Registry / llm-agents / ag-ui-langgraph

ag-ui-langgraph

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library0.0.41pypypiunverified

ag-ui-langgraph is a Python library that provides a comprehensive integration of the Agent User Interaction (AG-UI) protocol with LangGraph. It enables standardized, event-driven communication between frontend applications and LangGraph-powered AI agents, facilitating real-time streaming interactions and state synchronization. The current version is 0.0.33 and it appears to have a relatively active release cadence with frequent updates to align with LangChain/LangGraph developments.

pip install ag-ui-langgraph
INSTALL
IMPORT
SIG · AG-UI-LANGGRAPH
A
ag-ui-langgraph
llm-agentspythonv0.0.41
Install
7.3s avg
Import
Disk
77MB
Pass rate
8/ 10
Env Coverage8 / 10
glibc
3.93.13
musl
3.93.13
Install & Compatibility
Where this runs
tested against v0.0.41 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
musl
glibc
py 3.10
✓ —
✓ 9.03s
py 3.11
✓ —
✓ 7.6s
py 3.12
✓ —
✓ 6.23s
py 3.13
✓ —
✓ 6.28s
py 3.9
✕ build_error
✕ build_error
77MB installed
● package 77MB
Code
Verified usage

Verified import paths — ran on the pinned version, not inferred.

LangGraphAgent
from ag_ui_langgraph import LangGraphAgent
from ag_ui_langgraph import LangGraphAgent

This quickstart demonstrates how to expose a simple LangGraph agent as a FastAPI endpoint using `ag-ui-langgraph`. It defines a basic `StateGraph` with a single node that calls an OpenAI model, then integrates it into a FastAPI application, ready to serve AG-UI compatible requests.

import os from fastapi import FastAPI from langgraph.graph import StateGraph, MessagesState from langchain_openai import ChatOpenAI from langchain_core.messages import HumanMessage, AIMessage from ag_ui_langgraph import add_langgraph_fastapi_endpoint # Ensure OPENAI_API_KEY is set in your environment os.environ['OPENAI_API_KEY'] = os.environ.get('OPENAI_API_KEY', 'your_openai_api_key_here') # Define your LangGraph workflow class AgentState(MessagesState): pass def call_model(state): messages = state['messages'] model = ChatOpenAI(model="gpt-4o-mini") # Using a cost-effective model for quickstart response = model.invoke(messages) return {"messages": [response]} workflow = StateGraph(AgentState) workflow.add_node("oracle", call_model) workflow.set_entry_point("oracle") workflow.set_finish_point("oracle") graph = workflow.compile() # Create a FastAPI app app = FastAPI() # Integrate LangGraph with FastAPI using ag-ui-langgraph # The endpoint will be available at /agent add_langgraph_fastapi_endpoint(app, graph, "/agent") # To run this: # 1. Save as, e.g., main.py # 2. pip install 'fastapi[all]' uvicorn ag-ui-langgraph langchain-openai langgraph # 3. uvicorn main:app --reload --port 8000 # 4. Access http://localhost:8000/agent with a compatible AG-UI frontend # or use curl: # curl -X POST "http://localhost:8000/agent" \ # -H "Content-Type: application/json" \ # -d '{ "thread_id": "test_thread_123", "messages": [{ "role": "user", "content": "Hello!" }] }'
Debug
Known issues
gotchaThe `ag-ui-langgraph` adapter has been observed to throw warnings related to deprecated functions from `Pydantic` and `LangGraph` versions. While not always breaking, this can create noise in logs.
fix
Monitor official GitHub for updates. Consider patching locally or downgrading `pydantic` if warnings are disruptive and do not indicate a critical issue. Keep `langchain-core` updated to v1.x or higher as recommended by `langsmith` security patches.
affects: All versions, particularly when `langchain-core` or `pydantic` update their APIs.
breakingConcurrent requests to an endpoint created with `add_langgraph_fastapi_endpoint` can lead to state corruption. This is due to `LangGraphAgent` storing per-request state in a shared `self.active_run` instance variable, leading to interleaving and corrupted state when multiple requests hit the same singleton agent instance.
fix
Implement a factory pattern where `add_langgraph_fastapi_endpoint` accepts a function that returns a *fresh* agent instance for each request, rather than a shared singleton. Alternatively, refactor the `LangGraphAgent` to pass `active_run` as a local variable or via `contextvars` for true thread-safety.
affects: All versions up to 0.0.25 (and likely current versions if not addressed).
gotchaWhen one LangGraph agent calls another as a tool (agent-to-agent communication), the `ToolMessage.name` can be `None`, causing a `Pydantic validation error` in `ToolCallStartEvent` and crashing the Server-Sent Events (SSE) stream.
fix
Apply a fallback when retrieving `tool_call_name`, using `tool_msg.name or event.get("name", "")` to ensure a valid string is always provided to `ToolCallStartEvent`.
affects: Versions up to 0.0.25 (and potentially later if not patched).
breakingOlder versions of `ag-ui-langgraph` might depend on `@langchain/core ^0.3.80`, which transitively pulls in `langsmith < 0.4.6`. This older `langsmith` version is affected by `CVE-2026-25528` (SSRF via tracing header injection).
fix
Update `ag-ui-langgraph` and related `langchain` packages to use `@langchain/core ^1.1.0` or higher, which requires `langsmith >= 0.5.0`. This may require manually overriding package manager dependencies if the direct dependency is not updated.
affects: Versions depending on `langchain-core` 0.3.x.
Upgrade
Version history
0.0.41latest on PyPI · released Jun 9, 2026
Audit
Dependencies
langgraphrequiredCore dependency for defining agent workflows.
langchain-corerequiredFoundational LangChain components.
langchainrequiredUsed for various LangChain utilities and integrations.
pydanticrequiredData validation and settings management, with some noted deprecation warnings.
ag-ui-protocolrequiredDefines the core AG-UI event types and structures.
Agent activity
72 hits · last 30 days
node
66
OpenAI (training)
1
Resources
ag-ui-langgraph — pip install ag-ui-langgraph · libregistry