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https://github.com/james-m-jordan/morphik-core.git
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63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
import os
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from dotenv import load_dotenv
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from morphik import Morphik
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# Load environment variables
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load_dotenv()
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# Connect to Morphik
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db = Morphik(os.getenv("MORPHIK_URI"), timeout=10000, is_local=True)
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# First, ensure we have some documents to work with
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sample_texts = [
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{
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"text": "AI technology is advancing rapidly with applications in healthcare. Machine learning models are being used to predict patient outcomes.",
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"metadata": {"category": "tech", "domain": "healthcare"},
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},
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{
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"text": "Cloud computing enables AI systems to scale. AWS, Azure, and Google Cloud provide infrastructure for machine learning.",
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"metadata": {"category": "tech", "domain": "cloud"},
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},
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{
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"text": "Electronic health records are being analyzed with natural language processing to improve diagnoses.",
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"metadata": {"category": "tech", "domain": "nlp"},
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},
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]
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# Ingest the documents
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doc_ids = []
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for item in sample_texts:
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doc = db.ingest_text(item["text"], metadata=item["metadata"])
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doc_ids.append(doc.external_id)
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print(f"Ingested document with ID: {doc.external_id}")
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# Create a knowledge graph from the documents
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print("Creating knowledge graph...")
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graph = db.create_graph(name="tech_healthcare_graph", filters={"category": "tech"})
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print(f"Created graph with name: {graph.name}")
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# Query using the knowledge graph
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response = db.query(
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"How is AI technology being used in healthcare?",
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graph_name="tech_healthcare_graph",
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hop_depth=2, # Consider connections up to 2 hops away
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)
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print("Graph-enhanced query response:")
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print(response.completion)
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# Example of using a graph with path information
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response_with_paths = db.query(
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"What technologies are used for analyzing electronic health records?",
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graph_name="tech_healthcare_graph",
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hop_depth=2,
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include_paths=True,
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)
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# If path information is included, it will be in the response metadata
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if response_with_paths.metadata and "graph" in response_with_paths.metadata:
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print("\nGraph paths found:")
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for path in response_with_paths.metadata["graph"]["paths"]:
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print(" -> ".join(path))
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