Python SDK

export HINOW_API_KEY="hi_sua_chave_aqui"

import os
from hinow_ai import Hinow

# The key comes from HINOW_API_KEY when you pass nothing.
client = Hinow(api_key=os.environ["HINOW_API_KEY"])

response = client.chat.completions.create(
    model="hinow/higenesis",
    messages=[{"role": "user", "content": "Explain what an embedding is in one sentence."}],
    max_tokens=120,
    temperature=0,
)

print(response.choices[0].message.content)
print("tokens:", response.usage.total_tokens)

from hinow_ai import Hinow

client = Hinow()

for chunk in client.chat.completions.create(
    model="hinow/hinova",
    messages=[{"role": "user", "content": "List three uses of an LLM, one per line."}],
    stream=True,
):
    print(chunk.choices[0].delta.content or "", end="", flush=True)
print()

from hinow_ai import Hinow

client = Hinow()

# The shape of the answer follows `type`: news carries date and source,
# places carries phone and coordinates, autocomplete carries suggestions.
web = client.tools.search("plataforma de IA brasileira", country="br", lang="pt-br")

print(f"{web['total_results']} results · US$ {web['cost']}")
for r in web["results"][:3]:
    print(f"{r['position']}. {r['title']}")
    print(f"   {r['url']}")

news = client.tools.search("artificial intelligence", type="news", country="br")
print(f"\n{news['results'][0]['source']} — {news['results'][0]['date']}")

from hinow_ai import Hinow

client = Hinow()

# The crawl runs as a job. This method waits and raises if it fails,
# so "result" always exists when it returns.
job = client.tools.website_contacts_and_wait(
    ["https://teclia.com"],
    max_depth=1,
    max_links_per_page=5,
    on_poll=lambda j: print("…", j["status"]),
)

print(f"cost US$ {job['cost']} · cached: {job['cached']}")
for contact in job["result"]["items"]:
    print(f"{contact['type']}: {contact['value']}  ({contact['sourceUrl']})")

import json
from hinow_ai import Hinow

client = Hinow()

assistant = client.beta.assistants.create(
    model="hinow/hinova",
    name="Order support",
    instructions="You look up order status. Always use the tool. Answer in one sentence.",
    tools=[{
        "type": "function",
        "function": {
            "name": "get_order",
            "description": "Lookup um order pelo identificador.",
            "parameters": {
                "type": "object",
                "properties": {"order_id": {"type": "string", "description": 'ex.: "A-1001"'}},
                "required": ["order_id"],
            },
        },
    }],
)

thread = client.beta.threads.create()
client.beta.threads.messages.create(thread["id"], content="What is the status of order A-1001?")

run = client.beta.threads.runs.create_and_poll(thread["id"], assistant_id=assistant["id"])

# "requires_action" is not an error: it is the run handing control back to you.
if run["status"] == "requires_action":
    chamadas = run["required_action"]["submit_tool_outputs"]["tool_calls"]

    run = client.beta.threads.runs.submit_tool_outputs(
        thread["id"], run["id"],
        tool_outputs=[
            {"tool_call_id": c["id"], "output": json.dumps({"id": "A-1001", "status": "delivered"})}
            for c in chamadas
        ],
    )
    run = client.beta.threads.runs.poll(thread["id"], run["id"])

messages = client.beta.threads.messages.list(thread["id"], order="desc", limit=1)
print(messages["data"][0]["content"][0]["text"]["value"])

client.beta.assistants.delete(assistant["id"])
client.beta.threads.delete(thread["id"])

import time
from hinow_ai import Hinow

client = Hinow()

text = b"Free shipping on orders over $200. Standard delivery takes 5 business days."
file = client.files.create(text, filename="shipping-policy.txt", purpose="assistants")

base = client.vector_stores.create(name="Politicas")
anexo = client.vector_stores.files.create(base["id"], file_id=file["id"])

# Indexing is asynchronous. Searching before it finishes returns nothing,
# with no error to say why.
while anexo["status"] == "in_progress":
    time.sleep(1)
    anexo = client.vector_stores.files.retrieve(base["id"], file["id"])

# The per-store filter is called rag_id. Passing vector_store_id raises no error:
# the search sweeps every document on the account.
hits = client.rag.search("qual o prazo de entrega?", rag_id=base["id"], top_k=2)

for a in hits["results"]:
    print(f"{a['score']:.2f}  {a['source']}: {a['text'][:60]}")

client.vector_stores.delete(base["id"])
client.files.delete(file["id"])

from hinow_ai import Hinow, AuthenticationError, RateLimitError, InsufficientBalanceError

client = Hinow(api_key="hi_invalid_key")

try:
    client.get_balance()
except AuthenticationError as e:
    print("invalid or revoked key:", e)
except RateLimitError:
    print("rate limited; wait and try again")
except InsufficientBalanceError:
    print("out of credit")

const client = new Hinow({
  apiKey: process.env.HINOW_API_KEY,  // ou deixe em branco e use a variável
  baseURL: 'https://api.hinow.ai',    // ou HINOW_BASE_URL
  timeout: 120_000,                   // milissegundos
  maxRetries: 3,
});