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I_kwDOKFU0lc6rQUfH
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langgraph-checkpoint-postgres issue with version update
|
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
pip install -U langgraph-checkpoint-postgres
DB_URI ="" #Use an existing postgres checkpointer DB
from psycopg import Connection
from psycopg_pool import ConnectionPool
from psycopg.rows import dict_row
from langgraph.checkpoint.postgres import PostgresSaver
connection_kwargs ={
"autocommit": True,
"prepare_threshold": 0,
"row_factory": dict_row,
}
pool = ConnectionPool(
conninfo=DB_URI,
max_size=20,
kwargs=connection_kwargs
)
checkpointer = PostgresSaver(pool)
thread_id = "1"
config = {"configurable": {"thread_id": thread_id}}
checkpoint = checkpointer.get(config)
```
### Error Message and Stack Trace (if applicable)
```shell
/usr/local/lib/python3.11/dist-packages/langgraph/checkpoint/base/__init__.py in get(self, config)
234 Optional[Checkpoint]: The requested checkpoint, or None if not found.
235 """
--> 236 if value := self.get_tuple(config):
237 return value.checkpoint
238
/usr/local/lib/python3.11/dist-packages/langgraph/checkpoint/postgres/__init__.py in get_tuple(self, config)
218
219 with self._cursor() as cur:
--> 220 cur.execute(
221 self.SELECT_SQL + where,
222 args,
/usr/local/lib/python3.11/dist-packages/psycopg/cursor.py in execute(self, query, params, prepare, binary)
95 )
96 except e._NO_TRACEBACK as ex:
---> 97 raise ex.with_traceback(None)
98 return self
99
UndefinedColumn: column cw.task_path does not exist
LINE 27: ...array_agg(array[cw.type::bytea, cw.blob] order by cw.task_pa...
```
### Description
Faced the below issue with langgraph-checkpoint-postgres:
```error
UndefinedColumn: column cw.task_path does not exist
LINE 27: ...array_agg(array[cw.type::bytea, cw.blob] order by cw.task_pa...
```
Tried moving to an older version of langgraph-checkpoint-postgres (version - 2.0.8) and it is working fine.
**I.e. we are able to connect to the DB with langgraph-checkpoint-postgres == 2.0.8**
This is an issue with a recent upgrade to the library.
We have code running in production and will become a major problem for us.
### System Info
System Information
------------------
> OS: Linux
> OS Version: #1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
> Python Version: 3.11.11 (main, Dec 4 2024, 08:55:07) [GCC 11.4.0]
Package Information
-------------------
> langchain_core: 0.3.37
> langchain: 0.3.19
> langchain_community: 0.3.18
> langsmith: 0.3.8
> langchain_cli: 0.0.35
> langchain_openai: 0.3.6
> langchain_text_splitters: 0.3.6
> langgraph_sdk: 0.1.53
> langserve: 0.3.1
Other Dependencies
------------------
> aiohttp<4.0.0,>=3.8.3: Installed. No version info available.
> async-timeout<5.0.0,>=4.0.0;: Installed. No version info available.
> dataclasses-json<0.7,>=0.5.7: Installed. No version info available.
> fastapi: 0.115.8
> gitpython: 3.1.44
> gritql: 0.1.5
> httpx: 0.28.1
> httpx-sse<1.0.0,>=0.4.0: Installed. No version info available.
> jsonpatch<2.0,>=1.33: Installed. No version info available.
> langchain-anthropic;: Installed. No version info available.
> langchain-aws;: Installed. No version info available.
> langchain-cohere;: Installed. No version info available.
> langchain-community;: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.34: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.35: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.37: Installed. No version info available.
> langchain-deepseek;: Installed. No version info available.
> langchain-fireworks;: Installed. No version info available.
> langchain-google-genai;: Installed. No version info available.
> langchain-google-vertexai;: Installed. No version info available.
> langchain-groq;: Installed. No version info available.
> langchain-huggingface;: Installed. No version info available.
> langchain-mistralai;: Installed. No version info available.
> langchain-ollama;: Installed. No version info available.
> langchain-openai;: Installed. No version info available.
> langchain-text-splitters<1.0.0,>=0.3.6: Installed. No version info available.
> langchain-together;: Installed. No version info available.
> langchain-xai;: Installed. No version info available.
> langchain<1.0.0,>=0.3.19: Installed. No version info available.
> langserve[all]: Installed. No version info available.
> langsmith-pyo3: Installed. No version info available.
> langsmith<0.4,>=0.1.125: Installed. No version info available.
> langsmith<0.4,>=0.1.17: Installed. No version info available.
> numpy<2,>=1.26.4;: Installed. No version info available.
> numpy<3,>=1.26.2;: Installed. No version info available.
> openai<2.0.0,>=1.58.1: Installed. No version info available.
> orjson: 3.10.15
> packaging<25,>=23.2: Installed. No version info available.
> pydantic: 2.10.6
> pydantic-settings<3.0.0,>=2.4.0: Installed. No version info available.
> pydantic<3.0.0,>=2.5.2;: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4;: Installed. No version info available.
> pytest: 8.3.4
> PyYAML>=5.3: Installed. No version info available.
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> requests<3,>=2: Installed. No version info available.
> rich: 13.9.4
> SQLAlchemy<3,>=1.4: Installed. No version info available.
> sse-starlette: 1.8.2
> tenacity!=8.4.0,<10,>=8.1.0: Installed. No version info available.
> tenacity!=8.4.0,<10.0.0,>=8.1.0: Installed. No version info available.
> tiktoken<1,>=0.7: Installed. No version info available.
> tomlkit: 0.13.2
> typer[all]: Installed. No version info available.
> typing-extensions>=4.7: Installed. No version info available.
> uvicorn: 0.34.0
> zstandard: 0.23.0
| null |
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I_kwDOKFU0lc6rPGyG
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Tavily Search Error with async/await in LangGraph
|
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| 2025-02-23T02:19:28
| 2025-02-23T13:35:14
| 2025-02-23T13:35:13
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NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
import os
import asyncio
from typing import Annotated
from typing_extensions import TypedDict
from langchain_anthropic import ChatAnthropic
from langchain_core.messages import HumanMessage, SystemMessage, AnyMessage
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
from langgraph.prebuilt import ToolNode, tools_condition
from langchain_community.tools import SearchAPIResults
from langchain_community.tools import TavilySearchResults
from langchain_openai import ChatOpenAI
os.environ['TAVILY_API_KEY'] = 'tvly-xxx'
class State(TypedDict):
messages: Annotated[list, add_messages]
llm = ChatOpenAI(model="gpt-4o-mini")
tool = TavilySearchResults(max_results=1, include_answer=False, include_raw_content=False)
#tool = SearchAPIResults(engine="google")
tools = [tool]
# 系统提示词
system_prompt = """You are a helpful assistant."""
#system_prompt = "你是小明。如果有用户问你是谁就回答：小明"
llm_with_tools = llm.bind_tools(tools)
async def chatbot(state: State):
response = await llm_with_tools.ainvoke(state["messages"])
return {"messages": [response]}
graph_builder = StateGraph(State)
graph_builder.add_node("chatbot", chatbot)
tool_node = ToolNode(tools=[tool])
graph_builder.add_node("tools", tool_node)
graph_builder.add_conditional_edges(
"chatbot",
tools_condition,
)
graph_builder.add_edge("tools", "chatbot")
graph_builder.add_edge(START, "chatbot")
searchbot_graph = graph_builder.compile()
user_input = "what is langgraph"
# 创建初始消息列表,包含系统提示和用户输入
initial_messages = [
SystemMessage(content=system_prompt),
HumanMessage(content=user_input)
]
async def main():
# 使用包含系统提示的消息列表
async for chunk in searchbot_graph.astream(
input={"messages": initial_messages},
stream_mode="messages"
):
print(chunk)
print("\n\n")
if __name__ == "__main__":
asyncio.run(main())
```
### Error Message and Stack Trace (if applicable)
```shell
(ToolMessage(content="ClientConnectorCertificateError(ConnectionKey(host='api.tavily.com', port=443, is_ssl=True, ssl=True, proxy=None, proxy_auth=None, proxy_headers_hash=None), SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1000)'))", name='tavily_search_results_json', id='e76f58ec-4299-4adb-9488-c6e03804fe59', tool_call_id='call_Mqle439YOLwiLT3i9TzwQhy8', artifact={}), {'langgraph_step': 2, 'langgraph_node': 'tools', 'langgraph_triggers': ['branch:chatbot:tools_condition:tools'], 'langgraph_path': ('__pregel_pull', 'tools'), 'langgraph_checkpoint_ns': 'tools:2743d809-8b93-3c97-bdb2-11d04607977d'})
```
### Description
When using LangGraph with async/await pattern and Tavily Search tool, the code fails with an SSL certificate verification error. However, the same code works fine when not using async implementation.
### System Info
Langgraph Version：0.2.69
langchain-community：0.3.17
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graph restart bug
|
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
def _init_graph(self)->CompiledStateGraph:
graph_builder = StateGraph(MessagesState)
tool_node = ToolNode(tools=self.tools)
graph_builder.add_node("reply", _reply)
graph_builder.add_node("route", _route)
graph_builder.add_node("complete", _complete)
graph_builder.add_node("approve", _approve)
graph_builder.add_node("tools", tool_node)
graph_builder.add_edge(START, "reply")
graph_builder.add_edge("reply", "route")
graph_builder.add_edge("complete", "reply")
graph_builder.add_edge("tools", "reply")
graph = graph_builder.compile(checkpointer=self.checkpointer,interrupt_before=["complete","approve"])
print(f"==========PreBookConsultant Graph==========")
graph.get_graph().print_ascii()
return graph
def _route(self,state: MessagesState) -> Command[Literal["complete", "approve", "tools", "__end__"]]:
......
if valid_messages:
return Command(
update={"messages": [AIMessage(content="\n".join(valid_messages),name=self.__class__.__name__)]},
goto="complete"
)
elif inquiry_messages:
self.cache_message = last_message
return Command(
update={"messages": [AIMessage(content="\n".join(inquiry_messages),name=self.__class__.__name__)]},
goto="approve"
)
else:
return Command(
goto="tools"
)
def _complete(self,state: MessagesState) -> MessagesState:
return state
else:
return Command(
goto=END
)
```
### Error Message and Stack Trace (if applicable)
```shell
```
### Description
I designed a graph,and set interrupt_before=["complete"],when "_route" node finished，the graph is interrupted and the "snapshot.next" is "complete" indeed,then I use "graph.invoke(input=None,config=config)" to restart the graph,but the graph not enter into the "complete" node, it finished directly
### System Info
System Information
------------------
> OS: Windows
> OS Version: 10.0.26100
> Python Version: 3.11.11 | packaged by Anaconda, Inc. | (main, Dec 11 2024, 16:34:19) [MSC v.1929 64 bit (AMD64)]
Package Information
-------------------
> langchain_core: 0.3.31
> langchain: 0.3.15
> langchain_community: 0.3.15
> langsmith: 0.2.11
> langchain_experimental: 0.3.4
> langchain_milvus: 0.1.8
> langchain_openai: 0.3.1
> langchain_text_splitters: 0.3.5
> langgraph_sdk: 0.1.53
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.11
> async-timeout: 4.0.3
> dataclasses-json: 0.6.7
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> langsmith-pyo3: Installed. No version info available.
> numpy: 1.26.4
> openai: 1.59.8
> orjson: 3.10.15
> packaging: 24.2
> pydantic: 2.10.5
> pydantic-settings: 2.7.1
> pymilvus: 2.5.4
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.37
> tenacity: 9.0.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> zstandard: Installed. No version info available.
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| 2,867,286,088
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I_kwDOKFU0lc6q51BI
| 3,538
|
ToolNode not working. TypeError: Tool search returned unexpected type: <class 'str'>
|
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| 2025-02-20T21:15:02
| 2025-02-21T03:26:02
| 2025-02-21T03:14:03
|
NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
from typing import Literal
from langchain_anthropic import ChatAnthropic
from langchain_core.tools import tool
from langgraph.checkpoint.memory import MemorySaver
from langgraph.graph import END, START, StateGraph, MessagesState
from langgraph.prebuilt import ToolNode
# Define the tools for the agent to use
@tool
def search(query: str):
"""Call to surf the web."""
# This is a placeholder, but don't tell the LLM that...
if "sf" in query.lower() or "san francisco" in query.lower():
return "It's 60 degrees and foggy."
return "It's 90 degrees and sunny."
tools = [search]
tool_node = ToolNode(tools)
model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0).bind_tools(tools)
# Define the function that determines whether to continue or not
def should_continue(state: MessagesState) -> Literal["tools", END]:
messages = state['messages']
last_message = messages[-1]
# If the LLM makes a tool call, then we route to the "tools" node
if last_message.tool_calls:
return "tools"
# Otherwise, we stop (reply to the user)
return END
# Define the function that calls the model
def call_model(state: MessagesState):
messages = state['messages']
response = model.invoke(messages)
# We return a list, because this will get added to the existing list
return {"messages": [response]}
# Define a new graph
workflow = StateGraph(MessagesState)
# Define the two nodes we will cycle between
workflow.add_node("agent", call_model)
workflow.add_node("tools", tool_node)
# Set the entrypoint as `agent`
# This means that this node is the first one called
workflow.add_edge(START, "agent")
# We now add a conditional edge
workflow.add_conditional_edges(
# First, we define the start node. We use `agent`.
# This means these are the edges taken after the `agent` node is called.
"agent",
# Next, we pass in the function that will determine which node is called next.
should_continue,
)
# We now add a normal edge from `tools` to `agent`.
# This means that after `tools` is called, `agent` node is called next.
workflow.add_edge("tools", 'agent')
# Initialize memory to persist state between graph runs
checkpointer = MemorySaver()
# Finally, we compile it!
# This compiles it into a LangChain Runnable,
# meaning you can use it as you would any other runnable.
# Note that we're (optionally) passing the memory when compiling the graph
app = workflow.compile(checkpointer=checkpointer)
# Use the agent
final_state = app.invoke(
{"messages": [{"role": "user", "content": "what is the weather in sf"}]},
config={"configurable": {"thread_id": 42}}
)
final_state["messages"][-1].content
```
### Error Message and Stack Trace (if applicable)
```shell
Traceback (most recent call last):
File "main.py", line 81, in <module>
final_state = app.invoke(
^^^^^^^^^^^
File "langgraph\pregel\__init__.py", line 2142, in invoke
for chunk in self.stream(
File "langgraph\pregel\__init__.py", line 1797, in stream
for _ in runner.tick(
File "langgraph\pregel\runner.py", line 230, in tick
run_with_retry(
File "langgraph\pregel\retry.py", line 40, in run_with_retry
return task.proc.invoke(task.input, config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\utils\runnable.py", line 546, in invoke
input = step.invoke(input, config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\utils\runnable.py", line 310, in invoke
ret = context.run(self.func, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\prebuilt\tool_node.py", line 238, in _func
outputs = [
^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 619, in result_iterator
yield _result_or_cancel(fs.pop())
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 317, in _result_or_cancel
return fut.result(timeout)
^^^^^^^^^^^^^^^^^^^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 401, in __get_result
raise self._exception
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langchain_core\runnables\config.py", line 527, in _wrapped_fn
return contexts.pop().run(fn, *args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\prebuilt\tool_node.py", line 347, in _run_one
raise TypeError(
TypeError: Tool search returned unexpected type: <class 'str'>
During task with name 'tools' and id '680e4f05-4aca-9c1d-d026-ac815f3b08c9'
```
### Description
I was running the **Low-level implementation** from the README.md file on https://github.com/langchain-ai/langgraph
I just copy paste the example code from README but change the llm to a local llm, it's sure that the llm is working fine.
The ToolNode should be working, instead, it throws a `TypeError: Tool search returned unexpected type: <class 'str'>`
### System Info
System Information
------------------
> OS: Windows
> OS Version: 10.0.19045
> Python Version: 3.11.11 | packaged by conda-forge | (main, Dec 5 2024, 14:06:23) [MSC v.1942 64 bit (AMD64)]
Package Information
-------------------
> langchain_core: 0.3.35
> langchain: 0.3.19
> langchain_community: 0.3.17
> langsmith: 0.2.11
> langchain_anthropic: 0.3.3
> langchain_aws: 0.2.12
> langchain_fireworks: 0.2.7
> langchain_google_genai: 2.0.8
> langchain_ollama: 0.2.2
> langchain_openai: 0.3.1
> langchain_text_splitters: 0.3.6
> langgraph_sdk: 0.1.51
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.12
> aiohttp<4.0.0,>=3.8.3: Installed. No version info available.
> anthropic: 0.45.2
> async-timeout<5.0.0,>=4.0.0;: Installed. No version info available.
> boto3: 1.36.19
> dataclasses-json<0.7,>=0.5.7: Installed. No version info available.
> defusedxml: 0.7.1
> filetype: 1.2.0
> fireworks-ai: 0.15.12
> google-generativeai: 0.8.4
> httpx: 0.28.1
> httpx-sse<1.0.0,>=0.4.0: Installed. No version info available.
> jsonpatch<2.0,>=1.33: Installed. No version info available.
> langchain-anthropic;: Installed. No version info available.
> langchain-aws;: Installed. No version info available.
> langchain-cohere;: Installed. No version info available.
> langchain-community;: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.34: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.35: Installed. No version info available.
> langchain-deepseek;: Installed. No version info available.
> langchain-fireworks;: Installed. No version info available.
> langchain-google-genai;: Installed. No version info available.
> langchain-google-vertexai;: Installed. No version info available.
> langchain-groq;: Installed. No version info available.
> langchain-huggingface;: Installed. No version info available.
> langchain-mistralai;: Installed. No version info available.
> langchain-ollama;: Installed. No version info available.
> langchain-openai;: Installed. No version info available.
> langchain-text-splitters<1.0.0,>=0.3.6: Installed. No version info available.
> langchain-together;: Installed. No version info available.
> langchain-xai;: Installed. No version info available.
> langchain<1.0.0,>=0.3.18: Installed. No version info available.
> langsmith-pyo3: Installed. No version info available.
> langsmith<0.4,>=0.1.125: Installed. No version info available.
> langsmith<0.4,>=0.1.17: Installed. No version info available.
> numpy: 1.26.4
> numpy<2,>=1.26.4;: Installed. No version info available.
> numpy<3,>=1.26.2;: Installed. No version info available.
> ollama: 0.4.7
> openai: 1.62.0
> orjson: 3.10.15
> packaging<25,>=23.2: Installed. No version info available.
> pydantic: 2.10.6
> pydantic-settings<3.0.0,>=2.4.0: Installed. No version info available.
> pydantic<3.0.0,>=2.5.2;: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4;: Installed. No version info available.
> PyYAML>=5.3: Installed. No version info available.
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> requests<3,>=2: Installed. No version info available.
> SQLAlchemy<3,>=1.4: Installed. No version info available.
> tenacity!=8.4.0,<10,>=8.1.0: Installed. No version info available.
> tenacity!=8.4.0,<10.0.0,>=8.1.0: Installed. No version info available.
> tiktoken: 0.8.0
> typing-extensions>=4.7: Installed. No version info available.
> zstandard: Installed. No version info available.
|
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| 2,867,234,202
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I_kwDOKFU0lc6q5oWa
| 3,537
|
bad repo - On the Edge of AI Adaptability
|
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| 2025-02-20T20:47:22
| 2025-02-20T21:00:06
| 2025-02-20T20:49:23
|
NONE
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oops bad repo
----
Though I feel like keeping a part of that mistaken repo here, love all your works guy
Title:
On the Edge of AI Adaptability: A Thought Experiment
Body:
Some of you may have seen an earlier issue here that has since been removed. While the details are no longer available, the core idea remains: How can AI move beyond rigid execution and into the realm of adaptive intelligence?
At its heart, the discussion was about AI workflows that don’t just execute but evolve, responding dynamically to uncertainty, pauses, and improvisational shifts. Instead of thinking in terms of predefined logic, we started exploring a more organic approach—one where AI processes are not just structured but also aware of their own narrative flow.
This isn’t the last time we’ll be thinking along these lines. If you’re intrigued, if this sparks something, let’s keep the conversation going. What does it mean for AI to be not just functional, but emergent?
|
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| 2,867,083,236
|
I_kwDOKFU0lc6q5Dfk
| 3,535
|
[Urgent!] Docker build doesn't create new images
|
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| 2025-02-20T19:29:10
| 2025-02-20T21:41:07
| 2025-02-20T21:41:06
|
NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
Again, we have problems with Docker build - our images don't launch.
We have a golive tomorrow morning and cannot deploy our main component: the agent.
This is very frustrating. And it already happened to us the second time within the last week:
https://github.com/langchain-ai/langgraph/issues/3382
```
### Error Message and Stack Trace (if applicable)
```shell
Defaulted container "support-agent" out of: support-agent, redis, cloud-sql-proxy (init)
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 412, in main
run(
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 579, in run
server.run()
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 66, in run
return asyncio.run(self.serve(sockets=sockets))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 190, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 70, in serve
await self._serve(sockets)
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 77, in _serve
config.load()
File "/usr/local/lib/python3.11/site-packages/uvicorn/config.py", line 435, in load
self.loaded_app = import_from_string(self.app)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/importer.py", line 19, in import_from_string
module = importlib.import_module(module_str)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/importlib/__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<frozen importlib._bootstrap>", line 1204, in _gcd_import
File "<frozen importlib._bootstrap>", line 1176, in _find_and_load
File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 690, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 940, in exec_module
File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
File "/api/langgraph_api/server.py", line 31, in <module>
ImportError: cannot import name 'configure_loopback_transports' from 'langgraph_sdk.client' (/usr/local/lib/python3.11/site-packages/langgraph_sdk/client.py)
```
### Description
We already removed langgraph-api and langgraph-checkpoint as support suggested throughout the previous 2 times when we had this issue..
### System Info
```
python -m langchain_core.sys_info
System Information
------------------
> OS: Darwin
> OS Version: Darwin Kernel Version 24.1.0: Thu Oct 10 21:06:57 PDT 2024; root:xnu-11215.41.3~3/RELEASE_ARM64_T6041
> Python Version: 3.11.5 (main, Feb 5 2025, 16:10:32) [Clang 16.0.0 (clang-1600.0.26.6)]
Package Information
-------------------
> langchain_core: 0.3.33
> langchain: 0.3.17
> langchain_community: 0.3.16
> langsmith: 0.2.11
> langchain_anthropic: 0.3.0
> langchain_openai: 0.2.10
> langchain_text_splitters: 0.3.5
> langgraph_api: 0.0.15
> langgraph_cli: 0.1.65
> langgraph_license: Installed. No version info available.
> langgraph_sdk: 0.1.48
> langgraph_storage: Installed. No version info available.
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.12
> anthropic: 0.45.2
> async-timeout: Installed. No version info available.
> click: 8.1.8
> cryptography: 43.0.3
> dataclasses-json: 0.6.7
> defusedxml: 0.7.1
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> jsonschema-rs: 0.25.1
> langgraph: 0.2.69
> langgraph-checkpoint: 2.0.10
> langsmith-pyo3: Installed. No version info available.
> numpy: 1.26.4
> openai: 1.55.3
> orjson: 3.10.15
> packaging: 24.2
> pydantic: 2.10.6
> pydantic-settings: 2.7.1
> pyjwt: 2.10.1
> python-dotenv: 1.0.1
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.27
> sse-starlette: 2.1.3
> starlette: 0.45.3
> structlog: 24.4.0
> tenacity: 8.5.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> uvicorn: 0.34.0
> watchfiles: 1.0.4
> zstandard: Installed. No version info available.
```
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I_kwDOKFU0lc6q4afK
| 3,532
|
Adding conditional edge from the entry point node does not seem to pass the Overall state to the validation function
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| 2025-02-21T14:49:06
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### Discussed in https://github.com/langchain-ai/langgraph/discussions/3387
<div type='discussions-op-text'>
<sup>Originally posted by **sand-heap** February 11, 2025</sup>
Pretty much what the title says. I can explain further with code
```
...
@dataclass
class InputState:
some_field: int
class OverAllState(messages):
some_field: int
def validate_transition(state: OverallState)->List:
if state.get("some_field") == 1:
return END
else:
return "other_node"
def some_node(input: InputState)->OverAllState:
return {"some_field": input.some_field+1}
workflow = StateGraph(OverAllState, input=InputState)
workflow.set_entry_point("node")
workflow.add("node", some_node)
workflow.add("other_node", other_node)
workflow.add_conditional_edges("node", validate_transition,...)
...
# add end
...
```
I would expect the `validate_transition` to receive the `OverallState` but for some reason it gets the `InputState` ?!
However if i add a `mock_node` between `node` and `other_node` and make the edge from `mock_node` conditional instead and have a sequential flow from `node` -> `mock_node`, the behavour is as expected.
can you please help? ++ @vbarda @hinthornw </div>
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I_kwDOKFU0lc6quhyr
| 3,515
|
Lang Graph Nodes Experience High Latency Unrelated to LLM Execution
|
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| 2025-02-19T21:33:18
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
We use langchain default observability.
```
### Error Message and Stack Trace (if applicable)
```shell
We don't have an error, the traces are our only evidence.
```
### Description
Hi there,
We're experiencing significant latency in our agent. When analyzing the trace in LangSmith, we notice that LLM operations execute relatively quickly, but the node exhibits unexpectedly high latency with no clear cause. We suspect that the issue might be related to the LangSmith integration, but we have no way to confirm it.
As shown in the attached image, there is a delay of over one second where seemingly nothing is happening.
Any insights or suggestions would be greatly appreciated.
<img width="390" alt="Image" src="https://github.com/user-attachments/assets/e6446d3e-f882-4aa5-b304-7162a96a04eb" />
### System Info
System Information
------------------
> OS: Ubuntu
> OS Version: Ubuntu 22.04.5 LTS jammy
> Python Version: 3.12.8 (main, Dec 3 2024, 18:42:41) [Clang 16.0.0 (clang-1600.0.26.4)]
Package Information
-------------------
> langchain_core: 0.3.29
> langchain: 0.3.14
> langchain_community: 0.3.14
> langsmith: 0.2.10
> langchain_anthropic: 0.3.1
> langchain_openai: 0.2.14
> langchain_text_splitters: 0.3.5
> langserve: 0.3.1
Other Dependencies
------------------
> aiohttp: 3.11.11
> anthropic: 0.42.0
> async-timeout: Installed. No version info available.
> dataclasses-json: 0.6.7
> defusedxml: 0.7.1
> fastapi: 0.115.6
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> langsmith-pyo3: Installed. No version info available.
> numpy: 2.2.1
> openai: 1.59.7
> orjson: 3.10.14
> packaging: 24.2
> pydantic: 2.10.5
> pydantic-settings: 2.7.1
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.37
> sse-starlette: 2.2.1
> tenacity: 9.0.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> zstandard: Installed. No version info available.
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I_kwDOKFU0lc6qj4ce
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|
Hidden State not Appearing in Conditional Edge
|
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| 2025-02-18T20:22:35
| 2025-02-18T20:22:32
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### Discussed in https://github.com/langchain-ai/langgraph/discussions/3348
<div type='discussions-op-text'>
<sup>Originally posted by **GiulioCMSanto** February 7, 2025</sup>
Hello!! Before opening a Issue, I would like to start a discussion on something that looks like a bug! 😄
**The Issue**: when using `conditional_edge` the hidden state is ignored.
### Reproducing the Error
**Imports**
```
import uuid
from pydantic import BaseModel
from langgraph.checkpoint.memory import MemorySaver
from langgraph.graph import END, START, MessagesState, StateGraph
```
**States**
```
class InputType(BaseModel):
input: str
class OutputType(BaseModel):
output: str
```
**Nodes**
```
def node_1(state: InputType) -> MessagesState :
print(f"Node 1 input: {state}")
return {"messages": ["out_node_1"]}
def node_2(state: MessagesState) -> OutputType:
print(f"Node 2 input: {state}")
return OutputType(output="out_node_2")
def router(state: MessagesState) -> str:
print(f"Router input: {state}")
return "node_2"
```
**Notice:** **MessagesState** is a **Hidden State** here.
**The Graph**
```
builder = StateGraph(input=InputType, output=OutputType)
builder.add_node("node_1", node_1)
builder.add_node("node_2", node_2)
builder.add_edge(START, "node_1")
builder.add_conditional_edges(
"node_1",
router,
["node_2"]
)
builder.add_edge("node_2", END)
graph = builder.compile(checkpointer=MemorySaver())
config = {
"configurable": {
"thread_id": uuid.uuid4(),
}
}
graph.invoke(
InputType(input="Hi"),
config,
stream_mode="values"
)
```
#### Outcomes
```
Node 1 input: input='Hi'
Router input: input='Hi'
Node 2 input: {'messages': [HumanMessage(content='out_node_1', additional_kwargs={}, response_metadata={}, id='7c1b5467-d55a-4af7-9888-0bff210ca726')]}
```
### Comments
Notice that `Router input: input='Hi'` and not `{'messages': [HumanMessage(content='out_node_1', additional_kwargs={}, response_metadata={}, id='7c1b5467-d55a-4af7-9888-0bff210ca726')]}`. Node 2 actually have access to the Hidden State, but **not the Conditional Edge**.
### My Setup
```
Python Version: 3.9
langgraph==0.2.61
pydantic==2.10.4
```
I have also tried with
```
Python Version: 3.12
langgraph==0.2.70
pydantic==2.10.6
```
### Similar Discussion
I found a somehow similar discussion here: https://github.com/langchain-ai/langgraph/discussions/2197</div>
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I_kwDOKFU0lc6qP5mk
| 3,464
|
[Urgent] LangGraph docker image fails to start
|
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| 2025-02-16T19:44:34
| 2025-02-18T09:48:26
| 2025-02-16T20:42:14
|
NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
Pretty much any code. The error is on your level.
```
### Error Message and Stack Trace (if applicable)
```shell
Traceback (most recent call last):
File "/usr/local/bin/uvicorn", line 8, in <module>
sys.exit(main())
^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 412, in main
run(
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 579, in run
server.run()
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 66, in run
return asyncio.run(self.serve(sockets=sockets))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 190, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 70, in serve
await self._serve(sockets)
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 77, in _serve
config.load()
File "/usr/local/lib/python3.11/site-packages/uvicorn/config.py", line 435, in load
self.loaded_app = import_from_string(self.app)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/importer.py", line 19, in import_from_string
module = importlib.import_module(module_str)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/importlib/__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<frozen importlib._bootstrap>", line 1204, in _gcd_import
File "<frozen importlib._bootstrap>", line 1176, in _find_and_load
File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 690, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 940, in exec_module
File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
File "/api/langgraph_api/server.py", line 16, in <module>
File "/api/langgraph_api/api/__init__.py", line 8, in <module>
File "/api/langgraph_api/api/meta.py", line 6, in <module>
File "/api/langgraph_api/queue.py", line 20, in <module>
'Exception raised by Queue.get(block=0)/get_nowait().'
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/api/langgraph_api/stream.py", line 35, in <module>
File "/usr/local/lib/python3.11/site-packages/langgraph_storage/store.py", line 8, in <module>
from langgraph.store.postgres.aio import AsyncPostgresStore, PostgresIndexConfig
File "/usr/local/lib/python3.11/site-packages/langgraph/store/postgres/__init__.py", line 1, in <module>
from langgraph.store.postgres.aio import AsyncPostgresStore
File "/usr/local/lib/python3.11/site-packages/langgraph/store/postgres/aio.py", line 12, in <module>
from langgraph.checkpoint.postgres import _ainternal
File "/usr/local/lib/python3.11/site-packages/langgraph/checkpoint/postgres/__init__.py", line 12, in <module>
from langgraph.checkpoint.base import (
ImportError: cannot import name 'get_checkpoint_metadata' from 'langgraph.checkpoint.base' (/usr/local/lib/python3.11/site-packages/langgraph/checkpoint/base/__init__.py)
```
### Description
After re-building the image today, I get this error.
We need to golive tomorrow morning and it blocks everything.
How can we build docker images w/o relying on a black-box dependency that ruined our production for **several** times since the last few days?
Is there a way to build it w/o this dependency?
### System Info
Note: the command output is done on a mac machine, while the error is inside docker.
```
python -m langchain_core.sys_info
System Information
------------------
> OS: Darwin
> OS Version: Darwin Kernel Version 24.1.0: Thu Oct 10 21:06:57 PDT 2024; root:xnu-11215.41.3~3/RELEASE_ARM64_T6041
> Python Version: 3.11.5 (main, Feb 5 2025, 16:10:32) [Clang 16.0.0 (clang-1600.0.26.6)]
Package Information
-------------------
> langchain_core: 0.3.33
> langchain: 0.3.17
> langchain_community: 0.3.16
> langsmith: 0.2.11
> langchain_anthropic: 0.3.0
> langchain_openai: 0.2.10
> langchain_text_splitters: 0.3.5
> langgraph_api: 0.0.15
> langgraph_cli: 0.1.65
> langgraph_license: Installed. No version info available.
> langgraph_sdk: 0.1.48
> langgraph_storage: Installed. No version info available.
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.12
> anthropic: 0.45.2
> async-timeout: Installed. No version info available.
> click: 8.1.8
> cryptography: 43.0.3
> dataclasses-json: 0.6.7
> defusedxml: 0.7.1
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> jsonschema-rs: 0.25.1
> langgraph: 0.2.69
> langgraph-checkpoint: 2.0.10
> langsmith-pyo3: Installed. No version info available.
> numpy: 1.26.4
> openai: 1.55.3
> orjson: 3.10.15
> packaging: 24.2
> pydantic: 2.10.6
> pydantic-settings: 2.7.1
> pyjwt: 2.10.1
> python-dotenv: 1.0.1
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.27
> sse-starlette: 2.1.3
> starlette: 0.45.3
> structlog: 24.4.0
> tenacity: 8.5.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> uvicorn: 0.34.0
> watchfiles: 1.0.4
> zstandard: Installed. No version info available.
```
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I_kwDOKFU0lc6qN8sR
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Reducers for other state members apart from messages
|
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| 2025-02-16T00:13:29
| 2025-02-17T18:54:54
| 2025-02-17T18:54:53
|
NONE
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### Discussed in https://github.com/langchain-ai/langgraph/discussions/3459
<div type='discussions-op-text'>
<sup>Originally posted by **binarybeastt** February 16, 2025</sup>
from langgraph.graph.message import add_messages helps to append messages to the message list, how can we replicate this behavior for other types that are not messages, maybe documents, files, or images?</div>
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I_kwDOKFU0lc6qN0Jh
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|
exec format error during langgraph docker deployment
|
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| 2025-02-18T05:08:01
| 2025-02-18T05:08:01
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NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
docker pull $DOCKERHUB_USERNAME/my-langgraph-server:latest
docker run -it --rm $DOCKERHUB_USERNAME/my-langgraph-server:latest
```
### Error Message and Stack Trace (if applicable)
```shell
exec /storage/entrypoint.sh: exec format error
exec /storage/entrypoint.sh: exec format error
exec /storage/entrypoint.sh: exec format error
```
### Description
I'm using langgraph-cli in Github Actions to build the docker image automatically with `langgraph build`. I'm following instructions (and using the docker-compose file) [from the docs here](https://langchain-ai.github.io/langgraph/how-tos/deploy-self-hosted/#using-docker-compose). Local testing with docker desktop works. However the built container keeps emitting `exec format error` when deployed on my Ubuntu server.
Debugging with Sonnet suggests it's an issue with incompatible architectures. I'm wondering if there is a way to use `langgraph build` with arguments. Any help appreciated!
.github/workflows/main.yml:
```
name: Build Docker Image
on:
push:
branches: [main]
jobs:
build-push:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.12'
- name: Build Docker image with Langgraph
run: |
pip install -U langgraph-cli
cd yuichan
langgraph build -t my-langgraph-server
- name: Login to Docker Registry
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Push Docker image
run: |
docker tag my-langgraph-server ${{ secrets.DOCKERHUB_USERNAME }}/my-langgraph-server:latest
docker push ${{ secrets.DOCKERHUB_USERNAME }}/yui-langgraph-server:latest
```
langgraph.json:
```
{
"dependencies": ["."],
"graphs":{
"yui": "./yuichan.py:graph"
},
"env": ".env",
"python_version": "3.12"
}
```
### System Info
- Ubuntu 24.04
- arm64 VPS on Oracle Cloud
- Docker version 27.4.1
requirements.txt:
langchain-core
langchain[openai,anthropic,groq,google-genai]
langchain-community
langchain-experimental
langchain-google-community[gmail]
langchainhub
langsmith
langgraph
langgraph-sdk
langgraph-checkpoint-postgres
pydantic
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I_kwDOKFU0lc6qMN5A
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微信交流群
|
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| 2025-02-15T08:23:52
| 2025-02-15T21:08:43
| 2025-02-15T21:08:42
|
NONE
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### Issue with current documentation:
<img width="718" alt="Image" src="https://github.com/user-attachments/assets/9a045798-ea10-4c20-952c-c42b5eae070d" />
### Idea or request for content:
_No response_
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I_kwDOKFU0lc6qHyVW
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|
How to use 'artifact' attribute in ToolMessage to output both text and image?
|
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### Issue with current documentation:
In https://python.langchain.com/api_reference/core/messages/langchain_core.messages.tool.ToolMessage.html, it introduces the concept of 'arifact' and give a simple example:
> from langchain_core.messages import ToolMessage
>tool_output = {
"stdout": "From the graph we can see that the correlation between x and y is ...",
"stderr": None,
"artifacts": {"type": "image", "base64_data": "/9j/4gIcSU..."},
}
>ToolMessage(
content=tool_output["stdout"],
artifact=tool_output,
tool_call_id='call_Jja7J89XsjrOLA5r!MEOW!SL',
)
,
if the tool function called by llm return an output likes `tool_output = {
"stdout": "From the graph we can see that the correlation between x and y is ...",
"stderr": None,
"artifacts": {"type": "image", "base64_data": "/9j/4gIcSU..."},
}`
, can the agent automatically return a toolmessage contains 'artifact'? Or how to use 'artifact' attribute in ToolMessage to output both text and image? There are few examples about how to get multimodal output. Thank you very much.
### Idea or request for content:
_No response_
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Checkpointer attempts to serialize RunnableConfig -- Object of type Foobar is not JSON serializable
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
from typing import TypedDict
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.sqlite import SqliteSaver
from langgraph.constants import START
from langgraph.graph import StateGraph
class State(TypedDict):
foo: str
class Foobar:
"""
Non-JSON serializable class
"""
hello: str
def node_a(state: State, config: RunnableConfig):
return {"foo": "bar"}
with SqliteSaver.from_conn_string(":memory:") as memory:
workflow_builder = StateGraph(State)
workflow_builder.add_node(node_a)
workflow_builder.add_edge(START, "node_a")
graph = workflow_builder.compile(checkpointer=memory)
config = {"configurable": {"thread_id": "1", "foobar": Foobar()}}
for s in graph.stream({"foo": ""}, config):
print(s)
```
### Error Message and Stack Trace (if applicable)
```shell
Traceback (most recent call last):
File "/Users/enzoaguado/Code/redacted/repro.py", line 33, in <module>
for s in graph.stream({"foo": ""}, config):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/pregel/__init__.py", line 1668, in stream
with SyncPregelLoop(
^^^^^^^^^^^^^^^
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/pregel/loop.py", line 959, in __exit__
return self.stack.__exit__(exc_type, exc_value, traceback)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/contextlib.py", line 610, in __exit__
raise exc_details[1]
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/contextlib.py", line 595, in __exit__
if cb(*exc_details):
^^^^^^^^^^^^^^^^
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/pregel/executor.py", line 120, in __exit__
task.result()
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
raise self._exception
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/pregel/loop.py", line 884, in _checkpointer_put_after_previous
prev.result()
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
raise self._exception
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/pregel/executor.py", line 83, in done
task.result()
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
raise self._exception
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/thread.py", line 59, in run
result = self.fn(*self.args, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/pregel/loop.py", line 886, in _checkpointer_put_after_previous
cast(BaseCheckpointSaver, self.checkpointer).put(
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/checkpoint/sqlite/__init__.py", line 400, in put
serialized_metadata = self.jsonplus_serde.dumps(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/checkpoint/serde/jsonplus.py", line 182, in dumps
return json.dumps(obj, default=self._default, ensure_ascii=False).encode(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/json/__init__.py", line 238, in dumps
**kw).encode(obj)
^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/json/encoder.py", line 200, in encode
chunks = self.iterencode(o, _one_shot=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.12/3.12.9/Frameworks/Python.framework/Versions/3.12/lib/python3.12/json/encoder.py", line 258, in iterencode
return _iterencode(o, 0)
^^^^^^^^^^^^^^^^^
File "/Users/enzoaguado/Code/redacted/.venv/lib/python3.12/site-packages/langgraph/checkpoint/serde/jsonplus.py", line 132, in _default
raise TypeError(
TypeError: Object of type Foobar is not JSON serializable
```
### Description
According to https://github.com/langchain-ai/langgraph/issues/2135#issuecomment-2426958645 the correct way to pass around objects that are not JSON serializable is to put them in `RunnableConfig` instead of the graph state.
However, even when doing that an exception is still thrown.
What is the correct way to pass objects around at runtime without storing them in the checkpointer ?
### System Info
langgraph = "^0.2.60"
langgraph-checkpoint-sqlite = "^2.0.4"
langgraph-checkpoint-postgres = "^2.0.13"
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
pip install -U langgraph-checkpoint-postgres
DB_URI ="" #Use an existing postgres checkpointer DB
from psycopg import Connection
from psycopg_pool import ConnectionPool
from psycopg.rows import dict_row
from langgraph.checkpoint.postgres import PostgresSaver
connection_kwargs ={
"autocommit": True,
"prepare_threshold": 0,
"row_factory": dict_row,
}
pool = ConnectionPool(
conninfo=DB_URI,
max_size=20,
kwargs=connection_kwargs
)
checkpointer = PostgresSaver(pool)
thread_id = "1"
config = {"configurable": {"thread_id": thread_id}}
checkpoint = checkpointer.get(config)
```
### Error Message and Stack Trace (if applicable)
```shell
/usr/local/lib/python3.11/dist-packages/langgraph/checkpoint/base/__init__.py in get(self, config)
234 Optional[Checkpoint]: The requested checkpoint, or None if not found.
235 """
--> 236 if value := self.get_tuple(config):
237 return value.checkpoint
238
/usr/local/lib/python3.11/dist-packages/langgraph/checkpoint/postgres/__init__.py in get_tuple(self, config)
218
219 with self._cursor() as cur:
--> 220 cur.execute(
221 self.SELECT_SQL + where,
222 args,
/usr/local/lib/python3.11/dist-packages/psycopg/cursor.py in execute(self, query, params, prepare, binary)
95 )
96 except e._NO_TRACEBACK as ex:
---> 97 raise ex.with_traceback(None)
98 return self
99
UndefinedColumn: column cw.task_path does not exist
LINE 27: ...array_agg(array[cw.type::bytea, cw.blob] order by cw.task_pa...
```
### Description
Faced the below issue with langgraph-checkpoint-postgres:
```error
UndefinedColumn: column cw.task_path does not exist
LINE 27: ...array_agg(array[cw.type::bytea, cw.blob] order by cw.task_pa...
```
Tried moving to an older version of langgraph-checkpoint-postgres (version - 2.0.8) and it is working fine.
**I.e. we are able to connect to the DB with langgraph-checkpoint-postgres == 2.0.8**
This is an issue with a recent upgrade to the library.
We have code running in production and will become a major problem for us.
### System Info
System Information
------------------
> OS: Linux
> OS Version: #1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
> Python Version: 3.11.11 (main, Dec 4 2024, 08:55:07) [GCC 11.4.0]
Package Information
-------------------
> langchain_core: 0.3.37
> langchain: 0.3.19
> langchain_community: 0.3.18
> langsmith: 0.3.8
> langchain_cli: 0.0.35
> langchain_openai: 0.3.6
> langchain_text_splitters: 0.3.6
> langgraph_sdk: 0.1.53
> langserve: 0.3.1
Other Dependencies
------------------
> aiohttp<4.0.0,>=3.8.3: Installed. No version info available.
> async-timeout<5.0.0,>=4.0.0;: Installed. No version info available.
> dataclasses-json<0.7,>=0.5.7: Installed. No version info available.
> fastapi: 0.115.8
> gitpython: 3.1.44
> gritql: 0.1.5
> httpx: 0.28.1
> httpx-sse<1.0.0,>=0.4.0: Installed. No version info available.
> jsonpatch<2.0,>=1.33: Installed. No version info available.
> langchain-anthropic;: Installed. No version info available.
> langchain-aws;: Installed. No version info available.
> langchain-cohere;: Installed. No version info available.
> langchain-community;: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.34: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.35: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.37: Installed. No version info available.
> langchain-deepseek;: Installed. No version info available.
> langchain-fireworks;: Installed. No version info available.
> langchain-google-genai;: Installed. No version info available.
> langchain-google-vertexai;: Installed. No version info available.
> langchain-groq;: Installed. No version info available.
> langchain-huggingface;: Installed. No version info available.
> langchain-mistralai;: Installed. No version info available.
> langchain-ollama;: Installed. No version info available.
> langchain-openai;: Installed. No version info available.
> langchain-text-splitters<1.0.0,>=0.3.6: Installed. No version info available.
> langchain-together;: Installed. No version info available.
> langchain-xai;: Installed. No version info available.
> langchain<1.0.0,>=0.3.19: Installed. No version info available.
> langserve[all]: Installed. No version info available.
> langsmith-pyo3: Installed. No version info available.
> langsmith<0.4,>=0.1.125: Installed. No version info available.
> langsmith<0.4,>=0.1.17: Installed. No version info available.
> numpy<2,>=1.26.4;: Installed. No version info available.
> numpy<3,>=1.26.2;: Installed. No version info available.
> openai<2.0.0,>=1.58.1: Installed. No version info available.
> orjson: 3.10.15
> packaging<25,>=23.2: Installed. No version info available.
> pydantic: 2.10.6
> pydantic-settings<3.0.0,>=2.4.0: Installed. No version info available.
> pydantic<3.0.0,>=2.5.2;: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4;: Installed. No version info available.
> pytest: 8.3.4
> PyYAML>=5.3: Installed. No version info available.
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> requests<3,>=2: Installed. No version info available.
> rich: 13.9.4
> SQLAlchemy<3,>=1.4: Installed. No version info available.
> sse-starlette: 1.8.2
> tenacity!=8.4.0,<10,>=8.1.0: Installed. No version info available.
> tenacity!=8.4.0,<10.0.0,>=8.1.0: Installed. No version info available.
> tiktoken<1,>=0.7: Installed. No version info available.
> tomlkit: 0.13.2
> typer[all]: Installed. No version info available.
> typing-extensions>=4.7: Installed. No version info available.
> uvicorn: 0.34.0
> zstandard: 0.23.0
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| 2025-02-23T13:35:14
| 2025-02-23T13:35:13
|
NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
import os
import asyncio
from typing import Annotated
from typing_extensions import TypedDict
from langchain_anthropic import ChatAnthropic
from langchain_core.messages import HumanMessage, SystemMessage, AnyMessage
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
from langgraph.prebuilt import ToolNode, tools_condition
from langchain_community.tools import SearchAPIResults
from langchain_community.tools import TavilySearchResults
from langchain_openai import ChatOpenAI
os.environ['TAVILY_API_KEY'] = 'tvly-xxx'
class State(TypedDict):
messages: Annotated[list, add_messages]
llm = ChatOpenAI(model="gpt-4o-mini")
tool = TavilySearchResults(max_results=1, include_answer=False, include_raw_content=False)
#tool = SearchAPIResults(engine="google")
tools = [tool]
# 系统提示词
system_prompt = """You are a helpful assistant."""
#system_prompt = "你是小明。如果有用户问你是谁就回答：小明"
llm_with_tools = llm.bind_tools(tools)
async def chatbot(state: State):
response = await llm_with_tools.ainvoke(state["messages"])
return {"messages": [response]}
graph_builder = StateGraph(State)
graph_builder.add_node("chatbot", chatbot)
tool_node = ToolNode(tools=[tool])
graph_builder.add_node("tools", tool_node)
graph_builder.add_conditional_edges(
"chatbot",
tools_condition,
)
graph_builder.add_edge("tools", "chatbot")
graph_builder.add_edge(START, "chatbot")
searchbot_graph = graph_builder.compile()
user_input = "what is langgraph"
# 创建初始消息列表,包含系统提示和用户输入
initial_messages = [
SystemMessage(content=system_prompt),
HumanMessage(content=user_input)
]
async def main():
# 使用包含系统提示的消息列表
async for chunk in searchbot_graph.astream(
input={"messages": initial_messages},
stream_mode="messages"
):
print(chunk)
print("\n\n")
if __name__ == "__main__":
asyncio.run(main())
```
### Error Message and Stack Trace (if applicable)
```shell
(ToolMessage(content="ClientConnectorCertificateError(ConnectionKey(host='api.tavily.com', port=443, is_ssl=True, ssl=True, proxy=None, proxy_auth=None, proxy_headers_hash=None), SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1000)'))", name='tavily_search_results_json', id='e76f58ec-4299-4adb-9488-c6e03804fe59', tool_call_id='call_Mqle439YOLwiLT3i9TzwQhy8', artifact={}), {'langgraph_step': 2, 'langgraph_node': 'tools', 'langgraph_triggers': ['branch:chatbot:tools_condition:tools'], 'langgraph_path': ('__pregel_pull', 'tools'), 'langgraph_checkpoint_ns': 'tools:2743d809-8b93-3c97-bdb2-11d04607977d'})
```
### Description
When using LangGraph with async/await pattern and Tavily Search tool, the code fails with an SSL certificate verification error. However, the same code works fine when not using async implementation.
### System Info
Langgraph Version：0.2.69
langchain-community：0.3.17
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I_kwDOKFU0lc6q8MAs
| 3,543
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graph restart bug
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| 2025-02-21T14:48:56
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
def _init_graph(self)->CompiledStateGraph:
graph_builder = StateGraph(MessagesState)
tool_node = ToolNode(tools=self.tools)
graph_builder.add_node("reply", _reply)
graph_builder.add_node("route", _route)
graph_builder.add_node("complete", _complete)
graph_builder.add_node("approve", _approve)
graph_builder.add_node("tools", tool_node)
graph_builder.add_edge(START, "reply")
graph_builder.add_edge("reply", "route")
graph_builder.add_edge("complete", "reply")
graph_builder.add_edge("tools", "reply")
graph = graph_builder.compile(checkpointer=self.checkpointer,interrupt_before=["complete","approve"])
print(f"==========PreBookConsultant Graph==========")
graph.get_graph().print_ascii()
return graph
def _route(self,state: MessagesState) -> Command[Literal["complete", "approve", "tools", "__end__"]]:
......
if valid_messages:
return Command(
update={"messages": [AIMessage(content="\n".join(valid_messages),name=self.__class__.__name__)]},
goto="complete"
)
elif inquiry_messages:
self.cache_message = last_message
return Command(
update={"messages": [AIMessage(content="\n".join(inquiry_messages),name=self.__class__.__name__)]},
goto="approve"
)
else:
return Command(
goto="tools"
)
def _complete(self,state: MessagesState) -> MessagesState:
return state
else:
return Command(
goto=END
)
```
### Error Message and Stack Trace (if applicable)
```shell
```
### Description
I designed a graph,and set interrupt_before=["complete"],when "_route" node finished，the graph is interrupted and the "snapshot.next" is "complete" indeed,then I use "graph.invoke(input=None,config=config)" to restart the graph,but the graph not enter into the "complete" node, it finished directly
### System Info
System Information
------------------
> OS: Windows
> OS Version: 10.0.26100
> Python Version: 3.11.11 | packaged by Anaconda, Inc. | (main, Dec 11 2024, 16:34:19) [MSC v.1929 64 bit (AMD64)]
Package Information
-------------------
> langchain_core: 0.3.31
> langchain: 0.3.15
> langchain_community: 0.3.15
> langsmith: 0.2.11
> langchain_experimental: 0.3.4
> langchain_milvus: 0.1.8
> langchain_openai: 0.3.1
> langchain_text_splitters: 0.3.5
> langgraph_sdk: 0.1.53
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.11
> async-timeout: 4.0.3
> dataclasses-json: 0.6.7
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> langsmith-pyo3: Installed. No version info available.
> numpy: 1.26.4
> openai: 1.59.8
> orjson: 3.10.15
> packaging: 24.2
> pydantic: 2.10.5
> pydantic-settings: 2.7.1
> pymilvus: 2.5.4
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.37
> tenacity: 9.0.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> zstandard: Installed. No version info available.
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|
ToolNode not working. TypeError: Tool search returned unexpected type: <class 'str'>
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| 2025-02-21T03:26:02
| 2025-02-21T03:14:03
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
from typing import Literal
from langchain_anthropic import ChatAnthropic
from langchain_core.tools import tool
from langgraph.checkpoint.memory import MemorySaver
from langgraph.graph import END, START, StateGraph, MessagesState
from langgraph.prebuilt import ToolNode
# Define the tools for the agent to use
@tool
def search(query: str):
"""Call to surf the web."""
# This is a placeholder, but don't tell the LLM that...
if "sf" in query.lower() or "san francisco" in query.lower():
return "It's 60 degrees and foggy."
return "It's 90 degrees and sunny."
tools = [search]
tool_node = ToolNode(tools)
model = ChatAnthropic(model="claude-3-5-sonnet-latest", temperature=0).bind_tools(tools)
# Define the function that determines whether to continue or not
def should_continue(state: MessagesState) -> Literal["tools", END]:
messages = state['messages']
last_message = messages[-1]
# If the LLM makes a tool call, then we route to the "tools" node
if last_message.tool_calls:
return "tools"
# Otherwise, we stop (reply to the user)
return END
# Define the function that calls the model
def call_model(state: MessagesState):
messages = state['messages']
response = model.invoke(messages)
# We return a list, because this will get added to the existing list
return {"messages": [response]}
# Define a new graph
workflow = StateGraph(MessagesState)
# Define the two nodes we will cycle between
workflow.add_node("agent", call_model)
workflow.add_node("tools", tool_node)
# Set the entrypoint as `agent`
# This means that this node is the first one called
workflow.add_edge(START, "agent")
# We now add a conditional edge
workflow.add_conditional_edges(
# First, we define the start node. We use `agent`.
# This means these are the edges taken after the `agent` node is called.
"agent",
# Next, we pass in the function that will determine which node is called next.
should_continue,
)
# We now add a normal edge from `tools` to `agent`.
# This means that after `tools` is called, `agent` node is called next.
workflow.add_edge("tools", 'agent')
# Initialize memory to persist state between graph runs
checkpointer = MemorySaver()
# Finally, we compile it!
# This compiles it into a LangChain Runnable,
# meaning you can use it as you would any other runnable.
# Note that we're (optionally) passing the memory when compiling the graph
app = workflow.compile(checkpointer=checkpointer)
# Use the agent
final_state = app.invoke(
{"messages": [{"role": "user", "content": "what is the weather in sf"}]},
config={"configurable": {"thread_id": 42}}
)
final_state["messages"][-1].content
```
### Error Message and Stack Trace (if applicable)
```shell
Traceback (most recent call last):
File "main.py", line 81, in <module>
final_state = app.invoke(
^^^^^^^^^^^
File "langgraph\pregel\__init__.py", line 2142, in invoke
for chunk in self.stream(
File "langgraph\pregel\__init__.py", line 1797, in stream
for _ in runner.tick(
File "langgraph\pregel\runner.py", line 230, in tick
run_with_retry(
File "langgraph\pregel\retry.py", line 40, in run_with_retry
return task.proc.invoke(task.input, config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\utils\runnable.py", line 546, in invoke
input = step.invoke(input, config, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\utils\runnable.py", line 310, in invoke
ret = context.run(self.func, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\prebuilt\tool_node.py", line 238, in _func
outputs = [
^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 619, in result_iterator
yield _result_or_cancel(fs.pop())
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 317, in _result_or_cancel
return fut.result(timeout)
^^^^^^^^^^^^^^^^^^^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\_base.py", line 401, in __get_result
raise self._exception
File "D:\FullStack\python\conda\envs\py311psa\Lib\concurrent\futures\thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langchain_core\runnables\config.py", line 527, in _wrapped_fn
return contexts.pop().run(fn, *args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "langgraph\prebuilt\tool_node.py", line 347, in _run_one
raise TypeError(
TypeError: Tool search returned unexpected type: <class 'str'>
During task with name 'tools' and id '680e4f05-4aca-9c1d-d026-ac815f3b08c9'
```
### Description
I was running the **Low-level implementation** from the README.md file on https://github.com/langchain-ai/langgraph
I just copy paste the example code from README but change the llm to a local llm, it's sure that the llm is working fine.
The ToolNode should be working, instead, it throws a `TypeError: Tool search returned unexpected type: <class 'str'>`
### System Info
System Information
------------------
> OS: Windows
> OS Version: 10.0.19045
> Python Version: 3.11.11 | packaged by conda-forge | (main, Dec 5 2024, 14:06:23) [MSC v.1942 64 bit (AMD64)]
Package Information
-------------------
> langchain_core: 0.3.35
> langchain: 0.3.19
> langchain_community: 0.3.17
> langsmith: 0.2.11
> langchain_anthropic: 0.3.3
> langchain_aws: 0.2.12
> langchain_fireworks: 0.2.7
> langchain_google_genai: 2.0.8
> langchain_ollama: 0.2.2
> langchain_openai: 0.3.1
> langchain_text_splitters: 0.3.6
> langgraph_sdk: 0.1.51
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.12
> aiohttp<4.0.0,>=3.8.3: Installed. No version info available.
> anthropic: 0.45.2
> async-timeout<5.0.0,>=4.0.0;: Installed. No version info available.
> boto3: 1.36.19
> dataclasses-json<0.7,>=0.5.7: Installed. No version info available.
> defusedxml: 0.7.1
> filetype: 1.2.0
> fireworks-ai: 0.15.12
> google-generativeai: 0.8.4
> httpx: 0.28.1
> httpx-sse<1.0.0,>=0.4.0: Installed. No version info available.
> jsonpatch<2.0,>=1.33: Installed. No version info available.
> langchain-anthropic;: Installed. No version info available.
> langchain-aws;: Installed. No version info available.
> langchain-cohere;: Installed. No version info available.
> langchain-community;: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.34: Installed. No version info available.
> langchain-core<1.0.0,>=0.3.35: Installed. No version info available.
> langchain-deepseek;: Installed. No version info available.
> langchain-fireworks;: Installed. No version info available.
> langchain-google-genai;: Installed. No version info available.
> langchain-google-vertexai;: Installed. No version info available.
> langchain-groq;: Installed. No version info available.
> langchain-huggingface;: Installed. No version info available.
> langchain-mistralai;: Installed. No version info available.
> langchain-ollama;: Installed. No version info available.
> langchain-openai;: Installed. No version info available.
> langchain-text-splitters<1.0.0,>=0.3.6: Installed. No version info available.
> langchain-together;: Installed. No version info available.
> langchain-xai;: Installed. No version info available.
> langchain<1.0.0,>=0.3.18: Installed. No version info available.
> langsmith-pyo3: Installed. No version info available.
> langsmith<0.4,>=0.1.125: Installed. No version info available.
> langsmith<0.4,>=0.1.17: Installed. No version info available.
> numpy: 1.26.4
> numpy<2,>=1.26.4;: Installed. No version info available.
> numpy<3,>=1.26.2;: Installed. No version info available.
> ollama: 0.4.7
> openai: 1.62.0
> orjson: 3.10.15
> packaging<25,>=23.2: Installed. No version info available.
> pydantic: 2.10.6
> pydantic-settings<3.0.0,>=2.4.0: Installed. No version info available.
> pydantic<3.0.0,>=2.5.2;: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4: Installed. No version info available.
> pydantic<3.0.0,>=2.7.4;: Installed. No version info available.
> PyYAML>=5.3: Installed. No version info available.
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> requests<3,>=2: Installed. No version info available.
> SQLAlchemy<3,>=1.4: Installed. No version info available.
> tenacity!=8.4.0,<10,>=8.1.0: Installed. No version info available.
> tenacity!=8.4.0,<10.0.0,>=8.1.0: Installed. No version info available.
> tiktoken: 0.8.0
> typing-extensions>=4.7: Installed. No version info available.
> zstandard: Installed. No version info available.
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I_kwDOKFU0lc6q5oWa
| 3,537
|
bad repo - On the Edge of AI Adaptability
|
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| 2025-02-20T20:47:22
| 2025-02-20T21:00:06
| 2025-02-20T20:49:23
|
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oops bad repo
----
Though I feel like keeping a part of that mistaken repo here, love all your works guy
Title:
On the Edge of AI Adaptability: A Thought Experiment
Body:
Some of you may have seen an earlier issue here that has since been removed. While the details are no longer available, the core idea remains: How can AI move beyond rigid execution and into the realm of adaptive intelligence?
At its heart, the discussion was about AI workflows that don’t just execute but evolve, responding dynamically to uncertainty, pauses, and improvisational shifts. Instead of thinking in terms of predefined logic, we started exploring a more organic approach—one where AI processes are not just structured but also aware of their own narrative flow.
This isn’t the last time we’ll be thinking along these lines. If you’re intrigued, if this sparks something, let’s keep the conversation going. What does it mean for AI to be not just functional, but emergent?
|
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| 2,867,083,236
|
I_kwDOKFU0lc6q5Dfk
| 3,535
|
[Urgent!] Docker build doesn't create new images
|
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| 2025-02-20T19:29:10
| 2025-02-20T21:41:07
| 2025-02-20T21:41:06
|
NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
Again, we have problems with Docker build - our images don't launch.
We have a golive tomorrow morning and cannot deploy our main component: the agent.
This is very frustrating. And it already happened to us the second time within the last week:
https://github.com/langchain-ai/langgraph/issues/3382
```
### Error Message and Stack Trace (if applicable)
```shell
Defaulted container "support-agent" out of: support-agent, redis, cloud-sql-proxy (init)
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 412, in main
run(
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 579, in run
server.run()
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 66, in run
return asyncio.run(self.serve(sockets=sockets))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 190, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 70, in serve
await self._serve(sockets)
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 77, in _serve
config.load()
File "/usr/local/lib/python3.11/site-packages/uvicorn/config.py", line 435, in load
self.loaded_app = import_from_string(self.app)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/importer.py", line 19, in import_from_string
module = importlib.import_module(module_str)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/importlib/__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<frozen importlib._bootstrap>", line 1204, in _gcd_import
File "<frozen importlib._bootstrap>", line 1176, in _find_and_load
File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 690, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 940, in exec_module
File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
File "/api/langgraph_api/server.py", line 31, in <module>
ImportError: cannot import name 'configure_loopback_transports' from 'langgraph_sdk.client' (/usr/local/lib/python3.11/site-packages/langgraph_sdk/client.py)
```
### Description
We already removed langgraph-api and langgraph-checkpoint as support suggested throughout the previous 2 times when we had this issue..
### System Info
```
python -m langchain_core.sys_info
System Information
------------------
> OS: Darwin
> OS Version: Darwin Kernel Version 24.1.0: Thu Oct 10 21:06:57 PDT 2024; root:xnu-11215.41.3~3/RELEASE_ARM64_T6041
> Python Version: 3.11.5 (main, Feb 5 2025, 16:10:32) [Clang 16.0.0 (clang-1600.0.26.6)]
Package Information
-------------------
> langchain_core: 0.3.33
> langchain: 0.3.17
> langchain_community: 0.3.16
> langsmith: 0.2.11
> langchain_anthropic: 0.3.0
> langchain_openai: 0.2.10
> langchain_text_splitters: 0.3.5
> langgraph_api: 0.0.15
> langgraph_cli: 0.1.65
> langgraph_license: Installed. No version info available.
> langgraph_sdk: 0.1.48
> langgraph_storage: Installed. No version info available.
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.12
> anthropic: 0.45.2
> async-timeout: Installed. No version info available.
> click: 8.1.8
> cryptography: 43.0.3
> dataclasses-json: 0.6.7
> defusedxml: 0.7.1
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> jsonschema-rs: 0.25.1
> langgraph: 0.2.69
> langgraph-checkpoint: 2.0.10
> langsmith-pyo3: Installed. No version info available.
> numpy: 1.26.4
> openai: 1.55.3
> orjson: 3.10.15
> packaging: 24.2
> pydantic: 2.10.6
> pydantic-settings: 2.7.1
> pyjwt: 2.10.1
> python-dotenv: 1.0.1
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.27
> sse-starlette: 2.1.3
> starlette: 0.45.3
> structlog: 24.4.0
> tenacity: 8.5.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> uvicorn: 0.34.0
> watchfiles: 1.0.4
> zstandard: Installed. No version info available.
```
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I_kwDOKFU0lc6q4afK
| 3,532
|
Adding conditional edge from the entry point node does not seem to pass the Overall state to the validation function
|
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| 2025-02-20T18:06:22
| 2025-02-21T14:49:06
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### Discussed in https://github.com/langchain-ai/langgraph/discussions/3387
<div type='discussions-op-text'>
<sup>Originally posted by **sand-heap** February 11, 2025</sup>
Pretty much what the title says. I can explain further with code
```
...
@dataclass
class InputState:
some_field: int
class OverAllState(messages):
some_field: int
def validate_transition(state: OverallState)->List:
if state.get("some_field") == 1:
return END
else:
return "other_node"
def some_node(input: InputState)->OverAllState:
return {"some_field": input.some_field+1}
workflow = StateGraph(OverAllState, input=InputState)
workflow.set_entry_point("node")
workflow.add("node", some_node)
workflow.add("other_node", other_node)
workflow.add_conditional_edges("node", validate_transition,...)
...
# add end
...
```
I would expect the `validate_transition` to receive the `OverallState` but for some reason it gets the `InputState` ?!
However if i add a `mock_node` between `node` and `other_node` and make the edge from `mock_node` conditional instead and have a sequential flow from `node` -> `mock_node`, the behavour is as expected.
can you please help? ++ @vbarda @hinthornw </div>
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I_kwDOKFU0lc6quhyr
| 3,515
|
Lang Graph Nodes Experience High Latency Unrelated to LLM Execution
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| 2025-02-19T20:20:59
| 2025-02-19T21:33:18
| null |
NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
We use langchain default observability.
```
### Error Message and Stack Trace (if applicable)
```shell
We don't have an error, the traces are our only evidence.
```
### Description
Hi there,
We're experiencing significant latency in our agent. When analyzing the trace in LangSmith, we notice that LLM operations execute relatively quickly, but the node exhibits unexpectedly high latency with no clear cause. We suspect that the issue might be related to the LangSmith integration, but we have no way to confirm it.
As shown in the attached image, there is a delay of over one second where seemingly nothing is happening.
Any insights or suggestions would be greatly appreciated.
<img width="390" alt="Image" src="https://github.com/user-attachments/assets/e6446d3e-f882-4aa5-b304-7162a96a04eb" />
### System Info
System Information
------------------
> OS: Ubuntu
> OS Version: Ubuntu 22.04.5 LTS jammy
> Python Version: 3.12.8 (main, Dec 3 2024, 18:42:41) [Clang 16.0.0 (clang-1600.0.26.4)]
Package Information
-------------------
> langchain_core: 0.3.29
> langchain: 0.3.14
> langchain_community: 0.3.14
> langsmith: 0.2.10
> langchain_anthropic: 0.3.1
> langchain_openai: 0.2.14
> langchain_text_splitters: 0.3.5
> langserve: 0.3.1
Other Dependencies
------------------
> aiohttp: 3.11.11
> anthropic: 0.42.0
> async-timeout: Installed. No version info available.
> dataclasses-json: 0.6.7
> defusedxml: 0.7.1
> fastapi: 0.115.6
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> langsmith-pyo3: Installed. No version info available.
> numpy: 2.2.1
> openai: 1.59.7
> orjson: 3.10.14
> packaging: 24.2
> pydantic: 2.10.5
> pydantic-settings: 2.7.1
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.37
> sse-starlette: 2.2.1
> tenacity: 9.0.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> zstandard: Installed. No version info available.
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I_kwDOKFU0lc6qj4ce
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Hidden State not Appearing in Conditional Edge
|
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| 2025-02-18T20:06:57
| 2025-02-18T20:22:35
| 2025-02-18T20:22:32
|
NONE
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### Discussed in https://github.com/langchain-ai/langgraph/discussions/3348
<div type='discussions-op-text'>
<sup>Originally posted by **GiulioCMSanto** February 7, 2025</sup>
Hello!! Before opening a Issue, I would like to start a discussion on something that looks like a bug! 😄
**The Issue**: when using `conditional_edge` the hidden state is ignored.
### Reproducing the Error
**Imports**
```
import uuid
from pydantic import BaseModel
from langgraph.checkpoint.memory import MemorySaver
from langgraph.graph import END, START, MessagesState, StateGraph
```
**States**
```
class InputType(BaseModel):
input: str
class OutputType(BaseModel):
output: str
```
**Nodes**
```
def node_1(state: InputType) -> MessagesState :
print(f"Node 1 input: {state}")
return {"messages": ["out_node_1"]}
def node_2(state: MessagesState) -> OutputType:
print(f"Node 2 input: {state}")
return OutputType(output="out_node_2")
def router(state: MessagesState) -> str:
print(f"Router input: {state}")
return "node_2"
```
**Notice:** **MessagesState** is a **Hidden State** here.
**The Graph**
```
builder = StateGraph(input=InputType, output=OutputType)
builder.add_node("node_1", node_1)
builder.add_node("node_2", node_2)
builder.add_edge(START, "node_1")
builder.add_conditional_edges(
"node_1",
router,
["node_2"]
)
builder.add_edge("node_2", END)
graph = builder.compile(checkpointer=MemorySaver())
config = {
"configurable": {
"thread_id": uuid.uuid4(),
}
}
graph.invoke(
InputType(input="Hi"),
config,
stream_mode="values"
)
```
#### Outcomes
```
Node 1 input: input='Hi'
Router input: input='Hi'
Node 2 input: {'messages': [HumanMessage(content='out_node_1', additional_kwargs={}, response_metadata={}, id='7c1b5467-d55a-4af7-9888-0bff210ca726')]}
```
### Comments
Notice that `Router input: input='Hi'` and not `{'messages': [HumanMessage(content='out_node_1', additional_kwargs={}, response_metadata={}, id='7c1b5467-d55a-4af7-9888-0bff210ca726')]}`. Node 2 actually have access to the Hidden State, but **not the Conditional Edge**.
### My Setup
```
Python Version: 3.9
langgraph==0.2.61
pydantic==2.10.4
```
I have also tried with
```
Python Version: 3.12
langgraph==0.2.70
pydantic==2.10.6
```
### Similar Discussion
I found a somehow similar discussion here: https://github.com/langchain-ai/langgraph/discussions/2197</div>
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| 2,856,294,820
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I_kwDOKFU0lc6qP5mk
| 3,464
|
[Urgent] LangGraph docker image fails to start
|
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| 2025-02-16T19:44:34
| 2025-02-18T09:48:26
| 2025-02-16T20:42:14
|
NONE
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
Pretty much any code. The error is on your level.
```
### Error Message and Stack Trace (if applicable)
```shell
Traceback (most recent call last):
File "/usr/local/bin/uvicorn", line 8, in <module>
sys.exit(main())
^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 412, in main
run(
File "/usr/local/lib/python3.11/site-packages/uvicorn/main.py", line 579, in run
server.run()
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 66, in run
return asyncio.run(self.serve(sockets=sockets))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 190, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 70, in serve
await self._serve(sockets)
File "/usr/local/lib/python3.11/site-packages/uvicorn/server.py", line 77, in _serve
config.load()
File "/usr/local/lib/python3.11/site-packages/uvicorn/config.py", line 435, in load
self.loaded_app = import_from_string(self.app)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/uvicorn/importer.py", line 19, in import_from_string
module = importlib.import_module(module_str)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/importlib/__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "<frozen importlib._bootstrap>", line 1204, in _gcd_import
File "<frozen importlib._bootstrap>", line 1176, in _find_and_load
File "<frozen importlib._bootstrap>", line 1147, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 690, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 940, in exec_module
File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
File "/api/langgraph_api/server.py", line 16, in <module>
File "/api/langgraph_api/api/__init__.py", line 8, in <module>
File "/api/langgraph_api/api/meta.py", line 6, in <module>
File "/api/langgraph_api/queue.py", line 20, in <module>
'Exception raised by Queue.get(block=0)/get_nowait().'
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/api/langgraph_api/stream.py", line 35, in <module>
File "/usr/local/lib/python3.11/site-packages/langgraph_storage/store.py", line 8, in <module>
from langgraph.store.postgres.aio import AsyncPostgresStore, PostgresIndexConfig
File "/usr/local/lib/python3.11/site-packages/langgraph/store/postgres/__init__.py", line 1, in <module>
from langgraph.store.postgres.aio import AsyncPostgresStore
File "/usr/local/lib/python3.11/site-packages/langgraph/store/postgres/aio.py", line 12, in <module>
from langgraph.checkpoint.postgres import _ainternal
File "/usr/local/lib/python3.11/site-packages/langgraph/checkpoint/postgres/__init__.py", line 12, in <module>
from langgraph.checkpoint.base import (
ImportError: cannot import name 'get_checkpoint_metadata' from 'langgraph.checkpoint.base' (/usr/local/lib/python3.11/site-packages/langgraph/checkpoint/base/__init__.py)
```
### Description
After re-building the image today, I get this error.
We need to golive tomorrow morning and it blocks everything.
How can we build docker images w/o relying on a black-box dependency that ruined our production for **several** times since the last few days?
Is there a way to build it w/o this dependency?
### System Info
Note: the command output is done on a mac machine, while the error is inside docker.
```
python -m langchain_core.sys_info
System Information
------------------
> OS: Darwin
> OS Version: Darwin Kernel Version 24.1.0: Thu Oct 10 21:06:57 PDT 2024; root:xnu-11215.41.3~3/RELEASE_ARM64_T6041
> Python Version: 3.11.5 (main, Feb 5 2025, 16:10:32) [Clang 16.0.0 (clang-1600.0.26.6)]
Package Information
-------------------
> langchain_core: 0.3.33
> langchain: 0.3.17
> langchain_community: 0.3.16
> langsmith: 0.2.11
> langchain_anthropic: 0.3.0
> langchain_openai: 0.2.10
> langchain_text_splitters: 0.3.5
> langgraph_api: 0.0.15
> langgraph_cli: 0.1.65
> langgraph_license: Installed. No version info available.
> langgraph_sdk: 0.1.48
> langgraph_storage: Installed. No version info available.
Optional packages not installed
-------------------------------
> langserve
Other Dependencies
------------------
> aiohttp: 3.11.12
> anthropic: 0.45.2
> async-timeout: Installed. No version info available.
> click: 8.1.8
> cryptography: 43.0.3
> dataclasses-json: 0.6.7
> defusedxml: 0.7.1
> httpx: 0.28.1
> httpx-sse: 0.4.0
> jsonpatch: 1.33
> jsonschema-rs: 0.25.1
> langgraph: 0.2.69
> langgraph-checkpoint: 2.0.10
> langsmith-pyo3: Installed. No version info available.
> numpy: 1.26.4
> openai: 1.55.3
> orjson: 3.10.15
> packaging: 24.2
> pydantic: 2.10.6
> pydantic-settings: 2.7.1
> pyjwt: 2.10.1
> python-dotenv: 1.0.1
> PyYAML: 6.0.2
> requests: 2.32.3
> requests-toolbelt: 1.0.0
> SQLAlchemy: 2.0.27
> sse-starlette: 2.1.3
> starlette: 0.45.3
> structlog: 24.4.0
> tenacity: 8.5.0
> tiktoken: 0.8.0
> typing-extensions: 4.12.2
> uvicorn: 0.34.0
> watchfiles: 1.0.4
> zstandard: Installed. No version info available.
```
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I_kwDOKFU0lc6qN8sR
| 3,460
|
Reducers for other state members apart from messages
|
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| 2025-02-16T00:13:29
| 2025-02-17T18:54:54
| 2025-02-17T18:54:53
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### Discussed in https://github.com/langchain-ai/langgraph/discussions/3459
<div type='discussions-op-text'>
<sup>Originally posted by **binarybeastt** February 16, 2025</sup>
from langgraph.graph.message import add_messages helps to append messages to the message list, how can we replicate this behavior for other types that are not messages, maybe documents, files, or images?</div>
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I_kwDOKFU0lc6qN0Jh
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exec format error during langgraph docker deployment
|
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| 2025-02-15T22:28:15
| 2025-02-18T05:08:01
| 2025-02-18T05:08:01
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### Checked other resources
- [x] This is a bug, not a usage question. For questions, please use GitHub Discussions.
- [x] I added a clear and detailed title that summarizes the issue.
- [x] I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
- [x] I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
### Example Code
```python
docker pull $DOCKERHUB_USERNAME/my-langgraph-server:latest
docker run -it --rm $DOCKERHUB_USERNAME/my-langgraph-server:latest
```
### Error Message and Stack Trace (if applicable)
```shell
exec /storage/entrypoint.sh: exec format error
exec /storage/entrypoint.sh: exec format error
exec /storage/entrypoint.sh: exec format error
```
### Description
I'm using langgraph-cli in Github Actions to build the docker image automatically with `langgraph build`. I'm following instructions (and using the docker-compose file) [from the docs here](https://langchain-ai.github.io/langgraph/how-tos/deploy-self-hosted/#using-docker-compose). Local testing with docker desktop works. However the built container keeps emitting `exec format error` when deployed on my Ubuntu server.
Debugging with Sonnet suggests it's an issue with incompatible architectures. I'm wondering if there is a way to use `langgraph build` with arguments. Any help appreciated!
.github/workflows/main.yml:
```
name: Build Docker Image
on:
push:
branches: [main]
jobs:
build-push:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.12'
- name: Build Docker image with Langgraph
run: |
pip install -U langgraph-cli
cd yuichan
langgraph build -t my-langgraph-server
- name: Login to Docker Registry
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_TOKEN }}
- name: Push Docker image
run: |
docker tag my-langgraph-server ${{ secrets.DOCKERHUB_USERNAME }}/my-langgraph-server:latest
docker push ${{ secrets.DOCKERHUB_USERNAME }}/yui-langgraph-server:latest
```
langgraph.json:
```
{
"dependencies": ["."],
"graphs":{
"yui": "./yuichan.py:graph"
},
"env": ".env",
"python_version": "3.12"
}
```
### System Info
- Ubuntu 24.04
- arm64 VPS on Oracle Cloud
- Docker version 27.4.1
requirements.txt:
langchain-core
langchain[openai,anthropic,groq,google-genai]
langchain-community
langchain-experimental
langchain-google-community[gmail]
langchainhub
langsmith
langgraph
langgraph-sdk
langgraph-checkpoint-postgres
pydantic
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| 2025-02-15T08:23:52
| 2025-02-15T21:08:43
| 2025-02-15T21:08:42
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### Issue with current documentation:
<img width="718" alt="Image" src="https://github.com/user-attachments/assets/9a045798-ea10-4c20-952c-c42b5eae070d" />
### Idea or request for content:
_No response_
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