copilotkit__copilotkit/showcase/aimock

Showcase aimock

Deterministic LLM fixture server for showcase E2E testing. Replaces real LLM API calls (OpenAI, Anthropic, Gemini) with pre-recorded responses so Playwright tests can run PR-gated in CI without API keys and without rate limits or non-determinism.

Railway pulls ghcr.io/copilotkit/aimock:latest directly (no wrapper image). The fixtures in this directory are loaded at boot via GitHub raw URLs configured in the Railway service's startCommand.

What aimock is

aimock (@copilotkit/aimock) is a general-purpose LLM mock server. It speaks the OpenAI, Anthropic, and Gemini REST shapes (including SSE streaming), loads fixtures from disk at startup, and responds to incoming chat completions by matching the user's message text against fixture match criteria.

The showcase deployment runs aimock in proxy mode — --proxy-only with real upstream URLs configured for each provider. Unmatched requests are forwarded to the real API; matched requests short-circuit with the fixture response. This makes the sidecar safe to deploy as a general-purpose smoke-test aid: tests that hit fixture-matched prompts get deterministic responses, and anything else just falls through.

Directory Structure

showcase/aimock/
  shared/              Fixtures loaded by ALL integrations (smoke, universal prompts)
  d4/                  D4-depth fixtures — per-integration, single-demo coverage
    <slug>/            One directory per integration slug (e.g. langgraph-python/)
  d6/                  D6-depth fixtures — per-integration, all-pills coverage
    <slug>/            One directory per integration slug
  feature-parity.json  Legacy flat fixture file (pre-context-routing)
  smoke.json           Minimal smoke fixture
  README.md            This file

Context routing. D4 and D6 fixtures use aimock's --context-field flag to scope fixture matching by integration. Each integration's dev server passes its slug as the context value in LLM requests (via X-AIMock-Context header or request body field). Aimock only considers fixtures whose match.context equals the incoming context value, so d4/langgraph-python/ fixtures never interfere with d4/mastra/ fixtures even if they share the same userMessage pattern.

Per-integration isolation. Every <slug>/ directory contains fixtures specific to that integration. This prevents cross-contamination: if mastra needs a different tool name than langgraph-python for the same demo, each has its own fixture file. The shared/ directory holds fixtures that apply regardless of context (e.g., smoke checks, universal greeting prompts).

Fixtures in this directory

• feature-parity.json — 35+ fixtures covering the nine showcase demos across 17 packages: agentic chat (weather, backgrounds, themes), tool rendering (pie/bar charts, weather cards), HITL (plans, steps, approvals), Sales Dashboard (deals, pipelines, todos), and assorted meeting/flight/greeting prompts. Consumed by the per-package test_e2e-showcase-on-demand Playwright suites and loaded at Railway boot via GitHub raw URL.
• smoke.json — a single minimal fixture (userMessage: "Respond with exactly: OK" → content: "OK"). Used by /api/smoke endpoints in each package to verify the aimock → package → UI round-trip without depending on a real agent.

Fixture match semantics: userMessage is a substring match against the last user turn. First fixture to match wins, so more specific prompts should appear before more generic ones (see the "Based on the following context, write a concise" entry that precedes the generic report / plan fixtures to protect CrewAI's startup probe).

Sync policy

Fixtures are hand-maintained. There is no automated capture, no scheduled re-recording, and no drift-detection job that compares fixture responses against what a real LLM would say. The authoritative behavior is whatever is checked in.

The safety net is two-layered load-time validation, not behavioral verification:

1. Load-time schema validation (--validate-on-load in the Railway startCommand and in every test entrypoint that boots aimock) — the container refuses to start if any fixture uses an unrecognized response key (e.g. text instead of content). See #3973.
2. CI schema validation (showcase/scripts/__tests__/aimock-fixtures.test.ts) — the showcase_validate workflow runs loadFixtureFile + validateFixtures from @copilotkit/aimock against every showcase/aimock/*.json on every PR. A broken fixture fails the PR before merge.

Neither layer catches behavioral drift — if a package's agent code changes what it asks the LLM (new prompt, new tool, renamed tool), the existing fixture keeps matching and keeps returning the old response. The test either keeps passing (wrong assertion) or fails at the UI-assertion layer (missing tool call, missing text), and a human has to trace it back to the fixture.

Adding or updating a fixture

The process is manual. There is no CLI for this directory specifically — aimock's upstream --record mode can proxy real API calls and write fixtures, but the showcase repo does not wire it up and does not commit recorded fixtures.

1. Identify the user prompt your test issues and decide what response you need (plain text, a tool call, an error).
2. Add an entry to feature-parity.json under fixtures. Keep more specific userMessage matches above more generic ones. Valid response keys: content, toolCalls, error, embedding.
3. Run the fixture-validation suite locally:

   pnpm --filter @copilotkit/showcase-scripts test aimock-fixtures
   

4. Run the per-package E2E against the new fixture:

   ./showcase/scripts/run-e2e-with-aimock.sh <slug> [test-filter]
   

5. Ship it. Fixture changes take effect on the next Railway service restart (aimock fetches fixtures from GitHub raw URLs at boot).

When a package's agent code changes in a way that changes its LLM calls, the person making the change is responsible for updating the corresponding fixture. There is no automation to remind you.

Drift risk

Drift surfaces as flaky or silently-wrong E2E tests, not as a dedicated signal. Symptoms and how to respond:

• Playwright assertion fails on a UI element that depends on a tool call (WeatherCard missing, chart not rendering) → the agent is now calling a differently-named tool than the fixture has; update the fixture's toolCalls[].name / arguments.
• Assertion on assistant text fails → the agent's prompt changed; either update the fixture's match.userMessage to the new prompt substring or update the fixture's content.
• smoke.json healthcheck fails against a deployed package (/api/smoke returns non-OK) → either the package's smoke route changed or aimock is down; check the Railway service and the smoke-monitor workflow.
• Container fails to start post-deploy → load-time validation caught a broken fixture; CI should have caught it first, investigate why it didn't.

There is no scheduled drift-detection job that compares fixture responses against live LLM output. If this becomes a problem, the path forward is to wire aimock's --record mode into a periodic workflow that re-captures against real providers and diffs against checked-in fixtures — but that's not built today.

Related workflows

• test_e2e-showcase-on-demand.yml (historically showcase_aimock-e2e.yml) — triggered by /test-aimock <slug> PR comments or workflow_dispatch. Installs @copilotkit/aimock@latest, boots it with feature-parity.json, spins up the target package's dev server against OPENAI_BASE_URL=http://localhost:4010/v1, and runs the package's Playwright suite. Posts pass/fail back to the PR.
• showcase_validate.yml — runs fixture schema validation (aimock-fixtures.test.ts) on every PR that touches showcase/**.
• showcase_deploy.yml — builds and deploys all showcase services. aimock is no longer in this workflow's matrix (Railway pulls the upstream ghcr.io/copilotkit/aimock:latest image directly).
• showcase_smoke-monitor.yml — every 15 minutes, polls /api/smoke on all deployed showcase packages. Those smoke endpoints internally hit aimock's smoke.json fixture to verify the full stack.