LLM Conveyors Python SDK
Official Python SDK for the LLM Conveyors AI Agent Platform API.
Installation
pip install llmconveyors
Quick Start
from llmconveyors import LLMConveyors
# Uses LLMCONVEYORS_API_KEY env var, or pass api_key= directly
client = LLMConveyors(api_key="llmc_...")
# Generate with streaming
result = client.agents.run(
"job-hunter",
{
"companyName": "Acme Corp",
"jobTitle": "Senior Engineer",
"companyWebsite": "https://acme.com",
"contactEmail": "hiring@acme.com",
"genericEmail": "info@acme.com",
"jobSourceUrl": "https://acme.com/careers",
},
on_progress=lambda e: print(f"[{e.step}] {e.percent}%"),
)
print(f"Success: {result.success}, Artifacts: {len(result.artifacts)}")
Async Usage
import asyncio
from llmconveyors import AsyncLLMConveyors
async def main():
async with AsyncLLMConveyors() as client:
result = await client.agents.run(
"b2b-sales",
{
"companyName": "Target Corp",
"companyWebsite": "https://target.com",
"skipResearchCache": False,
},
)
print(result.artifacts)
asyncio.run(main())
Features
- Sync + Async clients with identical APIs
- 15 resource namespaces: agents, stream, sessions, upload, resume, ats, settings, privacy, auth, documents, logging, health, content, shares, referral
- SSE streaming via generators (sync) and async generators
- High-level
run()method — generate + stream + interact in one call poll()method for non-streaming environments- Typed exceptions for all 17 API error codes
- Automatic retry with exponential backoff and jitter
- Webhook verification with HMAC-SHA256 and constant-time comparison
- Pydantic v2 models for all request/response types
Webhook Verification
from llmconveyors import construct_event
event = construct_event(
payload=request.body, # raw bytes
sig_header=request.headers["X-Webhook-Signature"],
secret="your_webhook_secret",
)
Documentation
License
MIT
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