metadata

title: Vocca-ai Prototype
emoji: 📚
colorFrom: red
colorTo: blue
sdk: streamlit
sdk_version: 1.42.0
app_file: app.py
pinned: false

MedCall AI - Call Analysis

What is this?

MedCall AI is a tool that helps analyze patient calls. It figures out the caller’s intent, urgency, and mood, then generates a useful AI response. This makes handling medical calls easier and faster.

Features

Summarizes Calls: Takes a long call transcript and shortens it.
Understands Intent: Detects if the caller wants an appointment, medical advice, billing help, etc.
Checks Urgency: Decides if the request is urgent or not.
Analyzes Sentiment: Detects if the caller is worried, neutral, or positive.
Stores Call Logs: Saves call details in a database for reference.
Easy-to-Use Interface: Built using Streamlit for a simple web-based UI.

What’s Inside?

├── app.py                  # Main application (UI)
├── vocca_ai/
│   ├── ai_response.py      # Call summarization
│   ├── intent_classifier.py # Intent detection
│   ├── sentiment.py        # Sentiment analysis
│   ├── db_handler.py       # Saves call logs
│   ├── preprocess.py       # Urgency scoring
├── requirements.txt        # Required dependencies
├── README.md               # This file

How to Set Up

Clone the repository:

git clone https://huggingface.co./spaces/Yuvrajspd09/MedCall-AI

Move into the project folder:
```
cd MedCall-AI
```

Set up a virtual environment:

python -m venv venv
source venv/bin/activate  # Windows: `venv\Scripts\activate`

Install necessary libraries:
```
pip install -r requirements.txt
```

How to Use It

Run the application:

streamlit run app.py

Example Usage

Summarizing a Call

from vocca_ai.ai_response import generate_call_summary

sample_text = "I need an appointment as soon as possible."
summary = generate_call_summary(sample_text)
print(f"Summary: {summary}")

Detecting Intent

from vocca_ai.intent_classifier import classify_intent

sample_text = "I want to book an appointment."
intent = classify_intent(sample_text)
print(f"Intent: {intent}")

Checking Sentiment

from vocca_ai.sentiment import analyze_sentiment

sample_text = "I have been feeling really sick."
sentiment = analyze_sentiment(sample_text)
print(f"Sentiment: {sentiment}")

Logging Calls

from vocca_ai.db_handler import log_call

log_call("I need an appointment", "appointment", "Low", "Neutral", "You can book an appointment online.")

Want to Help?

If you’d like to improve this project, feel free to fork it, make changes, and submit a pull request!

License

This project is open-source under the MIT License.