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Intermittent InvalidSqlStatementName: prepared statement "_pg3_4" does not exist Error with AsyncPostgresSaver in LangGraph #329

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opened 2026-02-20 17:36:44 -05:00 by yindo · 8 comments
yindo commented 2026-02-20 17:36:44 -05:00
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Originally created by @Zolastic on GitHub (Nov 28, 2024).

Checked other resources

  • I added a very descriptive title to this issue.
  • I searched the LangGraph/LangChain documentation with the integrated search.
  • I used the GitHub search to find a similar question and didn't find it.
  • I am sure that this is a bug in LangGraph/LangChain rather than my code.
  • I am sure this is better as an issue rather than a GitHub discussion, since this is a LangGraph bug and not a design question.

Example Code

import os
from dotenv import load_dotenv

from pydantic import BaseModel, ConfigDict, Field
from typing import Annotated, Optional, Dict, Any, List
from typing_extensions import TypedDict
import traceback

from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage, AIMessage, ToolMessage
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.tools import BaseTool

from langgraph.graph.message import AnyMessage
from langgraph.graph import StateGraph, END
from langgraph.graph.graph import CompiledGraph
from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver

import json
from uuid import uuid4

# Load environment variables
load_dotenv(override=True)

class State(TypedDict):
    query: Annotated[str, "The user's query"] = ""
    messages: Annotated[list[AnyMessage], "The messages exchanged with the assistant"] = []
    intent_response: Annotated[Optional[Dict[str, Any]], "The response from the intent assistant"] = None
    response_sent: Annotated[bool, "Flag to indicate if the response has been sent."] = False

class ProductAssistant(BaseModel):
    name: str
    builder: Optional[StateGraph] = Field(default=None, exclude=True)
    graph: Optional[CompiledGraph] = None

    model_config = ConfigDict(arbitrary_types_allowed=True)

    def __init__(self, **kwargs):
        super().__init__(**kwargs)
        self.builder = StateGraph(State)

        # Adding nodes to the graph
        self.builder.add_node("main_assistant", self.main_assistant)
        self.builder.add_node("intent_assistant", self.intent_assistant)
        self.builder.add_node("generic_reply_assistant", self.generic_reply_assistant)
        self.builder.add_node("single_product_assistant", self.single_product_assistant)
        self.builder.add_node("multiple_products_assistant", self.multiple_products_assistant)
        self.builder.add_node("call_tool", self.call_tool)
        self.builder.add_node("clean_and_respond", self.clean_and_respond)

        self.builder.set_entry_point("main_assistant")

        self.builder.add_conditional_edges(
            "main_assistant",
            self.should_call_tool,
            {
                "continue": "call_tool",
                "end": "intent_assistant"
            }
        )

        self.builder.add_conditional_edges(
            "call_tool",
            self.should_call_tool,
            {
                "continue": "call_tool",
                "end": "main_assistant",
            }
        )

        self.builder.add_conditional_edges(
            "intent_assistant",
            self.assistant_to_call,
        )

        self.builder.add_edge("single_product_assistant", "clean_and_respond")
        self.builder.add_edge("multiple_products_assistant", "clean_and_respond")

        self.builder.add_edge("clean_and_respond", END)

    def main_assistant(self, state: State, config):
        messages = state["messages"]

        # Build the prompt (implementation omitted for brevity)
        prompt_builder: ChatPromptTemplate = ...  # Your prompt setup here
        prompt = prompt_builder.invoke(state)

        model = ChatOpenAI(model="gpt-4o-mini")

        tools = self.create_tools()

        model = model.bind_tools(tools, parallel_tool_calls=False)

        response = model.invoke(prompt)

        if hasattr(response, "tool_calls") and response.tool_calls:
            messages.append(response)

            tool_names = [tool_call["name"] for tool_call in response.tool_calls]
            print(f"Tool detected and appended: {tool_names}")
        else:
            print("No tool detected.")

        return {"messages": messages}

    # ... [Other methods omitted for brevity] ...

    def create_tools(
        self,
    ) -> List[BaseTool]:
        # Tools are created here (implementation omitted)
        return [fetch_products, fetch_product_details, fetch_terms_and_conditions]

    async def invoke(
        self,
        query: str,
        user_metadata: Optional[Dict[str, Any]] = None,
        search_config: Optional[Dict[str, Any]] = None,
    ):
        thread_id = uuid4().hex

        config = {
            "configurable": {"thread_id": thread_id},
            "user_metadata": user_metadata or None,
            "search_config": search_config or None,
        }

        initial_state: State = {
            "messages": [HumanMessage(content=query)],
            "query": query,
            "response_sent": False,
        }

        async with AsyncPostgresSaver.from_conn_string(os.getenv("DATABASE_URL", "")) as async_memory:
            await async_memory.setup()
            self.graph = self.builder.compile(checkpointer=async_memory)

            try:
                async for event in self.graph.astream_events(initial_state, config, version="v2"):
                    event_type = event.get('event')
                    event_data = event.get('data')

                    if event_type == "on_chain_stream":
                        chunk = event_data.get('chunk', {})
                        response_sent = chunk.get('response_sent', False)

                        messages = chunk.get('messages', [])
                        if messages:
                            last_ai_message = next(
                                (msg.content for msg in reversed(messages) if isinstance(msg, AIMessage)), None
                            )

                            if last_ai_message and response_sent:
                                if last_ai_message and isinstance(last_ai_message, str):
                                    try:
                                        structured_response_dict = json.loads(last_ai_message)
                                        yield json.dumps(structured_response_dict)
                                    except json.JSONDecodeError:
                                        last_ai_message = last_ai_message.replace('"', "'")
                                        yield json.dumps({"message": last_ai_message})

            except Exception as e:
                print(f"Error in invoking the assistant: {str(e)}")
                traceback.print_exc()

Error Message and Stack Trace (if applicable)

Error in invoking the assistant: prepared statement "_pg3_4" does not exist
Traceback (most recent call last):
  File "/path/to/product_assistant.py", line 442, in invoke
    async for event in self.graph.astream_events(initial_state, config, version="v2"):
  File "/path/to/langchain_core/runnables/base.py", line 1388, in astream_events
    async for event in event_stream:
  File "/path/to/langchain_core/tracers/event_stream.py", line 1012, in _astream_events_implementation_v2
    await task
  File "/path/to/langchain_core/tracers/event_stream.py", line 967, in consume_astream
    async for _ in event_streamer.tap_output_aiter(run_id, stream):
  File "/path/to/langchain_core/tracers/event_stream.py", line 203, in tap_output_aiter
    async for chunk in output:
  File "/path/to/langgraph/pregel/__init__.py", line 1823, in astream
    async with AsyncPregelLoop(
               ^^^^^^^^^^^^^^^^
  File "/path/to/langgraph/pregel/loop.py", line 1011, in __aexit__
    return await asyncio.shield(
           ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/contextlib.py", line 754, in __aexit__
    raise exc_details[1]
  File "/usr/local/lib/python3.12/contextlib.py", line 737, in __aexit__
    cb_suppress = await cb(*exc_details)
                  ^^^^^^^^^^^^^^^^^^^^^^
  File "/path/to/langgraph/pregel/executor.py", line 191, in __aexit__
    raise exc
  File "/path/to/langgraph/checkpoint/postgres/aio.py", line 320, in aput_writes
    async with self._cursor(pipeline=True) as cur:
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/contextlib.py", line 217, in __aexit__
    await anext(self.gen)
  File "/path/to/langgraph/checkpoint/postgres/aio.py", line 349, in _cursor
    async with self.lock, conn.pipeline(), conn.cursor(
                          ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/contextlib.py", line 217, in __aexit__
    await anext(self.gen)
  File "/path/to/psycopg/connection_async.py", line 398, in pipeline
    async with pipeline:
               ^^^^^^^^
  File "/path/to/psycopg/_pipeline.py", line 266, in __aexit__
    raise exc2.with_traceback(None)
psycopg.errors.InvalidSqlStatementName: prepared statement "_pg3_4" does not exist

Description

I'm trying to use LangGraph with Supabase PostgreSQL as my database. I have an assistant implemented in product_assistant.py that uses AsyncPostgresSaver for asynchronous database operations. My assistant works fine most of the time, but sometimes it throws the following error:

psycopg.errors.InvalidSqlStatementName: prepared statement "_pg3_4" does not exist

This error seems to occur intermittently, and I haven't been able to identify a consistent pattern.

Additional Information:

  • My tools, which are invoked by the assistant, also make database calls using SQLAlchemy (synchronous operations).

  • I suspect that mixing asynchronous database operations (via AsyncPostgresSaver in LangGraph) and synchronous database operations (via SQLAlchemy in my tools) might be causing conflicts or unexpected behavior.

  • I have tried removing any explicit DEALLOCATE ALL statements, but the error still occurs.

  • Occasionally, I also encounter another error:

    psycopg.OperationalError: the connection is closed

    This error also happens intermittently, similar to the InvalidSqlStatementName error.

Question:

How can I resolve this intermittent InvalidSqlStatementName error? Is there a recommended way to handle database operations in tools when using LangGraph, especially when both the assistant and the tools make database calls? Should I refactor my tools to use asynchronous database sessions? Any guidance on how to solve this issue would be greatly appreciated.

System Info

  • LangGraph Version: 0.2.53
  • Python Version: 3.12
  • Langgraph Checkpoint Postgres Version: 2.0.3
  • Operating System: MacOS
Originally created by @Zolastic on GitHub (Nov 28, 2024). ### Checked other resources - [X] I added a very descriptive title to this issue. - [X] I searched the [LangGraph](https://langchain-ai.github.io/langgraph/)/LangChain documentation with the integrated search. - [X] I used the GitHub search to find a similar question and didn't find it. - [X] I am sure that this is a bug in LangGraph/LangChain rather than my code. - [X] I am sure this is better as an issue [rather than a GitHub discussion](https://github.com/langchain-ai/langgraph/discussions/new/choose), since this is a LangGraph bug and not a design question. ### Example Code ```python import os from dotenv import load_dotenv from pydantic import BaseModel, ConfigDict, Field from typing import Annotated, Optional, Dict, Any, List from typing_extensions import TypedDict import traceback from langchain_openai import ChatOpenAI from langchain_core.messages import HumanMessage, AIMessage, ToolMessage from langchain_core.prompts import ChatPromptTemplate from langchain_core.tools import BaseTool from langgraph.graph.message import AnyMessage from langgraph.graph import StateGraph, END from langgraph.graph.graph import CompiledGraph from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver import json from uuid import uuid4 # Load environment variables load_dotenv(override=True) class State(TypedDict): query: Annotated[str, "The user's query"] = "" messages: Annotated[list[AnyMessage], "The messages exchanged with the assistant"] = [] intent_response: Annotated[Optional[Dict[str, Any]], "The response from the intent assistant"] = None response_sent: Annotated[bool, "Flag to indicate if the response has been sent."] = False class ProductAssistant(BaseModel): name: str builder: Optional[StateGraph] = Field(default=None, exclude=True) graph: Optional[CompiledGraph] = None model_config = ConfigDict(arbitrary_types_allowed=True) def __init__(self, **kwargs): super().__init__(**kwargs) self.builder = StateGraph(State) # Adding nodes to the graph self.builder.add_node("main_assistant", self.main_assistant) self.builder.add_node("intent_assistant", self.intent_assistant) self.builder.add_node("generic_reply_assistant", self.generic_reply_assistant) self.builder.add_node("single_product_assistant", self.single_product_assistant) self.builder.add_node("multiple_products_assistant", self.multiple_products_assistant) self.builder.add_node("call_tool", self.call_tool) self.builder.add_node("clean_and_respond", self.clean_and_respond) self.builder.set_entry_point("main_assistant") self.builder.add_conditional_edges( "main_assistant", self.should_call_tool, { "continue": "call_tool", "end": "intent_assistant" } ) self.builder.add_conditional_edges( "call_tool", self.should_call_tool, { "continue": "call_tool", "end": "main_assistant", } ) self.builder.add_conditional_edges( "intent_assistant", self.assistant_to_call, ) self.builder.add_edge("single_product_assistant", "clean_and_respond") self.builder.add_edge("multiple_products_assistant", "clean_and_respond") self.builder.add_edge("clean_and_respond", END) def main_assistant(self, state: State, config): messages = state["messages"] # Build the prompt (implementation omitted for brevity) prompt_builder: ChatPromptTemplate = ... # Your prompt setup here prompt = prompt_builder.invoke(state) model = ChatOpenAI(model="gpt-4o-mini") tools = self.create_tools() model = model.bind_tools(tools, parallel_tool_calls=False) response = model.invoke(prompt) if hasattr(response, "tool_calls") and response.tool_calls: messages.append(response) tool_names = [tool_call["name"] for tool_call in response.tool_calls] print(f"Tool detected and appended: {tool_names}") else: print("No tool detected.") return {"messages": messages} # ... [Other methods omitted for brevity] ... def create_tools( self, ) -> List[BaseTool]: # Tools are created here (implementation omitted) return [fetch_products, fetch_product_details, fetch_terms_and_conditions] async def invoke( self, query: str, user_metadata: Optional[Dict[str, Any]] = None, search_config: Optional[Dict[str, Any]] = None, ): thread_id = uuid4().hex config = { "configurable": {"thread_id": thread_id}, "user_metadata": user_metadata or None, "search_config": search_config or None, } initial_state: State = { "messages": [HumanMessage(content=query)], "query": query, "response_sent": False, } async with AsyncPostgresSaver.from_conn_string(os.getenv("DATABASE_URL", "")) as async_memory: await async_memory.setup() self.graph = self.builder.compile(checkpointer=async_memory) try: async for event in self.graph.astream_events(initial_state, config, version="v2"): event_type = event.get('event') event_data = event.get('data') if event_type == "on_chain_stream": chunk = event_data.get('chunk', {}) response_sent = chunk.get('response_sent', False) messages = chunk.get('messages', []) if messages: last_ai_message = next( (msg.content for msg in reversed(messages) if isinstance(msg, AIMessage)), None ) if last_ai_message and response_sent: if last_ai_message and isinstance(last_ai_message, str): try: structured_response_dict = json.loads(last_ai_message) yield json.dumps(structured_response_dict) except json.JSONDecodeError: last_ai_message = last_ai_message.replace('"', "'") yield json.dumps({"message": last_ai_message}) except Exception as e: print(f"Error in invoking the assistant: {str(e)}") traceback.print_exc() ``` ### Error Message and Stack Trace (if applicable) ```shell Error in invoking the assistant: prepared statement "_pg3_4" does not exist Traceback (most recent call last): File "/path/to/product_assistant.py", line 442, in invoke async for event in self.graph.astream_events(initial_state, config, version="v2"): File "/path/to/langchain_core/runnables/base.py", line 1388, in astream_events async for event in event_stream: File "/path/to/langchain_core/tracers/event_stream.py", line 1012, in _astream_events_implementation_v2 await task File "/path/to/langchain_core/tracers/event_stream.py", line 967, in consume_astream async for _ in event_streamer.tap_output_aiter(run_id, stream): File "/path/to/langchain_core/tracers/event_stream.py", line 203, in tap_output_aiter async for chunk in output: File "/path/to/langgraph/pregel/__init__.py", line 1823, in astream async with AsyncPregelLoop( ^^^^^^^^^^^^^^^^ File "/path/to/langgraph/pregel/loop.py", line 1011, in __aexit__ return await asyncio.shield( ^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/contextlib.py", line 754, in __aexit__ raise exc_details[1] File "/usr/local/lib/python3.12/contextlib.py", line 737, in __aexit__ cb_suppress = await cb(*exc_details) ^^^^^^^^^^^^^^^^^^^^^^ File "/path/to/langgraph/pregel/executor.py", line 191, in __aexit__ raise exc File "/path/to/langgraph/checkpoint/postgres/aio.py", line 320, in aput_writes async with self._cursor(pipeline=True) as cur: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/contextlib.py", line 217, in __aexit__ await anext(self.gen) File "/path/to/langgraph/checkpoint/postgres/aio.py", line 349, in _cursor async with self.lock, conn.pipeline(), conn.cursor( ^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/contextlib.py", line 217, in __aexit__ await anext(self.gen) File "/path/to/psycopg/connection_async.py", line 398, in pipeline async with pipeline: ^^^^^^^^ File "/path/to/psycopg/_pipeline.py", line 266, in __aexit__ raise exc2.with_traceback(None) psycopg.errors.InvalidSqlStatementName: prepared statement "_pg3_4" does not exist ``` ### Description I'm trying to use LangGraph with Supabase PostgreSQL as my database. I have an assistant implemented in `product_assistant.py` that uses `AsyncPostgresSaver` for asynchronous database operations. My assistant works fine most of the time, but sometimes it throws the following error: ``` psycopg.errors.InvalidSqlStatementName: prepared statement "_pg3_4" does not exist ``` This error seems to occur intermittently, and I haven't been able to identify a consistent pattern. **Additional Information:** - My tools, which are invoked by the assistant, also make database calls using SQLAlchemy (synchronous operations). - I suspect that mixing asynchronous database operations (via `AsyncPostgresSaver` in LangGraph) and synchronous database operations (via SQLAlchemy in my tools) might be causing conflicts or unexpected behavior. - I have tried removing any explicit `DEALLOCATE ALL` statements, but the error still occurs. - Occasionally, I also encounter another error: ``` psycopg.OperationalError: the connection is closed ``` This error also happens intermittently, similar to the `InvalidSqlStatementName` error. **Question:** How can I resolve this intermittent `InvalidSqlStatementName` error? Is there a recommended way to handle database operations in tools when using LangGraph, especially when both the assistant and the tools make database calls? Should I refactor my tools to use asynchronous database sessions? Any guidance on how to solve this issue would be greatly appreciated. ### System Info - **LangGraph Version:** 0.2.53 - **Python Version:** 3.12 - **Langgraph Checkpoint Postgres Version:** 2.0.3 - **Operating System:** MacOS
yindo closed this issue 2026-02-20 17:36:44 -05:00
yindo commented 2026-02-20 17:36:44 -05:00
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@Zolastic commented on GitHub (Nov 28, 2024):

After further investigation, I've discovered that the issue arises when one of my tools makes a database call. Specifically, when the assistant invokes a tool that interacts with the database using SQLAlchemy, I intermittently encounter the following error:

psycopg.errors.InvalidSqlStatementName: prepared statement "_pg3_4" does not exist

Relevant Code:

Here are the key snippets of my tools:

# tools.py

from langchain_core.tools import tool
from dxs.gerica.repository.sql import ProductSQLRepository
from dxs.gerica.utils.sql_utils import get_database_session
from .utils import Citation, Product as ProductDetails

@tool(
    "fetch_products",
    response_format="content_and_artifact"
)
def fetch_products():
    try:
        db_session = get_database_session()
        product_repository = ProductSQLRepository(session=db_session)
        products = product_repository.fetch_all()

        if not products:
            return "No products found."

        context_str = "<products>\n"
        for product in products:
            context_str += f"""
            <product>
                <id>{product.id}</id>
                <name>{product.name}</name>
                <summary>{product.summary or 'N/A'}</summary>
                <description>{product.description or 'N/A'}</description>
            </product>
            """
        context_str += "</products>"

        citations = [
            Citation(
                id="",
                type="URL",
                title="Example Products Page",
                url="https://www.example.com/products",
                checksum="",
            )
        ]

        return context_str, {"citations": citations}
    finally:
        db_session.close()

@tool(
    "fetch_product_details",
    response_format="content_and_artifact"
)
def fetch_product_details(product_ids):
    try:
        db_session = get_database_session()
        product_repository = ProductSQLRepository(session=db_session)

        products = [product_repository.find_one(pid) for pid in product_ids]
        if not products:
            return "No products found for the given IDs."

        product_details = []
        context_str = "<products>\n"
        for product in products:
            context_str += f"""
            <product>
                <id>{product.id}</id>
                <name>{product.name}</name>
                <summary>{product.summary}</summary>
                <description>{product.description}</description>
            </product>
            """
            product_details.append(ProductDetails(id=product.id, name=product.name))

        context_str += "</products>"

        citations = [
            Citation(id=product.id, type="URL", title=product.name, url=product.product_page_url or "")
            for product in products
        ]

        return context_str, {"product_details": product_details, "citations": citations}
    finally:
        db_session.close()

# sql_utils.py

import os
import sqlalchemy as sa
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
from dotenv import load_dotenv

load_dotenv()

def get_database_session():
    db_url = os.getenv("DATABASE_URL")
    db = sa.create_engine(db_url)
    Session = sessionmaker(bind=db)
    return Session()

Base = declarative_base()

Observation:

  • The tools use synchronous database calls (SQLAlchemy with a synchronous engine).
  • The error seems to be related to a conflict between the synchronous database operations and the asynchronous components of LangGraph, which rely on AsyncPostgresSaver.
  • The error occurs intermittently, suggesting a possible issue with connection management or prepared statement handling.

Request for Assistance:

Would refactoring my tools to use asynchronous database sessions (e.g., SQLAlchemy AsyncIO) resolve this issue? Are there other steps I should take to prevent this conflict between synchronous and asynchronous database interactions?

Any guidance or recommendations would be greatly appreciated! Thank you.

@Zolastic commented on GitHub (Nov 28, 2024): After further investigation, I've discovered that the issue arises when one of my tools makes a database call. Specifically, when the assistant invokes a tool that interacts with the database using SQLAlchemy, I intermittently encounter the following error: ``` psycopg.errors.InvalidSqlStatementName: prepared statement "_pg3_4" does not exist ``` **Relevant Code:** Here are the key snippets of my tools: ```python # tools.py from langchain_core.tools import tool from dxs.gerica.repository.sql import ProductSQLRepository from dxs.gerica.utils.sql_utils import get_database_session from .utils import Citation, Product as ProductDetails @tool( "fetch_products", response_format="content_and_artifact" ) def fetch_products(): try: db_session = get_database_session() product_repository = ProductSQLRepository(session=db_session) products = product_repository.fetch_all() if not products: return "No products found." context_str = "<products>\n" for product in products: context_str += f""" <product> <id>{product.id}</id> <name>{product.name}</name> <summary>{product.summary or 'N/A'}</summary> <description>{product.description or 'N/A'}</description> </product> """ context_str += "</products>" citations = [ Citation( id="", type="URL", title="Example Products Page", url="https://www.example.com/products", checksum="", ) ] return context_str, {"citations": citations} finally: db_session.close() @tool( "fetch_product_details", response_format="content_and_artifact" ) def fetch_product_details(product_ids): try: db_session = get_database_session() product_repository = ProductSQLRepository(session=db_session) products = [product_repository.find_one(pid) for pid in product_ids] if not products: return "No products found for the given IDs." product_details = [] context_str = "<products>\n" for product in products: context_str += f""" <product> <id>{product.id}</id> <name>{product.name}</name> <summary>{product.summary}</summary> <description>{product.description}</description> </product> """ product_details.append(ProductDetails(id=product.id, name=product.name)) context_str += "</products>" citations = [ Citation(id=product.id, type="URL", title=product.name, url=product.product_page_url or "") for product in products ] return context_str, {"product_details": product_details, "citations": citations} finally: db_session.close() ``` ```python # sql_utils.py import os import sqlalchemy as sa from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base from dotenv import load_dotenv load_dotenv() def get_database_session(): db_url = os.getenv("DATABASE_URL") db = sa.create_engine(db_url) Session = sessionmaker(bind=db) return Session() Base = declarative_base() ``` --- **Observation:** - The tools use synchronous database calls (`SQLAlchemy` with a synchronous engine). - The error seems to be related to a conflict between the synchronous database operations and the asynchronous components of LangGraph, which rely on `AsyncPostgresSaver`. - The error occurs intermittently, suggesting a possible issue with connection management or prepared statement handling. --- **Request for Assistance:** Would refactoring my tools to use asynchronous database sessions (e.g., `SQLAlchemy AsyncIO`) resolve this issue? Are there other steps I should take to prevent this conflict between synchronous and asynchronous database interactions? Any guidance or recommendations would be greatly appreciated! Thank you.
yindo commented 2026-02-20 17:36:44 -05:00
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@HasnainKhanNiazi commented on GitHub (Dec 13, 2024):

@Zolastic I am also facing the same issue. I am using Supabase and in one of my tool, I am calling database with psycopg2 and with psycopg2.connect() and it is giving me the same error.

@HasnainKhanNiazi commented on GitHub (Dec 13, 2024): @Zolastic I am also facing the same issue. I am using Supabase and in one of my tool, I am calling database with `psycopg2` and with `psycopg2.connect()` and it is giving me the same error.
yindo commented 2026-02-20 17:36:44 -05:00
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@HasnainKhanNiazi commented on GitHub (Dec 13, 2024):

I did another test by removing the database calling from tools and it is still giving me the same error.

psycopg.errors.DuplicatePreparedStatement: prepared statement "_pg3_1" already exists

@HasnainKhanNiazi commented on GitHub (Dec 13, 2024): I did another test by removing the database calling from tools and it is still giving me the same error. `psycopg.errors.DuplicatePreparedStatement: prepared statement "_pg3_1" already exists `
yindo commented 2026-02-20 17:36:45 -05:00
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@vbarda commented on GitHub (Dec 16, 2024):

@Zolastic could you try using a connection pool and see if this resolves your issue? https://langchain-ai.github.io/langgraph/how-tos/persistence_postgres/#use-async-connection

@vbarda commented on GitHub (Dec 16, 2024): @Zolastic could you try using a connection pool and see if this resolves your issue? https://langchain-ai.github.io/langgraph/how-tos/persistence_postgres/#use-async-connection
yindo commented 2026-02-20 17:36:46 -05:00
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@HasnainKhanNiazi commented on GitHub (Dec 17, 2024):

@vbarda I used connection pool but I am still getting the same issue.

@HasnainKhanNiazi commented on GitHub (Dec 17, 2024): @vbarda I used `connection pool` but I am still getting the same issue.
yindo commented 2026-02-20 17:36:48 -05:00
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@HasnainKhanNiazi commented on GitHub (Dec 18, 2024):

I changed keyword arguments to: connection_kwargs = { "autocommit": True, "prepare_threshold": None, }

prepare_threshold": None and it is working for me now.

@HasnainKhanNiazi commented on GitHub (Dec 18, 2024): I changed keyword arguments to: `connection_kwargs = { "autocommit": True, "prepare_threshold": None, }` `prepare_threshold": None` and it is working for me now.
yindo commented 2026-02-20 17:36:49 -05:00
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@vbarda commented on GitHub (Dec 18, 2024):

Will close due to inactivity, but let me know if you're still running into issues and the above suggestions re: connection pool / prepare_threshold don't resolve them

@vbarda commented on GitHub (Dec 18, 2024): Will close due to inactivity, but let me know if you're still running into issues and the above suggestions re: connection pool / `prepare_threshold` don't resolve them
yindo commented 2026-02-20 17:36:51 -05:00
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@Jackoder commented on GitHub (Dec 27, 2024):

@vbarda After calling checkpoint.setup(), I can only see checkpoint_blobs, checkpoint_migrations, checkpoint_writes and checkpoints tables. And it throws error when I execute docker run.

  • command
docker run --env-file .env -p 8123:8000 -e REDIS_URI="redis:<…>:6379" -e DATABASE_URI="postgres://postgres:postgres@<…>:5432/postgres?sslmode=disable" -e LANGSMITH_API_KEY="<…>" expert_system
  • Error
2024-12-27T14:14:59.759516Z [error    ] Traceback (most recent call last):
  File "/usr/local/lib/python3.11/site-packages/starlette/routing.py", line 693, in lifespan
    async with self.lifespan_context(app) as maybe_state:
  File "/usr/local/lib/python3.11/contextlib.py", line 210, in __aenter__
    return await anext(self.gen)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/api/langgraph_api/lifespan.py", line 29, in lifespan
  File "/usr/local/lib/python3.11/site-packages/langgraph_storage/database.py", line 148, in start_pool
    await migrate()
  File "/usr/local/lib/python3.11/site-packages/langgraph_storage/database.py", line 108, in migrate
    await cur.execute(stmt.strip(), prepare=False)
  File "/usr/local/lib/python3.11/site-packages/psycopg/cursor_async.py", line 97, in execute
    raise ex.with_traceback(None)
psycopg.errors.UndefinedTable: relation "thread" does not exist
@Jackoder commented on GitHub (Dec 27, 2024): @vbarda After calling `checkpoint.setup()`, I can only see `checkpoint_blobs`, `checkpoint_migrations`, `checkpoint_writes` and `checkpoints` tables. And it throws error when I execute docker run. - command ``` docker run --env-file .env -p 8123:8000 -e REDIS_URI="redis:<…>:6379" -e DATABASE_URI="postgres://postgres:postgres@<…>:5432/postgres?sslmode=disable" -e LANGSMITH_API_KEY="<…>" expert_system ``` - Error ``` 2024-12-27T14:14:59.759516Z [error ] Traceback (most recent call last): File "/usr/local/lib/python3.11/site-packages/starlette/routing.py", line 693, in lifespan async with self.lifespan_context(app) as maybe_state: File "/usr/local/lib/python3.11/contextlib.py", line 210, in __aenter__ return await anext(self.gen) ^^^^^^^^^^^^^^^^^^^^^ File "/api/langgraph_api/lifespan.py", line 29, in lifespan File "/usr/local/lib/python3.11/site-packages/langgraph_storage/database.py", line 148, in start_pool await migrate() File "/usr/local/lib/python3.11/site-packages/langgraph_storage/database.py", line 108, in migrate await cur.execute(stmt.strip(), prepare=False) File "/usr/local/lib/python3.11/site-packages/psycopg/cursor_async.py", line 97, in execute raise ex.with_traceback(None) psycopg.errors.UndefinedTable: relation "thread" does not exist ```
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