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AI Agent Control Plane SDK — hard spending caps, automatic failover, per-agent cost attribution

Project description

Solwyn Python SDK

Budget enforcement, circuit breaking, and usage tracking for OpenAI, Anthropic, and Google LLM clients.

CI PyPI version Python 3.11+ License

Solwyn wraps your existing LLM client. Calls go directly to the provider — the SDK only reports metadata (token counts, latency, model name) to the Solwyn API. Prompts and responses never leave your application.

Installation

pip install solwyn

For improved token estimation with OpenAI models:

pip install solwyn[openai]

Quick Start

from openai import OpenAI
from solwyn import Solwyn

client = Solwyn(
    OpenAI(),
    api_key="sk_proj_...",
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
)

client.close()

Or use as a context manager:

with Solwyn(OpenAI(), api_key="sk_proj_...") as client:
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Hello!"}],
    )

Providers

OpenAI

from openai import OpenAI
from solwyn import Solwyn

client = Solwyn(OpenAI(), api_key="sk_proj_...")
response = client.chat.completions.create(model="gpt-4o", messages=[...])

Anthropic

from anthropic import Anthropic
from solwyn import Solwyn

client = Solwyn(Anthropic(), api_key="sk_proj_...")
response = client.messages.create(model="claude-sonnet-4-20250514", max_tokens=1024, messages=[...])

Google Gemini

from google import genai
from solwyn import Solwyn

client = Solwyn(genai.Client(api_key="..."), api_key="sk_proj_...")
response = client.models.generate_content(model="gemini-2.0-flash", contents="Hello!")

Async

from openai import AsyncOpenAI
from solwyn import AsyncSolwyn

async with AsyncSolwyn(
    AsyncOpenAI(),
    api_key="sk_proj_...",
) as client:
    response = await client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Hello!"}],
    )

Streaming

Pass stream=True as you normally would. Solwyn wraps the stream transparently and reports usage when it completes:

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True,
)

for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

Budget Enforcement

Set budget_mode to control spending:

client = Solwyn(
    OpenAI(),
    api_key="sk_proj_...",
    budget_mode="hard_deny",
)
Mode Behavior
alert_only Log a warning when budget is exceeded (default)
hard_deny Raise BudgetExceededError and block the call
from solwyn import BudgetExceededError

try:
    response = client.chat.completions.create(model="gpt-4o", messages=[...])
except BudgetExceededError as e:
    print(f"Budget limit: ${e.budget_limit}, usage: ${e.current_usage}")

Configuration

Parameter Env Var Default Description
api_key SOLWYN_API_KEY required Solwyn project API key
api_url SOLWYN_API_URL https://api.solwyn.ai Solwyn API endpoint
fail_open SOLWYN_FAIL_OPEN True Allow LLM calls when Solwyn API is unreachable
budget_mode SOLWYN_BUDGET_MODE alert_only Budget enforcement mode
fallback_model SOLWYN_FALLBACK_MODEL None Model name to retry with when the primary call fails (same provider, same client)

Use env vars to avoid passing credentials in code:

export SOLWYN_API_KEY="sk_proj_..."
client = Solwyn(OpenAI())  # picks up from environment

Error Handling

All SDK errors inherit from SolwynError:

Exception Raised when
BudgetExceededError Budget exceeded in hard_deny mode
ProviderUnavailableError Circuit breaker is open
ConfigurationError Invalid API key format

Provider errors (e.g., openai.RateLimitError) pass through unmodified.

Data Transparency

The SDK sends a MetadataEvent after each LLM call. This is everything it transmits:

Field Type Description
model str Model name (e.g., gpt-4o)
provider str openai, anthropic, or google
input_tokens int Input token count
output_tokens int Output token count
token_details object Breakdown: cached, reasoning, audio tokens
latency_ms float Call duration in milliseconds
status str success, error, or budget_denied
is_model_fallback bool Whether the call used fallback_model after the primary model failed
sdk_instance_id str Per-process UUID for deduplication
timestamp datetime When the call completed (UTC)

The SDK never captures, logs, or transmits prompts or responses. This is enforced by structural tests and the privacy module.

Requirements

Python 3.11+

Contributing

make install          # install in dev mode
make install-hooks    # install pre-commit hook
make check            # lint + format + typecheck
make test             # run unit tests

Links

License

Apache 2.0 — see LICENSE for details.

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