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Knowledge Graph Extraction¶

Extract knowledge graphs from LLM outputs.

Workflow¶

1. Generate Text (GPU 0)¶

from llcuda.api import LlamaCppClient

client = LlamaCppClient()
response = client.chat.completions.create(
    messages=[{
        "role": "user",
        "content": "Extract entities and relationships from: ..."
    }]
)

text = response.choices[0].message.content

2. Parse Entities¶

import json

# Parse LLM output
data = json.loads(text)
entities = data['entities']
relationships = data['relationships']

3. Build Graph (GPU 1)¶

import cudf

nodes_df = cudf.DataFrame(entities)
edges_df = cudf.DataFrame(relationships)

4. Visualize (GPU 1)¶

import graphistry

g = graphistry.edges(edges_df).nodes(nodes_df)
g.plot()

Use Cases¶

Document analysis
Semantic networks
Entity relationship mapping
Knowledge base visualization