Official Python client for the Caedral API
Project description
Caedral Python SDK
Official Python client for the Caedral API. OpenAI-compatible request shapes — point your existing code at Caedral with minimal changes.
Installation
pip install caedral
Local development (editable install)
cd sdk-python
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -e ".[dev]"
Quickstart
from caedral import Caedral
caedral = Caedral(
api_key="cd_live_...",
base_url="http://localhost:5001", # local API gateway
)
completion = caedral.chat.completions.create(
model="caedral-titan",
messages=[{"role": "user", "content": "Hello!"}],
)
print(completion.choices[0].message["content"])
caedral.close()
Or use a context manager:
with Caedral(api_key="cd_live_...", base_url="http://localhost:5001") as caedral:
usage = caedral.usage.get()
print(usage.weeklyPool.remaining)
Production default base URL: https://api.caedral.com.
Configuration
| Parameter | Default | Description |
|---|---|---|
api_key |
— | Required. Your cd_live_... API key |
base_url |
https://api.caedral.com |
API gateway base URL |
max_retries |
3 |
Retries for idempotent GET requests (exponential backoff) |
timeout |
120.0 |
Request timeout in seconds |
Methods
caedral.chat.completions.create(...)
OpenAI-compatible chat completions.
Non-streaming:
response = caedral.chat.completions.create(
model="caedral-olympus",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Explain quantum computing briefly."},
],
temperature=0.7,
max_tokens=500,
)
print(response.choices[0].message["content"])
print(response.usage.total_tokens if response.usage else None)
Streaming (generator):
stream = caedral.chat.completions.create(
model="caedral-titan",
messages=[{"role": "user", "content": "Write a haiku about code."}],
stream=True,
)
for chunk in stream:
delta = chunk.choices[0].delta.get("content")
if delta:
print(delta, end="", flush=True)
print()
Models: caedral-base, caedral-titan, caedral-olympus, caedral-primordial.
caedral.models.list()
models = caedral.models.list()
for model in models.data:
print(model.id, model.name, model.pricing_tier)
caedral.usage.get()
usage = caedral.usage.get()
print("Pool remaining:", usage.weeklyPool.remaining)
print("Balance (cents):", usage.balanceCents)
print("Overage used:", usage.overage.usedCents)
caedral.embeddings.create(...)
result = caedral.embeddings.create(
model="caedral-embed",
input="Caedral unifies frontier models behind one API.",
)
print(len(result.data[0].embedding))
caedral.images.generate(...)
image = caedral.images.generate(
model="caedral-vision",
prompt="A minimal geometric logo on a dark background",
)
print(image.data[0].url or "b64 payload returned")
caedral.audio.generate(...)
audio = caedral.audio.generate(
model="caedral-voice",
input="Welcome to Caedral.",
voice="alloy",
)
print(audio.model)
caedral.rerank.create(...)
ranked = caedral.rerank.create(
model="caedral-rerank",
query="billing and subscriptions",
documents=[
"Caedral pricing tiers include Starter and Pro.",
"The API gateway runs on port 5001 in local dev.",
],
top_n=2,
)
for item in ranked.results:
print(item.index, item.relevance_score)
Error handling
from caedral import Caedral, CaedralAPIError
try:
caedral.chat.completions.create(
model="caedral-base",
messages=[{"role": "user", "content": "Hi"}],
)
except CaedralAPIError as err:
print(err.status_code, err.type, err.message)
Async client
AsyncCaedral is planned as a fast-follow. The synchronous client covers all endpoints today.
Integration tests
Requires a running local gateway (http://localhost:5001) and DATABASE_URL in the repo root .env (tests create a temporary API key automatically).
cd sdk-python
pip install -e ".[dev]"
pytest -v
Optional environment variables:
| Variable | Description |
|---|---|
CAEDRAL_BASE_URL |
Gateway URL (default http://localhost:5001) |
CAEDRAL_TEST_API_KEY |
Skip auto key creation and use an existing key |
License
MIT
Project details
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