hiresquire 1.2.2

HireSquire SDK - AI-powered candidate screening for agents and humans

HireSquire Python SDK

Python SDK for HireSquire's AI-powered candidate screening API. Includes native LangChain and AutoGen integration.

Installation

pip install hiresquire

Quick Start

Option 1: Client Class (Recommended)

from hiresquire import HireSquire

client = HireSquire("YOUR_API_TOKEN")

# Submit and wait automatically
job = client.screen(
    title="Senior Python Developer", 
    description="Looking for experienced Python developer with Django experience...",
    resumes=["./resumes/john_doe.pdf", "./resumes/jane_smith.pdf"]
)

# Get results when complete
results = client.wait_for_completion(job["job_id"])

for candidate in results["candidates"]:
    print(f"{candidate['name']}: {candidate['score']}/100")

Option 2: Direct Function Calls

from hiresquire import create_screening_job, get_screening_status, get_screening_results

# Submit a screening job
result = create_screening_job(
    title="Senior Python Developer",
    description="Looking for experienced Python developer with Django experience...",
    resumes=[
        {"filename": "john_doe.pdf", "content": "John Doe\n5 years Python experience..."}
    ]
)
job_id = result["job_id"]

# Poll for completion
status = get_screening_status(job_id=job_id)
while status["status"] == "processing":
    time.sleep(3)
    status = get_screening_status(job_id=job_id)

# Get results
results = get_screening_results(job_id=job_id)
for candidate in results["candidates"]:
    print(f"{candidate['name']}: {candidate['score']}/100")

Environment Variables

Set these before using the SDK:

export HIRESQUIRE_API_TOKEN="your_api_token_here"
export HIRESQUIRE_BASE_URL="https://api.hiresquireai.com/api/v1"  # optional

LangChain Integration

from langchain.agents import AgentExecutor, create_openai_functions_agent
from langchain_openai import ChatOpenAI
from hiresquire import get_hiresquire_tools

llm = ChatOpenAI(temperature=0)
tools = get_hiresquire_tools()

agent = create_openai_functions_agent(llm, tools)
executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

# Use in an agent
result = executor.invoke({
    "input": "Submit a screening job for a Python developer and find candidates with score > 80"
})

Available Tools

Tool	Description
create_screening_job	Submit a new screening job
get_screening_status	Check job status
get_screening_results	Get completed job results
wait_for_screening_completion	Poll until job completes
generate_candidate_email	Generate outreach email
get_candidates_by_score	Filter candidates by score
compare_candidates	Compare candidates side-by-side
report_hiring_outcome	Report hiring outcome
test_webhook	Test a webhook endpoint
get_rate_limit	Check API rate limit status
whoami	Verify token and get profile info
get_credit_balance	Check current credit balance
estimate_screening_cost	Estimate cost for N candidates
list_credit_packs	List available credit packs
get_credit_transactions	View credit transaction history
enable_auto_reload	Enable automatic credit reloading
disable_auto_reload	Disable automatic credit reloading
list_calendar_connections	List connected calendar tools
create_calendar_connection	Connect Calendly or Cal.com
get_available_slots	Get available time slots
create_interview	Schedule an interview
generate_meeting_link	Generate Zoom/Meet links

API Documentation

Full API documentation available at: https://hiresquireai.com/docs/api

License

MIT License - see LICENSE file for details.