total: 0,\n needsUpdate: 0,\n updated: 0,\n skipped: 0,\n errors: 0,\n authorFound: 0,\n authorNotFound: 0,\n };\n\n try {\n // Fetch all existing projects\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (searchResponse.errorCode !== 0) {\n throw new Error(`Failed to fetch projects: ${searchResponse.errorMessage}`);\n }\n\n const existingProjects = searchResponse.results || [];\n stats.total = existingProjects.length;\n \n console.log(`📥 Found ${existingProjects.length} existing projects`);\n\n // Create author lookup from data.json\n const authorLookup = new Map();\n const titleToIdMap = new Map();\n \n if (data.projects && Array.isArray(data.projects)) {\n for (const project of data.projects) {\n if (project.title) {\n const normalizedTitle = cabbabCase(project.title);\n \n if (project.author?.name) {\n authorLookup.set(normalizedTitle, project.author.name);\n }\n \n if (project.id) {\n titleToIdMap.set(normalizedTitle, project.id);\n }\n }\n }\n }\n \n console.log(`📝 Created lookup for ${authorLookup.size} projects with author data`);\n\n // Process projects in batches\n for (let i = 0; i < existingProjects.length; i += CONFIG.batchSize) {\n const batch = existingProjects.slice(i, i + CONFIG.batchSize);\n console.log(`\\n📦 Processing batch ${Math.floor(i / CONFIG.batchSize) + 1}/${Math.ceil(existingProjects.length / CONFIG.batchSize)}`);\n\n for (const projectResult of batch) {\n const { oid, data: projectData } = projectResult;\n \n try {\n // Check if author needs updating\n if (!shouldUpdateAuthor(projectData.author)) {\n console.log(`⏭️ \"${projectData.title}\" - author OK: \"${projectData.author}\"`);\n stats.skipped++;\n continue;\n }\n\n stats.needsUpdate++;\n\n // Look up author from data.json\n const rawAuthorName = authorLookup.get(oid);\n \n if (!rawAuthorName) {\n console.log(`⚠️ No author data found for \"${projectData.title}\" (oid: ${oid})`);\n stats.authorNotFound++;\n continue;\n }\n\n stats.authorFound++;\n const authorName = getAuthorDisplayName(rawAuthorName);\n\n console.log(`🔄 ${CONFIG.dryRun ? \"[DRY RUN] \" : \"\"}Updating \"${projectData.title}\"`);\n console.log(` 📝 Author: \"${projectData.author || 'undefined'}\" → \"${authorName}\"`);\n\n if (!CONFIG.dryRun) {\n // Update the project with the author name\n const updatedProjectData = {\n ...projectData,\n author: authorName,\n updatedAt: new Date().toISOString(),\n };\n\n const updateResponse = await makeGigyaRequest(\"ds.store\", {\n type: \"oss_projects\",\n data: JSON.stringify(updatedProjectData),\n oid: oid,\n });\n\n if (updateResponse.errorCode === 0) {\n console.log(` ✅ Successfully updated`);\n stats.updated++;\n } else {\n console.error(` ❌ Failed to update: ${updateResponse.errorMessage}`);\n stats.errors++;\n }\n\n // Rate limiting delay\n await new Promise((resolve) => setTimeout(resolve, CONFIG.delayBetweenRequests));\n } else {\n stats.updated++; // Count as updated for dry run stats\n }\n\n } catch (error) {\n console.error(`❌ Error processing \"${projectData.title}\":`, error);\n stats.errors++;\n }\n }\n }\n\n return stats;\n\n } catch (error) {\n console.error(\"❌ Error during author update process:\", error);\n throw error;\n }\n}\n\nasync function generateReport(stats: UpdateStats): Promise {\n console.log(\"\\n📊 Final Update Report:\");\n console.log(\"=\" .repeat(50));\n console.log(`📁 Total projects processed: ${stats.total}`);\n console.log(`🔍 Projects needing update: ${stats.needsUpdate}`);\n console.log(`✅ Successfully updated: ${stats.updated}`);\n console.log(`⏭️ Skipped (already have author): ${stats.skipped}`);\n console.log(`❌ Errors during update: ${stats.errors}`);\n console.log(`📝 Author data found: ${stats.authorFound}`);\n console.log(`❓ Author data not found: ${stats.authorNotFound}`);\n \n const successRate = stats.needsUpdate > 0 ? (stats.updated / stats.needsUpdate * 100).toFixed(1) : \"0\";\n console.log(`📈 Success rate: ${successRate}%`);\n\n if (CONFIG.dryRun) {\n console.log(\"\\n⚠️ This was a DRY RUN - no changes were actually made\");\n console.log(\" Set DRY_RUN=false to apply the changes\");\n }\n}\n\nasync function verifyUpdates(): Promise {\n if (CONFIG.dryRun) return;\n \n console.log(\"\\n🔍 Verifying updates...\");\n \n try {\n const response = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (response.errorCode === 0) {\n const projects = response.results || [];\n const withAuthors = projects.filter(p => p.data.author && p.data.author !== \"Unknown\" && p.data.author.trim() !== \"\");\n const stillNeedUpdate = projects.filter(p => shouldUpdateAuthor(p.data.author));\n \n console.log(`✅ Verification complete:`);\n console.log(` 📝 Projects with authors: ${withAuthors.length}/${projects.length}`);\n console.log(` ❓ Projects still needing update: ${stillNeedUpdate.length}`);\n \n if (stillNeedUpdate.length > 0) {\n console.log(\"\\n📋 Projects still missing authors:\");\n stillNeedUpdate.slice(0, 5).forEach((project, index) => {\n console.log(` ${index + 1}. \"${project.data.title}\" (author: \"${project.data.author || 'undefined'}\")`);\n });\n if (stillNeedUpdate.length > 5) {\n console.log(` ... and ${stillNeedUpdate.length - 5} more`);\n }\n }\n } else {\n console.error(\"❌ Verification failed:\", response.errorMessage);\n }\n } catch (error) {\n console.error(\"❌ Error during verification:\", error);\n }\n}\n\n// Main execution\nasync function main() {\n console.log(\"🚀 Advanced Project Author Update Script\");\n console.log(\"=\" .repeat(50));\n \n if (CONFIG.dryRun) {\n console.log(\"⚠️ DRY RUN MODE - No changes will be made\");\n }\n \n if (CONFIG.updateUnknownOnly) {\n console.log(\"🎯 UPDATE MODE - Only updating 'Unknown' authors\");\n } else {\n console.log(\"🎯 UPDATE MODE - Updating missing and 'Unknown' authors\");\n }\n \n try {\n await analyzeProjects();\n const stats = await updateProjectAuthors();\n await generateReport(stats);\n await verifyUpdates();\n \n console.log(\"\\n🎉 Script completed successfully!\");\n \n } catch (error) {\n console.error(\"❌ Script execution failed:\", error);\n process.exit(1);\n }\n}\n\n// Run the script\nmain();",[],[257],{"_104":265,"_95":266,"_153":267,"_155":-5,"_156":138,"_157":268,"_159":160,"_106":269,"_100":251,"_162":185,"_164":270,"_166":22,"_167":-5,"_168":271,"_98":272},"6581e7dc-42de-11f0-9f0a-76b3cceeab13","update-project-authors.ts","efd5b9aa-42dd-11f0-8f1d-76b3cceeab13",64,["D",1749218340157],"// Script to update existing projects with author names where missing or \"Unknown\"\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n process.exit(1);\n}\n\ninterface ProjectData {\n id?: number;\n title: string;\n description: string;\n repositoryUrl: string;\n votes: number;\n comments: number;\n commitment?: string;\n skills?: string[];\n contribution?: string;\n author?: string;\n enabled: boolean;\n createdAt?: string;\n updatedAt?: string;\n deleted?: boolean;\n}\n\ninterface GigyaResponse {\n errorCode: number;\n errorMessage?: string;\n results?: Array<{\n oid: string;\n data: ProjectData;\n }>;\n object?: {\n data: ProjectData;\n };\n}\n\nasync function makeGigyaRequest(endpoint: string, params: Record): Promise {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY!,\n userKey: GIGYA_APP_KEY!,\n secret: GIGYA_APP_SECRET!,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\nfunction cabbabCase(str: string): string {\n return str.replaceAll(/[\\W_]+/g, \"-\").toLowerCase();\n}\n\n// Import the data.json to get author information\nimport data from \"./data.json\" with { \"type\": \"json\" };\n\nasync function updateProjectAuthors() {\n console.log(\"🔍 Starting author update process...\");\n \n try {\n // Step 1: Fetch all existing projects from Gigya DS\n console.log(\"📥 Fetching all projects from Gigya DS...\");\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (searchResponse.errorCode !== 0) {\n throw new Error(`Failed to fetch projects: ${searchResponse.errorMessage}`);\n }\n\n const existingProjects = searchResponse.results || [];\n console.log(`📊 Found ${existingProjects.length} existing projects`);\n\n // Step 2: Create a lookup map from data.json for author information\n console.log(\"📋 Creating author lookup from data.json...\");\n const authorLookup = new Map();\n \n if (data.projects && Array.isArray(data.projects)) {\n for (const project of data.projects) {\n if (project.title && project.author?.name) {\n const normalizedTitle = cabbabCase(project.title);\n authorLookup.set(normalizedTitle, project.author.name);\n }\n }\n }\n \n console.log(`📝 Created lookup for ${authorLookup.size} projects with author data`);\n\n // Step 3: Identify and update projects with missing or \"Unknown\" authors\n let updatedCount = 0;\n let skippedCount = 0;\n let errorCount = 0;\n\n for (const projectResult of existingProjects) {\n const { oid, data: projectData } = projectResult;\n \n try {\n // Check if author needs updating\n const needsUpdate = !projectData.author || \n projectData.author === \"Unknown\" || \n projectData.author.trim() === \"\";\n\n if (!needsUpdate) {\n console.log(`⏭️ Skipping \"${projectData.title}\" - author already set: \"${projectData.author}\"`);\n skippedCount++;\n continue;\n }\n\n // Look up author from data.json\n const authorName = authorLookup.get(oid);\n \n if (!authorName) {\n console.log(`⚠️ No author data found for \"${projectData.title}\" (oid: ${oid})`);\n skippedCount++;\n continue;\n }\n\n // Update the project with the author name\n const updatedProjectData = {\n // ...projectData,\n author: authorName,\n // updatedAt: new Date().toISOString(),\n };\n\n console.log(`🔄 Updating \"${projectData.title}\" with author: \"${authorName}\"`);\n\n const updateResponse = await makeGigyaRequest(\"ds.store\", {\n type: \"oss_projects\",\n data: JSON.stringify(updatedProjectData),\n oid: oid,\n });\n\n if (updateResponse.errorCode === 0) {\n console.log(`✅ Successfully updated \"${projectData.title}\"`);\n updatedCount++;\n } else {\n console.error(`❌ Failed to update \"${projectData.title}\": ${updateResponse.errorMessage}`);\n errorCount++;\n }\n\n // Add a small delay to avoid rate limiting\n await new Promise((resolve) => setTimeout(resolve, 100));\n\n } catch (error) {\n console.error(`❌ Error processing project \"${projectData.title}\":`, error);\n errorCount++;\n }\n }\n\n // Step 4: Summary\n console.log(\"\\n📊 Update Summary:\");\n console.log(`✅ Successfully updated: ${updatedCount} projects`);\n console.log(`⏭️ Skipped: ${skippedCount} projects`);\n console.log(`❌ Errors: ${errorCount} projects`);\n console.log(`📁 Total processed: ${updatedCount + skippedCount + errorCount} projects`);\n\n return { updatedCount, skippedCount, errorCount };\n\n } catch (error) {\n console.error(\"❌ Error during author update process:\", error);\n throw error;\n }\n}\n\nasync function verifyUpdates() {\n console.log(\"\\n🔍 Verifying author updates...\");\n \n try {\n const response = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true\",\n });\n\n if (response.errorCode === 0) {\n const projects = response.results || [];\n const withAuthors = projects.filter(p => p.data.author && p.data.author !== \"Unknown\");\n const withoutAuthors = projects.filter(p => !p.data.author || p.data.author === \"Unknown\");\n \n console.log(`✅ Verification complete:`);\n console.log(` 📝 Projects with authors: ${withAuthors.length}`);\n console.log(` ❓ Projects without authors: ${withoutAuthors.length}`);\n \n if (withoutAuthors.length > 0) {\n console.log(\"\\n📋 Projects still missing authors:\");\n withoutAuthors.slice(0, 5).forEach((project, index) => {\n console.log(` ${index + 1}. \"${project.data.title}\" (oid: ${project.oid})`);\n });\n if (withoutAuthors.length > 5) {\n console.log(` ... and ${withoutAuthors.length - 5} more`);\n }\n }\n } else {\n console.error(\"❌ Verification failed:\", response.errorMessage);\n }\n } catch (error) {\n console.error(\"❌ Error during verification:\", error);\n }\n}\n\n// Run the script\nupdateProjectAuthors()\n .then(async (result) => {\n if (result.updatedCount > 0) {\n await verifyUpdates();\n console.log(\"\\n🎉 Author update process completed successfully!\");\n console.log(\"\\nNext steps:\");\n console.log(\"1. Test the application to ensure author names are displaying correctly\");\n console.log(\"2. Check if any projects still need manual author assignment\");\n } else {\n console.log(\"\\n⚠️ No projects were updated!\");\n await verifyUpdates();\n }\n })\n .catch((error) => {\n console.error(\"❌ Script execution failed:\", error);\n process.exit(1);\n });",[],[266],{"_104":274,"_95":275,"_153":276,"_155":-5,"_156":138,"_157":277,"_159":160,"_106":278,"_100":279,"_162":185,"_164":280,"_166":22,"_167":-5,"_168":281,"_98":282},"9b6020ac-4217-11f0-b14a-76b3cceeab13","verify","7dbd0010-4217-11f0-aeec-76b3cceeab13",35,["D",1749132960681],3,"// Script to verify Gigya DS setup and data integrity\n\nconst GIGYA_DOMAIN = process.env.GIGYA_DOMAIN || \"accounts.eu1.gigya.com\";\nconst GIGYA_API_KEY = process.env.GIGYA_API_KEY;\nconst GIGYA_APP_KEY = process.env.GIGYA_APP_KEY;\nconst GIGYA_APP_SECRET = process.env.GIGYA_APP_SECRET;\n\nif (!GIGYA_API_KEY || !GIGYA_APP_KEY || !GIGYA_APP_SECRET) {\n console.error(\"Missing Gigya environment variables!\");\n console.log(\"Required variables: GIGYA_API_KEY, GIGYA_APP_KEY, GIGYA_APP_SECRET\");\n process.exit(1);\n}\n\nasync function makeGigyaRequest(endpoint, params) {\n const url = `https://${GIGYA_DOMAIN}/${endpoint}?httpStatusCodes=true`;\n\n const body = new URLSearchParams({\n apiKey: GIGYA_API_KEY,\n userKey: GIGYA_APP_KEY,\n secret: GIGYA_APP_SECRET,\n ...params,\n });\n\n const response = await fetch(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/x-www-form-urlencoded\" },\n body,\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`${response.statusText}: ${text}`);\n }\n\n const text = await response.text();\n return JSON.parse(text);\n}\n\nasync function verifyDSSetup() {\n console.log(\"🔍 Verifying Gigya DS setup for OSS Contribution project...\\n\");\n\n try {\n // 1. Check if schema exists\n console.log(\"1. Checking DS schema...\");\n const schemaResponse = await makeGigyaRequest(\"ds.getSchema\", {\n type: \"oss_projects\",\n });\n\n if (schemaResponse.errorCode === 0) {\n console.log(\"✅ Schema exists for oss_projects\");\n console.log(` Fields: ${schemaResponse.schema.fields.length}`);\n\n const requiredFields = [\"id\", \"title\", \"description\", \"repositoryUrl\", \"votes\", \"comments\"];\n const existingFields = Object.entries(schemaResponse.schema.fields).map((f) => f.name);\n const missingFields = requiredFields.filter((field) => !existingFields.includes(field));\n\n if (missingFields.length === 0) {\n console.log(\"✅ All required fields present\");\n } else {\n console.log(`⚠️ Missing required fields: ${missingFields.join(\", \")}`);\n }\n } else {\n console.log(\"❌ Schema not found for oss_projects\");\n console.log(\" Run create-ds-schema.js first\");\n return false;\n }\n\n // 2. Check data count\n console.log(\"\\n2. Checking data count...\");\n const countResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT COUNT(*) FROM oss_projects WHERE deleted != true\",\n });\n\n if (countResponse.errorCode === 0) {\n const count = countResponse.totalCount || 0;\n console.log(`✅ Found ${count} active projects in DS`);\n\n if (count === 0) {\n console.log(\"⚠️ No projects found. Run load-projects-to-ds.js to load data\");\n }\n } else {\n console.log(\"❌ Failed to count projects:\", countResponse.errorMessage);\n }\n\n // 3. Sample data verification\n console.log(\"\\n3. Verifying sample data...\");\n const sampleResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE deleted != true LIMIT 5\",\n });\n\n if (sampleResponse.errorCode === 0 && sampleResponse.results) {\n console.log(`✅ Retrieved ${sampleResponse.results.length} sample projects`);\n\n sampleResponse.results.forEach((result, index) => {\n const project = result.data;\n console.log(` ${index + 1}. ${project.title} (ID: ${project.id})`);\n\n // Check data integrity\n const issues = [];\n if (!project.title) issues.push(\"missing title\");\n if (!project.description) issues.push(\"missing description\");\n if (!Array.isArray(project.skills)) issues.push(\"skills not array\");\n if (typeof project.votes !== \"number\") issues.push(\"votes not number\");\n\n if (issues.length > 0) {\n console.log(` ⚠️ Issues: ${issues.join(\", \")}`);\n }\n });\n } else {\n console.log(\"❌ Failed to retrieve sample data\");\n }\n\n // 4. Test search functionality\n console.log(\"\\n4. Testing search functionality...\");\n const searchResponse = await makeGigyaRequest(\"ds.search\", {\n query: \"SELECT * FROM oss_projects WHERE title LIKE '%bolt%'\",\n });\n\n if (searchResponse.errorCode === 0) {\n console.log(`✅ Search test successful (found ${searchResponse.results?.length || 0} results)`);\n } else {\n console.log(\"❌ Search test failed:\", searchResponse.errorMessage);\n }\n\n // 5. Test connection to accounts API\n console.log(\"\\n5. Testing accounts API connection...\");\n try {\n const testResponse = await makeGigyaRequest(\"accounts.getAccountInfo\", {\n uid: \"test_uid_12345\",\n });\n\n // We expect this to fail with \"user not found\" which means the API is working\n if (testResponse.errorCode === 403005) {\n console.log(\"✅ Accounts API connection working (user not found as expected)\");\n } else {\n console.log(`⚠️ Unexpected accounts API response: ${testResponse.errorMessage}`);\n }\n } catch (error) {\n console.log(\"❌ Accounts API connection failed:\", error.message);\n }\n\n console.log(\"\\n🎉 DS setup verification completed!\");\n return true;\n } catch (error) {\n console.error(\"❌ Error during verification:\", error.message);\n return false;\n }\n}\n\n// Run the verification\nverifyDSSetup()\n .then((success) => {\n if (success) {\n console.log(\"\\n✅ All checks passed! Your Gigya DS setup is ready.\");\n } else {\n console.log(\"\\n❌ Some checks failed. Please review the output above.\");\n process.exit(1);\n }\n })\n .catch((error) => {\n console.error(\"❌ Verification script failed:\", error);\n process.exit(1);\n });",[],[275],"files",[150,171,179,189,199,209,219,228,237,247,255,264,273],"counts",{"_287":32,"_288":251,"_289":32,"_290":291},"pulls","branches","forks","envVars",5,"contents",[],{"_104":180,"_95":99,"_153":181,"_155":-5,"_156":138,"_157":182,"_159":160,"_106":295,"_100":184,"_162":185,"_164":186,"_166":22,"_167":-5,"_98":296},["D",1749158826598],[99],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.version.$version.code.$",{"_93":94,"_95":96,"_97":43,"_100":101,"_98":99,"_102":305,"_148":310,"_283":350,"_163":351,"_292":353,"_354":-5,"_355":22,"_356":-5,"_357":-5,"_358":-5,"_359":360},{"_104":105,"_95":96,"_106":306,"_108":-5,"_109":22,"_110":111,"_112":-5,"_113":-5,"_14":114,"_115":-5,"_116":22,"_117":-5,"_118":32,"_16":119,"_120":121,"_122":121,"_123":124,"_125":124,"_126":124,"_127":121,"_128":121,"_23":307,"_132":308,"_135":309,"_147":22},["D",1749131789618],{"_93":94,"_130":131},{"_93":94,"_134":131},{"_100":137,"_95":43,"_104":138,"_139":105,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":-5,"_145":96,"_146":94},[311,314,317,320,323,326,329,332,335,338,341,344,347],{"_104":151,"_95":152,"_153":154,"_155":-5,"_156":138,"_157":158,"_159":160,"_106":161,"_100":32,"_162":163,"_164":165,"_166":22,"_167":-5,"_168":312,"_98":313},[],[152],{"_104":172,"_95":173,"_153":174,"_155":-5,"_156":138,"_157":101,"_159":160,"_106":175,"_100":32,"_162":163,"_164":176,"_166":22,"_167":-5,"_168":315,"_98":316},[],[173],{"_104":180,"_95":99,"_153":181,"_155":-5,"_156":138,"_157":182,"_159":160,"_106":183,"_100":184,"_162":185,"_164":186,"_166":22,"_167":-5,"_168":318,"_98":319},[],[99],{"_104":190,"_95":191,"_153":192,"_155":-5,"_156":138,"_157":193,"_159":160,"_106":194,"_100":195,"_162":185,"_164":196,"_166":22,"_167":-5,"_168":321,"_98":322},[],[191],{"_104":200,"_95":201,"_153":202,"_155":-5,"_156":138,"_157":203,"_159":160,"_106":204,"_100":205,"_162":185,"_164":206,"_166":22,"_167":-5,"_168":324,"_98":325},[],[201],{"_104":210,"_95":211,"_153":212,"_155":-5,"_156":138,"_157":213,"_159":160,"_106":214,"_100":215,"_162":163,"_164":216,"_166":22,"_167":-5,"_168":327,"_98":328},[],[211],{"_104":220,"_95":221,"_153":222,"_155":-5,"_156":138,"_157":223,"_159":22,"_106":224,"_100":32,"_162":185,"_164":225,"_166":22,"_167":-5,"_168":330,"_98":331},[],[221],{"_104":229,"_95":230,"_153":231,"_155":-5,"_156":138,"_157":232,"_159":160,"_106":233,"_100":32,"_162":185,"_164":234,"_166":22,"_167":-5,"_168":333,"_98":334},[],[230],{"_104":238,"_95":239,"_153":240,"_155":-5,"_156":138,"_157":241,"_159":160,"_106":242,"_100":243,"_162":185,"_164":244,"_166":22,"_167":-5,"_168":336,"_98":337},[],[239],{"_104":248,"_95":249,"_153":250,"_155":-5,"_156":138,"_157":251,"_159":160,"_106":252,"_100":32,"_162":185,"_164":72,"_166":22,"_167":-5,"_168":339,"_98":340},[],[249],{"_104":256,"_95":257,"_153":258,"_155":-5,"_156":138,"_157":259,"_159":160,"_106":260,"_100":32,"_162":185,"_164":261,"_166":22,"_167":-5,"_168":342,"_98":343},[],[257],{"_104":265,"_95":266,"_153":267,"_155":-5,"_156":138,"_157":268,"_159":160,"_106":269,"_100":251,"_162":185,"_164":270,"_166":22,"_167":-5,"_168":345,"_98":346},[],[266],{"_104":274,"_95":275,"_153":276,"_155":-5,"_156":138,"_157":277,"_159":160,"_106":278,"_100":279,"_162":185,"_164":280,"_166":22,"_167":-5,"_168":348,"_98":349},[],[275],[311,314,317,320,323,326,329,332,335,338,341,344,347],{"_104":180,"_95":99,"_153":181,"_155":-5,"_156":138,"_157":182,"_159":160,"_106":295,"_100":184,"_162":185,"_164":186,"_166":22,"_167":-5,"_98":352},[99],[],"upstream","showCompareCallout","pull","ahead","behind","templates",[],"actionData","errors"]