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Hyper-Extract

Python Quickstart

yifanfeng97/hyper-extract

Python Quickstart¶

Get started with the Hyper-Extract Python SDK in 5 minutes.

Prerequisites¶

Python 3.11+
OpenAI API key

Installation¶

pip install hyperextract

Basic Usage¶

1. Configure API Key¶

import os
os.environ["OPENAI_API_KEY"] = "your-api-key"

Or use a .env file:

from dotenv import load_dotenv
load_dotenv()

2. Extract Knowledge¶

from hyperextract import Template

# Create a template
ka = Template.create("general/biography_graph", language="en")

# Your text
text = """
Marie Curie was a Polish-French physicist and chemist who conducted 
pioneering research on radioactivity. She was the first woman to win 
a Nobel Prize and the only person to win Nobel Prizes in two different 
scientific fields.
"""

# Extract
result = ka.parse(text)

# Access results
print(f"Nodes: {len(result.nodes)}")
print(f"Edges: {len(result.edges)}")

# Print first node
if result.nodes:
    node = result.nodes[0]
    print(f"\nFirst: {node.name} ({node.type})")
    print(f"Description: {node.description}")

Output:

Entities: 5
Relations: 4

First: Marie Curie (person)
Description: Polish-French physicist and chemist

3. Visualize¶

# Build index for search/chat capabilities
result.build_index()

# Open interactive visualization
result.show()

Interactive Visualization

4. Search¶

# Build search index
result.build_index()

# Search
results = result.search("Nobel Prize", top_k=3)
for item in results:
    print(item)

5. Chat¶

# Ask questions
response = result.chat("What did Marie Curie discover?")
print(response.content)

6. Save and Load¶

# Save to disk
result.dump("./curie_kb/")

# Load later
new_ka = Template.create("general/biography_graph", language="en")
new_ka.load("./curie_kb/")

Complete Example¶

"""Complete example: Extract, explore, and save knowledge."""

from dotenv import load_dotenv
load_dotenv()

from hyperextract import Template

def main():
    # Create template
    print("Creating template...")
    ka = Template.create("general/biography_graph", language="en")

    # Sample text
    text = """
    Ada Lovelace was an English mathematician and writer, chiefly known 
    for her work on Charles Babbage's early mechanical general-purpose 
    computer, the Analytical Engine. She is often regarded as the first 
    computer programmer.
    """

    # Extract knowledge
    print("Extracting knowledge...")
    result = ka.parse(text)

    # Display results
    print(f"\nExtraction Results:")
    print(f"  Nodes: {len(result.nodes)}")
    print(f"  Edges: {len(result.edges)}")

    # List nodes
    print("\nNodes found:")
    for node in result.nodes:
        print(f"  - {node.name} ({node.type})")

    # Build index and search
    print("\nBuilding search index...")
    result.build_index()

    search_nodes, search_edges = result.search("computer programming", top_k=2)
    print(f"\nSearch results: {len(search_nodes)} nodes, {len(search_edges)} edges")

    # Save
    print("\nSaving knowledge abstract...")
    result.dump("./ada_kb/")

    print("\nDone! Try: he show ./ada_kb/")

if __name__ == "__main__":
    main()

Next Steps¶