medicalsphere-hopper 0.5.0

Unified Python library for AI model API calls

Hopper

A unified Python library for AI model API calls.

Named after Grace Hopper — the original abstraction layer between human intent and machine execution.

Supported providers

Anthropic, OpenAI, Google Gemini, Together AI, Perplexity, xAI Grok, Kimi (Moonshot AI), Z.AI (GLM).

Installation

pip install medicalsphere-hopper

Install only the provider SDKs you need:

pip install "medicalsphere-hopper[anthropic]"       # Anthropic
pip install "medicalsphere-hopper[openai]"          # OpenAI, Perplexity, Grok, Kimi, Z.AI
pip install "medicalsphere-hopper[google]"          # Google Gemini
pip install "medicalsphere-hopper[together]"        # Together AI
pip install "medicalsphere-hopper[anthropic,openai,google,together]"  # all

For local development:

git clone <repo>
cd hopper
uv sync --all-extras

Usage

import asyncio
import hopper
from hopper import CanonicalRequest, CanonicalMessage, Credentials

request = CanonicalRequest(
    model="claude-sonnet",   # model ID or alias
    messages=[CanonicalMessage(role="user", content="Hello!")],
    system="You are a helpful assistant.",
)

credentials = Credentials(api_key="sk-ant-...")

# single response
envelope = asyncio.run(hopper.complete(request, credentials))
print(envelope.response.content)

# streaming
async def stream():
    async for chunk in hopper.stream(request, credentials):
        print(chunk.delta, end="", flush=True)

asyncio.run(stream())

Image input

from hopper import ImagePart, TextPart

request = CanonicalRequest(
    model="claude-sonnet",
    messages=[
        CanonicalMessage(
            role="user",
            content=[
                ImagePart(data="<base64>", media_type="image/jpeg"),
                TextPart(text="What is in this image?"),
            ],
        )
    ],
)

Multi-turn conversations

messages = [
    CanonicalMessage(role="user",      content="My name is Alice."),
    CanonicalMessage(role="assistant", content="Got it, Alice!"),
    CanonicalMessage(role="user",      content="What's my name?"),
]
request = CanonicalRequest(model="claude-sonnet", messages=messages)

Model aliases

Every model has short aliases so you don't need to remember full IDs:

"claude-sonnet"  →  claude-sonnet-4-6
"claude-haiku"   →  claude-haiku-4-5-20251001
"gemini-3-flash" →  gemini-3-flash-preview
"gpt-5.4-mini"   →  gpt-5.4-mini-2026-03-17
"grok"           →  grok-4.20
"sonar"          →  perplexity/sonar
"kimi"           →  kimi-k2.6
"glm"            →  glm-5.2
"zai"            →  glm-5.2

Calling models not in the registry

Hopper ships with a curated model registry, but providers release new models frequently. You can call any model from a supported provider without waiting for the registry to be updated — just pass provider=:

request = CanonicalRequest(
    model="claude-sonnet-5-new",   # not in the registry yet
    provider="anthropic",          # tells Hopper which adapter to use
    messages=[CanonicalMessage(role="user", content="Hello!")],
)

Use extra_params to pass any parameters alongside it:

request = CanonicalRequest(
    model="claude-sonnet-5-new",
    provider="anthropic",
    messages=[...],
    extra_params={"temperature": 0.7, "top_p": 0.9},
)

extra_params works for registered models too — anything in there is forwarded to the provider API without filtering.

Smoke tests

Hopper never reads API keys from the environment — credentials are always passed explicitly by the caller. This keeps secret management entirely outside the library.

The smoke test is the one exception: it's a developer tool for verifying real API connectivity, so it reads keys from a local .env file that is never committed.

Setup:

cp .env.example .env
# fill in keys for the providers you want to test:
#   ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY,
#   TOGETHER_API_KEY, PERPLEXITY_API_KEY, XAI_API_KEY, KIMI_API_KEY, ZAI_API_KEY

Providers without a key are skipped automatically.

Run:

uv run python tests/smoke_test.py              # all sections (basic + image + multi-turn)
uv run python tests/smoke_test.py --stream     # streaming mode
uv run python tests/smoke_test.py --no-image   # skip image tests
uv run python tests/smoke_test.py --no-multi   # skip multi-turn tests

The image test uses tests/assets/image_example.jpeg and verifies that models can count the five asterisk markers in the image.

Unit tests

uv run pytest

Adding a provider

1. Add hopper/models/<provider>.yaml
2. Add hopper/adapters/<provider>.py exposing an ADAPTER instance

The router picks them up automatically — no other files need to change.