Project Info
A powerful voice-augmented AI assistant for developers and researchers, built for UCBerkeleyHackathon2025. SAGE AI helps users converse and brainstorm on the content they browse online. It combines real-time web summarization, semantic memory, and natural voice interaction. π
Inspiration
We set out to build an interactive tool that developers and researchers can use to talk with their own web browsing historyβto reflect, analyze, or brainstorm using AI. SAGE AI is powered by: Vapi for real-time voice interaction Gemini API for smart summarization Pinecone for semantic vector storage and retrieval Google Cloud Storage (GCS) for scalable backend data handling β¨ Features π§ Chrome Extension β Capture and summarize webpage content with one click π AI Summarization β Generate concise, meaningful summaries via Gemini API π§ Semantic Memory β Embed summaries into Pinecone for context-aware search π€ Voice Assistant β Interact with your saved context via voice, powered by Vapi π API Integration β Send summaries to external APIs or download as .txt files π§© Getting Started 1οΈβ£ Chrome Extension Navigate to chrome://extensions/ and enable Developer mode Click Load unpacked and select the dom-extension folder Click the extension icon to extract and summarize content from any webpage 2οΈβ£ FastAPI Vector Server Install dependencies: pip install fastapi uvicorn pinecone-client Install dependencies: Set API keys: export PINECONE_API_KEY=your_pinecone_key export GEMINI_API_KEY=your_gemini_key Set API keys: Run the backend server: uvicorn main:app --reload Run the backend server: Available API Endpoints: Available API Endpoints: POST /vectorize β Store a summary as a vector POST /vectorize β Store a summary as a vector POST /search β Search for semantically similar summaries POST /search β Search for semantically similar summaries 3οΈβ£ Vapi Voice Assistant The Chrome extension or web app integrates with Vapi for conversational interaction See popup.js or your frontend code for integration details π§ Example API Usage Vectorize a summary: Semantic search: π¨ Customization Download summaries as .txt files or send to external APIs Voice Assistant toggle available directly in the extension popup Easily tweak styles in style.css to match your UI theme π Credits Google Gemini API Pinecone Vector DB Vapi Voice SDK UCBerkeleyHackathon2025 Team π License MIT License
πΏ SAGE AI: System for Automatic Gyan Extraction

A powerful voice-augmented AI assistant for developers and researchers, built for UCBerkeleyHackathon2025.
SAGE AI helps users converse and brainstorm on the content they browse online. It combines real-time web summarization, semantic memory, and natural voice interaction.
π Inspiration
We set out to build an interactive tool that developers and researchers can use to talk with their own web browsing historyβto reflect, analyze, or brainstorm using AI.
SAGE AI is powered by:
- Vapi for real-time voice interaction
- Gemini API for smart summarization
- Pinecone for semantic vector storage and retrieval
- Google Cloud Storage (GCS) for scalable backend data handling
β¨ Features
- π§ Chrome Extension β Capture and summarize webpage content with one click
- π AI Summarization β Generate concise, meaningful summaries via Gemini API
- π§ Semantic Memory β Embed summaries into Pinecone for context-aware search
- π€ Voice Assistant β Interact with your saved context via voice, powered by Vapi
- π API Integration β Send summaries to external APIs or download as
.txtfiles
π§© Getting Started
1οΈβ£ Chrome Extension
- Navigate to
chrome://extensions/and enable Developer mode - Click Load unpacked and select the
dom-extensionfolder - Click the extension icon to extract and summarize content from any webpage

2οΈβ£ FastAPI Vector Server
- Install dependencies:
pip install fastapi uvicorn pinecone-client
- Set API keys:
export PINECONE_API_KEY=your_pinecone_key
export GEMINI_API_KEY=your_gemini_key
- Run the backend server:
uvicorn main:app --reload
- Available API Endpoints:
POST /vectorizeβ Store a summary as a vectorPOST /searchβ Search for semantically similar summaries
3οΈβ£ Vapi Voice Assistant
- The Chrome extension or web app integrates with Vapi for conversational interaction
- See
popup.jsor your frontend code for integration details
π§ Example API Usage
Vectorize a summary:
curl -X POST http://localhost:8000/vectorize -H "Content-Type: application/json" -d '{"text": "Your summary text here"}'
Semantic search:
curl -X POST http://localhost:8000/search -H "Content-Type: application/json" -d '{"query": "What are the benefits of apples?"}'
π¨ Customization
- Download summaries as
.txtfiles or send to external APIs - Voice Assistant toggle available directly in the extension popup
- Easily tweak styles in
style.cssto match your UI theme
π Credits
π License
Analysis
View
Metric
- 19
- 3
- 2
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
- CSSIn code
- FastAPIIn code
- HTMLIn code
- JavaScriptIn code
- PythonIn code
- ReactIn code
- Tailwind CSSIn code
- Google GeminiClaimed
- OpenAIClaimed
7 of 9 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
47 KB
Source files
20
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
Aditya-Dawadikar/UCBerkeleyHackathon2025
33 files Β· 358 KB Β· @ 26951ec
Structure
Interface
3 files Β· 9%Screens, components and styles rendered to the user.
Application logic
10 files Β· 30%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here β open the file browser to check anything the diagram implies.
Languages
- Markdown41%
- JavaScript30%
- Python18%
- CSS8%
- HTML3%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
example-hackathon-demo/package.json
npm Β· 18- @vapi-ai/web
- clsx
- framer-motion
- lucide-react
- react
- react-dom
- tailwind-merge
- +11 more
vector-server/requirements.txt
pypi Β· 5- fastapi
- pinecone
- pydantic
- uuid
- uvicorn
Declared in the repositoryβs manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
This projectβs features have not been analysed yet.
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