Open Source Windows Large Language Models (LLM) - Page 2

This is an experimental search engine for conversational AI such as parl.ai, large language models such as OpenAI GPT3, and humans (maybe).

A git prepare-commit-msg hook for authoring commit messages with GPT-3. With this tool, you can easily generate clear, comprehensive and descriptive commit messages letting you focus on writing code. To use gptcommit, simply run git commit as you normally would. The hook will automatically generate a commit message for you using a large language model like GPT. If you're not satisfied with the generated message, you can always edit it before committing. By default, gptcommit uses the GPT-3 model. Please ensure you have sufficient credits in your OpenAI account to use it. Commit messages are a key channel for developers to communicate their work with others, especially in code reviews. When making complex code changes, it can be tedious to thoroughly document the contents of each change. I often felt the impulse to just title my commit “fix bug” and move on. Surfacing these changes with gptcommit helps the author and reviewer by bringing attention to these additional changes.

Output from a language model using standard input as the prompt. Now supporting GPT3.5 chat completions! gptee was designed for use within shell scripts and other programs and also works in interactive shells. You can compose commands and execute them in a script. Proceed with caution before running arbitrary shell scripts. Using a chat completion model (like gpt-3.5-turbo), you can then inject a system message with -s or --system messages. For davinci and other non-chat models, the output is prefixed to the prompt. Compose shell commands like you would in a script. Try with a custom model. By default gptee uses gpt-3.5-turbo.

Large Language Models (LLMs) are interesting and useful  -  building apps that use them responsibly feels like a no-brainer. Tools like Langchain make it easier to build apps using LLMs. We need to know details about how our apps work, even when we want to use tools with convenient abstractions that may obfuscate those details. Prefect is built to help data people build, run, and observe event-driven workflows wherever they want. It provides a framework for creating deployments on a whole slew of runtime environments (from Lambda to Kubernetes), and is cloud agnostic (best supports AWS, GCP, Azure). For this reason, it could be a great fit for observing apps that use LLMs. RecordLLMCalls is a ContextDecorator that can be used to track LLM calls made by Langchain LLMs as Prefect flows. Run several LLM calls via langchain agent as Prefect subflows.

I-powered CLI git wrapper, boilerplate code generator, chat history manager, and code search engine to streamline your dev workflow. The ChatGPT-powered swiss army knife for the modern developer! We provide an AI-powered CLI git wrapper, boilerplate code generator, code search engine, a conversation history manager, and much more! Configure the model used for generating responses by running mf config and selecting either GPT 3.5 Turbo (default) or GPT 4. In order to use GPT 4, you'll need to have special access to the API. If you have access, you can run mf config and select GPT 4. If you don't have access, you'll get an error message. Interact with chatGPT directly just like on the chatGPT website. We also have chat persistence, so it will remember the previous chat messages. You can provide single or multi-file context to chatGPT by passing in any number of files as a separate argument in the mf chat call.