Project Info
Inspiration
Every day, we’re flooded with articles, videos, and news, but it’s hard to keep up without getting overwhelmed. We built FeedCast to turn that chaos into clarity: personalized, bite-sized audio summaries that let you stay informed while you’re on the go. Whether you’re commuting, walking to class, or grabbing coffee, FeedCast turns downtime into learning. What It Does FeedCast creates your own AI-generated news podcast — tailored to your interests. It curates trending stories, summarizes them into natural-sounding audio, and delivers them through an intuitive iOS app with real-time voice interaction. Users can interact with the podcast information, ask follow ups and clarifying questions. How We Built It We built a full-stack iOS app powered by a FastAPI backend. The iOS app uses SwiftUI for the interface and LiveKit for real-time voice chat. On the backend, we integrated Claude AI for script generation and fact-checking, OpenAI for conversation handling, and automated audio synthesis. Supabase manages authentication, database storage, and audio hosting. Our agent system orchestrates personalized content generation using prompt engineering for high-quality, engaging results. Challenges We Ran Into Getting LiveKit working smoothly for real-time audio was tougher than expected — a lot of debugging went into stable streaming. We initially tried FetchAI for the agent system but pivoted to a custom Claude-based pipeline for better control and content quality. Balancing personalization, accuracy, and natural flow in long-form AI speech took several prompt-engineering iterations. Accomplishments We’re Proud Of Built seamless real-time AI voice interaction with LiveKit Created an end-to-end system from user preferences → curated content → audio generation Designed synchronized text transcripts that follow along with playback Achieved natural, coherent AI-generated podcast segments through prompt refinement What We Learned We deepened our understanding of prompt engineering, real-time audio streaming, and multi-agent orchestration. We also learned how to integrate AI systems with a robust FastAPI backend and SwiftUI front end. What’s Next We plan to expand beyond news — adding educational content, research topics, and custom themes. The goal is to utilize this project as a way to make small quick actions based on your personal goals from adding a to do list to writing emails.
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Analysis
View
Metric
- 5
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
- AnthropicIn code
- FastAPIIn code
- OpenAIIn code
- PythonIn code
- SQLIn code
- SupabaseIn code
- SwiftIn code
7 of 7 appear in the indexed code.
AI coding agents
- Claude CodeConfig
- CodexConfig
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
915 KB
Source files
173
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
metahdev/feedcast
307 files · 3.3 MB · @ 704a0e7
Structure
Interface
12 files · 4%Screens, components and styles rendered to the user.
Application logic
190 files · 62%Domain rules, services and shared utilities.
+11 moreData & schema
8 files · 3%Schema definitions, migrations and data access.
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 — open the file browser to check anything the diagram implies.
Languages
- Swift38%
- Python31%
- Markdown30%
- YAML1%
- SQL0%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
requirements.txt
pypi · 15- aiohttp
- anthropic
- backoff
- fastapi
- google-api-python-client
- httpx
- numpy
- openai
- pydantic
- python-dotenv
- requests
- sentence-transformers
- supabase
- uagents
- uvicorn
feedcast-livekit/feedcast-agent/pyproject.toml
pypi · 3- livekit-agents[silero,turn-detector]
- livekit-plugins-noise-cancellation
- python-dotenv
Declared in the repository’s manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
This project’s features have not been analysed yet.
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