Verta Reviews

Meet Ape, our first AI prompt engineer. Equipped with tracing and dataset curation. Batch testing, evals, and evalus. Ape achieved an impressive 93% in the GSM8K benchmark. This is higher than DSPy (86%), and base LLMs (70%) Continuously optimize prompts by using real-world data. Integrating CI/CD can prevent performance regression. Human-in-the loop with feedback and scoring. Ape uses the Weavel SDK in order to automatically log your dataset and add LLM generation as you use it. This allows for seamless integration and continuous improvements specific to your use cases. Ape automatically generates evaluation code and relies on LLMs to be impartial judges for complex tasks. This streamlines your assessment process while ensuring accurate and nuanced performance metrics. Ape is reliable because it works under your guidance and feedback. Ape will improve if you send in scores and tips. Equipped with logging and testing for LLM applications.

ChainForge is a visual programming environment that is open-source and designed for large language model evaluation. It allows users to evaluate the robustness and accuracy of text-generation models and prompts beyond anecdotal data. Test prompt ideas and variations simultaneously across multiple LLMs in order to identify the most efficient combinations. Evaluate response quality for different prompts, models and settings to determine the optimal configuration. Set up evaluation metrics, and visualize results for prompts, parameters and models. This will facilitate data-driven decisions. Manage multiple conversations at once, template follow-ups, and inspect the outputs to refine interactions. ChainForge supports a variety of model providers including OpenAI HuggingFace Anthropic Google PaLM2, Azure OpenAI Endpoints and locally hosted models such as Alpaca and Llama. Users can modify model settings and use visualization nodes.