Prune SDK

Drop-in OpenAI / Anthropic clients for the Prune AI proxy — lower bills on every call, vaulted API keys, and a receipt on every response. Cache helps on repeats.

# Before
from anthropic import Anthropic

# After
from prune import Anthropic

Supported providers

Links

• Website: https://www.withprune.com
• Docs: https://www.withprune.com/docs
• API: https://api.withprune.com

Installation

pip install prune-sdk

For local backend development:

export PRUNE_BASE_URL="http://127.0.0.1:8000"

Install from source (contributors):

pip install -e "./prune-sdk[dev]"

Quick start

Anthropic (Claude)

from prune import Anthropic

client = Anthropic(
    api_key="sk-ant-your-key",
    prune_api_key="prune_your_key",
)

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello, Claude!"}],
)

print(message.content[0].text)
print(client.last_prune_metadata)  # cache hit, tokens saved, etc.

OpenAI (GPT)

from prune import OpenAI

client = OpenAI(
    api_key="sk-your-openai-key",
    prune_api_key="prune_your_key",
)

completion = client.chat.completions.create(
    model="gpt-4o-mini",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello!"}],
)

print(completion.choices[0].message.content)

Async

from prune import AsyncAnthropic

client = AsyncAnthropic(
    api_key="sk-ant-...",
    prune_api_key="prune_...",
)

message = await client.messages.create(
    model="claude-3-5-haiku-20241022",
    max_tokens=100,
    messages=[{"role": "user", "content": "Hi"}],
)

Configuration

Environment variables:

export PRUNE_API_KEY="prune_your_key"
export PRUNE_BASE_URL="https://api.withprune.com"   # or http://127.0.0.1:8000 for local backend
export PRUNE_FALLBACK="true"                     # fallback to direct API if proxy fails

Programmatic:

import prune

prune.configure(api_key="prune_your_key", base_url="https://api.withprune.com")

client = prune.Anthropic(api_key="sk-ant-...")

Workload packs & dashboard settings

Optimization mode (Recommended / Max / Off) and your default workload pack are saved in the dashboard and applied on every proxy request — no SDK changes required.

Optional: override or hint workload per app via headers:

import prune

prune.configure(
    api_key="prune_your_key",
    prune_workload="structured_planning",      # X-Prune-Workload
    prune_template_id="focus_breakdown_v1",    # X-Prune-Template-Id
)

client = prune.OpenAI(
    api_key="sk-...",
    prune_workload="support_chat",  # client default; per-call prune_workload= wins
)

client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello"}],
    prune_workload="rag",  # per-request override
)

Valid pack ids: structured_planning, structured_extraction, support_chat, agent_step, rag, batch, creative (see prune.WORKLOAD_PACKS).

Per-request kwargs: prune_session_id, prune_end_user_id, prune_org_id, prune_run_id, prune_workload, prune_template_id.

Behavior

Direct HTTP (no SDK)

If you only need to test the proxy, skip the SDK and POST to the backend:

curl -X POST http://127.0.0.1:8000/v1/proxy/anthropic/messages ^
  -H "X-Prune-Key: prune_your_key" ^
  -H "Content-Type: application/json" ^
  -d "{\"model\":\"claude-sonnet-4-20250514\",\"max_tokens\":64,\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}],\"user_api_key\":\"sk-ant-...\"}"

import httpx

resp = httpx.post(
    "http://127.0.0.1:8000/v1/proxy/anthropic/messages",
    headers={"X-Prune-Key": "prune_your_key"},
    json={
        "model": "claude-sonnet-4-20250514",
        "max_tokens": 64,
        "messages": [{"role": "user", "content": "Hello"}],
        "user_api_key": "sk-ant-...",
    },
    timeout=60,
)
print(resp.json())

Development

cd prune-sdk
pip install -e ".[dev]"
pytest tests/ -q
pytest tests/ -m integration  # needs ANTHROPIC_API_KEY + PRUNE_API_KEY

License

MIT