⚡ Auto Prompting ⚡
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YiVal: Your Automatic Prompt Engineering Assistant for GenAI Applications YiVal is a state-of-the-art tool designed to streamline the tuning process for your GenAI app prompts and ANY configs in the loop. With YiVal, manual adjustments are a thing of the past. This data-driven and evaluation-centric approach ensures optimal prompts, precise RAG configurations, and fine-tuned model parameters. Empower your applications to achieve enhanced results, reduce latency, and minimize inference costs effortlessly with YiVal!
Problems YiVal trying to tackle:
- Prompt Development Challenge: "I can't create a better prompt. A score of 60 for my current prompt isn't helpful at all🤔."
- Fine-tuning Difficulty: "I don't know how to fine-tune; the terminology and numerous fine-tune algorithms are overwhelming😵."
- Confidence and Scalability: "I learned tutorials to build agents from Langchain and LlamaIndex, but am I doing it right? Will the bot burn through my money when I launch? Will users like my GenAI app🤯?"
- Models and Data Drift: "Models and data keep changing; I worry a well-performing GenAI app now may fail later😰."
- Relevant Metrics and Evaluators: "Which metrics and evaluators should I focus on for my use case📊?"
Check out our quickstart guide!
Install Docker and pull ourimage on DockerHub:
docker pull yival/release:latestRun our image:
docker run --it yival/release:latestVSCode with Docker extension is recommended for running and developments. If you are developer using GPU with Pytorch, or need jupyter lab for data science:
docker pull yival/release:cu12_torch_jupyter
docker run --gpus all --it -p 8888:8888 yival/release:cu12_torch_jupyter- Python Version: Ensure you have
Python 3.10or later installed. - OpenAI API Key: Obtain an API key from OpenAI. Once you have the key, set
it as an environment variable named
OPENAI_API_KEY.
Install the yival package directly using pip:
pip install yivalIf you're looking to contribute or set up a development environment:
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Install Poetry: If you haven't already, install Poetry.
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Clone the Repository, or use CodeSpace:
2.1 Use CodeSpace The easiest way to get YiVal enviornment. Click below to use the GitHub Codespace, then go to the next step.
2.2 Clone the Repository
git clone https://github.com/YiVal/YiVal.git cd YiVal -
Setup with Poetry: Initialize the Python virtual environment and install dependencies using Poetry. Make sure to run the below cmd in
/YiValdirectory:poetry install --sync
After setting up, you can quickly get started with YiVal by generating datasets of random tech startup business names.
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Navigate to the yival Directory:
cd /YiVal/src/yival -
Set OpenAI API Key: Replace
$YOUR_OPENAI_API_KEYwith your actual OpenAI API key.On macOS or Linux systems,
export OPENAI_API_KEY=$YOUR_OPENAI_API_KEY
On Windows systems,
setx OPENAI_API_KEY $YOUR_OPENAI_API_KEY -
Define YiVal Configuration: Create a configuration file named
config_data_generation.ymlfor automated test dataset generation with the following content:description: Generate test data dataset: data_generators: openai_prompt_data_generator: chunk_size: 100000 diversify: true model_name: gpt-4 input_function: description: # Description of the function Given a tech startup business, generate a corresponding landing page headline name: headline_generation_for_business parameters: tech_startup_business: str # Parameter name and type number_of_examples: 3 output_csv_path: generated_examples.csv source_type: machine_generated
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Execute YiVal: Run the following command from within the
/YiVal/src/yivaldirectory:yival run config_data_generation.yml
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Check the Generated Dataset: The generated test dataset will be stored in
generated_examples.csv.
Please refer to YiVal Docs Page for more details about YiVal!
Translation.Bot.mp4
| Use Case Demo | Supported Features | Github Link | Video Demo Link |
|---|---|---|---|
| 🐯 Craft your AI story with ChatGPT and MidJourney | Multi-modal support: Design an AI-powered narrative using YiVal's multi-modal support of simultaneous text and images. It supports native and seamless Reinforcement Learning from Human Feedback(RLHF) and Reinforcement Learning from AI Feedback(RLAIF). Please watch the video above for this use case. |  |
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| 🌟 Evaluate performance of multiple LLMs with your own Q&A test dataset | Convenientlyevaluate and compare performance of your model of choice against 100+ models, thanks to LiteLLM. Analyze model performance benchmarks tailored to your customized test data or use case. | |
|
| 🔥 Startup Company Headline Generation Bot | Streamline generation of headlines for your startup with automated test datacreation, prompt crafting, results evaluation, and performance enhancement via GPT-4. | |
|
| 🧳 Build a Customized Travel Guide Bot | Leverageautomated prompts inspired by the travel community's most popular suggestions, such as those from awesome-chatgpt-prompts. | |
|
| 📖 Build a Cheaper Translator: Use GPT-3.5 to teach Llama2 to create a translator with lower inference cost | UsingReplicate and GPT-3.5's test data, you can fine-tune Llama2's translation bot. Benefit from 18x savings while experiencing only a 6% performance decrease. | |
|
| 🤖️ Chat with Your Favorite Characters - Dantan Ji from Till the End of the Moon | Bring your favorite characters to life through automated prompt creation andcharacter script retrieval. | |
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| 🔍Evaluate guardrails's performance in generating Python(.py) outputs | Guardrails: where are my guardrails? 😭 <br>Yival: I am here. ⭐️<br><br>The integrated evaluation experiment is carried out with 80 LeetCode problems in csv, using guardrail and using only GPT-4. The accuracy drops from 0.625 to 0.55 with guardrail, latency increases by 44%, and cost increases by 140%. Guardrail still has a long way to go from demo to production. |
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| 🍨Visualize different foods around the world!🍱 | Just give the place where the food belongs and the best season to taste it, and you can get a video of the season-specific food!🤩 | |
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| 🎈News article summary with CoD | By integrating the"Chain of Density" method, evaluate the enhancer's ability in text summarization.🎆 Using 3 articles points generated by GPT-4 for evaluation, the coherent score increased by 20.03%, the attributive score increased by 25.18%!, the average token usage from 2054.6 -> 1473.4(-28.3%) 🚀. | |
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| 🥐 Automated TikTok Title Generation Bot | With only two input lines, you can easily createconcise and polished TikTok video titles based on your desired target audience and video content summaries. This is presented by our auto-prompt feature: the process is automated, so you can input your requirements and enjoy the results hassle-free! | |
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If you want to contribute to YiVal, be sure to review the contribution guidelines. We use GitHub issues for tracking requests and bugs. Please join YiVal's discord channel for general questions and discussion. Join our collaborative community where your unique expertise as researchers and software engineers is highly valued! Contribute to our project and be a part of an innovative space where every line of code and research insight actively fuels advancements in technology, fostering a future that is intelligently connected and universally accessible.
🌟 YiVal welcomes your contributions! 🌟
🥳 Thanks so much to all of our amazing contributors 🥳