Skip to main content

SynapsAI Python SDK

License Python Version

The official SynapsAI Cloud AI inference Python SDK. Seamlessly integrate multi-modal AI capabilities into your applications.


Installation

Install the latest version of the SDK:

pip install --upgrade synapsai-python

Requirements

  • Python >= 3.8
  • httpx >= 0.23.0, < 1.0.0
  • pydantic >= 2.0, < 3
  • typing-extensions >= 4.5, < 5
  • Pillow >= 12.2.0
  • click >= 8.0

Quick Start

1. Setup Environment Variables

You can configure the SDK using environment variables instead of hardcoding your credentials:

  • SYNAPSAI_API_KEY - Your SynapsAI API key
  • SYNAPSAI_API_BASE - Custom base URL (Defaults to https://api.synapsai.cloud/v1)

2. Initialization & Example Usage

Here is how to initialize the client and fetch a list of all deployed models on your account:

import os
from synapsai import SynapsAI

# Initialize the client (picks up env variables automatically if arguments are omitted)
client = SynapsAI(
    api_key=os.environ.get("SYNAPSAI_API_KEY"),
)

# Fetch and view deployed models
models_page = client.models.list()
for model in models_page.data:
    print(f"Model ID: {model.id} | Status: {model.status}")

Documentation

Local guides live in docs/ (getting started, every resource, CLI, async, errors).

Online examples: docs.synapsai.cloud.


Available Resources

The SDK provides native support for the following SynapsAI Cloud capabilities:

Resource Description
models Model management and discovery
chat.completions Chat completions, streaming, and stored CRUD
responses Responses API create / retrieve / delete
completions Classic text completions
embeddings Text embeddings generation
images Image generation and manipulation
audio Speech-to-text and text-to-speech processing
videos Video generation and processing
classifications Text classification tasks
question_answering Targeted question answering
feature_extraction Feature extraction pipelines
fill_mask Masked Language Modeling (MLM)
rerank Text reranking for search optimization
vector_stores Vector stores and file ingestion/search
model_artifacts Model artifact upload sessions
agents Persisted agent runs, resume, and delete (AG-UI SSE)

CLI

After install, the synapsai command is available:

# Upload a model directory into an existing artifact
synapsai upload-model ./my-model --artifact-id artifact-demo-abc12345

# Upload files or directories into a vector store
synapsai upload-vector-store-files vs_abc123 ./docs ./readme.md

Environment variables:

  • SYNAPSAI_API_KEY — API key
  • SYNAPSAI_API_BASE — API base URL (default https://api.synapsai.cloud/v1)

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Metadata

Release files for synapsai-python 0.1.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for synapsai-python 0.1.7
File Size Uploaded Provenance Actions
synapsai_python-0.1.7.tar.gz 50.9 kB Without provenance Details for synapsai_python-0.1.7.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for synapsai-python 0.1.7
File Interpreter ABI Platform Actions
synapsai_python-0.1.7-py3-none-any.whl Python 3 none any Details for synapsai_python-0.1.7-py3-none-any.whl

Total release size: 127.7 kB

Release files / synapsai_python-0.1.7.tar.gz

Download URL synapsai_python-0.1.7.tar.gz
Size 50.9 kB
Tags Source
SHA-256 checksum
How to use checksums
14112831534519dd896c1a1ac0129a67ecd81d47f78cc1651e243afc0bb99543
BLAKE2b-256 checksum
How to use checksums
fad9a7d25d96f36c4c2506b92b932e6541c0d7f296cdaac3320cb075a15fe0c3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.2

Release files / synapsai_python-0.1.7-py3-none-any.whl

Download URL synapsai_python-0.1.7-py3-none-any.whl
Size 76.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d26fdae5eb6363cf5f9bccf051055577fbe54bfbb04f7c40ba1839ab8809fefa
BLAKE2b-256 checksum
How to use checksums
c43cc69836aaaeb9282d8d7779b3b24e5a5036d25445c1bad3864ee60a62f9fd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.2

Security for synapsai-python 0.1.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page