Python SDK

pip install memorymachines

from memorymachines import MemoryMachines

mm = MemoryMachines(api_key="YOUR_API_KEY")

# Upload a document
mm.memorize("meeting-notes.txt")

# Ask a question
response = mm.ask("What were the action items?")
print(response)

# From file path
result = mm.memorize("notes.txt")

# With metadata
result = mm.memorize(
    "notes.txt",
    user_name="Alice",
    source_type="text",
    item_id="custom-id-123"
)

response = mm.ask("What did we discuss in the last meeting?")
print(response)
# "Based on your meeting notes from January 15th, you discussed..."

memories = mm.recall("meeting")

for memory in memories:
    print(memory.narrative)
    print(memory.participants)
    print(memory.when)

mm.feedback(
    memory_id="abc123_memory_0",
    query="action items",
    rating=1  # 1 = relevant, -1 = not relevant
)

status = mm.health()
print(status)  # {"status": "healthy", "message": "..."}

from memorymachines import MemoryMachines, MemoryMachinesError

mm = MemoryMachines(api_key="YOUR_API_KEY")

try:
    mm.memorize("document.txt")
except MemoryMachinesError as e:
    print(f"Error: {e}")

from memorymachines import MemoryMachines

mm = MemoryMachines()

# Upload meeting notes
result = mm.memorize(
    "meeting-notes.txt",
    user_name="Alice",
    source_type="notes"
)
print(f"Uploaded: {result['item_id']}")

# Wait for processing (10-15 seconds)
import time
time.sleep(15)

# Ask questions
answer = mm.ask("What are my action items?")
print(answer)

# Get raw memories
memories = mm.recall("meeting")
for m in memories:
    print(f"- {m.narrative}")

# Provide feedback
if memories:
    mm.feedback(
        memory_id=memories[0].custom_id,
        query="meeting",
        rating=1
    )