pip install cerebe

from cerebe import Cerebe

client = Cerebe(api_key="ck_live_...")

# Store a memory
client.memory.add(
    "User prefers visual explanations",
    "session_abc",
    type="semantic",
    importance=0.8,
)

# Search memories
results = client.memory.search("What does the user prefer?", "session_abc")

from cerebe import AsyncCerebe

async with AsyncCerebe(api_key="ck_live_...") as client:
    results = await client.memory.search(
        "user preferences",
        "session_abc",
    )
    # Client automatically closed on exit

client.memory          # Memory operations (add, search, harvest, consolidate)
client.knowledge       # Knowledge graph (ingest, query, entities, visualize)
client.rag             # Retrieval-Augmented Generation (embed, search, stats)
client.storage         # File storage (upload, presigned URLs, extract)
client.meta_learning   # PLRE state, learning pattern analysis
client.agents          # Agent trace ingestion, working memory
client.sessions        # Session management, cognitive state
client.graph           # Graph traversal, temporal views

# Embed a document
with open("docs/auth.md") as f:
    client.rag.embed(source="docs/auth.md", content=f.read())

# Semantic search — returns top-k chunks ranked by similarity
results = client.rag.search("how does authentication work?", k=3)
for r in results.data["results"]:
    print(r["source"], r["score"])

from cerebe import Cerebe
from cerebe._errors import AuthenticationError, RateLimitError, NotFoundError

try:
    result = client.memory.search("query", "sess_1")
except AuthenticationError:
    print("Invalid API key")
except RateLimitError as e:
    print(f"Rate limited. Retry after {e.retry_after}s")
except NotFoundError:
    print("Resource not found")

# Ingest execution traces
client.agents.ingest_trace(
    "Called search tool with query 'quadratic formula'",
    "sess_123",
    metadata={"tool": "search", "latency_ms": 120},
)

# Set working memory with TTL
client.agents.set_working_memory(
    "Current task: algebra homework",
    "sess_123",
    ttl_seconds=3600,
)