Spaces:
Running
Running
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title: Reem — Virtual Call Centre Voice Bot
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emoji: 📞
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colorFrom: green
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colorTo: yellow
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sdk: docker
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pinned: false
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license: mit
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---
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Browser mic → Gradio Audio → Deepgram STT (nova-2, multilingual)
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↓
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Router (sql / rag)
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↙ ↘
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SQLite orders FAISS + SentenceTransformer
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↘ ↙
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Groq LLaMA-3.3-70b (streaming)
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↓
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edge-tts TTS
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↓
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Gradio Audio (autoplay)
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```
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## Features
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| Feature | Details |
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|---|---|
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| **STT** | Deepgram nova-2, auto language detection (EN / AR / UR) |
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| **LLM** | Groq `llama-3.3-70b-versatile` with streaming |
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| **TTS** | edge-tts — `en-US-AriaNeural`, `ar-SA-ZariyahNeural`, `ur-PK-UzmaNeural` |
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| **Memory** | 10-turn sliding window + entity cache (order IDs, customer name) |
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| **Routing** | SQL path for order tracking, RAG path for knowledge base Q&A |
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| **Languages** | English · Arabic · Urdu |
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---
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## Environment Variables
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Set these in **HF Spaces → Settings → Repository secrets**:
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| Variable | Required | Description |
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|---|---|---|
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| `GROQ_API_KEY` | ✅ | [console.groq.com](https://console.groq.com) |
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| `DEEPGRAM_API_KEY` | ✅ | [console.deepgram.com](https://console.deepgram.com) |
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| `LIVEKIT_API_KEY` | ⬜ | Reserved for future WebRTC streaming |
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---
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## Deployment — HF Spaces (Gradio SDK)
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1. Create a new Space → **Gradio** SDK
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2. Push these files — no Dockerfile needed:
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```
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app.py
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requirements.txt
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README.md
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```
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3. Add secrets under **Settings → Repository secrets**: `GROQ_API_KEY`, `DEEPGRAM_API_KEY`
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4. HF installs `requirements.txt` automatically and runs `app.py`
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---
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## Knowledge Base Setup
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1. Open **Admin Panel** (left sidebar) after launch
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2. Upload one or more `.txt` files → click **Build KB**
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3. FAISS index is built in-memory and persisted to `faiss.index` + `chunks.npy`
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## Orders Database Setup
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1. Export your SQLite `.db` file with an `orders` table:
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```sql
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CREATE TABLE orders (
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order_id INTEGER PRIMARY KEY,
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order_date TEXT,
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customer_name TEXT,
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customer_city TEXT,
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customer_address TEXT,
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status TEXT,
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delivery_date TEXT,
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comments TEXT
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);
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```
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2. Upload via **Admin Panel → Orders Database**
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---
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## Usage Flow
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1. Page loads → **welcome message plays** in EN / AR / UR
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2. Say or click your **language** → Reem confirms
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3. **Speak** into mic or **type** in the text box
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4. Reem routes your query:
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- Order number / tracking keywords → **SQL lookup**
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- General questions → **RAG knowledge base**
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5. Response **streams** from Groq → TTS plays automatically
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6. Reem **remembers** order IDs and customer name across turns
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---
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## Local Development
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```bash
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# Create venv
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python -m venv .venv && source .venv/bin/activate
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# Install
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pip install -r requirements.txt
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# Set env vars
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export GROQ_API_KEY=gsk_...
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export DEEPGRAM_API_KEY=...
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# Run
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python app.py
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# → http://localhost:7860
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```
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---
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## File Structure
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```
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├── app.py # Main Gradio app
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├── requirements.txt
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├── README.md # HF Spaces config frontmatter lives here
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├── faiss.index # Auto-generated after KB build
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├── chunks.npy # Auto-generated after KB build
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├── saudi_orders_database.db # Upload via Admin Panel
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└── agent_photo.jpg # Optional — replaces emoji avatar
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```
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---
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## Differences from Streamlit Version
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| Aspect | Streamlit + Railway | Gradio on HF Spaces |
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| Port management | FastAPI proxy required | Single port, native |
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| Streaming TTS | `st.components.v1.html` workaround | `gr.Audio(autoplay=True)` |
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| STT | `streamlit-mic-recorder` | `gr.Audio(sources=["microphone"])` |
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| Re-render issues | Duplicate responses on rerun | State-based, no reruns |
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| Barge-in | Manual WebSocket lifecycle | Deepgram `stop_recording` event |
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FROM python:3.11-slim
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg libsndfile1 curl \
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&& rm -rf /var/lib/apt/lists/*
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RUN useradd -m -u 1000 user
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USER user
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ENV HOME=/home/user PATH=/home/user/.local/bin:$PATH PYTHONUNBUFFERED=1
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WORKDIR $HOME/app
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COPY --chown=user requirements.txt .
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RUN pip install --no-cache-dir --upgrade pip \
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&& pip install --no-cache-dir -r requirements.txt
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COPY --chown=user . .
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EXPOSE 7860
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CMD ["python", "app.py"]
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