VMware Tanzu Platform - CLI Testing Guide

Prerequisites

goose CLI built from the feat/tanzu-ai-provider branch
A Tanzu AI Services endpoint and API key (single-model or multi-model plan)

Locate the CLI Binary

macOS:

bash

# If built from source:
export GOOSE_CLI=~/claude/goose-fork/target/release/goose

# Verify:
$GOOSE_CLI --version

Linux:

bash

# If installed via .deb:
export GOOSE_CLI=/usr/bin/goose

# If built from source:
export GOOSE_CLI=~/goose-fork/target/release/goose

# Verify:
$GOOSE_CLI --version

Test 1: Configure VMware Tanzu Platform Provider

bash

goose configure

Select Configure Providers
Scroll to / search for VMware Tanzu Platform
When prompted for TANZU_AI_ENDPOINT, enter your endpoint URL:
- Single-model: https://genai-proxy.sys.example.com/tanzu-my-model-abc1234
- Multi-model: https://genai-proxy.sys.example.com/tanzu-all-models-abc1234
When prompted for TANZU_AI_API_KEY, paste the JWT token from your service key
Select a model from the dynamically fetched list

Expected: Models are fetched from the endpoint and displayed for selection.

Test 2: Start a Session (Single-Model Plan)

bash

export TANZU_AI_ENDPOINT="https://genai-proxy.sys.tas-tdc.kuhn-labs.com/tanzu-Qwen3-Coder-30B-A3B-vllm-v1-f3b0d18"
export TANZU_AI_API_KEY="<your-jwt-token>"

goose session

Type a simple prompt:

> What is 2 + 2?

Expected: The model responds with an answer. If streaming is enabled, tokens appear incrementally.

Test 3: Start a Session (Multi-Model Plan)

bash

export TANZU_AI_ENDPOINT="https://genai-proxy.sys.tas-tdc.kuhn-labs.com/tanzu-all-models-a8a9e22"
export TANZU_AI_API_KEY="<your-jwt-token>"

goose session

Expected: Session starts with whichever model was selected during goose configure.

Test 4: Verify Streaming

With streaming enabled (supports_streaming: true), responses should appear token-by-token rather than all at once.

> Write a short poem about clouds

Expected: Text streams in progressively, not appearing all at once after a delay.

Test 5: Verify Dynamic Model Fetching

bash

goose configure

Select Configure Providers > VMware Tanzu Platform.

Expected for single-model plan: One model appears (e.g., Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8) Expected for multi-model plan: Multiple models appear (e.g., Qwen3.5-122B, Qwen3-Coder-30B, gpt-oss-120b)

Test 6: Verify Error Messages

Missing API Key

bash

unset TANZU_AI_API_KEY
goose session

Expected: Clear error message: "Required API key TANZU_AI_API_KEY is not set."

Missing Endpoint

bash

unset TANZU_AI_ENDPOINT
goose session

Expected: Clear error message about TANZU_AI_ENDPOINT not being set.

Wrong Endpoint

bash

export TANZU_AI_ENDPOINT="https://genai-proxy.sys.example.com/nonexistent"
export TANZU_AI_API_KEY="invalid-key"
goose session

Expected: Connection or authentication error, not a crash.

Test 7: Switch Between Plans

Configure with multi-model endpoint, select a model, start a session, verify it works
Run goose configure again
Change TANZU_AI_ENDPOINT to the single-model endpoint
Select the single model
Start a new session, verify it works

Expected: Both plans work without needing to restart goose.

Quick Curl Verification

Before testing with goose, you can verify endpoints directly:

bash

# Test models endpoint
curl -s -H "Authorization: Bearer $TANZU_AI_API_KEY" \
  "$TANZU_AI_ENDPOINT/openai/v1/models" | python3 -m json.tool

# Test chat completions
curl -s -X POST "$TANZU_AI_ENDPOINT/openai/v1/chat/completions" \
  -H "Authorization: Bearer $TANZU_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8","messages":[{"role":"user","content":"hello"}],"max_tokens":10}'

# Test streaming
curl -s -N -X POST "$TANZU_AI_ENDPOINT/openai/v1/chat/completions" \
  -H "Authorization: Bearer $TANZU_AI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8","messages":[{"role":"user","content":"hello"}],"max_tokens":10,"stream":true}'