temporian
GPTCache
| temporian | GPTCache | |
|---|---|---|
| 12 | 43 | |
| 629 | 6,446 | |
| 2.6% | 2.1% | |
| 9.8 | 7.7 | |
| 4 days ago | about 1 month ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
temporian
GPTCache
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Ask HN: What are the drawbacks of caching LLM responses?
Just found this: https://github.com/zilliztech/GPTCache which seems to address this idea/issue.
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Open Source Advent Fun Wraps Up!
21. GPTCache | Github | tutorial
- Semantic Cache
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Show HN: Danswer – open-source question answering across all your docs
Check this out. Built on a vector database (https://github.com/milvus-io/milvus) and a semantic cache (https://github.com/zilliztech/GPTCache)
https://osschat.io/
- GPTCache
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Ask HN: Is LLM Caching Necessary?
With the proliferation of large models, an increasing number of enterprises and individual developers are now developing applications based on these models. As such, it is worth considering whether large model caching is necessary during the development process.
Our project: https://github.com/zilliztech/GPTCache
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Gorilla-CLI: LLMs for CLI including K8s/AWS/GCP/Azure/sed and 1500 APIs
Maybe [GPTCache](https://github.com/zilliztech/GPTCache) can make it more attractive, because similar problems can be less expensive, and can also be responded to faster. Of course, the specific configuration needs to be based on real usage scenarios.
- Limited budget or machine resources, how to achieve a decent LLM experience?
What are some alternatives?
functime - Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
guardrails - Adding guardrails to large language models.
OpenVoice - Instant voice cloning by MyShell.
gorilla-cli - LLMs for your CLI
tsflex - Flexible time series feature extraction & processing
danswer - Gen-AI Chat for Teams - Think ChatGPT if it had access to your team's unique knowledge.
hamilton - Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
DB-GPT - AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
gpt4free - The official gpt4free repository | various collection of powerful language models
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
sheetgpt - ChatGPT integration with Google Sheets