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Installation

pip install agentset

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Basic Usage

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Creating an Ingest Job

Here’s how you can use the Agentset Python SDK to create an ingest job: 
import os
from agentset import Agentset

a = Agentset(
  namespace_id="ns_123",
  token=os.environ['AGENTSET_API_KEY'],
)

res = a.ingest_jobs.create(
  payload={
    "type": "FILE",
    "fileUrl": "https://example.com/annual-report-2024.pdf",
    "name": "Annual Report 2024",
  },
  config={
    "metadata": {
      "documentType": "financial",
      "year": 2024,
    },
  },
)

print(f"Job created with ID: {res.data.id}")
Ingest jobs are processed asynchronously. After creating a job, you’ll need to check its status to know when processing is complete.

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Checking Job Status

Since ingestion is asynchronous, you can check the status of your job: 
import time

# Get the job status
job = a.ingest_jobs.get(res.data.id)
print(f"Job status: {job.data.status}")

# Poll for completion
while job.data.status not in ["COMPLETED", "FAILED"]:
    time.sleep(10)  # Wait 10 seconds before checking again
    job = a.ingest_jobs.get(res.data.id)
    print(f"Job status: {job.data.status}")

if job.data.status == "COMPLETED":
    print("Job completed successfully!")
elif job.data.status == "FAILED":
    print(f"Job failed: {job.error}")

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Searching Documents

Once your documents are ingested, you can search through them: 
# Perform a search
search_results = a.search.execute(
  query="financial performance Q4 2024",
  top_k=20,
  rerank=True,
  rerank_limit=10,
  include_metadata=True,
  filters={
    "$or": [
      {"documentType": "financial"},
      {"year": {"$gte": 2024}}
    ]
  }
)

# Process results
for result in search_results.data:
    print(f"Score: {result.score}")
    print(f"Content: {result.text}")
    print(f"Metadata: {result.metadata}")
    print("---")

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Additional Resources

PyPI Package

Download and install the Agentset Python SDK on PyPI

SDK Reference

View the complete SDK reference documentation

Source Code

View the complete source code for the Agentset Python SDK