pip install httpx

import asyncio
import httpx

API_BASE = "http://localhost:8000"
TENANT_ID = "demo"
USER_ID = "user-1"

DOCUMENTS = [
    {
        "title": "Introduction to Machine Learning",
        "content_text": """
        Machine learning is a subset of artificial intelligence that enables 
        systems to learn and improve from experience. Dr. Andrew Ng from 
        Stanford University has been instrumental in popularizing ML.
        """,
        "content_type": "article",
        "source": "files",
    },
    {
        "title": "Natural Language Processing",
        "content_text": """
        NLP is a branch of AI that helps computers understand human language.
        Major breakthroughs include BERT from Google and GPT from OpenAI.
        """,
        "content_type": "article",
        "source": "files",
    },
]

async def ingest_documents():
    async with httpx.AsyncClient() as client:
        for doc in DOCUMENTS:
            response = await client.post(
                f"{API_BASE}/items",
                json={
                    "tenant_id": TENANT_ID,
                    "user_id": USER_ID,
                    **doc,
                },
            )
            print(f"Created: {response.json()['kos_id']}")

asyncio.run(ingest_documents())

# In another terminal
kos run-worker

async def search(query: str):
    async with httpx.AsyncClient() as client:
        response = await client.post(
            f"{API_BASE}/search",
            json={
                "tenant_id": TENANT_ID,
                "query": query,
                "facets_requested": ["source", "content_type"],
                "limit": 10,
            },
        )
        return response.json()

results = asyncio.run(search("machine learning"))

# Display results
print(f"Found {results['total']} results")
for hit in results["hits"]:
    print(f"\n{hit['title']} (score: {hit['score']:.2f})")
    if hit["highlights"]:
        print(f"  {hit['highlights'][0]}")

for facet in results["facets"]:
    print(f"\n{facet['field']}:")
    for bucket in facet["buckets"]:
        print(f"  {bucket['value']}: {bucket['count']}")

source:
  files: 2

content_type:
  article: 2

async def search_filtered(query: str, filters: dict):
    async with httpx.AsyncClient() as client:
        response = await client.post(
            f"{API_BASE}/search",
            json={
                "tenant_id": TENANT_ID,
                "query": query,
                "filters": filters,
                "limit": 10,
            },
        )
        return response.json()

# Only search in files
results = asyncio.run(search_filtered(
    "AI",
    {"source": "files"}
))

for entity in results.get("related_entities", []):
    print(f"- {entity['name']} ({entity['type']})")

- Andrew Ng (person)
- Stanford University (organization)
- Google (organization)
- OpenAI (organization)

import asyncio
import httpx

API_BASE = "http://localhost:8000"
TENANT_ID = "demo"

async def main():
    async with httpx.AsyncClient() as client:
        # Search
        response = await client.post(
            f"{API_BASE}/search",
            json={
                "tenant_id": TENANT_ID,
                "query": "machine learning",
                "facets_requested": ["source", "content_type"],
                "limit": 10,
            },
        )
        results = response.json()
        
        # Display
        print(f"=== Search Results ({results['total']} total) ===\n")
        
        for hit in results["hits"]:
            print(f"📄 {hit['title']}")
            print(f"   Score: {hit['score']:.2f}")
            if hit["highlights"]:
                print(f"   {hit['highlights'][0][:100]}...")
            print()
        
        print("=== Facets ===\n")
        for facet in results["facets"]:
            print(f"{facet['field']}:")
            for bucket in facet["buckets"]:
                print(f"  • {bucket['value']}: {bucket['count']}")
            print()
        
        if results.get("related_entities"):
            print("=== Related Entities ===\n")
            for entity in results["related_entities"]:
                print(f"  • {entity['name']} ({entity['type']})")

asyncio.run(main())