celeste-ai 0.9.1

Open source, type-safe primitives for multi-modal AI. All capabilities, all providers, one interface

Celeste AI

The primitive layer for multi-modal AI

All modalities. All providers. One interface.

Primitives, not frameworks.

Quick Start • Request Provider

🚀 This is the v1 Beta release. We're validating the new architecture before the stable v1.0 release. Feedback welcome!

Celeste AI

Type-safe, modality/provider-agnostic primitives.

• Unified Interface: One API for OpenAI, Anthropic, Gemini, Mistral, and 14+ others.
• True Multi-Modal: Text, Image, Audio, Video, Embeddings, Search —all first-class citizens.
• Type-Safe by Design: Full Pydantic validation and IDE autocomplete.
• Zero Lock-In: Switch providers instantly by changing a single config string.
• Primitives, Not Frameworks: No agents, no chains, no magic. Just clean I/O.
• Lightweight Architecture: No vendor SDKs. Pure, fast HTTP.

🚀 Quick Start

import celeste

# "We need a catchy slogan for our new eco-friendly sneaker."
slogan = await celeste.text.generate(
    "Write a slogan for an eco-friendly sneaker.",
    model="gpt-5",
)
print(slogan.content)

🎨 Multimodal example

import celeste
from pydantic import BaseModel, Field

class ProductCampaign(BaseModel):
    visual_prompt: str
    audio_script: str

# 2. Extract Campaign Assets (Anthropic)
# -----------------------------------------------------
campaign_output = await celeste.text.generate(
    f"Create campaign assets for slogan: {slogan.content}",
    model="claude-opus-4-1",
    output_schema=ProductCampaign,
)
campaign = campaign_output.content

# 3. Generate Ad Visual (Flux)
# -----------------------------------------------------
image_output = await celeste.images.generate(
    campaign.visual_prompt,
    model="flux-2-flex",
    aspect_ratio="1:1"
)
image = image_output.content

# 4. Generate Radio Spot (ElevenLabs)
# -----------------------------------------------------
speech_output = await celeste.audio.speak(
    campaign.audio_script,
    model="eleven_v3",
    voice="adam"
)
speech = speech_output.content

No special cases. No separate libraries. One consistent interface.

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15+ providers. Zero lock-in.

and many more

Missing a provider? Request it – ⚡ we ship fast.

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🔄 Switch providers in one line

from pydantic import BaseModel

class User(BaseModel):
    name: str
    age: int

# Model IDs
anthropic_model_id = "claude-4-5-sonnet"
google_model_id = "gemini-2.5-flash"

# ❌ Anthropic Way
from anthropic import Anthropic
import json

client = Anthropic()
response = client.messages.create(
    model=anthropic_model_id,
    messages=[
        {"role": "user",
         "content": "Extract user info: John is 30"}
    ],
    output_format={
        "type": "json_schema",
        "schema": User.model_json_schema()
    }
)
user_data = json.loads(response.content[0].text)

# ❌ Google Gemini Way
from google import genai
from google.genai import types

client = genai.Client()
response = await client.aio.models.generate_content(
    model=gemini_model_id,
    contents="Extract user info: John is 30",
    config=types.GenerateContentConfig(
        response_mime_type="application/json",
        response_schema=User
    )
)
user = response.parsed

# ✅ Celeste Way
import celeste

response = await celeste.text.generate(
    "Extract user info: John is 30",
    model=google_model_id,  # <--- Choose any model from any provider
    output_schema=User,  # <--- Unified parameter working across all providers
)
user = response.content  # Already parsed as User instance

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🧭 Namespace API (recommended)

Namespaces are domain-first: start from the resource you want to work with (e.g., videos) even if the input is text. Under the hood, Celeste maps (domain, operation) to the output modality (e.g., celeste.images.analyze(...) routes to the text modality because analysis returns text).

import celeste

# Async (default)
result = await celeste.images.analyze(
    image=img,
    prompt="Describe this image",
    model="gpt-4o"
)

# Sync
result = celeste.images.sync.analyze(
    image=img,
    prompt="Describe this image",
    model="gpt-4o"
)

# Async streaming
async for chunk in celeste.text.stream.generate("Hello", model="gpt-4o"):
    print(chunk.content, end="")

# Sync streaming
for chunk in celeste.text.sync.stream.generate("Hello", model="gpt-4o"):
    print(chunk.content, end="")

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⚙️ Advanced: create_client

For explicit configuration or client reuse, use create_client with modality + operation. This is modality-first: you choose the output type and operation explicitly.

from celeste import create_client, Modality, Operation

client = create_client(
    modality=Modality.TEXT,
    operation=Operation.GENERATE,
    model=google_model_id,
)
response = await client.generate("Extract user info: John is 30", output_schema=User)

capability is still supported but deprecated. Prefer modality + operation.

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🪶 Install

pip install celeste-ai
# or
uv add celeste-ai

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🔁 Behavior changes since v0.3.9

• Capabilities → modalities + operations.
• Namespace API is now the default entry point.
• create_client now uses modality + operation; capability is deprecated.
• analyze for image/audio/video routes through the text modality.
• Namespaces are domain-first (resource you work with); create_client is modality-first (output type). Domain + operation maps to modality.
• extra_body allows provider-specific parameters without first-class mapping.
• Single-package install (no extras).

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🔧 Type-Safe by Design

# Full IDE autocomplete
import celeste

response = await celeste.text.generate(
    "Explain AI",
    model="gpt-4o-mini",
    temperature=0.7,    # ✅ Validated (0.0-2.0)
    max_tokens=100,     # ✅ Validated (int)
)

# Typed response
print(response.content)              # str (IDE knows the type)
print(response.usage.input_tokens)   # int
print(response.metadata["model"])     # str

Catch errors before production.

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🤝 Contributing

We welcome contributions! See CONTRIBUTING.md.

Request a provider: GitHub Issues Report bugs: GitHub Issues

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📄 License

MIT license – see LICENSE for details.

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Get Started • Documentation • GitHub

Made with ❤️ by developers tired of framework lock-in