Comments (1)
I have addressed this in version 0.57. You can now provide an indexSpec
parameter to the PineconeDb constructor that specifies the details of the new index. The environment variable PINECONE_ENVIRONMENT
is not required.
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Related Issues (20)
- Getting Started and Documentation Clarification HOT 2
- Limit token usage output parameter across all queried llm models
- Error during npm install HOT 11
- Allow conversation history to persist HOT 5
- Add Groq for super fast inference with LLM's (supported by Langchain)
- Add Amazon Bedrock (included in langchain)
- Add OllamaEmbedding (It is available in langchain) HOT 2
- Windows install problem version 0.0.89 HOT 2
- I'm trying to install the package on my window and get the following error: HOT 2
- response duplicate HOT 1
- Add Support for In Memory Vector Store Which stores everything in memory or in a flat file
- Add support for Elasticsearch for Vector database
- Maximum context length exceeded HOT 3
- throw new Error("OpenAI or Azure OpenAI API key or Token Provider not found"); HOT 2
- No Verbose option: unable to debug where the issue is. Also unable to track progress HOT 1
- Revisit - Embeddings Tokens In, Out, Total and Cost - Critical for hosting and using this library HOT 2
- Documentation needs to be updated for loaders (overlap and chunksize) as causing undefined errors when migrating
- Dependency issue when attempting to use vectordb (LanceDB) HOT 1
- issue for conversations path in package.json HOT 2
- Don't understand if embedder is working or not
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