# Verification Methods Success verification steps for AI Coaching Best Practice skill execution. ## Overview This document provides step-by-step verification commands to confirm each stage of the AI Coaching system deployment was successful. --- ## Step 0: Verify NAT Gateway and SNAT Configuration ### Verification Command ```bash # Check NAT Gateway exists aliyun vpc describe-nat-gateways --profile adbpg \ --biz-region-id cn-hangzhou --vpc-id vpc-xxxxx \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - `TotalCount` >= 1 - NAT Gateway `Status` is `Available` - `NatType` is `Enhanced` - `SnatTableIds` contains at least one entry - Verify SNAT entry covers the VSwitch CIDR with a valid EIP ### Failure Indicators - `TotalCount` is 0 — no NAT Gateway exists - NAT Gateway `Status` is `Creating` or `Deleting` - No SNAT entries configured — Supabase public access will fail - EIP not bound to NAT Gateway --- ## Step 1: Verify Supabase Project Creation ### Verification Command ```bash aliyun gpdb get-supabase-project --profile adbpg \ --project-id sbp-xxxxx \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - `ProjectId` matches the created project (sbp-xxx format) - `ProjectName` equals the specified name - `Status` is `Running` or `Active` - `PublicConnectUrl` is populated - `ApiKeys` section contains `anon_key` and `service_role_key` ### Failure Indicators - Error: `InvalidProjectId.NotFound` - `Status` is `Creating` or `Failed` - Missing connection URL or API keys --- ## Step 2: Verify ADBPG Instance Creation ### Verification Command ```bash aliyun gpdb describe-db-instances --profile adbpg \ --biz-region-id cn-hangzhou \ --output cols="DBInstanceId,DBInstanceDescription,DBInstanceStatus,EngineVersion,VectorConfigurationStatus" rows="Items.DBInstance[]" \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - Instance appears in the list with correct `DBInstanceId` (gp-xxx format) - `DBInstanceStatus` is `Running` - `EngineVersion` is `7.0` - `VectorConfigurationStatus` is `enabled` - `DBInstanceCategory` is `HighAvailability` ### Failure Indicators - Instance not found in list - `DBInstanceStatus` is `Creating`, `Modifying`, or `Failed` - `VectorConfigurationStatus` is `disabled` or `null` --- ## Step 3: Verify Database Account ### Verification Command ```bash aliyun gpdb describe-accounts --profile adbpg \ --db-instance-id gp-xxxxx \ --output cols="AccountName,AccountType,AccountStatus" rows="Accounts.DBInstanceAccount[]" \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - Super account exists with specified name - `AccountType` is `Super` - `AccountStatus` is `Active` ### Failure Indicators - No accounts listed - Only `Normal` accounts exist - Account status is `Locked` or `Creating` --- ## Step 4: Verify Vector Database Initialization ### Verification Command ```bash aliyun gpdb describe-namespaces --profile adbpg \ --biz-region-id cn-hangzhou \ --db-instance-id gp-xxxxx \ --manager-account admin_user \ --manager-account-password '' \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - Vector database is initialized - No error about uninitialized vector DB ### Failure Indicators - Error: `VectorDatabase.NotInitialized` - Error: `ManagerAccount.PasswordMismatch` --- ## Step 5: Verify Namespace Creation ### Verification Command ```bash aliyun gpdb describe-namespaces --profile adbpg \ --biz-region-id cn-hangzhou \ --db-instance-id gp-xxxxx \ --manager-account admin_user \ --manager-account-password '' \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - Command succeeds without error - Can create collection in the namespace ### Failure Indicators - Error: `Namespace.NotExist` - Error: `Namespace.AlreadyExists` - Error: `ManagerAccount.PasswordMismatch` --- ## Step 6: Verify Document Collection Creation ### Verification Command ```bash # Query collections (if available via API) # Or verify by listing documents in collection ``` ### Expected Success Indicators - Collection exists with specified name - Embedding model matches specification - Dimension matches specification ### Failure Indicators - Error: `Collection.NotExist` - Embedding model mismatch --- ## Step 7: Verify Document Upload ### Verification Command ```bash aliyun gpdb upload-document-async --profile adbpg \ --biz-region-id cn-hangzhou \ --db-instance-id gp-xxxxx \ --namespace ns_coaching \ --namespace-password '' \ --collection coaching_knowledge \ --file-name "test_verify.pdf" \ --file-url "https://example.com/test.pdf" \ --document-loader-name ADBPGLoader \ --chunk-size 500 \ --chunk-overlap 50 \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - Returns `TaskId` for async operation - Document status becomes `Processed` after completion ### Check Upload Status ```bash # Query document upload task status (if API available) ``` ### Failure Indicators - Error: `Collection.NotExist` - Error: `InvalidFileUrl` - Error: `UnsupportedFileType` - Task status remains `Processing` indefinitely --- ## Step 8: Verify Knowledge Base Chat (AI Coaching) ### Verification Command ```bash aliyun gpdb chat-with-knowledge-base --profile adbpg \ --biz-region-id cn-hangzhou \ --db-instance-id gp-xxxxx \ --model-params '{ "Model": "qwen-max", "Messages": [ {"Role": "user", "Content": "Hello, I need coaching on my sales process."} ] }' \ --knowledge-params '{ "SourceCollection": [{ "Collection": "coaching_knowledge", "Namespace": "ns_coaching", "NamespacePassword": "", "QueryParams": {"TopK": 5} }] }' \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Expected Success Indicators - Response contains meaningful coaching guidance - Response includes retrieved knowledge context - No authentication or permission errors ### Failure Indicators - Error: `AccountOrPassword.VerificationError` - Error: `Collection.NotExist` - Error: `Namespace.NotExist` - Empty or nonsensical response - Model inference timeout --- ## Step 9: Verify Supabase Database Schema ### Verification Command Connect to Supabase database using psql: ```bash psql "postgres://:@:/postgres" -c " SELECT table_name FROM information_schema.tables WHERE table_schema = 'public' AND table_type = 'BASE TABLE'; " ``` ### Expected Success Indicators Tables exist: - `coaching_domains` - `coaching_personas` - `learners` - `coaching_sessions` ### Verify Preset Coaching Domains ```sql SELECT id, name, category, difficulty, is_active FROM coaching_domains ORDER BY category, difficulty; ``` Expected domains: - `sales_workflow_coach` (workflow_coaching, intermediate) - `architecture_advisor` (decision_support, advanced) - `communication_coach` (skill_development, intermediate) - `onboarding_mentor` (onboarding, beginner) ### Verify Coaching Personas ```sql SELECT domain_id, LEFT(system_prompt, 50) as prompt_preview FROM coaching_personas; ``` ### Failure Indicators - Tables don't exist - Missing expected coaching domains - Empty coaching_personas table --- ## Step 10: End-to-End Coaching Test ### Full Flow Test 1. **Query a coaching domain from Supabase:** ```sql SELECT d.id, d.name, p.system_prompt FROM coaching_domains d LEFT JOIN coaching_personas p ON d.id = p.domain_id WHERE d.id = 'sales_workflow_coach'; ``` 2. **Call ChatWithKnowledgeBase with coaching prompt:** ```bash aliyun gpdb chat-with-knowledge-base --profile adbpg \ --biz-region-id cn-hangzhou \ --db-instance-id gp-xxxxx \ --model-params '{ "Model": "qwen-max", "Messages": [ {"Role": "system", "Content": ""}, {"Role": "user", "Content": "I have a prospect who keeps delaying the decision. How should I handle this?"} ] }' \ --knowledge-params '{ "SourceCollection": [{ "Collection": "coaching_knowledge", "Namespace": "ns_coaching", "NamespacePassword": "", "QueryParams": {"TopK": 5} }] }' \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` 3. **Verify response quality:** - Response matches the coaching persona style - Response incorporates knowledge from uploaded documents - Response provides actionable coaching guidance - Response uses Socratic questioning or appropriate coaching technique ### Failure Indicators - Coaching domain not found in database - Chat API returns errors - Response doesn't match expected coaching style - No knowledge retrieval in response --- ## Quick Health Check Script Run this script to verify all components: ```bash #!/bin/bash # Configuration PROFILE="adbpg" REGION="cn-hangzhou" DB_INSTANCE="gp-xxxxx" MANAGER_ACCOUNT="admin_user" MANAGER_PASSWORD="" # Replace with actual password NAMESPACE="ns_coaching" NAMESPACE_PASSWORD="" # Replace with actual password COLLECTION="coaching_knowledge" echo "=== AI Coaching System Health Check ===" echo "" # 1. Check CLI version echo "1. Checking Aliyun CLI version..." aliyun version # 2. Check credentials echo "" echo "2. Checking credentials..." aliyun configure list # 3. Check ADBPG instance echo "" echo "3. Checking ADBPG instance status..." aliyun gpdb describe-db-instances --profile $PROFILE \ --biz-region-id $REGION \ --output cols="DBInstanceId,DBInstanceStatus,VectorConfigurationStatus" rows="Items.DBInstance[]" \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # 4. Check accounts echo "" echo "4. Checking database accounts..." aliyun gpdb describe-accounts --profile $PROFILE \ --db-instance-id $DB_INSTANCE \ --output cols="AccountName,AccountType,AccountStatus" rows="Accounts.DBInstanceAccount[]" \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # 5. Test ChatWithKnowledgeBase echo "" echo "5. Testing ChatWithKnowledgeBase..." aliyun gpdb chat-with-knowledge-base --profile $PROFILE \ --biz-region-id $REGION \ --db-instance-id $DB_INSTANCE \ --model-params '{"Model": "qwen-max", "Messages": [{"Role": "user", "Content": "Hello"}]}' \ --knowledge-params "{\"SourceCollection\": [{\"Collection\": \"$COLLECTION\", \"Namespace\": \"$NAMESPACE\", \"NamespacePassword\": \"$NAMESPACE_PASSWORD\", \"QueryParams\": {\"TopK\": 5}}]}" \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice echo "" echo "=== Health Check Complete ===" ``` --- ## Troubleshooting Common Issues ### Issue: `InvalidAccessKeyId.NotFound` **Solution:** Re-verify credentials with `aliyun configure list` ### Issue: `Forbidden.RAM` **Solution:** Check RAM policies - ensure user has required GPDB permissions ### Issue: `AccountOrPassword.VerificationError` **Solution:** Verify manager account password is correct ### Issue: `Namespace.NotExist` **Solution:** Create namespace first with `CreateNamespace` ### Issue: `VectorDatabase.NotInitialized` **Solution:** Run `InitVectorDatabase` first ### Issue: Response quality is poor **Solution:** 1. Verify documents were uploaded successfully 2. Increase `TopK` value (try 10) 3. Check document content quality 4. Verify embedding model compatibility