Comments (2)
The error you're encountering is likely related to memory management issues within the underlying C extensions or libraries used by the timescale_vector
client. Here are some steps to help resolve this issue:
-
Update Dependencies: Ensure you have the latest versions of
llama-index
,timescale_vector
, and other dependencies. -
Check for Known Issues: Look for any reported issues on the GitHub repositories of
llama-index
andtimescale_vector
. -
Isolate the Problem: Create a minimal reproducible example to identify whether the issue is with the
TimescaleVectorStore
class or thetimescale_vector
client. -
Debugging: Use debugging tools to set breakpoints and inspect memory allocation. The error message suggests setting a breakpoint in
malloc_error_break
. -
Contact Support: If the issue persists, consider reaching out to the maintainers of the
llama-index
ortimescale_vector
packages.
Here's a minimal example to help isolate the problem:
from llama_index.legacy.vector_stores.timescalevector import TimescaleVectorStore
# Set up the Timescale service URL
TIMESCALE_SERVICE_URL = "postgres://tsdbadmin:<password>@<id>.tsdb.cloud.timescale.com:<port>/tsdb?sslmode=require"
# Create a TimescaleVectorStore instance
try:
vector_store = TimescaleVectorStore.from_params(
service_url=TIMESCALE_SERVICE_URL,
table_name="your_table_name_here",
)
print("Vector store created successfully.")
except Exception as e:
print(f"An error occurred: {e}")
Ensure that the timescale-vector
package is correctly installed and imported:
pip install timescale-vector
If the issue persists, you might need to provide more detailed logs or context for further assistance [1][2].
To continue talking to Dosu, mention @dosu.
from llama_index.
@Banjomaestro this seems like an issue with either your env or the timescale vector store package. Maybe you are missing some core libraries (i.e. not python libraries, but system libraries) on the machine you are running on?
It works fine on google colab
https://colab.research.google.com/drive/1krUnNZ6q47B0KoCkTAIWdE9t-oVaIUd5?usp=sharing
from llama_index.
Related Issues (20)
- [Question]: How to insert/delete document to/from VectorStoreIndex when using IngestionPipeline? HOT 2
- Compatibility issue between Qdrant and DSPy when Qdrant is used as the VectorStoreIndex's storage context HOT 5
- [Question]: AttributeError: 'property' object has no attribute 'context_window' HOT 1
- [Question]: The created knowledge graph does not have edge relationships neo4j HOT 13
- [Documentation]: Some of the URL Not Working HOT 3
- [Question]: Unable to understand how document storage works in case nodes are deleted HOT 1
- [Documentation]: Broken 'Examples' Link HOT 3
- [Feature Request]: Add a notebook to show llamaindex agent works with graphRAG and Vertex AI
- [Bug]: File rename error in llama-index-finetuning/llama_index/finetuning/mistralai/utils.py HOT 1
- [Question]: How to enable "Calling function" print out after querying from Multi-Document Agent example HOT 3
- [Question]: Access LLM's response object CompleteResponse() attribute `additional_kwarg` in RAG HOT 2
- [Bug]: Error in initializing neo4j HOT 2
- Indexes cannot be created correctly using the MilvusVectorStore. HOT 12
- How should the dim parameter value of MilvusVectorStore be calculated? HOT 4
- [Bug]: ERROR: Failed building wheel for pystemmer HOT 1
- How to deploy open-source embedding models in auto-merging retriever: ValueError: shapes (1024,) and (384,) not aligned: 1024 (dim 0) != 384 (dim 0) HOT 3
- [Bug]: No module named 'llama_index.llms.openai.base HOT 1
- [Bug]: [OpenAILike] Cannot use llm_chat_callback on an instance without a callback_manager attribute HOT 4
- [Feature Request]: Version pinning for sub packages HOT 2
- I wonder how to use llama_index to retrieve the Milvus collection after it is created and indexed using the MilvusVectorStore. HOT 4
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from llama_index.