download-simulator-2023
lmql
| download-simulator-2023 | lmql | |
|---|---|---|
| 1 | 30 | |
| 0 | 3,375 | |
| - | 4.4% | |
| 1.4 | 9.5 | |
| 9 months ago | 15 days ago | |
| Go | Python | |
| - | Apache License 2.0 |
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download-simulator-2023
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Ask HN: What's your favorite GPT powered tool?
- Drafting an action plan and coming up with open questions based on specific requirements (issue: https://github.com/mobyvb/download-simulator-2023/issues/1, PR created by bot: https://github.com/mobyvb/download-simulator-2023/pull/2/fil...)
lmql
- Show HN: Fructose, LLM calls as strongly typed functions
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Prompting LLMs to constrain output
have been experimenting with guidance and lmql. a bit too early to give any well formed opinions but really do like the idea of constraining llm output.
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[D] Prompt Engineering Seems Like Guesswork - How To Evaluate LLM Application Properly?
the only time i've ever felt like it was anything other than guesswork was using LMQL . not coincidentally, LMQL works with LLMs as autocomplete engines rather than q&a ones.
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Guidance for selecting a function-calling library?
lqml
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Show HN: Magentic – Use LLMs as simple Python functions
This is also similar in spirit to LMQL
https://github.com/eth-sri/lmql
- Show HN: LLMs can generate valid JSON 100% of the time
- LangChain Agent Simulation – Multi-Player Dungeons and Dragons
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The Problem with LangChain
LLM calls are just function calls, so most functional composition is already afforded by any general-purpose language out there. If you need fancy stuff, use something like Python‘s functools.
Working on https://github.com/eth-sri/lmql (shameless plug, sorry), we have always found that compositional abstractions on top of LMQL are mostly there already, once you internalize prompts being functions.
- Is there a UI that can limit LLM tokens to a preset list?
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Local LLMs: After Novelty Wanes
LMQL is another.
What are some alternatives?
pull-pal - A digital assistant that writes code and collaborates with humans on git repositories
guidance - A guidance language for controlling large language models.
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
ChatVRM
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
chisel - Open source writing app
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
midi-looper
guardrails - Adding guardrails to large language models.
plz-cli - Copilot for your terminal
basaran - Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.