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People are writing great tools and papers for improving outputs from GPT. Here are some cool ones we've seen:
## Prompting libraries & tools
## Prompting libraries & tools (in alphabetical order)
- [Guidance](https://github.com/microsoft/guidance): A handy looking Python library from Microsoft that uses Handlebars templating to interleave generation, prompting, and logical control.
- [LangChain](https://github.com/hwchase17/langchain): A popular Python/JavaScript library for chaining sequences of language model prompts.
- [FLAML (A Fast Library for Automated Machine Learning & Tuning)](https://microsoft.github.io/FLAML/docs/Getting-Started/): A Python library for automating selection of models, hyperparameters, and other tunable choices.
- [Arthur Shield](https://www.arthur.ai/get-started): A paid product for detecting toxicity, hallucination, prompt injection, etc.
- [Chainlit](https://docs.chainlit.io/overview): A Python library for making chatbot interfaces.
- [FLAML (A Fast Library for Automated Machine Learning & Tuning)](https://microsoft.github.io/FLAML/docs/Getting-Started/): A Python library for automating selection of models, hyperparameters, and other tunable choices.
- [Guardrails.ai](https://shreyar.github.io/guardrails/): A Python library for validating outputs and retrying failures. Still in alpha, so expect sharp edges and bugs.
- [Semantic Kernel](https://github.com/microsoft/semantic-kernel): A Python/C#/Java library from Microsoft that supports prompt templating, function chaining, vectorized memory, and intelligent planning.
- [YiVal](https://github.com/YiVal/YiVal): An open-source GenAI-Ops tool for tuning and evaluating prompts, retrieval configurations, and model parameters using customizable datasets, evaluation methods, and evolution strategies.
- [Prompttools](https://github.com/hegelai/prompttools): Open-source Python tools for testing and evaluating models, vector DBs, and prompts.
- [Guidance](https://github.com/microsoft/guidance): A handy looking Python library from Microsoft that uses Handlebars templating to interleave generation, prompting, and logical control.
- [Haystack](https://github.com/deepset-ai/haystack): Open-source LLM orchestration framework to build customizable, production-ready LLM applications in Python.
- [LangChain](https://github.com/hwchase17/langchain): A popular Python/JavaScript library for chaining sequences of language model prompts.
- [LlamaIndex](https://github.com/jerryjliu/llama_index): A Python library for augmenting LLM apps with data.
- [LMQL](https://lmql.ai): A programming language for LLM interaction with support for typed prompting, control flow, constraints, and tools.
- [OpenAI Evals](https://github.com/openai/evals): An open-source library for evaluating task performance of language models and prompts.
- [Outlines](https://github.com/normal-computing/outlines): A Python library that provides a domain-specific language to simplify prompting and constrain generation.
- [Promptify](https://github.com/promptslab/Promptify): A small Python library for using language models to perform NLP tasks.
- [Scale Spellbook](https://scale.com/spellbook): A paid product for building, comparing, and shipping language model apps.
- [PromptPerfect](https://promptperfect.jina.ai/prompts): A paid product for testing and improving prompts.
- [Prompttools](https://github.com/hegelai/prompttools): Open-source Python tools for testing and evaluating models, vector DBs, and prompts.
- [Scale Spellbook](https://scale.com/spellbook): A paid product for building, comparing, and shipping language model apps.
- [Semantic Kernel](https://github.com/microsoft/semantic-kernel): A Python/C#/Java library from Microsoft that supports prompt templating, function chaining, vectorized memory, and intelligent planning.
- [Weights & Biases](https://wandb.ai/site/solutions/llmops): A paid product for tracking model training and prompt engineering experiments.
- [OpenAI Evals](https://github.com/openai/evals): An open-source library for evaluating task performance of language models and prompts.
- [LlamaIndex](https://github.com/jerryjliu/llama_index): A Python library for augmenting LLM apps with data.
- [Arthur Shield](https://www.arthur.ai/get-started): A paid product for detecting toxicity, hallucination, prompt injection, etc.
- [LMQL](https://lmql.ai): A programming language for LLM interaction with support for typed prompting, control flow, constraints, and tools.
- [Haystack](https://github.com/deepset-ai/haystack): Open-source LLM orchestration framework to build customizable, production-ready LLM applications in Python.
- [YiVal](https://github.com/YiVal/YiVal): An open-source GenAI-Ops tool for tuning and evaluating prompts, retrieval configurations, and model parameters using customizable datasets, evaluation methods, and evolution strategies.
## Prompting guides
- [Brex's Prompt Engineering Guide](https://github.com/brexhq/prompt-engineering): Brex's introduction to language models and prompt engineering.
- [promptingguide.ai](https://www.promptingguide.ai/): A prompt engineering guide that demonstrates many techniques.
- [OpenAI Cookbook: Techniques to improve reliability](https://github.com/openai/openai-cookbook/blob/main/techniques_to_improve_reliability.md): A slightly dated (Sep 2022) review of techniques for prompting language models.
- [Lil'Log Prompt Engineering](https://lilianweng.github.io/posts/2023-03-15-prompt-engineering/): An OpenAI researcher's review of the prompt engineering literature (as of March 2023).
- [learnprompting.org](https://learnprompting.org/): An introductory course to prompt engineering.
- [Lil'Log Prompt Engineering](https://lilianweng.github.io/posts/2023-03-15-prompt-engineering/): An OpenAI researcher's review of the prompt engineering literature (as of March 2023).
- [OpenAI Cookbook: Techniques to improve reliability](https://github.com/openai/openai-cookbook/blob/main/techniques_to_improve_reliability.md): A slightly dated (Sep 2022) review of techniques for prompting language models.
- [promptingguide.ai](https://www.promptingguide.ai/): A prompt engineering guide that demonstrates many techniques.
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