Project Info

Vault Form Agent

Devpost

Inspiration

Filling government, healthcare, insurance, and enterprise forms is still a painful copy-paste workflow. The harder version is not just typing into fields: users need to find the right official site, understand what the form asks for, extract details from scattered documents, protect PII/PHI, avoid accidental submission, and keep an audit trail. Vault Form Agent explores what a safer form-filling agent should look like when documents are sensitive and the user still needs control.

What it does

Vault Form Agent is an enterprise-grade web app with a secure document locker, redaction policy engine, chat-style form agent, visible browser runner, audit trail, CLI, and Codex/Claude-style skill scaffold. Users can upload any kind of document with a name, description, tags, metadata, sensitivity label, consent flag, and retention context. The backend extracts text from PDFs, scanned images, text files, JSON, and document-like inputs through a Docling-ready extraction layer with OCR fallbacks. Before data reaches the agent, built-in and custom redaction rules can mask PII/PHI such as emails, phone numbers, SSNs, dates of birth, member IDs, policy numbers, patient IDs, or any custom user-defined field. The agent page behaves like a chat workspace. A user selects whether the agent should use no documents, selected documents, all non-sensitive documents, or all documents. The user then describes the task in natural language, optionally enables web research, reviews the plan, and lets the browser runner prepare a real web form. The demo proves the process on a public Google Form: eight fields are matched and prepared while a submit guard prevents accidental final submission. Visual proof The GitHub README now includes an embedded visual walkthrough so judges and automated reviewers can see the project without hunting through folders: Agent chat workspace: https://github.com/SonuSV7719/vault-form-agent/blob/main/demo-recordings/chat-agent-redesign.png Real Google Form filled by the agent: https://github.com/SonuSV7719/vault-form-agent/blob/main/demo-recordings/google-form-filled-before-submit.png Corrected eight-field Google Form proof with submit guard: https://github.com/SonuSV7719/vault-form-agent/blob/main/demo-recordings/google-form-clean-8of8-submit-guard.png End-to-end demo recording: https://github.com/SonuSV7719/vault-form-agent/blob/main/demo-recordings/system-end-to-end-google-form-fill.mp4 Clean browser-fill recording: https://github.com/SonuSV7719/vault-form-agent/blob/main/demo-recordings/google-form-clean-8of8-submit-guard.webm How it works FastAPI backend manages the locker, extraction, redaction, planning, audit logs, and browser orchestration. React/Vite frontend provides a multi-page enterprise UI: Dashboard, Document Locker, Agent Chat, Redaction Settings, Approvals, and Audit. Redaction engine supports built-in rules plus custom regex, exact-value, dictionary, and metadata-key rules with multiple masking strategies. Browser runner uses labels, nearby context, DOM roles, JavaScript execution, and page analysis to prepare matching fields. Human-control guard rails keep high-risk actions, especially final submit, reviewable. CLI and skill folders make the capability testable as a developer workflow, not just a web app. How Codex and GPT-5.6 were used Codex with GPT-5.6 was used for the majority of the project: planning the architecture, designing the enterprise UI, generating and iterating backend services, building the React screens, writing the redaction and document-scope mechanisms, implementing the visible browser fill runner, creating sample data, producing demo recordings, and writing the README and docs. The key decisions made with Codex were: make the agent chat-first, require document scope selection, separate extraction from redaction, treat sensitive data as policy-controlled, keep submission human-approved, and include a reusable CLI/skill path for Codex-style workflows. Built during the hackathon The final repo includes setup instructions, sample data, demo recordings, security notes, architecture documentation, redaction handbook, browser-agent handbook, demo guide, visual walkthrough screenshots, and a hackathon submission sheet for judges. Demo proof The included demo assets show the app workflow and a real Google Form preparation run where eight fields are filled and final submission is blocked for safety.

Analysis

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Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • FastAPIIn code
  • HTMLIn code
  • LangChainIn code
  • PythonIn code
  • ReactIn code
  • RedisIn code
  • TypeScriptIn code
  • JavaScriptClaimed
  • OpenAIClaimed

8 of 10 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

192 KB

Source files

76

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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