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a8259ca935
### Changes 🏗️ Adds `autogpt_platform/analytics/` — 14 SQL view definitions that expose production data safely through a locked-down `analytics` schema. **Security model:** - Views use `security_invoker = false` (PostgreSQL 15+), so they execute as their owner (`postgres`), not the caller - `analytics_readonly` role only has access to `analytics.*` — cannot touch `platform` or `auth` tables directly **Files:** - `backend/generate_views.py` — does everything; auto-reads credentials from `backend/.env` - `analytics/queries/*.sql` — 14 documented view definitions (auth, user activity, executions, onboarding funnel, cohort retention) --- ### Running locally (dev) ```bash cd autogpt_platform/backend # First time only — creates analytics schema, role, grants poetry run analytics-setup # Create / refresh views (auto-reads backend/.env) poetry run analytics-views ``` ### Running in production (Supabase) ```bash cd autogpt_platform/backend # Step 1 — first time only (run in Supabase SQL Editor as postgres superuser) poetry run analytics-setup --dry-run # Paste the output into Supabase SQL Editor and run # Step 2 — apply views (use direct connection host, not pooler) poetry run analytics-views --db-url "postgresql://postgres:PASSWORD@db.<ref>.supabase.co:5432/postgres" # Step 3 — set password for analytics_readonly so external tools can connect # Run in Supabase SQL Editor: # ALTER ROLE analytics_readonly WITH PASSWORD 'your-password'; ``` --- ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: - [x] Setup + views applied cleanly on local Postgres 15 - [x] `analytics_readonly` can `SELECT` from all 14 `analytics.*` views - [x] `analytics_readonly` gets `permission denied` on `platform.*` and `auth.*` directly --------- Co-authored-by: Otto (AGPT) <otto@agpt.co>
101 lines
3.7 KiB
SQL
101 lines
3.7 KiB
SQL
-- =============================================================
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-- View: analytics.user_onboarding_funnel
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-- Looker source alias: ds74 | Charts: 1
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-- =============================================================
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-- DESCRIPTION
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-- Pre-aggregated onboarding funnel showing how many users
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-- completed each step and the drop-off percentage from the
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-- previous step. One row per onboarding step (all 22 steps
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-- always present, even with 0 completions — prevents sparse
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-- gaps from making LAG compare the wrong predecessors).
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--
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-- SOURCE TABLES
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-- platform.UserOnboarding — Onboarding records with completedSteps array
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--
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-- OUTPUT COLUMNS
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-- step TEXT Onboarding step enum name (e.g. 'WELCOME', 'CONGRATS')
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-- step_order INT Numeric position in the funnel (1=first, 22=last)
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-- users_completed BIGINT Distinct users who completed this step
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-- pct_from_prev NUMERIC % of users from the previous step who reached this one
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--
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-- STEP ORDER
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-- 1 WELCOME 9 MARKETPLACE_VISIT 17 SCHEDULE_AGENT
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-- 2 USAGE_REASON 10 MARKETPLACE_ADD_AGENT 18 RUN_AGENTS
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-- 3 INTEGRATIONS 11 MARKETPLACE_RUN_AGENT 19 RUN_3_DAYS
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-- 4 AGENT_CHOICE 12 BUILDER_OPEN 20 TRIGGER_WEBHOOK
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-- 5 AGENT_NEW_RUN 13 BUILDER_SAVE_AGENT 21 RUN_14_DAYS
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-- 6 AGENT_INPUT 14 BUILDER_RUN_AGENT 22 RUN_AGENTS_100
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-- 7 CONGRATS 15 VISIT_COPILOT
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-- 8 GET_RESULTS 16 RE_RUN_AGENT
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--
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-- WINDOW
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-- Users who started onboarding in the last 90 days
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--
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-- EXAMPLE QUERIES
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-- -- Full funnel
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-- SELECT * FROM analytics.user_onboarding_funnel ORDER BY step_order;
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--
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-- -- Biggest drop-off point
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-- SELECT step, pct_from_prev FROM analytics.user_onboarding_funnel
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-- ORDER BY pct_from_prev ASC LIMIT 3;
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-- =============================================================
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WITH all_steps AS (
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-- Complete ordered grid of all 22 steps so zero-completion steps
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-- are always present, keeping LAG comparisons correct.
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SELECT step_name, step_order
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FROM (VALUES
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('WELCOME', 1),
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('USAGE_REASON', 2),
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('INTEGRATIONS', 3),
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('AGENT_CHOICE', 4),
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('AGENT_NEW_RUN', 5),
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('AGENT_INPUT', 6),
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('CONGRATS', 7),
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('GET_RESULTS', 8),
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('MARKETPLACE_VISIT', 9),
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('MARKETPLACE_ADD_AGENT', 10),
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('MARKETPLACE_RUN_AGENT', 11),
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('BUILDER_OPEN', 12),
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('BUILDER_SAVE_AGENT', 13),
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('BUILDER_RUN_AGENT', 14),
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('VISIT_COPILOT', 15),
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('RE_RUN_AGENT', 16),
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('SCHEDULE_AGENT', 17),
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('RUN_AGENTS', 18),
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('RUN_3_DAYS', 19),
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('TRIGGER_WEBHOOK', 20),
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('RUN_14_DAYS', 21),
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('RUN_AGENTS_100', 22)
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) AS t(step_name, step_order)
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),
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raw AS (
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SELECT
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u."userId",
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step_txt::text AS step
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FROM platform."UserOnboarding" u
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CROSS JOIN LATERAL UNNEST(u."completedSteps") AS step_txt
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WHERE u."createdAt" >= CURRENT_DATE - INTERVAL '90 days'
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),
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step_counts AS (
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SELECT step, COUNT(DISTINCT "userId") AS users_completed
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FROM raw GROUP BY step
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),
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funnel AS (
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SELECT
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a.step_name AS step,
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a.step_order,
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COALESCE(sc.users_completed, 0) AS users_completed,
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ROUND(
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100.0 * COALESCE(sc.users_completed, 0)
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/ NULLIF(
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LAG(COALESCE(sc.users_completed, 0)) OVER (ORDER BY a.step_order),
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0
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),
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2
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) AS pct_from_prev
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FROM all_steps a
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LEFT JOIN step_counts sc ON sc.step = a.step_name
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)
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SELECT * FROM funnel ORDER BY step_order
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