telegram-chatgpt-concierge-bot
phasellm
| telegram-chatgpt-concierge-bot | phasellm | |
|---|---|---|
| 4 | 14 | |
| 1,123 | 443 | |
| - | - | |
| 5.6 | 8.9 | |
| 4 months ago | 3 months ago | |
| TypeScript | Python | |
| - | MIT License |
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telegram-chatgpt-concierge-bot
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Cloud Tools You Probably Haven't Heard Of
Thanks to a generative AI model, ChatWithCloud allows users to interact with and manage their AWS cloud infrastructure using natural language commands in their terminal. Some key capabilities mentioned include:
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April 2023
Telegram ChatGPT Concierge Bot (+ Voice!) (https://github.com/RafalWilinski/telegram-chatgpt-concierge-bot)
- Personal Concierge Using OpenAI's ChatGPT via Telegram and Voice Messages
phasellm
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Ask HN: Any recommended AI tools to analyze data and generate insights?
If you're looking for an open source solution you can customize, check out the ResearchLLM demo: https://phasellm.com/researchllm
Code: https://github.com/wgryc/phasellm/tree/main/demos-and-produc...
- PhaseLLM Eval: run batch LLM jobs and evals via visual front-end (MIT licensed)
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To everyone who is using alternative bots (e.g. Claude) - your comparisons?
Using Claude, Cohere, GPT-4, OpenAssistant. Formally swapping between them using PhaseLLM (open source library similar to LangChain).
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April 2023
Large language model evaluation and workflow framework from Phase AI. (https://github.com/wgryc/phasellm)
- Ask HN: Freelancer? Seeking freelancer? (June 2023)
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ResearchGPT: Automated Data Analysis and Interpretation
Fantastic questions! Re: working/not working at times -- this is still an issue. It's why I'm building PhaseLLM more broadly (https://github.com/wgryc/phasellm) -- need a robust pipeline that can also "reset" parts of itself if an LLM makes errors or mistakes.
You can see my prompts in this file: https://github.com/wgryc/phasellm/blob/main/demos-and-produc... I autogenerate a fairly big starting prompt and keep resubmitting it. It describes the data set extensively, which helps quite a bit.
That being said, a lot more can be done here around prompt optimization + making this more robust.
- ResearchGPT: LLMs to write stats code, analyze, and interpret results for you
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Best way to use GPT offline with own content?
That being said, you might want to actually run head-to-head tests between models. PhaseLLM (free, open source) allows you to build a workflow and plug and play various models (including Dolly 2.0 and GPT-4). Then you can run tests to see how much worse/better the various LLMs are and if that's acceptable for your use case.
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12-Apr-2023 AI Summary
Large language model evaluation and workflow framework from Phase AI. (https://github.com/wgryc/phasellm)
- PhaseLLM: Standardized Chat LLM API (Cohere, Claude, GPT) + Evaluation Framework
What are some alternatives?
Flowise - Drag & drop UI to build your customized LLM flow
awesome-chatgpt - 🧠A curated list of awesome ChatGPT resources, including libraries, SDKs, APIs, and more. 🌟 Please consider supporting this project by giving it a star.
E2B - Secure cloud runtime for AI apps & AI agents. Fully open-source.
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
turbopilot - Turbopilot is an open source large-language-model based code completion engine that runs locally on CPU
rel-events - The relevant React Events Library.
prompt-engineering - ChatGPT Prompt Engineering for Developers - deeplearning.ai
kivy - Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS
vocode-python - 🤖 Build voice-based LLM agents. Modular + open source.
llm-apex-agents - Run Large Language Model "Agents" in Salesforce apex