Python SDK

Installation

pip install memoid

Quick Start

from memoid import MemoryClient

client = MemoryClient("your-api-key")

# Add a memory
client.add(
    messages=[
        {"role": "user", "content": "I love hiking and Italian food"},
        {"role": "assistant", "content": "Great! I'll remember that."}
    ],
    user_id="user_123"
)

# Search memories
results = client.search("What food does the user like?", user_id="user_123")

# Recall context (memories + graph in one call)
context = client.recall("Tell me about the user", user_id="user_123", include_graph=True)

Configuration

client = MemoryClient(
    api_key="your-api-key",
    base_url="https://api.memoid.dev"  # default
)

Memories

Add Memories

result = client.add(
    messages=[
        {"role": "user", "content": "My manager Sarah works at TechCorp"}
    ],
    user_id="user_123",
    project_id="proj_abc",
    metadata={"source": "chat"},
    extract_graph=True
)

Get & List

memory = client.get("memory_id")
memories = client.get_all(user_id="user_123", limit=50)

Update & Delete

client.update("memory_id", "Updated text")
client.delete("memory_id")
client.delete_all(user_id="user_123")

History

history = client.history("memory_id")

Search

results = client.search(
    "food preferences",
    user_id="user_123",
    limit=5,
    threshold=0.7
)

for r in results:
    print(f"{r['memory']} (score: {r['score']:.2f})")

Recall

Unified context retrieval for agents — memories + graph in one call.

context = client.recall(
    "What do I know about John?",
    user_id="user_123",
    include_graph=True,
    memory_limit=10
)

print(context["memories"])        # relevant memories
print(context["entities"])        # related graph entities
print(context["relationships"])   # entity relationships

User Context

Get all memories and graph data for a user — ideal for UI visualization.

context = client.get_user_context(user_id="user_123")

print(context["memories"])        # all memories
print(context["entities"])        # all graph entities
print(context["relationships"])   # all relationships
print(context["stats"])           # totals

Or via REST:

response = requests.get(
    "https://api.memoid.dev/v1/context",
    headers=headers,
    params={"user_id": "user_123"}
)
context = response.json()

Knowledge Graph

Extract Knowledge

result = client.extract_knowledge(
    "Sarah is the CEO of TechCorp. She founded it with Mike."
)
# result["entities"]: [{"name": "Sarah", "type": "person"}, ...]
# result["relationships"]: [{"subject": "Sarah", "predicate": "ceo_of", "object": "TechCorp"}, ...]

Add Entity & Relationship

client.add_entity("Acme Corp", "organization")
client.add_relationship("John", "person", "works_at", "Acme Corp", "organization")

Query & Search

related = client.graph_query("John", depth=2)
found = client.graph_search("tech companies")

Delete Entity

client.delete_entity("John")  # also removes relationships

REST API

All SDK methods map directly to REST endpoints. You can also use requests directly:

import requests

headers = {"Authorization": "Bearer YOUR_API_KEY"}

# Search
response = requests.post(
    "https://api.memoid.dev/v1/search",
    headers=headers,
    json={"query": "food preferences", "user_id": "user_123"}
)
results = response.json()["results"]

# Recall
response = requests.post(
    "https://api.memoid.dev/v1/recall",
    headers=headers,
    json={"query": "Tell me about John", "include_graph": True}
)
context = response.json()