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Examples

Examples

1. Raw Records to a Graph Target

from seocho import Seocho

client = Seocho(base_url="http://localhost:8001", workspace_id="default")

result = client.raw_ingest(
    [
        {"id": "doc-1", "content": "ACME acquired Beta in 2024."},
        {"id": "doc-2", "content": "Beta provides risk analytics to ACME."},
    ],
    target_database="accounts_graph",
)

print(result.status)

2. Semantic Query with Bounded Repair

semantic = client.semantic(
    "What is ACME related to?",
    databases=["accounts_graph"],
    reasoning_mode=True,
    repair_budget=2,
)

print(semantic.route)
print(semantic.response)
print(semantic.semantic_context["reasoning"])

3. Explicit Cross-Graph Comparison

advanced = client.advanced(
    "Compare what the baseline and finance graphs know about ACME.",
    graph_ids=["kgnormal", "kgfibo"],
)

print(advanced.debate_state)

4. Direct API Usage

curl -sS -X POST http://localhost:8001/platform/ingest/raw \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_id": "default",
    "target_database": "accounts_graph",
    "records": [
      {"id": "doc-1", "content": "ACME acquired Beta in 2024."}
    ]
  }'

curl -sS -X POST http://localhost:8001/run_agent_semantic \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_id": "default",
    "query": "What is ACME related to?",
    "databases": ["accounts_graph"],
    "reasoning_mode": true,
    "repair_budget": 2
  }'

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