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from supermemory import Supermemory
client = Supermemory()
USER_ID = "dhravya"
conversation = [
{"role": "assistant", "content": "Hello, how are you doing?"},
{"role": "user", "content": "Hello! I am Dhravya. I am 20 years old. I love to code!"},
{"role": "user", "content": "Can I go to the club?"},
]
# Get user profile + relevant memories for context
profile = client.profile(container_tag=USER_ID, q=conversation[-1]["content"])
context = f"""Static profile:
{ "\n".join(profile.profile.static)}
Dynamic profile:
{"\n".join(profile.profile.dynamic)}
Relevant memories:
{"\n".join(r.content for r in profile.search_results.results)}"""
# Build messages with memory-enriched context
messages = [{"role": "system", "content": f"User context:\n{context}"}, *conversation]
# response = llm.chat(messages=messages)
# Store conversation for future context
client.add(
content="\n".join(f"{m['role']}: {m['content']}" for m in conversation),
container_tag=USER_ID,
)
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