Python SDK#

pip install relata-sdk

from relata import RelataClient
 
with RelataClient("http://localhost:9090", purpose="analytics") as client:
    client.query("INSERT INTO Person (_pk, name, email) VALUES ('p1', 'Alice', 'a@x.com')")
    for row in client.query("SELECT * FROM Person LIMIT 5"):
        print(row["name"], row["email"])

from relata import select
 
result = (select("*").from_("Person")
          .where("age > $1").where_param("age > $1", 25)
          .order_by("name").limit(10)
          .purpose("analytics").execute())

from relata import (
    GovernanceClient, IdentityClient, ObjectClient, IngestClient,
    VectorClient, SearchClient, StreamingClient, AuditClient,
    TenantAdminClient, BackupClient, TokenClient, LogClient,
    SystemClient, A2AClient, McpClient, Namespace,
)

vc = client.vector_client          # or: VectorClient.from_client(client)
 
# Pure KNN over a named slot
vc.knn_search("Document", "embedding", [0.1, ...], k=10, ef_search=200)
 
# Hybrid: BM25 + vector + graph, RRF-fused
vc.hybrid_search("Document", query_text="graph retrieval", k=10,
                 rerank=True, weights=[0.2, 0.5, 0.3])
 
# Embedding (6 modalities) — uses server's CPU lexical default or GPU sidecar
emb = vc.embed("Alice Smith")            # → {embedding, model, dim}
vc.embed_image(base64_bytes)             # CLIP
vc.embed_face(base64_bytes)              # ArcFace
vc.embed_audio(base64_bytes)             # CLAP
vc.embed_video(base64_bytes)             # CLIP keyframe

client.graph_pagerank("Person", damping=0.85, max_iter=20)
client.graph_shortest_path("alice-id", "bob-id", max_hops=5)
client.graph_community("Person")
 
# Financial intelligence
client.sanctions_screen("Acme Holdings", threshold=0.85)
client.beneficial_ownership_chain("Acme Holdings", max_depth=6)
client.crypto_trace("0xabc...", purpose="compliance")
 
# Maritime
client.vessel_track(mmsi=123456789, window_secs=86400)
client.dark_fleet_detect(max_gap_hours=48)

from relata import Memory
 
mem = Memory("http://localhost:9090", bearer_token="<token>", purpose="agent")
mid = mem.add("Alice prefers dark mode", confidence=0.9, memory_class="semantic")
 
# retrieval-quality operators — tune what comes back
results = mem.search(
    "ui preferences", top_k=10,
    min_confidence=0.6,            # CONFIDENCE floor
    recency_half_life_secs=259200,  # 3-day decay  (RECENCY)
    budget_tokens=1500,            # hard prompt budget  (BUDGET)
    cancel_threshold=0.92,         # stop on a great match  (CANCEL_WHEN)
)
detail = mem.search_detailed(...)  # exposes recall_cost_tokens + cancelled

# Auto-detect which framework is installed and return the right adapter
from relata_adapters.registry import get_memory_adapter
Adapter = get_memory_adapter()   # LangChain/LlamaIndex/CrewAI/... or None
mem = Adapter(relata_memory_backend) if Adapter else None

client = RelataClient(
    "http://localhost:9090",
    bearer_token="<token>",
    purpose="analytics",
    tenant="org-acme",          # X-Relata-Tenant-Id on every request
    acting_as="user-42",        # X-Acting-As (delegation)
    delegated_by="admin-1",     # X-Delegated-By
    timeout=30.0,
    max_retries=3,
    admin_base_url="http://admin.internal:9090",  # /admin/* + /platform/* zero-trust split
)

RELATA_TOKEN=secret python -m examples.basic_query        # minimal connect + SELECT
RELATA_TOKEN=secret python -m examples.ingest             # bulk + CSV ingest
RELATA_TOKEN=secret python -m examples.advanced_query     # filter + aggregate + Arrow
RELATA_TOKEN=secret python -m examples.governance         # PURPOSE + audit + types
RELATA_TOKEN=secret python -m examples.memory_quickstart  # add / search / forget
RELATA_TOKEN=secret python -m examples.multi_tenant       # org isolation
RELATA_TOKEN=secret python -m examples.intelligence       # sanctions / UBO / crypto / convoy / DNS
RELATA_TOKEN=secret python -m examples.face_search        # FACE_SEARCH operator
RELATA_TOKEN=secret python -m examples.streaming          # SSE watch + transparency log
RELATA_TOKEN=secret python -m examples.a2a                # agent-to-agent + checkpoints
RELATA_TOKEN=secret python -m examples.bitemporal         # AS OF + WITH PROVENANCE