"RuntimeError: Event loop is closed During task" when ChatOllama is not a global and is not inside of function

[ChellShort]

Checked other resources

• I added a very descriptive title to this question.
• I searched the LangChain documentation with the integrated search.
• I used the GitHub search to find a similar question and didn't find it.

Commit to Help

• I commit to help with one of those options 👆

Example Code

class State(TypedDict):
    messages: Annotated[list, add_messages]
    filters: dict
    context_t: str
    llm: ChatOllama
    embeddings: OllamaEmbeddings

async def retrieve_context(state):
    filters = state.get("filters", {})
    embeddings = state.get("embeddings", {})
    if filters:
        context = await get_context(filters)
    else:
        user_messages = ""
        for doc in state["messages"]:
            user_messages += f"{str(doc.content)}\n\n"
        logging.info(f"User messages: {user_messages}")
        rrk_original, context_rrk = search_documents(os.getenv("RERANKER"), embeddings, user_messages)
        logging.info(f"Contexto original: {rrk_original}")
        logging.info(f"Contexto aplicando filtro de score: {context_rrk}")
        context = context_rrk
    return {"context_t": context}

async def retrieve_devices(state):
    llm = state.get("llm", {})
    user_input = state["messages"]  
    context_t = state["context_t"]
    prompt = ChatPromptTemplate.from_template(os.getenv("TEMPLATE2"))
    retrieval_chain = (
        {"context": lambda x: context_t, "question": RunnablePassthrough()}
        | prompt
        | llm
        | StrOutputParser()
    )
    response = await retrieval_chain.ainvoke(user_input)
    return {"messages": [{"role": "assistant", "content": response}]}

def define_graph():
    memory = MemorySaver()
    graph_builder = StateGraph(State)
    graph_builder.add_node("retrieve_context", retrieve_context)
    graph_builder.add_node("retrieve_devices", retrieve_devices)
    graph_builder.add_edge(START, "retrieve_context")
    graph_builder.add_edge("retrieve_context", "retrieve_devices")
    graph_builder.add_edge("retrieve_devices", END)
    graph = graph_builder.compile(checkpointer=memory)
    # display_graph(graph) if input("Mostrar graph? (y/n)").lower() == "y" else None
    return graph

async def stream_graph_updates(graph, stream, config):
    contenido=""
    async for msg, metadata in graph.astream(
        stream,
        config,
        stream_mode="messages",
    ):
        if msg.content and "retrieve_devices" in metadata['langgraph_node']:
            contenido+=msg.content
            # print(msg.content, end="", flush=True)
            yield msg.content
    logging.info(f"Respuesta:: {contenido}")


if __name__ == "__main__":

    import asyncio

    llm = ChatOllama(model=os.getenv("LLM")) 
    embeddings = OllamaEmbeddings(model=os.getenv("EMBEDDING_MODEL"))

    config=...

    graph = define_graph()

    while True:
        choice = ""
        choice = input("Desea buscar dentro del catalogo? (y/n): ").lower() == "y"
        if choice:
            ... Here I define the filters to use for my CSV search
        else:
            ... Here I use the user input for semantic search
        stream={"messages": [{"role": "user", "content": user_input}], "filters": filters, 'llm': llm, 
        'embeddings': embeddings}

        gc.collect()
        torch.cuda.empty_cache()

        async def main():
            async for i in stream_graph_updates(graph, stream, config):
                print(i, end="", flush=True)

        asyncio.run(main())

        logging.info("FIN DE LA PREGUNTA\n")

Description

I'm trying to make a RAG application where I can use a csv search to bring laptop models from a csv and semantic search to bring info of the components of those computers. But when I try to define Ollama in the "if name == "main":" and pass it through state, right at the second question of the "while" cycle, this error pops up:

File "C:\Users\iapracticante3\miniconda3\envs\Ollama_langchain\Lib\asyncio\base_events.py", line 520, in _check_closed
raise RuntimeError('Event loop is closed')
RuntimeError: Event loop is closed

During task with name 'retrieve_devices' and id '62ab0be5-0744-44ee-7103-eb6c6a86ff15'

I found two workarounds to this, first I could move the ChatOllama definition inside of the "retrieve devices" function or define it as a global variable to make it work; but honestly, I still would like to put in the main function, but I still don't know why this occurs.

System Info

Python Version: 3.11.11

Platform: Windows

Pip Freeze:

accelerate==1.5.2
aiofiles==24.1.0
aiohappyeyeballs @ file:///home/conda/feedstock_root/build_artifacts/aiohappyeyeballs_1739175731979/work
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aiosignal @ file:///home/conda/feedstock_root/build_artifacts/aiosignal_1734342155601/work
annotated-types @ file:///home/conda/feedstock_root/build_artifacts/annotated-types_1733247046149/work
antlr4-python3-runtime==4.9.3
anyio @ file:///home/conda/feedstock_root/build_artifacts/anyio_1736174388474/work
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asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1733250440834/work
async-timeout @ file:///home/conda/feedstock_root/build_artifacts/async-timeout_1691763562544/work
attr==0.3.1
attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1737819173731/work
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data==0.4
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django-filter==24.3
django-migration-linter==5.1.0
django-model-utils==4.1.1
django-ranged-fileresponse==0.1.2
django-rq==2.10.3
django-storages==1.12.3
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google-crc32c==1.7.0
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hpack @ file:///home/conda/feedstock_root/build_artifacts/hpack_1737618293087/work
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ijson==3.3.0
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ir_datasets==0.5.10
isodate==0.7.2
isort==5.13.2
jedi @ file:///home/conda/feedstock_root/build_artifacts/jedi_1733300866624/work
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jsf==0.11.2
jsonpatch @ file:///home/conda/feedstock_root/build_artifacts/jsonpatch_1733814567314/work
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keyboard==0.13.5
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label-studio-sdk==1.0.10
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langchain-cli==0.0.35
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mdurl==0.1.2
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olefile==0.47
ollama==0.4.7
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opencv-python==4.11.0.86
openpyxl==3.1.5
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opentelemetry-exporter-otlp-proto-common==1.30.0
opentelemetry-exporter-otlp-proto-grpc==1.30.0
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pandas @ file:///D:/bld/pandas_1726878554493/work
parso @ file:///home/conda/feedstock_root/build_artifacts/parso_1733271261340/work
pathspec==0.12.1
pdf2image==1.17.0
pdfkit==1.0.0
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pfzy==0.3.4
pi_heif==0.22.0
pickleshare @ file:///home/conda/feedstock_root/build_artifacts/pickleshare_1733327343728/work
pikepdf==9.5.2
pillow==11.0.0
platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1733232627818/work
portalocker==2.10.1
postgrest==0.19.3
posthog==3.14.2
primp==0.14.0
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propcache @ file:///D:/bld/propcache_1737635564183/work
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protobuf==5.29.3
psutil @ file:///D:/bld/psutil_1735327360263/work
psycopg2-binary==2.9.10
pure_eval @ file:///home/conda/feedstock_root/build_artifacts/pure_eval_1733569405015/work
pyarrow==19.0.1
pyasn1==0.6.1
pyasn1_modules==0.4.1
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pybind11_global @ file:///D:/bld/pybind11-split_1730237329882/work
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pycocotools==2.0.8
pycparser @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_pycparser_1733195786/work
pydantic @ file:///home/conda/feedstock_root/build_artifacts/pydantic_1737761369378/work
pydantic-settings==2.7.1
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pymilvus==2.5.6
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pypdfium2==4.30.1
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pyproject_hooks==1.2.0
pyreadline3==3.5.4
pyRFC3339==2.0.1
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python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1733215673016/work
python-dotenv==1.0.1
python-iso639==2025.2.18
python-json-logger==2.0.4
python-magic==0.4.27
python-multipart==0.0.20
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pytz==2022.7.1
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pyzmq @ file:///D:/bld/pyzmq_1738270978316/work
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rank-bm25==0.2.2
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requests @ file:///home/conda/feedstock_root/build_artifacts/requests_1733217035951/work
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requests-toolbelt @ file:///home/conda/feedstock_root/build_artifacts/requests-toolbelt_1733734787568/work
rich==13.9.4
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ruff==0.9.9
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scikit-learn @ file:///D:/bld/scikit-learn_1736496780928/work/dist/scikit_learn-1.6.1-cp311-cp311-win_amd64.whl#sha256=b8f37c282c66c737a09228918d0bfcadafb9f1d4bfb1dc6289040870d453703b
scipy @ file:///C:/bld/scipy-split_1739790799455/work/dist/scipy-1.15.2-cp311-cp311-win_amd64.whl#sha256=7d4ec4c2c958f31576b5ea44433874f567d6f5e65bfcde22e2d960ac86b80515
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semver==3.0.4
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threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1714400101435/work
tiktoken==0.9.0
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toml==0.10.2
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torchaudio==2.6.0+cu124
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transformers @ file:///home/conda/feedstock_root/build_artifacts/transformers_1739826231190/work
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tzdata @ file:///home/conda/feedstock_root/build_artifacts/python-tzdata_1737541069190/work
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watchfiles==1.0.4
wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1733231326287/work
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xxhash @ file:///D:/bld/python-xxhash_1725272140818/work
yarl @ file:///D:/bld/yarl_1737575828275/work
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1732827521216/work
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