PromptTools is a Python framework for testing and experimenting with prompts, language models, and vector databases.
The tool addresses the challenge of evaluating LLM behavior and vector database performance across different configurations and providers. It allows developers to systematically test prompts and parameters against multiple models—including OpenAI, Anthropic, LLaMA, Mistral, Google Gemini, and others—without switching between different interfaces. The framework also supports evaluating retrieval accuracy across vector databases like Chroma, Weaviate, Qdrant, LanceDB, and Pinecone. Users can work through familiar interfaces: Python code, Jupyter notebooks, or a local web-based playground powered by Streamlit.
The tool suits developers who need to compare LLM outputs across providers or tune prompts systematically before deployment. It works well for teams evaluating vector database retrieval quality or experimenting with different embedding strategies. The playground interface lowers the barrier for non-technical stakeholders to participate in prompt evaluation, while the code-based approach integrates naturally into development workflows. The framework supports LangChain and LlamaIndex, making it compatible with existing LLM application stacks.
The project maintains active support across a broad range of LLM providers and vector databases, with most integrations marked as supported and a few in exploratory or in-progress stages. Documentation is comprehensive, with a full API reference available online. The team operates a Discord community channel for issue discussion and updates. A hosted version of the playground is available on Streamlit Community Cloud, though it does not support local LLaMA execution.
