dosubot[bot]
commented
6 months ago The error you're encountering, "ConnectionError(Timeout context manager should be used inside a task)," suggests that the asynchronous operation with OpenSearch is being executed outside of an async function or context. To resolve this, ensure your code interacts with OpenSearch within an async context. Here's a structured approach:
-
Async Function: Wrap your OpenSearch query logic within an
asyncfunction. This ensures that the asynchronous code is executed within the correct context. -
Await Async Operations: Use
awaitfor asynchronous calls, such as querying OpenSearch, to wait for their completion within the async function. -
Async Context Manager: If using a context manager (e.g., for managing connections), use
async withto ensure it's handled asynchronously.
Here's an example to guide you:
import asyncio
from opensearchpy import AsyncOpenSearch
async def query_opensearch():
opensearch_url = 'http://localhost:9200' # Replace with your details
async with AsyncOpenSearch(
opensearch_url,
http_compress=True, # Optional
) as client:
response = await client.search(index="index_name", body={"query": {"match_all": {}}})
print(response)
if __name__ == "__main__":
asyncio.run(query_opensearch())This code demonstrates the correct way to perform asynchronous operations with OpenSearch, ensuring they're executed within an async context to avoid the "ConnectionError" you're experiencing.
For further troubleshooting, especially if adapting the code doesn't resolve the issue, providing more context about your execution environment (e.g., script, Jupyter notebook) could help identify additional factors contributing to the problem.
#### Details
**Sources** - [[Question]: vector_store.add(nodes) gives me error = opensearchpy.exceptions.ConnectionTimeout: ConnectionTimeout caused by - TimeoutError()](https://github.com/run-llama/llama_index/issues/13110) - [[Bug]: *** RuntimeError: Timeout context manager should be used inside a task](https://github.com/run-llama/llama_index/issues/9520) - [llama-index-core/llama_index/core/instrumentation/dispatcher.py](https://github.com/run-llama/llama_index/blob/main/llama-index-core/llama_index/core/instrumentation/dispatcher.py) - [llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/llama_index/vector_stores/opensearch/base.py](https://github.com/run-llama/llama_index/blob/main/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/llama_index/vector_stores/opensearch/base.py) - [llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/base.py](https://github.com/run-llama/llama_index/blob/main/llama-index-integrations/indices/llama-index-indices-managed-vectara/llama_index/indices/managed/vectara/base.py) - [llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/pyproject.toml](https://github.com/run-llama/llama_index/blob/main/llama-index-integrations/vector_stores/llama-index-vector-stores-opensearch/pyproject.toml) - [llama-index-integrations/retrievers/llama-index-retrievers-pathway/tests/BUILD](https://github.com/run-llama/llama_index/blob/main/llama-index-integrations/retrievers/llama-index-retrievers-pathway/tests/BUILD)**About Dosu** This response is meant to be useful and save you time. It is **not meant to be a precise solution**, but rather a starting point for your own research. Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.
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logan-markewich
chrfthr
GaLebel
Bug Description
After upgrading from 0.9.3 I get a connection error when querying my OpenSearch vectorstore. I'm not sure if I should post this here or open an opensearch-py issue..
I have llama-index installed in the following conda environment with Pyhton 3.10.0:
channels:
Version
0.13.34
Steps to Reproduce
Query a RetrieverQueryEngine built from a VectorIndexRetriever, a VectorStoreIndex and an OpensearchVectorStore. I implemented a custom version of the VectorIndexRetriever, but this should not be relevant as the error also appeared when using the library retriever. The custom vector retriever is also wrapped in a custom retriever.
Relevant Logs/Tracbacks