Zep — 内置会话摘要与混合检索的 LLM 记忆服务

Quick Start — Python SDK

The key API is memory.get(session_id).context — it returns a single pre-formatted string containing the running summary, extracted user facts, and the last N messages. Drop it into your system prompt and the rest of your LLM code stays unchanged.

# pip install zep-python openai
from zep_python.client import Zep
from openai import OpenAI

zep = Zep(api_key="z_...")  # or base_url="http://localhost:8000" for self-host
oai = OpenAI()

user_id, session_id = "william", "s_2026_04_14"
zep.user.add(user_id=user_id, email="william@example.com")
zep.memory.add_session(session_id=session_id, user_id=user_id)

def chat(message: str) -> str:
    zep.memory.add(session_id=session_id,
                   messages=[{"role": "user", "content": message}])

    # Zep returns pre-formatted context: summary + facts + recent messages
    ctx = zep.memory.get(session_id=session_id).context

    resp = oai.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "system", "content": ctx},
            {"role": "user", "content": message},
        ],
    )
    answer = resp.choices[0].message.content

    zep.memory.add(session_id=session_id,
                   messages=[{"role": "assistant", "content": answer}])
    return answer

print(chat("I'm planning a trip to Tokyo in May"))
print(chat("What should I pack for that trip?"))

核心能力

对比

实际用例

价格与许可

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