memorydb-langchain
LangChain chat message history backed by MemoryDB, so agent conversations survive process restarts and stay searchable alongside the facts you ingest from them.
pip install memorydb-langchain
export MEMORYDB_URL=memorydb://TOKEN@127.0.0.1:8080
from memorydb import MemoryDB
from memorydb_langchain import MemoryDBChatMessageHistory
from langchain_core.messages import HumanMessage, AIMessage
history = MemoryDBChatMessageHistory(session_id="user-42", client=MemoryDB())
history.add_message(HumanMessage("What is the capital of Rajasthan?"))
history.add_message(AIMessage("Jaipur."))
history.messages # [HumanMessage, AIMessage]
history.clear()
Every append writes a new immutable revision of one record rather than rewriting a table, so the server keeps the full trail:
db = MemoryDB()
db.objects.history(pk=history.record_id)["results"] # versions 1..n, a free audit log
Use one principal (token) per deployed product so sessions of different products land in
different workspaces, and give each end-user their own session_id. Search the whole history
with db.objects.search("Jaipur"), including hybrid BM25 + vector ranking.
1 maintainer
Metadata
1 maintainer
Release files for memorydb-langchain 0.2.1
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| File | Size | Uploaded | Provenance | Actions |
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