LangChain integration for the Progress Memory SDK
Project description
progress-memory-langchain
LangChain integration for the Progress Memory SDK.
Provides two integration tiers:
ProgressMemoryTools ⭐ recommended for production — exposes remember, recall, and forget as LLM-callable StructuredTool objects. The LLM decides when to invoke each one — token-efficient and semantically accurate.
ProgressMemoryLangChainMemory (quick start) — automatically recalls memories before every LLM call and saves each exchange after.
Quick start — Tools (production)
from progress_memory import ProgressMemoryClient, ProgressMemoryConfig
from progress_memory_langchain import ProgressMemoryTools
config = ProgressMemoryConfig.from_env()
client = ProgressMemoryClient(config)
tools_provider = ProgressMemoryTools(client=client, user_id="user-123", agent_id="bot")
tools = tools_provider.create_tools() # [remember, recall, forget]
Quick start — Automatic memory (demos)
from progress_memory_langchain import ProgressMemoryLangChainMemory
memory = ProgressMemoryLangChainMemory(
client=client, user_id="user-123", agent_id="bot", auto_remember=True
)
chain_with_memory = memory.wrap(chain)
response = chain_with_memory.invoke({"input": "What are my preferences?"})
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