Merge pull request Hannibal046#76 from Xin-Jing/main

Adding Prompting libraries & tools

README.md

@@ -310,6 +310,28 @@ The above tables coule be better summarized by this wonderful visualization from
 - [IntelliServer](https://github.com/intelligentnode/IntelliServer) - simplifies the evaluation of LLMs by providing a unified microservice to access and test multiple AI models.
 
 
+## Prompting libraries & tools
+
+- [YiVal](https://github.com/YiVal/YiVal) — Evaluate and Evolve: YiVal is an open-source GenAI-Ops tool for tuning and evaluating prompts, configurations, and model parameters using customizable datasets, evaluation methods, and improvement strategies.
+- [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.
+- [Chainlit](https://docs.chainlit.io/overview) — A Python library for making chatbot interfaces.
+- [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.
+- [Prompttools](https://github.com/hegelai/prompttools) — Open-source Python tools for testing and evaluating models, vector DBs, 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.
+- [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.
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 ## Tutorials about LLM
 - [Andrej Karpathy] State of GPT [video](https://build.microsoft.com/en-US/sessions/db3f4859-cd30-4445-a0cd-553c3304f8e2)
 - [Hyung Won Chung] Instruction finetuning and RLHF lecture [Youtube](https://www.youtube.com/watch?v=zjrM-MW-0y0)