Comments (2)
Spartee
commented on August 17, 2024
1
@bibinbalakrishnan this is a good point. We can make that change. We're about to cut 0.0.5, but this can make it into the next release. It'll be on main shortly.
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tylerhutcherson
commented on August 17, 2024
For now, we are deprecating from_existing as it causes too many issues for this layer in the client architecture and there's not enough need for this yet. Higher level clients like LangChain and LlamaIndex will retain similar patterns. For redisvl, all you have to do is provide your schema to the client and it will continue to work!
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Related Issues (20)
- Docstring error on schema `distance_metrics` -> `distance_metric`
- Automate docs build for future releases
- Support for OpenAI API >= 1.0.0 HOT 1
- Switch to poetry for package management HOT 4
- [Feat] Support for binary and scalar embedding quantization HOT 1
- Issue with search dialect 3 and JSON HOT 4
- How to access aws bed rock embedding models for vectorizer? HOT 1
- How to hold / cache a SemanticCache instance? HOT 2
- Improve & Enrich the LLM client implementation for TextVectorizer HOT 4
- Add Index Alias management capabilities HOT 4
- Adding a filter_expression to an existing VectorQuery is not always working HOT 2
- ValueError: Required Redis database module searchlight with version >= 20600 not installed. Refer to Redis Stack documentation: HOT 9
- Simplify the chaining of queries HOT 1
- Add Session Management Feat. HOT 4
- Redis semantic cache working with custom embeddings HOT 4
- Provide the utility to count the token saved using Semantic Cache
- How to apply filter on a semantic cache check() function HOT 3
- Usage of redisvl with redis without redis stack server HOT 1
- IndexError: list index out of range while applying filter on semantic cache check HOT 9
- Incorrect number of embedding dimensions in the YAML schema in README.md HOT 1
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