Use cases

NeoAthena transforms information retrieval across numerous domains:

1. Document Q&A Systems

Build sophisticated question-answering systems with minimal effort:

#Using the NeoAthena Python SDK for document Q&A
from neoathena import NeoAthenaClient
import langchain as lc

# Initialize NeoAthena client
client = NeoAthenaClient(api_key="your_api_key")

# Upload documents to a collection
client.upload_to_collection(
    collection_name="company_handbook",
    filepath="employee_handbook.pdf"
)
client.upload_to_collection(
    collection_name="company_handbook",
    filepath="onboarding_guide.pdf"
)
results = client.retrieve_from_collection(
        collection_name="company_handbook",
        query="What is our company's parental leave policy",
        top_k=4
    )

print(results)

2. Multimedia Knowledge Base

Effortlessly create a searchable archive of video meetings, presentations, and documents:

from neoathena import NeoAthenaClient

# Initialize client
client = NeoAthenaClient(api_key="your_api_key")

# Upload various media types to a collection
client.upload_to_collection(
    collection_name="team_meetings",
    filepath="quarterly_presentation.pdf"
)
client.upload_to_collection(
    collection_name="team_meetings",
    filepath="team_meeting_feb15.mp4"
)
client.upload_to_collection(
    collection_name="team_meetings",
    filepath="product_demo.mov"
)
client.upload_to_collection(
    collection_name="team_meetings",
    filepath="research_findings.jpg"
)

# Query across all media types with a single request
results = client.retrieve_from_collection(
    collection_name="team_meetings",
    query="What were the key points about the new feature launch?",
    top_k=5
)

print(results)

3. Data Extraction from Forms

Extract structured data from forms and documents for streamlined processing and automation:

from neoathena import NeoAthenaClient

# Initialize client
client = NeoAthenaClient(api_key="your_api_key")

# Upload invoice documents to a collection
client.upload_to_collection(
    collection_name="invoices",
    filepath="january_invoices.pdf"
)
client.upload_to_collection(
    collection_name="invoices",
    filepath="supplier_receipts.pdf"
)
client.upload_to_collection(
    collection_name="invoices",
    filepath="expense_reports.pdf"
)

# Extract specific structured data using natural language
results = client.retrieve_from_collection(
    collection_name="invoices",
    query="Extract the invoice number, date, total amount, and vendor name for january",
    top_k=5
)
print(results)