┌──────────────────────────────────────────────────────────────────┐
│                     console.hanzo.ai (Next.js 15, :3001)         │
├──────────────────────────────────────────────────────────────────┤
│  Traces Explorer | Prompts Manager | Evals Pipeline | Datasets  │
│                          │                                       │
│                    Console API                                   │
│            ┌─────────────┼─────────────┐                        │
│      PostgreSQL     ClickHouse      Redis ──► Worker            │
│      (metadata)     (analytics)     (queues)  (BullMQ 27+)     │
└──────────────────────────────────────────────────────────────────┘

Ingestion:  Your App ──► SDK/HTTP ──► api.hanzo.ai/v1/console/* ──► ClickHouse

from hanzoai import Hanzo

client = Hanzo(api_key="hk-your-api-key", trace=True)

# Every call is traced automatically
response = client.chat.completions.create(
    model="anthropic-claude-haiku-4.5",
    messages=[{"role": "user", "content": "Explain distributed tracing."}],
    metadata={"session_id": "sess-abc", "user_id": "user-42"},
)

from hanzoai.console import observe

@observe()
def my_pipeline(query: str) -> str:
    docs = retrieve(query)       # span: retrieval
    answer = generate(docs)      # span: generation
    return answer

@observe(name="generation", capture_input=True, capture_output=True)
def generate(docs: list) -> str:
    return client.chat.completions.create(
        model="alibaba-qwen3-32b",
        messages=[{"role": "user", "content": str(docs)}],
    ).choices[0].message.content

from hanzoai.console import get_prompt

prompt = get_prompt(name="qa-system", version=3)
compiled = prompt.compile(context="Hanzo docs", question="What is Console?")

response = client.chat.completions.create(
    model="anthropic-claude-haiku-4.5",
    messages=compiled,
    hanzo_prompt=prompt,  # links generation to prompt version
)

import Hanzo from '@hanzo/ai'

const client = new Hanzo({ apiKey: 'hk-your-api-key', trace: true })

const response = await client.chat.completions.create({
  model: 'anthropic-claude-haiku-4.5',
  messages: [{ role: 'user', content: 'Explain distributed tracing.' }],
  metadata: { sessionId: 'sess-abc', userId: 'user-42' },
})

import { ConsoleClient } from '@hanzo/ai/console'

const console = new ConsoleClient({ publicKey: 'hk-your-api-key' })
const trace = console.trace({ name: 'rag-pipeline' })

const retrieval = trace.span({ name: 'retrieval', input: { query } })
const docs = await vectorSearch(query)
retrieval.end({ output: docs })

const generation = trace.generation({
  name: 'llm-call',
  model: 'alibaba-qwen3-32b',
  input: messages,
})
const result = await llmCall(messages)
generation.end({ output: result, usage: { inputTokens: 120, outputTokens: 45 } })

from openai import OpenAI
from hanzoai.console import wrap_openai

openai_client = wrap_openai(OpenAI(
    api_key="your-hanzo-key",
    base_url="https://api.hanzo.ai/v1",
))

# All calls are now traced to Hanzo Console
response = openai_client.chat.completions.create(
    model="openai-gpt-5-nano",
    messages=[{"role": "user", "content": "Hello!"}],
)

curl -X POST https://api.hanzo.ai/v1/console/prompts \
  -H "Authorization: Bearer hk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "qa-system",
    "prompt": "Answer based on context.\n\nContext: {{context}}\nQuestion: {{question}}",
    "config": {"model": "anthropic-claude-haiku-4.5", "temperature": 0.2},
    "labels": ["production"]
  }'

kubectl port-forward svc/clickhouse 9000:9000 -n hanzo
migrate -path ./migrations -database "clickhouse://localhost:9000/console" up