GPTCache
shell_gpt
| GPTCache | shell_gpt | |
|---|---|---|
| 43 | 38 | |
| 6,446 | 8,341 | |
| 2.1% | - | |
| 7.7 | 8.0 | |
| about 1 month ago | 10 days ago | |
| Python | Python | |
| MIT License | 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.
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?
shell_gpt
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Oh My Zsh
https://github.com/TheR1D/shell_gpt?tab=readme-ov-file#shell...
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Is there a better way to feed my codebase to GPT than using this bash script? How could I bundle the source code more intelligently?
I would like to stay in the terminal, and am using https://github.com/TheR1D/shell_gpt, my format is simply to send GPT a file to discuss:
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Ask HN: How are you using LLMs in your command-line?
ShellGPT https://github.com/TheR1D/shell_gpt does pretty well for a lot of use cases. I mostly use it in REPL mode, switching topics as needed. I have wrappers around the `sgpt` command to, say, start a REPL with a particular topic, say, Python, which loads my previous history on that topic as part of the prompt.
I also have an alias to save existing chats as text files so I can go back and review history.
Finally, there is an alias to load a question up in an editor if I need to enter multiline text, e.g. to discuss code fragments, etc.
I expect command-line workflows to be pretty individualized and I'm curious what others do. For me (old programmer), using a command line REPL feels much more natural (and blissfully noise-free) than going to a Web page to talk to, say, ChatGPT.
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ChatGPT web and mobile UIs unavailable
The API still works. I've been using https://github.com/TheR1D/shell_gpt/ in my workflow.
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Gorilla-CLI: LLMs for CLI including K8s/AWS/GCP/Azure/sed and 1500 APIs
I recommend shell-gpt[1] for anyone with access to the OpenAI API. It works surprisingly well considering how simple it is. Be sure to browse the examples in the README.
[1] https://github.com/TheR1D/shell_gpt
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englizsh: Zsh plugin to interface command-line GPT programs intuitively through keybindings
Nice idea. You may want to mention in the docs that it requires https://github.com/TheR1D/shell_gpt ;)
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Sideloaded my app on an old second hand smartwarch, opened a shell and talked to AI on my wrist
I honestly bought the device just to play with the wearable version of my android app: a voice controlled ssh client that let me also pass voice input to shell_gpt. Other pre installed apps won't really work on this device, including google assistant, so I had to switch to google cloud speech to text APIs for speech recognition. I can still sideload compatible apps via bluetooth debugging tho
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Can I integrate my local LLM to enable it to run system commands and execute local code?
Maybe this can help : https://github.com/TheR1D/shell_gpt
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CLI to convert natural language to terminal commands
I'm not really following these but they tend to get released every other day, like https://github.com/nlml/YoCLI/ and https://github.com/TheR1D/shell_gpt
- LLM, ttok and strip-tags–CLI tools for working with ChatGPT and other LLMs
What are some alternatives?
guardrails - Adding guardrails to large language models.
gorilla-cli - LLMs for your CLI
ai-shell - A CLI that converts natural language to shell commands.
danswer - Gen-AI Chat for Teams - Think ChatGPT if it had access to your team's unique knowledge.
YoCLI - yo lets you find the the CLI command you are looking for by asking in natural language
DB-GPT - AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents
butterfish - A shell with AI superpowers
gpt4free - The official gpt4free repository | various collection of powerful language models
mods - AI on the command line
sheetgpt - ChatGPT integration with Google Sheets
shell-gpt-rs - Ask ChatGPT for a shell script, code, or anything, directly from your terminal 🤖🧠👨💻