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A newer version of the Gradio SDK is available: 5.49.1

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metadata
license: mit
title: TherapyBot++
sdk: gradio
emoji: ⛑️
colorFrom: gray
colorTo: gray
pinned: false
short_description: AI wellness bot for Chat, Symptoms, FAQs & Report Summary
sdk_version: 5.34.2

🧠 TherapyBot++ – Your AI Mental Wellness Companion

Welcome to TherapyBot++, an all-in-one mental wellness assistant — thoughtfully crafted to:

  • 💬 Converse like a caring therapist
  • 🧬 Suggest likely health conditions from symptoms
  • 📘 Instantly answer health-related FAQs
  • 🧾 Upload and summarize lab/medical reports using AI

⚠️ Disclaimer: This app is developed for educational and informational purposes only. It is not a substitute for professional medical advice, diagnosis, or treatment.

🚀 Live Demo

🔗 Try it out: TherapyBot++ on Hugging Face Spaces

🧠 Model Overview

🔹 raviix46/flan-t5-therapy-finetuned

A fine-tuned version of Google’s FLAN-T5-Base model trained to provide emotionally supportive, therapeutic-style responses.

💡 Note on Accuracy:
Due to computational limitations:

  • Only 1/8th of the data (1 lakh pairs out of 8.6 lakh) was used for fine-tuning
  • Model responses may lack full emotional nuance and accuracy

Still, it serves as a reliable baseline for mental wellness systems.

✨ Features at a Glance

💬 Therapy Chatbot (Tab 1)

Engage in supportive mental health conversations.

  • Responds empathetically using a fine-tuned FLAN-T5 model
  • Retains recent chat history (collapsible)
  • Cleans hallucinations & repetitive phrases
  • Accordion UI for focused conversation view

🧬 Symptom Checker (Tab 2)

Enter symptoms like “fever” or “rash” to get:

  • 🦠 Predicted Disease
  • 💊 Suggested Treatment
  • 🔍 Matches via all-MiniLM-L6-v2 sentence embeddings

📘 FAQ Support (Tab 3)

Ask generic health questions like:

  • “How do I cancel an appointment?”
  • “What services are available?”

Retrieves the most semantically similar pre-answered question from the dataset using embedding search.

🧾 OCR + Summary (Tab 4)

Upload lab reports (like blood tests) and get AI-generated health summaries.

  • 🧠 Uses Google Cloud Vision API to extract text from scanned reports
  • 🧬 Powered by Gemini 1.5 Pro via Google PaLM for medical summarization
  • 📄 Outputs:
    • 🔹 Plain-language report summary
    • 🔍 Highlighted abnormal values with explanations
    • ✅ Health recommendations
  • 🪄 Clean accordion UI to hide/show raw OCR text
  • 📥 Supports JPG/PNG reports with upload preview

Ideal for quick interpretation of CBCs, lipid profiles, and other basic diagnostic reports.

🧬 How It Works

🧠 Model Power

  • Chatbot: raviix46/flan-t5-therapy-finetuned (Generates response)
  • Embedding Model: all-MiniLM-L6-v2
    Used for:
    • FAQ matching
    • Symptom similarity checking
  • OCR Model: Google Cloud Vision OCR (image-to-text for medical reports)
  • Summarizer: Gemini-1.5 Pro API (Google PaLM) for health-focused summary generation

🔍 Retrieval Logic

  • Uses cosine similarity to match user input with embeddings from .pkl files.
  • Most similar match is retrieved and displayed as answer or diagnosis.

📁 Files Included

  • app.py – Main Gradio application script combining all four tools.

  • faq_embeddings.pkl –
    A serialized dictionary containing:

    • questions: List of frequently asked health-related queries
    • answers: Corresponding answers
    • embeddings: Vector representations of each question using the all-MiniLM-L6-v2 Sentence Transformer
      🔍 Used to find the best match for user input in the FAQ tab.

  • symptom_embeddings.pkl –
    A serialized dictionary containing:

    • symptoms: User symptom phrases
    • diseases: Associated disease names
    • treatments: Recommended treatments for each disease
    • embeddings: Vector representations of each symptom
      🧬 Used to match user-described symptoms to known conditions in the Symptom Checker tab.

  • components/llm_ocr_gcv.py –
    Google Cloud Vision API integration to extract text from uploaded lab report images (JPG/PNG).
    🧾 Used in the OCR + Summary tab for high-accuracy OCR.

  • components/palm_summarizer.py –
    Uses Gemini 1.5 Pro via Google PaLM API to generate simplified, patient-friendly medical summaries from the extracted OCR text.
    📋 Structures output into sections like Findings, Abnormal Values, and Recommendations.

  • tabs/image_ocr_llm.py –
    Implements the OCR + Summary tab UI with:

    • Image uploader (accordion view)
    • Status indicator (Processing...)
    • Structured markdown summary
    • Collapsible raw OCR viewer

  • style.css (optional) –
    Custom UI enhancements for Gradio interface:

    • Stylized summary boxes
    • Themed buttons
    • Font/color consistency

  • requirements.txt –
    Complete dependency list:

    # Core ML & Transformers
transformers>=4.36.0
torch>=2.0.0
sentencepiece>=0.1.99
sentence-transformers>=2.2.2
scikit-learn>=1.1.3
numpy>=1.21.0

# UI
gradio>=4.15.0
requests>=2.31.0  
gradio_client>=0.8.1

# OCR & Image Processing
pytesseract>=0.3.10
Pillow>=10.0.0
pymupdf>=1.23.7
pdf2image>=1.16.3
sacremoses>=0.0.53

# Translation & Tokenization
accelerate>=0.27.0
safetensors>=0.3.3

# Google Cloud Vision Support
google-cloud-vision>=3.4.5
google-generativeai>=0.3.2

🛠️ Tech Stack

  • 🐍 Python 3.10 – Core programming language
  • 🤗 Hugging Face Transformers – For FLAN-T5 text generation and model integration
  • 🔍 Sentence Transformers (MiniLM) – For semantic similarity in FAQ and symptom matching
  • 🧠 FLAN-T5 Fine-tuned Model – For therapist-style conversational responses
  • 📄 Google Cloud Vision API – High-accuracy OCR for scanned lab reports and prescriptions
  • ✍️ Gemini 1.5 Pro (via Google PaLM) – Summarizes extracted report text into readable health advice
  • 🖼 Pytesseract, PDF2Image, Pillow – Local fallback OCR and image preprocessing support
  • 🎨 Gradio – Interactive multi-tab front-end with collapsible sections and Markdown rendering
  • 📦 Hugging Face Spaces – Free and deployable hosting environment for the full web app

📌 Usage Instructions

Clone and run locally:

git clone https://huggingface.co/spaces/raviix46/therapy-chatbot
cd therapy-chatbot
pip install -r requirements.txt
python app.py