feat: HTTP-proxy LangGraph checkpointer

[danielmillerp]

What this does

This PR replaces LangGraph's direct-Postgres checkpointer with an HTTP-proxy checkpointer that routes all checkpoint operations through the agentex backend API.

Why

LangGraph agents need to persist state (checkpoints) between messages. The built-in approach (AsyncPostgresSaver) has each agent pod open its own Postgres connection pool. This doesn't scale — more agent pods means more connections, and we'd hit limits as we grow LangGraph usage. This is the same problem we already solved for Temporal: agents shouldn't talk to the DB directly. Instead, they go through the backend API, which manages a shared connection pool.

How it works

We implemented LangGraph's BaseCheckpointSaver abstract class — the same interface that AsyncPostgresSaver implements — but instead of running SQL queries, each method makes an HTTP POST to the backend:

BaseCheckpointSaver method	Backend endpoint called
aget_tuple()	POST /checkpoints/get-tuple
aput()	POST /checkpoints/put
aput_writes()	POST /checkpoints/put-writes
alist()	POST /checkpoints/list
adelete_thread()	POST /checkpoints/delete-thread

The HttpCheckpointSaver uses the existing AsyncAgentex httpx client (with EnvAuth for the agent API key), so authentication works the same way as every other SDK→backend call.

Serialization stays in the SDK — complex Python objects are serialized via LangGraph's serde, then base64-encoded for JSON transport. The backend just stores and retrieves the raw data.

What changed

• New: HttpCheckpointSaver class — the HTTP-proxy checkpointer implementation
• New: create_checkpointer() factory — returns an HttpCheckpointSaver wired up with the SDK client
• Removed: langgraph-checkpoint-postgres and psycopg[binary] dependencies (no longer needed)
• Added: langgraph-checkpoint (base types only — BaseCheckpointSaver, CheckpointTuple, etc.)

Impact on agents

Zero code changes. The create_checkpointer() API is unchanged — agents just call it and get back a checkpointer. The only difference is they no longer need DATABASE_URL in their environment.

Companion PR

• Backend (scale-agentex): feat: HTTP-proxy LangGraph checkpoint API scale-agentex#146 — adds the /checkpoints endpoints, ORM models, migration, repository with 19 integration tests

Test plan

• Pyright strict mode passes (0 errors)
• Ruff lint + format passes
• Manually tested end-to-end with langgraph agent: sent messages, confirmed checkpoints stored and conversation history restored across messages

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