Vector Retrieval and RAG · Public

prompttools

Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.

Vector databaseRAGEmbeddingsSemantic searchData boundaries

Best fitDevelopers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.

Check whether this project matches your task before installing it.

What it can doVector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot3.0k stars

256 forks · 13 contributors

Doramagic.ai Last verification date: 2026-06-27 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-06-27

What is prompttools?

prompttools is a vector database, retrieval, or RAG storage component for AI applications.
Best fit: Developers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.
Not for: Not for one-off model API calls or environments that cannot isolate indexed data, credentials, and persistence paths.
Capability added to an AI workflow: Vector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance
First safe verification step: Verify create, query, delete, and rollback with a small public text sample before using real data.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/hegelai/prompttools, https://github.com/hegelai/prompttools#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forDevelopers connecting knowledge bases, documents, or app data to semantic retrieval or RAG workflows.

Match the project to your task before installing it.

CapabilityVector database setup checks, embedding model boundaries, collection management, query acceptance, and deletion guidance

Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.

Repositoryhegelai/prompttools

3.0k stars · 256 forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Overview, Supported Integrations, and Quickstart

Related topics: Core Experiments API: LLMs, Vector Databases, and Frameworks, Playground, Widgets, and Visualization

Source: https://github.com/hegelai/prompttools / Human Manual

Core Experiments API: LLMs, Vector Databases, and Frameworks

Related topics: Overview, Supported Integrations, and Quickstart, Utilities, Harness, PromptTest, and Observability

Source: https://github.com/hegelai/prompttools / Human Manual

Playground, Widgets, and Visualization

Related topics: Overview, Supported Integrations, and Quickstart, Core Experiments API: LLMs, Vector Databases, and Frameworks

Source: https://github.com/hegelai/prompttools / Human Manual

Utilities, Harness, PromptTest, and Observability

Related topics: Core Experiments API: LLMs, Vector Databases, and Frameworks, Playground, Widgets, and Visualization

Source: https://github.com/hegelai/prompttools / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/hegelai/prompttools, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars3.0k stars

Forks256 forks

Contributors13 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using prompttools with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
Deprecation error : st.experimental_get_query_params and st.experimental
github / github_issue
02
package breaks while importing LanceDB experiment
github / github_issue
03
Support for OpenAI Assistants API
github / github_issue
04
Deprecation warnings
github / github_issue
05
Missing requirements - streamlit
github / github_issue
06
AzureOpenAIServiceExperiment notebook: TypeError: Missing required argum
github / github_issue
07
AttributeError: module 'openai' has no attribute 'types'
github / github_issue
08
OpenAI Chat Experiment Example dependency issue fix
github / github_issue
09
Add support for Microsoft Semantic-Kernel
github / github_issue
10
prompttools 0.0.45 - Introducing Observability features!
github / github_release
11
prompttools 0.0.41 - Hosted Playground Launch
github / github_release
12
prompttools 0.0.35
github / github_release

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install prompttools

Official start command · https://github.com/hegelai/prompttools#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

prompttools Manual

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).

Open the full manual

https://github.com/hegelai/prompttools Project Manual
Table of Contents
Overview, Supported Integrations, and Quickstart
Related Pages
1. Project Overview
2. Supported Integrations
Release-Driven Additions
Community-Reported Integration Gaps

Overview, Supported Integrations, and Quickstart

Related topics: Core Experiments API: LLMs, Vector Databases, and Frameworks, Playground, Widgets, and Visualization

Source: https://github.com/hegelai/prompttools / Human Manual

Core Experiments API: LLMs, Vector Databases, and Frameworks

Related topics: Overview, Supported Integrations, and Quickstart, Utilities, Harness, PromptTest, and Observability

Source: https://github.com/hegelai/prompttools / Human Manual

Playground, Widgets, and Visualization

Related topics: Overview, Supported Integrations, and Quickstart, Core Experiments API: LLMs, Vector Databases, and Frameworks

Source: https://github.com/hegelai/prompttools / Human Manual

Utilities, Harness, PromptTest, and Observability

Related topics: Core Experiments API: LLMs, Vector Databases, and Frameworks, Playground, Widgets, and Visualization

Source: https://github.com/hegelai/prompttools / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.

Pitfall Log and verification risks

Doramagic surfaces high-risk items before users treat a candidate capability as verified.

high

Maintenance risk requires verification

May increase setup, validation, or first-run risk for the user.

high

Security or permission risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Installation risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Capability evidence risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Runtime risk requires verification

May increase setup, validation, or first-run risk for the user.

medium

Runtime risk requires verification

May increase setup, validation, or first-run risk for the user.