Readme.md

---
title: Problem Decoder
emoji: 🧠
colorFrom: violet
colorTo: indigo
sdk: docker
pinned: false
license: mit
short_description: Paste a transcription or upload a PDF — get problem analysis and brainstormed ideas powered by Claude.
---

# 🧠 Problem Decoder

An AI-powered agent that helps interns understand real-world problems and brainstorm creative solutions from meeting transcriptions or PDF documents.

## Features

- **Text input** — paste any transcription, meeting notes, or problem description
- **PDF upload** — upload a text-based PDF doc (specs, reports, research)
- **Problem analysis** — clearly articulates the core problem, stakeholders, context
- **Root cause analysis** — breaks down *why* the problem exists
- **Brainstorming** — generates 5–8 diverse, creative solution directions
- **Next steps** — gives the intern 3 concrete actions to take immediately
- **Streaming output** — response streams in real time

## Deploying to HuggingFace (Docker Space)

### 1. Create a new Space

Go to [huggingface.co/new-space](https://huggingface.co/new-space) and choose **Docker** as the SDK.

Name it: `problem-decoder`

### 2. Upload these files

```
problem-decoder/
├── app.py
├── requirements.txt
├── Dockerfile
└── README.md
```

### 3. Add your Anthropic API key as a secret

Go to **Settings → Repository secrets** and add:

```
Name:  ANTHROPIC_API_KEY
Value: sk-ant-xxxxxxxxxxxxxxxx
```

### 4. Done — the Space builds and launches automatically

The build takes ~2 minutes on first deploy.

---

## Local development

```bash
# Build the image
docker build -t problem-decoder .

# Run (replace with your actual key)
docker run -p 7860:7860 -e ANTHROPIC_API_KEY=sk-ant-xxx problem-decoder
```

Then open http://localhost:7860

---

## Stack

| Layer | Technology |
|---|---|
| UI | Gradio 4 |
| LLM | Anthropic Claude Sonnet (streaming) |
| PDF parsing | pypdf |
| Container | Python 3.11 slim |