prompttools
PromptTools is an open-source Python library for testing, experimenting, and evaluating LLMs, prompts, and vector databases. It supports multiple LLM providers (OpenAI, Anthropic, LLaMA, Mistral, Google) and vector databases (Chroma, Weaviate, Pinecone, LanceDB), with both code-based and UI-based playground interfaces.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | hegelai/prompttools |
| Owner | hegelai |
| Primary language | Python |
| License | Apache-2.0 — OSI-approved |
| Stars | 3k |
| Forks | 256 |
| Open issues | 41 |
| Latest release | v0.0.45 (2024-01-02) |
| Last updated | 2026-02-11 |
| Source | https://github.com/hegelai/prompttools |
What prompttools is
Python-based experiment framework providing structured APIs for multi-model prompt evaluation, parameter sweeps, and vector database retrieval assessment. Includes local execution without server forwarding, Jupyter notebook integration, and Streamlit playground UI. Supports 10+ LLM integrations and 6+ vector database backends.
Get the prompttools source
Clone the repository and explore it locally.
git clone https://github.com/hegelai/prompttools.gitcd prompttools# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Requires local API keys (OpenAI, Anthropic, etc.) to be configured; no authentication broker provided by the library.
- Latest release v0.0.45 (Jan 2024) indicates active development with pre-1.0 API stability. Breaking changes possible in minor versions.
- Sentry error tracking is enabled by default; opt-out via SENTRY_OPT_OUT environment variable if telemetry concerns exist.
- For Streamlit playground deployment, ensure LlamaCpp limitations are understood (not supported in hosted cloud version).
- CSV/JSON/MongoDB export options exist for result persistence; design experiment structure to fit chosen export format early.
When to avoid it — and what to weigh
- Production Monitoring at Scale — Library is designed for development-phase experimentation and testing. Not positioned as an observability or production monitoring platform for live LLM applications.
- Fine-Tuning or Model Training — PromptTools evaluates and tests existing models; it does not support model fine-tuning workflows or training pipeline orchestration.
- Real-time Inference Serving — Focused on batch experimentation in notebooks and local playground. Does not provide inference serving, API gateway, or high-throughput request routing.
- Proprietary LLM Integrations Required — If your primary LLM is not in the supported list (OpenAI, Anthropic, Mistral, Google, Azure, Replicate, HuggingFace, LLaMA.Cpp, Ollama), integration effort is needed.
License & commercial use
Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved open-source license allowing commercial use, modification, and distribution with proper attribution and liability disclaimers.
Apache-2.0 permits commercial use. However, confirm with legal review: (1) the license file in the repo matches stated Apache-2.0 terms, (2) third-party dependencies' licenses are compatible with your deployment model, and (3) usage of proprietary LLM APIs (OpenAI, Anthropic, etc.) complies with their own commercial terms. No vendor lock-in or proprietary code-signing observed.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Low |
| DEV.co fit | Strong |
| Assessment confidence | High |
Library executes locally without server forwarding (per FAQ). API keys remain on user's machine; library claims no PII collection or server storage. Sentry telemetry enabled by default (error tracking only, opt-out available). Validate that API key handling follows your organization's secrets management policy. No security audit, CVE scan, or threat model data provided.
Alternatives to consider
LangSmith (LangChain)
Purpose-built observability and evaluation platform for LLM applications; offers hosted monitoring, tracing, and evaluation runs. Requires vendor lock-in to LangChain ecosystem.
Braintrust
Commercial evaluation and monitoring platform for LLM applications with collaborative workspace and dataset versioning. Managed service; different pricing/privacy model.
Promptfoo
Open-source CLI-based prompt testing and comparison tool. Lighter weight, simpler for single-model testing; less feature-rich for vector database evaluation.
Build on prompttools with DEV.co software developers
Start with PromptTools—pip install, run notebooks or the Streamlit playground, and begin systematic prompt engineering without server forwarding. Join the Discord community or review the documentation for advanced use cases.
Talk to DEV.coRelated on DEV.co
Explore the category and the services that help you build with it.
prompttools FAQ
Are my LLM API calls forwarded through a PromptTools server?
Does PromptTools store my API keys or prompts on its servers?
Can I use PromptTools in production?
What if my LLM provider or vector database is not listed as 'Supported'?
Custom software development services
From first prototype to production, DEV.co delivers software development services around tools like prompttools. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across vector databases and beyond.
Ready to Optimize Your LLM Prompts?
Start with PromptTools—pip install, run notebooks or the Streamlit playground, and begin systematic prompt engineering without server forwarding. Join the Discord community or review the documentation for advanced use cases.