langgraph-store-pixeltable 0.1.0

LangGraph BaseStore backend for Pixeltable — persistent, versioned, multimodal agent memory.

langgraph-store-pixeltable

LangGraph BaseStore backend for Pixeltable — persistent, versioned, multimodal agent memory.

Why Pixeltable for LangGraph Memory?

Feature	PostgresStore	PixeltableStore
Persistence	Yes	Yes + versioned
Vector search	pgvector only	Any embedding model
Multimodal values	JSON only	Image, Video, Audio via .table
Incremental embedding	Manual	Automatic via computed columns
History	No	Full version history per row
Computed columns	No	Arbitrary UDFs with lineage
External service	Requires PostgreSQL + pgvector	Embedded, no Docker

Installation

pip install langgraph-store-pixeltable

Quick Start

from langgraph.store.pixeltable import PixeltableStore

store = PixeltableStore(table_name="agent_memory.items")
store.setup()

# Store a memory
store.put(("users", "alice"), "prefs", {"color": "blue", "language": "Python"})

# Retrieve it
item = store.get(("users", "alice"), "prefs")
print(item.value)  # {"color": "blue", "language": "Python"}

# Search within a namespace
results = store.search(("users",), filter={"color": "blue"})

# List namespaces
namespaces = store.list_namespaces(prefix=("users",))

Semantic Search

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("all-MiniLM-L6-v2")

store = PixeltableStore(
    table_name="agent_memory.semantic",
    index={
        "dims": 384,
        "embed": lambda texts: model.encode(texts).tolist(),
        "fields": ["text"],
    },
)
store.setup()

store.put(("docs",), "d1", {"text": "Pixeltable handles multimodal data"})
store.put(("docs",), "d2", {"text": "LangGraph builds stateful agents"})
store.put(("docs",), "d3", {"text": "Python is great for AI"})

results = store.search(("docs",), query="multimodal AI pipelines", limit=2)
for r in results:
    print(f"{r.key}: {r.value['text']} (score={r.score:.3f})")

With LangGraph Agents

from langgraph.prebuilt import create_react_agent
from langgraph.store.pixeltable import PixeltableStore

store = PixeltableStore(table_name="agent_memory.items")
store.setup()

agent = create_react_agent(model, tools=tools, store=store)

.table Escape Hatch

Access the raw Pixeltable table for computed columns, UDFs, and multimodal lineage:

import pixeltable as pxt

t = store.table  # the underlying Pixeltable table
t.add_computed_column(value_length=t.value['text'].apply(len), if_exists='ignore')
rows = t.select(t.key, t.value, t.value_length).collect()

License

Apache 2.0