bio

Bio

Try the hosted version here 🙌

Then fork and get building…

Enterprise-grade biomedical deep research - Pick a life sciences workflow, fill in a few variables, and get back a cited research report with deliverables. Powered by Valyu DeepResearch over PubMed, ClinicalTrials.gov, FDA drug labels, patents, and the open web.

Why Bio?

Biomedical evidence is fragmented across dozens of databases, and stitching it together by hand is where the days go. Bio runs the whole search-read-synthesise loop for you:

• Prebuilt life sciences workflows - Competitive landscapes, clinical readouts, regulatory precedent, and business development scans, each with typed inputs instead of a blank prompt box
• Comprehensive biomedical data - PubMed articles, ClinicalTrials.gov records, FDA drug labels, patents, and more through Valyu’s unified API
• Cited reports - Every claim carries an inline citation that resolves to the underlying source
• Deliverables - Structured artifacts alongside the narrative, plus PDF export
• Example reports - Real finished reports per domain, so you can see the output before spending a credit
• Self-hostable - Local SQLite, no authentication, no rate limits

Key Features

Deep research reports

• Workflow browser - Browse the life sciences workflow catalog by lens: Pipeline & Assets, Clinical, Regulatory, and Business Development
• Three research modes - fast, standard, and heavy, trading depth against turnaround time
• Live activity feed - Watch the searches, reads, and reasoning steps as the report is built
• Report history - Every report is stored and re-openable, with cancel and sync controls while a run is in flight

Reading and sharing

• Inline citations - Hover any marker for the source title, date, and link
• Images and deliverables - Charts and structured outputs rendered next to the report body
• PDF export - Server-rendered PDF of any completed report
• Share links - Send a report to a colleague or post it

Example reports

Each domain ships with a seeded example report so the app is useful before you have run anything yourself. They render through the same report view as live output.

Quick Start (Self-Hosted)

Self-hosted mode is the recommended way to run Bio. It provides a complete local environment with:

• No authentication required - Auto-login as dev user
• Local SQLite database - No external database setup needed
• No rate limits - Credits are handled by your own Valyu API key

Prerequisites

• Node.js 18+
• pnpm (npm install -g pnpm)
• Valyu API key (get one at platform.valyu.ai)

Installation

1. Clone the repository

   git clone https://github.com/yorkeccak/bio.git
   cd bio
   

2. Install dependencies

   pnpm install
   

3. Set up environment variables

   Create a .env.local file in the root directory:

   # Enable Self-Hosted Mode
   NEXT_PUBLIC_APP_MODE=self-hosted
   
   # Valyu API Configuration (Required)
   VALYU_API_KEY=your-valyu-api-key
   
   # OpenAI Configuration (Optional - used to suggest report deliverables)
   OPENAI_API_KEY=your-openai-api-key
   
   # Local model servers (Optional - powers the local model status indicator)
   OLLAMA_BASE_URL=http://localhost:11434   # Default Ollama URL
   LMSTUDIO_BASE_URL=http://localhost:1234  # Default LM Studio URL
   

4. Run the development server

   pnpm dev
   

5. Open your browser

   Navigate to http://localhost:3000

   You’ll be automatically logged in as dev@localhost with full access to all features.

Self-Hosted Mode Guide

What is Self-Hosted Mode?

Self-hosted mode provides a complete local environment without any external dependencies beyond the Valyu API. It’s perfect for:

• Local Development - No Supabase setup required
• Testing Features - No auth wall between you and the app
• Privacy - Reports and user data stay on your machine
• Quick Prototyping - No authentication or rate limits

How It Works

When NEXT_PUBLIC_APP_MODE=self-hosted:

1. Local SQLite Database (/.local-data/dev.db)

   • Automatically created on first run
   • Stores the local user record
   • Easy to inspect with sqlite3 .local-data/dev.db

2. Mock Authentication

   • Auto-login as dev user (dev@localhost)
   • No sign-up/sign-in required

3. No Rate Limits

   • Usage is governed by the credits on your own Valyu API key

Local Model Servers (Optional)

Bio detects Ollama and LM Studio running on your machine and surfaces their status and available models in the top-right indicator.

Ollama:

# Install Ollama
brew install ollama              # macOS
# OR
curl -fsSL https://ollama.com/install.sh | sh  # Linux

# Start Ollama service
ollama serve

# Download a model
ollama pull qwen2.5:7b

LM Studio:

1. Download LM Studio from lmstudio.ai
2. Download a model - Search for qwen/qwen3-14b or google/gemma-3-12b
3. Start the server - Click the LM Studio menu bar icon -> “Start Server on Port 1234…”
4. Configure the context window - Set to at least 8192 tokens (16384+ recommended)

Managing Local Database

View Database:

sqlite3 .local-data/dev.db
# Then run SQL queries
SELECT * FROM users;

Reset Database:

rm -rf .local-data/
# Database recreated on next app start

Valyu Mode (Optional)

Valyu mode adds hosted authentication and billing: users sign in with their Valyu account through OAuth, and research runs are charged against their Valyu credits rather than a shared API key.

Prerequisites for Valyu Mode

• Valyu OAuth credentials (contact [email protected])
• A Supabase project for your app’s own user data

Valyu Mode Configuration

# Enable Valyu Mode
NEXT_PUBLIC_APP_MODE=valyu

# Valyu OAuth Credentials (contact [email protected])
NEXT_PUBLIC_VALYU_SUPABASE_URL=https://your-valyu-supabase-url
NEXT_PUBLIC_VALYU_CLIENT_ID=your-client-id
VALYU_CLIENT_SECRET=your-client-secret
VALYU_APP_URL=https://platform.valyu.ai

# Your App's Supabase (for user data)
NEXT_PUBLIC_SUPABASE_URL=https://your-project.supabase.co
NEXT_PUBLIC_SUPABASE_ANON_KEY=your-anon-key
SUPABASE_SERVICE_ROLE_KEY=your-service-role-key

# Optional fallback key for anonymous traffic
VALYU_API_KEY=your-valyu-api-key

Example Reports

Bio ships with a seeded example report for each life sciences lens:

• Pipeline & Assets - Competitive landscape across a target class
• Clinical - Trial landscape and readout analysis
• Regulatory - Approval pathway and precedent scan
• Business Development - Partnering and asset opportunity scan

Open one from the reports page to see the report view, citations, and deliverables without running a workflow.

Architecture

• Frontend: Next.js 15 with App Router, Tailwind CSS v4, shadcn/ui
• Research: Valyu DeepResearch workflows over biomedical and web sources
• Auth: Valyu OAuth in valyu mode, local dev user in self-hosted mode
• Storage: Supabase in valyu mode, SQLite via Drizzle in self-hosted mode
• PDF: Puppeteer with @sparticuz/chromium
• Analytics: PostHog and Vercel Analytics

Deploy to Vercel

The quickest way to get Bio running in production:

1. Fork this repository to your GitHub account
2. Create a new project on vercel.com and import your fork
3. Add environment variables in Vercel project settings (Settings > Environment Variables):
   • NEXT_PUBLIC_APP_MODE = self-hosted
   • VALYU_API_KEY = your Valyu API key
   • OPENAI_API_KEY = your OpenAI API key (optional, for deliverable suggestions)
4. Deploy - Vercel handles the rest

Security

• Secure API key management
• No storage of sensitive medical data
• HTTPS encryption for all API calls

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Here’s how to get started:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/your-feature)
3. Make your changes
4. Run pnpm dev and test locally
5. Commit your changes and push to your fork
6. Open a Pull Request against main

For bugs or feature requests, open an issue or start a discussion.

Acknowledgments

• Built with Valyu - The unified biomedical data API
• UI components from shadcn/ui

Made with love for biomedical researchers

Twitter - LinkedIn - GitHub