Upload folder using huggingface_hub

.env

@@ -0,0 +1 @@
+GOOGLE_API_KEY = AIzaSyBy75oZVqdS-2AUwS0TMH8aiIGF64GbTL8

.gitattributes

@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+
+.venv/* linguist-vendored
+.venv/** linguist-vendored
+gradio-env/** linguist-vendored
+.gradio/** linguist-vendored

.gitignore

@@ -0,0 +1,54 @@
+# Python
+__pycache__/
+*.py[cod]
+*.pyo
+*.so
+*.log
+
+# Virtual Environments
+.venv/
+venv/
+env/
+ENV/
+gradio-env/
+
+# Gradio
+.gradio/
+gradio/
+
+# Jupyter
+.ipynb_checkpoints/
+
+# VS Code
+.vscode/
+
+# System
+.DS_Store
+Thumbs.db
+
+# Hugging Face and Gradio
+*.huggingface
+*.gradio
+token
+
+# Model/Data files
+*.ckpt
+*.pt
+*.pth
+*.h5
+*.tflite
+*.pb
+*.onnx
+*.joblib
+*.pkl
+*.pickle
+*.npy
+*.npz
+*.tar
+*.tar.gz
+*.zip
+*.gz
+*.rar
+
+# LFS-tracked artifacts
+*.lfs.*

README.md

@@ -1,12 +1,140 @@
 ---
 title: MediSyncAI
-emoji: 🏃
-colorFrom: purple
-colorTo: blue
+emoji: 🏆
+colorFrom: pink
+colorTo: yellow
 sdk: gradio
 sdk_version: 5.25.0
 app_file: app.py
 pinned: false
+license: mit
+short_description: An AI-Powered Medical Assistant for Rural Clinics
 ---
 
+<!-- @format -->
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# 🏥 MediSync.AI – An AI-Powered Medical Assistant for Rural Clinics
+
+MediSync.AI is a GenAI-powered web application designed to **assist rural healthcare centers** by automatically understanding **prescriptions** and providing **interactive medical insights** through a conversational agent. Built using **Google Gemini 2.0 Flash API via Vertex AI**, this tool simplifies medical communication for patients and supports doctors with AI-enhanced assistance.
+
+---
+
+## 📌 Features
+
+-   🧠 **Prescription Understanding**  
+    Upload an image of a handwritten prescription – Gemini Flash API extracts medicine names, dosage, and additional instructions.
+
+-   💬 **Medical Chatbot Assistant**  
+    Chat with a friendly AI named _MediSync_ to understand your medications, their purpose, and general health-related queries.
+
+-   ✨ **Structured Output**  
+    Data is neatly parsed and presented to users in a patient-friendly format.
+
+-   🚀 **Powered by Gen AI**  
+    Uses Google's latest large language models (LLMs) from Vertex AI to process and reason with natural language.
+
+---
+
+## 🧑‍⚕️ Use Case
+
+In many **rural clinics**, patients receive handwritten prescriptions but often struggle to understand them. MediSync.AI bridges this gap using Gen AI, allowing users to:
+
+-   Understand medication names and dosages.
+-   Ask questions about medicines in natural language.
+-   Interact with a conversational assistant for basic medical advice (with disclaimers).
+
+---
+
+## 🔧 Tech Stack
+
+| Layer            | Tech Used                             |
+| ---------------- | ------------------------------------- |
+| 🌐 Frontend      | Gradio (Python-based interface)       |
+| 🧠 GenAI Backend | Gemini 2.0 Flash (via Vertex AI)      |
+| ☁️ Platform      | Google Cloud (Vertex AI, Gemini APIs) |
+| 🧪 Language      | Python                                |
+| 📁 File Handling | `requests`, `orjson`, `PIL`, etc.     |
+
+---
+
+## 📌 Key Gemini Features Used
+
+✅ Few-shot prompting  
+✅ Structured prompt engineering  
+✅ Document understanding (prescriptions)  
+✅ Conversational interface with memory  
+✅ Vertex AI managed model access (no fine-tuning required)
+
+---
+
+## 🧠 How GenAI Solves the Problem
+
+GenAI bridges the literacy and accessibility gap by:
+
+-   **Extracting structured medicine data** from unstructured prescription images.
+-   **Answering patient queries conversationally**, using large medical knowledge embedded in Gemini models.
+-   **Handling diverse handwriting**, typos, and low-context queries effectively.
+
+---
+
+## 📂 File Structure
+
+```
+mediSync-AI/
+│
+├── main.ipynb              # Jupyter notebook with the full GenAI flow
+├── requirements.txt        # Dependencies
+├── data/
+│   └── img1.jpg
+│   └── img2.jpg
+│   :
+│   :
+├── README.md
+```
+
+---
+
+## ▶️ How to Run
+
+1. Clone the repo
+
+```bash
+git clone https://github.com/Sarita-021/mediSync-AI.git
+cd mediSync-AI
+```
+
+2. Install requirements
+
+```bash
+pip install -r requirements.txt
+```
+
+3. Run the notebook or script
+
+```bash
+jupyter notebook main.ipynb
+```
+
+4. Upload a prescription image & start chatting with the bot 🎯
+
+---
+
+## ⚠️ Disclaimer
+
+> MediSync.AI does **not replace professional medical advice**. Always consult a licensed medical professional before taking any medication or making health-related decisions.
+
+---
+
+## 📸 Demo Screenshot
+
+![image](https://github.com/user-attachments/assets/5a495bdf-f61b-4c0c-b772-e66a14d7f051)
+
+![image](https://github.com/user-attachments/assets/c09139ea-7877-4246-97c9-3e580005ef39)
+
+---
+
+## 🧑‍💻 Author
+
+**Sarita** || Gen AI Intensive 2025Q1 Capstone Project || AI & ML Enthusiast

app.py

@@ -0,0 +1,176 @@
+import os
+import re
+import gradio as gr
+from PIL import Image
+import google.generativeai as genai
+
+import json
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Get the API key from environment variable
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+
+# Configure the GenAI client
+genai.configure(api_key=GOOGLE_API_KEY)
+# Load the Gemini model
+model = genai.GenerativeModel("gemini-2.0-flash") 
+#client = genai.Client()
+
+# Prompt for image-based structured output
+prompt = """
+You are a medical assistant AI. Extract structured data from this handwritten prescription image.
+
+Here are some common medicines there strength and usage
+Medicine Name	Strength Example	Usage
+Paracetamol	500mg, 650mg	Pain relief, fever
+Amoxicillin	250mg, 500mg	Antibiotic
+Azithromycin	250mg, 500mg	Antibiotic
+Ibuprofen	400mg, 600mg	Pain relief, anti-inflammatory
+Cefixime	200mg	Antibiotic
+Pantoprazole	40mg	Acidity, ulcer prevention
+Domperidone	10mg	Anti-nausea
+Metformin	500mg, 1000mg	Diabetes
+Amlodipine	5mg	Blood pressure
+Cetirizine	10mg	Anti-allergy
+Ranitidine	150mg	Acidity
+Dolo 650	650mg	Fever, pain relief
+Ondansetron	4mg, 8mg	Anti-vomiting
+Levocetirizine	5mg	Allergy
+Losartan	50mg	Blood pressure
+Clavulanic Acid	125mg (with Amox)	Antibiotic combo
+Salbutamol	Inhaler/Syrup	Asthma
+
+Even if handwritten, try your best to extract medicine names, dosage frequency (like 1-0-1), and strength (mg).
+
+Focus on extracting:
+- Patient name
+- List of medicines prescribed (Paracetamol)
+- Strength (mg, ml, etc.)
+- Dosage frequency (e.g., 1-0-1 or twice daily)
+- Duration
+- Additional notes
+
+Return ONLY this JSON format:
+{
+  "patient_name": "",
+  "medicines": [
+    {
+      "name": "",
+      "strength": "",
+      "dosage_frequency": "",
+      "duration": ""
+    }
+  ],
+  "notes": ""
+}
+If any field is missing, return it as null.
+"""
+
+# Function to handle image input
+def extract_prescription(image):
+    if image is None:
+        return "Please upload an image."
+    
+    #response = client.models.generate_content(
+    
+    response = model.generate_content(
+        contents=[
+            prompt,
+            image
+        ]
+    )
+    text = response.text.strip()
+
+    # Remove markdown formatting if any
+    if text.startswith("```json"):
+        text = re.sub(r"```json|```", "", text).strip()
+
+    try:
+        data = json.loads(text)
+
+        # Format nicely
+        output = f"### 👩‍⚕️ Prescription Summary\n"
+        output += f"- **Patient Name:** {data.get('patient_name', 'N/A') or 'N/A'}\n"
+        output += f"- **Medicines Prescribed:**\n"
+
+        for med in data.get("medicines", []):
+            name = med.get("name") or "Unknown"
+            strength = med.get("strength") or "N/A"
+            freq = med.get("dosage_frequency") or "N/A"
+            duration = med.get("duration") or "N/A"
+            output += f"  - 💊 **{name}** – {strength} – Dosage: {freq} – Duration: {duration}\n"
+
+        notes = data.get("notes") or "None"
+        output += f"- **Notes:** {notes}\n"
+
+        return output
+
+    except Exception as e:
+        return f"❌ Error parsing response:\n{text}"
+
+# Load Gemini Chat Model
+chat = model.start_chat(history=[])
+#chat = client.chats.create(model="gemini-2.0-flash")
+
+# Define few-shot prompt to guide the agent
+system_prompt = """
+You are a friendly and knowledgeable AI medical assistant named MediSync.
+You help patients understand their prescriptions, medications, and basic symptoms.
+
+Example Q&A:
+
+Q: I was prescribed Paracetamol 650mg. What is it for?
+A: Paracetamol is used to relieve fever and mild to moderate pain, such as headaches or body aches.
+
+Q: My prescription has Amoxicillin and Clavulanic acid. What condition could this be?
+A: That combination is often used to treat bacterial infections like sinusitis, throat infections, or bronchitis.
+
+Q: What medicine should I take for acidity?
+A: Over-the-counter medicines like Pantoprazole or Ranitidine are commonly used for acidity. Please consult a doctor before taking any medication.
+
+Always include a disclaimer like: "Please consult a licensed medical professional before taking any medication."
+
+Start interacting now.
+"""
+
+# Send system prompt to chat session
+chat.send_message(system_prompt)
+
+# Chatbot function
+def chat_with_medisync(user_question, history):
+    try:
+        response = chat.send_message(user_question)
+        return response.text
+    except Exception as e:
+        return f"❌ Error: {e}"
+
+# Gradio Interface
+with gr.Blocks() as MediSyncAI:
+    gr.Markdown("## 🧠 MediSync.AI - Prescription Reader + Chatbot")
+
+    with gr.Tab("📸 Upload Prescription"):
+        with gr.Row():
+            image_input = gr.Image(type="pil", label="Upload Prescription Image")
+            json_output = gr.Markdown(label="Prescription Summary")
+
+        extract_btn = gr.Button("Extract Info")
+        extract_btn.click(fn=extract_prescription, inputs=image_input, outputs=json_output)
+
+    with gr.Tab("💬 Chat with MediSync"):
+        chatbot = gr.ChatInterface(
+            fn=chat_with_medisync,
+            type="messages",
+            title="MediSync-AI Chatbot",
+            chatbot=gr.Chatbot(label="MediSync"),
+            textbox=gr.Textbox(placeholder="Type your medical question here...", label="Your question"),
+            theme="compact",
+        )
+
+#MediSyncAI.launch()
+if __name__ == "__main__":
+	# Launch the Gradio app	
+    MediSyncAI.launch(share=True, debug=True)
+	# Uncomment the line below to run the app locally without sharing	

medisync-ai.ipynb

@@ -0,0 +1,1135 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "17843267",
+   "metadata": {
+    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
+    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:39:38.864941Z",
+     "iopub.status.busy": "2025-04-10T12:39:38.864173Z",
+     "iopub.status.idle": "2025-04-10T12:39:40.726212Z",
+     "shell.execute_reply": "2025-04-10T12:39:40.725272Z"
+    },
+    "papermill": {
+     "duration": 1.869524,
+     "end_time": "2025-04-10T12:39:40.727823",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:38.858299",
+     "status": "completed"
+    },
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
+    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
+    "# For example, here's several helpful packages to load\n",
+    "\n",
+    "import numpy as np # linear algebra\n",
+    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
+    "\n",
+    "# Input data files are available in the read-only \"../input/\" directory\n",
+    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
+    "\n",
+    "# import os\n",
+    "# for dirname, _, filenames in os.walk('/kaggle/input'):\n",
+    "#     for filename in filenames:\n",
+    "#         print(os.path.join(dirname, filename))\n",
+    "\n",
+    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
+    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25998fd8",
+   "metadata": {
+    "papermill": {
+     "duration": 0.003574,
+     "end_time": "2025-04-10T12:39:40.735704",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:40.732130",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# ❗ What is the Problem?\n",
+    "In many clinics—especially in rural or under-resourced areas—handwritten medical prescriptions remain the norm. These prescriptions are often:\n",
+    "\n",
+    "- Hard to read due to illegible handwriting\n",
+    "- Prone to misinterpretation, leading to wrong medications\n",
+    "- Difficult for patients to understand dosage, strength, and purpose of the medicines\n",
+    "- Lacking digitization, making tracking and processing inefficient\n",
+    "\n",
+    "These challenges not only affect patient safety but also create bottlenecks in pharmacy operations, telemedicine, and healthcare delivery.\n",
+    "\n",
+    "- There is a strong need for an intelligent, automated system that can:\n",
+    "- Accurately read and interpret handwritten prescriptions\n",
+    "- Extract relevant information in structured formats\n",
+    "- Assist patients with friendly explanations of what their prescriptions mean"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ac631bc5",
+   "metadata": {
+    "papermill": {
+     "duration": 0.003458,
+     "end_time": "2025-04-10T12:39:40.743150",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:40.739692",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 💡 Idea - MediSync.AI :\n",
+    "A generative AI-powered assistant that extracts handwritten prescriptions, retrieves drug information, checks for possible interactions, and provides simplified explanations — specifically designed for use in low-resource rural clinics.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d6a51b27",
+   "metadata": {
+    "papermill": {
+     "duration": 0.003648,
+     "end_time": "2025-04-10T12:39:40.750749",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:40.747101",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# ❓ How can Gen AI solve the problem?\n",
+    "Handwritten medical prescriptions are often difficult to read and interpret, especially in rural or resource-constrained settings where access to qualified pharmacists is limited. Traditional OCR systems struggle with messy handwriting and lack contextual understanding. This is where Generative AI becomes powerful — it doesn't just extract text, it understands and structures the data meaningfully.\n",
+    "\n",
+    "By leveraging Google's Gemini-2.0-flash, a multimodal Gen AI model, the system can:\n",
+    "\n",
+    "- Understand handwritten prescription images\n",
+    "- Extract structured information like patient name, medicine names, strengths, dosage frequency, and additional notes\n",
+    "- Engage in interactive Q&A to explain medicines and symptoms to patients\n",
+    "\n",
+    "This significantly reduces manual effort, enhances accuracy, and makes healthcare more accessible — especially in rural clinics or telemedicine use cases."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3c32b7cd",
+   "metadata": {
+    "papermill": {
+     "duration": 0.003501,
+     "end_time": "2025-04-10T12:39:40.758115",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:40.754614",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 🧠 How is the problem solved in code with Gen AI?\n",
+    "The solution is implemented step-by-step using Python and Gemini APIs:\n",
+    "\n",
+    "1. **Image Input & Validation:**\n",
+    "   The image is read using cv2 and validated before being sent to the model.\n",
+    "\n",
+    "2. **Prompt Engineering:**\n",
+    "   A detailed prompt is crafted to instruct Gemini on how to extract and return information in a strict JSON format, including medicine names, dosage, duration, and patient name.\n",
+    "\n",
+    "3. **Calling Gemini-2.0-Flash:**\n",
+    "   The image and prompt are passed to Gemini using generate_content(), which returns a structured response based on its understanding of the prescription.\n",
+    "\n",
+    "4. **Parsing & Display:**\n",
+    "   The JSON output is parsed and the information is neatly formatted using Gradio to display patient info and prescriptions in a user-friendly manner.\n",
+    "\n",
+    "5. **Chatbot Integration:**\n",
+    "   A separate chat module is created using Gemini’s chat model. Few-shot examples guide the chatbot to answer health-related questions, explain prescribed medicines, and provide recommendations with a medical disclaimer.\n",
+    "\n",
+    "This seamless integration of multimodal Gen AI + chat interface makes the system intelligent, helpful, and highly usable in real-world medical settings.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8e450402",
+   "metadata": {
+    "papermill": {
+     "duration": 0.003449,
+     "end_time": "2025-04-10T12:39:40.765249",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:40.761800",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "# 👩🏻‍💻 Code Implementation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81fbb980",
+   "metadata": {
+    "papermill": {
+     "duration": 0.00343,
+     "end_time": "2025-04-10T12:39:40.772448",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:40.769018",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "**GenAI Capabilities Covered:**\n",
+    "\n",
+    "-> Structured output/JSON mode/controlled generation\n",
+    "\n",
+    "-> Few-shot prompting\n",
+    "\n",
+    "-> Image understanding\n",
+    "\n",
+    "-> Chatbot / Agents\n",
+    "\n",
+    "-> Long context window\n",
+    "\n",
+    "-> Function Calling\n",
+    "\n",
+    "-> Document understanding"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "021fda3e",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:39:40.781233Z",
+     "iopub.status.busy": "2025-04-10T12:39:40.780771Z",
+     "iopub.status.idle": "2025-04-10T12:41:24.720680Z",
+     "shell.execute_reply": "2025-04-10T12:41:24.719694Z"
+    },
+    "papermill": {
+     "duration": 103.946402,
+     "end_time": "2025-04-10T12:41:24.722539",
+     "exception": false,
+     "start_time": "2025-04-10T12:39:40.776137",
+     "status": "completed"
+    },
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: easyocr in /usr/local/lib/python3.11/dist-packages (1.7.2)\r\n",
+      "Requirement already satisfied: torch in /usr/local/lib/python3.11/dist-packages (from easyocr) (2.5.1+cu124)\r\n",
+      "Requirement already satisfied: torchvision>=0.5 in /usr/local/lib/python3.11/dist-packages (from easyocr) (0.20.1+cu124)\r\n",
+      "Requirement already satisfied: opencv-python-headless in /usr/local/lib/python3.11/dist-packages (from easyocr) (4.11.0.86)\r\n",
+      "Requirement already satisfied: scipy in /usr/local/lib/python3.11/dist-packages (from easyocr) (1.15.2)\r\n",
+      "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (from easyocr) (1.26.4)\r\n",
+      "Requirement already satisfied: Pillow in /usr/local/lib/python3.11/dist-packages (from easyocr) (11.1.0)\r\n",
+      "Requirement already satisfied: scikit-image in /usr/local/lib/python3.11/dist-packages (from easyocr) (0.25.1)\r\n",
+      "Requirement already satisfied: python-bidi in /usr/local/lib/python3.11/dist-packages (from easyocr) (0.6.6)\r\n",
+      "Requirement already satisfied: PyYAML in /usr/local/lib/python3.11/dist-packages (from easyocr) (6.0.2)\r\n",
+      "Requirement already satisfied: Shapely in /usr/local/lib/python3.11/dist-packages (from easyocr) (2.1.0)\r\n",
+      "Requirement already satisfied: pyclipper in /usr/local/lib/python3.11/dist-packages (from easyocr) (1.3.0.post6)\r\n",
+      "Requirement already satisfied: ninja in /usr/local/lib/python3.11/dist-packages (from easyocr) (1.11.1.4)\r\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (3.18.0)\r\n",
+      "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (4.13.1)\r\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (3.4.2)\r\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (3.1.6)\r\n",
+      "Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (2025.3.2)\r\n",
+      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (12.4.127)\r\n",
+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (12.4.127)\r\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (12.4.127)\r\n",
+      "Collecting nvidia-cudnn-cu12==9.1.0.70 (from torch->easyocr)\r\n",
+      "  Downloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\r\n",
+      "Collecting nvidia-cublas-cu12==12.4.5.8 (from torch->easyocr)\r\n",
+      "  Downloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\r\n",
+      "Collecting nvidia-cufft-cu12==11.2.1.3 (from torch->easyocr)\r\n",
+      "  Downloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\r\n",
+      "Collecting nvidia-curand-cu12==10.3.5.147 (from torch->easyocr)\r\n",
+      "  Downloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\r\n",
+      "Collecting nvidia-cusolver-cu12==11.6.1.9 (from torch->easyocr)\r\n",
+      "  Downloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\r\n",
+      "Collecting nvidia-cusparse-cu12==12.3.1.170 (from torch->easyocr)\r\n",
+      "  Downloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl.metadata (1.6 kB)\r\n",
+      "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (2.21.5)\r\n",
+      "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (12.4.127)\r\n",
+      "Collecting nvidia-nvjitlink-cu12==12.4.127 (from torch->easyocr)\r\n",
+      "  Downloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl.metadata (1.5 kB)\r\n",
+      "Requirement already satisfied: triton==3.1.0 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (3.1.0)\r\n",
+      "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch->easyocr) (1.13.1)\r\n",
+      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch->easyocr) (1.3.0)\r\n",
+      "Requirement already satisfied: mkl_fft in /usr/local/lib/python3.11/dist-packages (from numpy->easyocr) (1.3.8)\r\n",
+      "Requirement already satisfied: mkl_random in /usr/local/lib/python3.11/dist-packages (from numpy->easyocr) (1.2.4)\r\n",
+      "Requirement already satisfied: mkl_umath in /usr/local/lib/python3.11/dist-packages (from numpy->easyocr) (0.1.1)\r\n",
+      "Requirement already satisfied: mkl in /usr/local/lib/python3.11/dist-packages (from numpy->easyocr) (2025.1.0)\r\n",
+      "Requirement already satisfied: tbb4py in /usr/local/lib/python3.11/dist-packages (from numpy->easyocr) (2022.1.0)\r\n",
+      "Requirement already satisfied: mkl-service in /usr/local/lib/python3.11/dist-packages (from numpy->easyocr) (2.4.1)\r\n",
+      "Requirement already satisfied: imageio!=2.35.0,>=2.33 in /usr/local/lib/python3.11/dist-packages (from scikit-image->easyocr) (2.37.0)\r\n",
+      "Requirement already satisfied: tifffile>=2022.8.12 in /usr/local/lib/python3.11/dist-packages (from scikit-image->easyocr) (2025.1.10)\r\n",
+      "Requirement already satisfied: packaging>=21 in /usr/local/lib/python3.11/dist-packages (from scikit-image->easyocr) (24.2)\r\n",
+      "Requirement already satisfied: lazy-loader>=0.4 in /usr/local/lib/python3.11/dist-packages (from scikit-image->easyocr) (0.4)\r\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch->easyocr) (3.0.2)\r\n",
+      "Requirement already satisfied: intel-openmp<2026,>=2024 in /usr/local/lib/python3.11/dist-packages (from mkl->numpy->easyocr) (2024.2.0)\r\n",
+      "Requirement already satisfied: tbb==2022.* in /usr/local/lib/python3.11/dist-packages (from mkl->numpy->easyocr) (2022.1.0)\r\n",
+      "Requirement already satisfied: tcmlib==1.* in /usr/local/lib/python3.11/dist-packages (from tbb==2022.*->mkl->numpy->easyocr) (1.2.0)\r\n",
+      "Requirement already satisfied: intel-cmplr-lib-rt in /usr/local/lib/python3.11/dist-packages (from mkl_umath->numpy->easyocr) (2024.2.0)\r\n",
+      "Requirement already satisfied: intel-cmplr-lib-ur==2024.2.0 in /usr/local/lib/python3.11/dist-packages (from intel-openmp<2026,>=2024->mkl->numpy->easyocr) (2024.2.0)\r\n",
+      "Downloading nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl (363.4 MB)\r\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
+      "\u001b[?25hDownloading nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl (664.8 MB)\r\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m2.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
+      "\u001b[?25hDownloading nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl (211.5 MB)\r\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
+      "\u001b[?25hDownloading nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl (56.3 MB)\r\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m30.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
+      "\u001b[?25hDownloading nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl (127.9 MB)\r\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m12.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
+      "\u001b[?25hDownloading nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl (207.5 MB)\r\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m2.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
+      "\u001b[?25hDownloading nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\r\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m79.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
+      "\u001b[?25hInstalling collected packages: nvidia-nvjitlink-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12\r\n",
+      "  Attempting uninstall: nvidia-nvjitlink-cu12\r\n",
+      "    Found existing installation: nvidia-nvjitlink-cu12 12.8.93\r\n",
+      "    Uninstalling nvidia-nvjitlink-cu12-12.8.93:\r\n",
+      "      Successfully uninstalled nvidia-nvjitlink-cu12-12.8.93\r\n",
+      "  Attempting uninstall: nvidia-curand-cu12\r\n",
+      "    Found existing installation: nvidia-curand-cu12 10.3.9.90\r\n",
+      "    Uninstalling nvidia-curand-cu12-10.3.9.90:\r\n",
+      "      Successfully uninstalled nvidia-curand-cu12-10.3.9.90\r\n",
+      "  Attempting uninstall: nvidia-cufft-cu12\r\n",
+      "    Found existing installation: nvidia-cufft-cu12 11.3.3.83\r\n",
+      "    Uninstalling nvidia-cufft-cu12-11.3.3.83:\r\n",
+      "      Successfully uninstalled nvidia-cufft-cu12-11.3.3.83\r\n",
+      "  Attempting uninstall: nvidia-cublas-cu12\r\n",
+      "    Found existing installation: nvidia-cublas-cu12 12.8.4.1\r\n",
+      "    Uninstalling nvidia-cublas-cu12-12.8.4.1:\r\n",
+      "      Successfully uninstalled nvidia-cublas-cu12-12.8.4.1\r\n",
+      "  Attempting uninstall: nvidia-cusparse-cu12\r\n",
+      "    Found existing installation: nvidia-cusparse-cu12 12.5.8.93\r\n",
+      "    Uninstalling nvidia-cusparse-cu12-12.5.8.93:\r\n",
+      "      Successfully uninstalled nvidia-cusparse-cu12-12.5.8.93\r\n",
+      "  Attempting uninstall: nvidia-cudnn-cu12\r\n",
+      "    Found existing installation: nvidia-cudnn-cu12 9.3.0.75\r\n",
+      "    Uninstalling nvidia-cudnn-cu12-9.3.0.75:\r\n",
+      "      Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\r\n",
+      "  Attempting uninstall: nvidia-cusolver-cu12\r\n",
+      "    Found existing installation: nvidia-cusolver-cu12 11.7.3.90\r\n",
+      "    Uninstalling nvidia-cusolver-cu12-11.7.3.90:\r\n",
+      "      Successfully uninstalled nvidia-cusolver-cu12-11.7.3.90\r\n",
+      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\r\n",
+      "pylibcugraph-cu12 24.12.0 requires pylibraft-cu12==24.12.*, but you have pylibraft-cu12 25.2.0 which is incompatible.\r\n",
+      "pylibcugraph-cu12 24.12.0 requires rmm-cu12==24.12.*, but you have rmm-cu12 25.2.0 which is incompatible.\u001b[0m\u001b[31m\r\n",
+      "\u001b[0mSuccessfully installed nvidia-cublas-cu12-12.4.5.8 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127\r\n",
+      "Requirement already satisfied: sentence-transformers in /usr/local/lib/python3.11/dist-packages (3.4.1)\r\n",
+      "Collecting faiss-cpu\r\n",
+      "  Downloading faiss_cpu-1.10.0-cp311-cp311-manylinux_2_28_x86_64.whl.metadata (4.4 kB)\r\n",
+      "Requirement already satisfied: transformers<5.0.0,>=4.41.0 in /usr/local/lib/python3.11/dist-packages (from sentence-transformers) (4.51.1)\r\n",
+      "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from sentence-transformers) (4.67.1)\r\n",
+      "Requirement already satisfied: torch>=1.11.0 in /usr/local/lib/python3.11/dist-packages (from sentence-transformers) (2.5.1+cu124)\r\n",
+      "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.11/dist-packages (from sentence-transformers) (1.2.2)\r\n",
+      "Requirement already satisfied: scipy in /usr/local/lib/python3.11/dist-packages (from sentence-transformers) (1.15.2)\r\n",
+      "Requirement already satisfied: huggingface-hub>=0.20.0 in /usr/local/lib/python3.11/dist-packages (from sentence-transformers) (0.30.2)\r\n",
+      "Requirement already satisfied: Pillow in /usr/local/lib/python3.11/dist-packages (from sentence-transformers) (11.1.0)\r\n",
+      "Requirement already satisfied: numpy<3.0,>=1.25.0 in /usr/local/lib/python3.11/dist-packages (from faiss-cpu) (1.26.4)\r\n",
+      "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from faiss-cpu) (24.2)\r\n",
+      "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.20.0->sentence-transformers) (3.18.0)\r\n",
+      "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.20.0->sentence-transformers) (2025.3.2)\r\n",
+      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.20.0->sentence-transformers) (6.0.2)\r\n",
+      "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.20.0->sentence-transformers) (2.32.3)\r\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.20.0->sentence-transformers) (4.13.1)\r\n",
+      "Requirement already satisfied: mkl_fft in /usr/local/lib/python3.11/dist-packages (from numpy<3.0,>=1.25.0->faiss-cpu) (1.3.8)\r\n",
+      "Requirement already satisfied: mkl_random in /usr/local/lib/python3.11/dist-packages (from numpy<3.0,>=1.25.0->faiss-cpu) (1.2.4)\r\n",
+      "Requirement already satisfied: mkl_umath in /usr/local/lib/python3.11/dist-packages (from numpy<3.0,>=1.25.0->faiss-cpu) (0.1.1)\r\n",
+      "Requirement already satisfied: mkl in /usr/local/lib/python3.11/dist-packages (from numpy<3.0,>=1.25.0->faiss-cpu) (2025.1.0)\r\n",
+      "Requirement already satisfied: tbb4py in /usr/local/lib/python3.11/dist-packages (from numpy<3.0,>=1.25.0->faiss-cpu) (2022.1.0)\r\n",
+      "Requirement already satisfied: mkl-service in /usr/local/lib/python3.11/dist-packages (from numpy<3.0,>=1.25.0->faiss-cpu) (2.4.1)\r\n",
+      "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (3.4.2)\r\n",
+      "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (3.1.6)\r\n",
+      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (12.4.127)\r\n",
+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (12.4.127)\r\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (12.4.127)\r\n",
+      "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (9.1.0.70)\r\n",
+      "Requirement already satisfied: nvidia-cublas-cu12==12.4.5.8 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (12.4.5.8)\r\n",
+      "Requirement already satisfied: nvidia-cufft-cu12==11.2.1.3 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (11.2.1.3)\r\n",
+      "Requirement already satisfied: nvidia-curand-cu12==10.3.5.147 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (10.3.5.147)\r\n",
+      "Requirement already satisfied: nvidia-cusolver-cu12==11.6.1.9 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (11.6.1.9)\r\n",
+      "Requirement already satisfied: nvidia-cusparse-cu12==12.3.1.170 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (12.3.1.170)\r\n",
+      "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (2.21.5)\r\n",
+      "Requirement already satisfied: nvidia-nvtx-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (12.4.127)\r\n",
+      "Requirement already satisfied: nvidia-nvjitlink-cu12==12.4.127 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (12.4.127)\r\n",
+      "Requirement already satisfied: triton==3.1.0 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (3.1.0)\r\n",
+      "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch>=1.11.0->sentence-transformers) (1.13.1)\r\n",
+      "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=1.11.0->sentence-transformers) (1.3.0)\r\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.11/dist-packages (from transformers<5.0.0,>=4.41.0->sentence-transformers) (2024.11.6)\r\n",
+      "Requirement already satisfied: tokenizers<0.22,>=0.21 in /usr/local/lib/python3.11/dist-packages (from transformers<5.0.0,>=4.41.0->sentence-transformers) (0.21.0)\r\n",
+      "Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.11/dist-packages (from transformers<5.0.0,>=4.41.0->sentence-transformers) (0.5.2)\r\n",
+      "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from scikit-learn->sentence-transformers) (1.4.2)\r\n",
+      "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from scikit-learn->sentence-transformers) (3.6.0)\r\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=1.11.0->sentence-transformers) (3.0.2)\r\n",
+      "Requirement already satisfied: intel-openmp<2026,>=2024 in /usr/local/lib/python3.11/dist-packages (from mkl->numpy<3.0,>=1.25.0->faiss-cpu) (2024.2.0)\r\n",
+      "Requirement already satisfied: tbb==2022.* in /usr/local/lib/python3.11/dist-packages (from mkl->numpy<3.0,>=1.25.0->faiss-cpu) (2022.1.0)\r\n",
+      "Requirement already satisfied: tcmlib==1.* in /usr/local/lib/python3.11/dist-packages (from tbb==2022.*->mkl->numpy<3.0,>=1.25.0->faiss-cpu) (1.2.0)\r\n",
+      "Requirement already satisfied: intel-cmplr-lib-rt in /usr/local/lib/python3.11/dist-packages (from mkl_umath->numpy<3.0,>=1.25.0->faiss-cpu) (2024.2.0)\r\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface-hub>=0.20.0->sentence-transformers) (3.4.1)\r\n",
+      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface-hub>=0.20.0->sentence-transformers) (3.10)\r\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface-hub>=0.20.0->sentence-transformers) (2.3.0)\r\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface-hub>=0.20.0->sentence-transformers) (2025.1.31)\r\n",
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+      "\u001b[?25hDownloading ffmpy-0.5.0-py3-none-any.whl (6.0 kB)\r\n",
+      "Installing collected packages: uvicorn, tomlkit, semantic-version, ruff, python-multipart, groovy, ffmpy, starlette, safehttpx, gradio-client, fastapi, gradio\r\n",
+      "Successfully installed fastapi-0.115.12 ffmpy-0.5.0 gradio-5.24.0 gradio-client-1.8.0 groovy-0.1.2 python-multipart-0.0.20 ruff-0.11.4 safehttpx-0.1.6 semantic-version-2.10.0 starlette-0.46.1 tomlkit-0.13.2 uvicorn-0.34.0\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Install and import necessary libraries\n",
+    "!pip install easyocr\n",
+    "!pip install sentence-transformers faiss-cpu\n",
+    "!pip install -U -q \"google-genai==1.7.0\"  # Install latest Google GenAI SDK\n",
+    "!pip install gradio # To quickly build and share interactive web interfaces"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "585b1ccf",
+   "metadata": {
+    "papermill": {
+     "duration": 0.035728,
+     "end_time": "2025-04-10T12:41:24.794543",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:24.758815",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Step 1: Import necessary Libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "3d1d9fa3",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:41:24.870584Z",
+     "iopub.status.busy": "2025-04-10T12:41:24.870261Z",
+     "iopub.status.idle": "2025-04-10T12:41:41.412768Z",
+     "shell.execute_reply": "2025-04-10T12:41:41.411737Z"
+    },
+    "papermill": {
+     "duration": 16.583233,
+     "end_time": "2025-04-10T12:41:41.414603",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:24.831370",
+     "status": "completed"
+    },
+    "scrolled": true,
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import cv2  # For image validation\n",
+    "import easyocr  # For basic OCR (if needed)\n",
+    "import numpy as np\n",
+    "from PIL import Image  # For image loading\n",
+    "from google import genai  # Google Gemini API\n",
+    "from kaggle_secrets import UserSecretsClient  # Securely fetch API keys\n",
+    "from IPython.display import Markdown  # Display Markdown-formatted text\n",
+    "import json\n",
+    "import re\n",
+    "\n",
+    "genai.__version__\n",
+    "reader = easyocr.Reader(['en'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8ad151e0",
+   "metadata": {
+    "papermill": {
+     "duration": 0.035736,
+     "end_time": "2025-04-10T12:41:41.487309",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:41.451573",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Step 2: Set up your API key\n",
+    "\n",
+    "To run the following cell, your API key must be stored it in a [Kaggle secret](https://www.kaggle.com/discussions/product-feedback/114053) named `GOOGLE_API_KEY`.\n",
+    "\n",
+    "If you don't already have an API key, you can grab one from [AI Studio](https://aistudio.google.com/app/apikey). You can find [detailed instructions in the docs](https://ai.google.dev/gemini-api/docs/api-key).\n",
+    "\n",
+    "To make the key available through Kaggle secrets, choose `Secrets` from the `Add-ons` menu and follow the instructions to add your key or enable it for this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b67861f2",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:41:41.632499Z",
+     "iopub.status.busy": "2025-04-10T12:41:41.631925Z",
+     "iopub.status.idle": "2025-04-10T12:41:42.089240Z",
+     "shell.execute_reply": "2025-04-10T12:41:42.088225Z"
+    },
+    "papermill": {
+     "duration": 0.498242,
+     "end_time": "2025-04-10T12:41:42.091038",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:41.592796",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "GOOGLE_API_KEY = UserSecretsClient().get_secret(\"GOOGLE_API_KEY2\")\n",
+    "client = genai.Client(api_key=GOOGLE_API_KEY)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9b0c6ac3",
+   "metadata": {
+    "papermill": {
+     "duration": 0.036583,
+     "end_time": "2025-04-10T12:41:42.164665",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:42.128082",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Step 3: Write Prompt for gemini-2.0-flash"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "fb9f5f05",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:41:42.241566Z",
+     "iopub.status.busy": "2025-04-10T12:41:42.240797Z",
+     "iopub.status.idle": "2025-04-10T12:41:42.246150Z",
+     "shell.execute_reply": "2025-04-10T12:41:42.245230Z"
+    },
+    "papermill": {
+     "duration": 0.045459,
+     "end_time": "2025-04-10T12:41:42.247885",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:42.202426",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Prompt for image-based structured output\n",
+    "prompt = \"\"\"\n",
+    "You are a medical assistant AI. Extract structured data from this handwritten prescription image.\n",
+    "\n",
+    "Here are some common medicines there strength and usage\n",
+    "Medicine Name\tStrength Example\tUsage\n",
+    "Paracetamol\t500mg, 650mg\tPain relief, fever\n",
+    "Amoxicillin\t250mg, 500mg\tAntibiotic\n",
+    "Azithromycin\t250mg, 500mg\tAntibiotic\n",
+    "Ibuprofen\t400mg, 600mg\tPain relief, anti-inflammatory\n",
+    "Cefixime\t200mg\tAntibiotic\n",
+    "Pantoprazole\t40mg\tAcidity, ulcer prevention\n",
+    "Domperidone\t10mg\tAnti-nausea\n",
+    "Metformin\t500mg, 1000mg\tDiabetes\n",
+    "Amlodipine\t5mg\tBlood pressure\n",
+    "Cetirizine\t10mg\tAnti-allergy\n",
+    "Ranitidine\t150mg\tAcidity\n",
+    "Dolo 650\t650mg\tFever, pain relief\n",
+    "Ondansetron\t4mg, 8mg\tAnti-vomiting\n",
+    "Levocetirizine\t5mg\tAllergy\n",
+    "Losartan\t50mg\tBlood pressure\n",
+    "Clavulanic Acid\t125mg (with Amox)\tAntibiotic combo\n",
+    "Salbutamol\tInhaler/Syrup\tAsthma\n",
+    "\n",
+    "Even if handwritten, try your best to extract medicine names, dosage frequency (like 1-0-1), and strength (mg).\n",
+    "\n",
+    "Focus on extracting:\n",
+    "- Patient name\n",
+    "- List of medicines prescribed (Paracetamol)\n",
+    "- Strength (mg, ml, etc.)\n",
+    "- Dosage frequency (e.g., 1-0-1 or twice daily)\n",
+    "- Duration\n",
+    "- Additional notes\n",
+    "\n",
+    "Return ONLY this JSON format:\n",
+    "{\n",
+    "  \"patient_name\": \"\",\n",
+    "  \"medicines\": [\n",
+    "    {\n",
+    "      \"name\": \"\",\n",
+    "      \"strength\": \"\",\n",
+    "      \"dosage_frequency\": \"\",\n",
+    "      \"duration\": \"\"\n",
+    "    }\n",
+    "  ],\n",
+    "  \"notes\": \"\"\n",
+    "}\n",
+    "If any field is missing, return it as null.\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "202b4348",
+   "metadata": {
+    "papermill": {
+     "duration": 0.036349,
+     "end_time": "2025-04-10T12:41:42.321816",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:42.285467",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Step 4: Example OCR on an uploaded image "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "69aac56b",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:41:42.396698Z",
+     "iopub.status.busy": "2025-04-10T12:41:42.396369Z",
+     "iopub.status.idle": "2025-04-10T12:41:42.435333Z",
+     "shell.execute_reply": "2025-04-10T12:41:42.434378Z"
+    },
+    "papermill": {
+     "duration": 0.077791,
+     "end_time": "2025-04-10T12:41:42.437051",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:42.359260",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Load image\n",
+    "image_path = '/kaggle/input/sample-prescriptions/data/103.jpg'\n",
+    "image = Image.open(image_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ed1b2825",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:41:42.512695Z",
+     "iopub.status.busy": "2025-04-10T12:41:42.511923Z",
+     "iopub.status.idle": "2025-04-10T12:41:44.240251Z",
+     "shell.execute_reply": "2025-04-10T12:41:44.239285Z"
+    },
+    "papermill": {
+     "duration": 1.767306,
+     "end_time": "2025-04-10T12:41:44.241756",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:42.474450",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "```json\n",
+      "{\n",
+      "  \"patient_name\": \"Greg Stefans\",\n",
+      "  \"medicines\": [\n",
+      "    {\n",
+      "      \"name\": \"Cocaine\",\n",
+      "      \"strength\": \"SUOU\",\n",
+      "      \"dosage_frequency\": null,\n",
+      "      \"duration\": null\n",
+      "    },\n",
+      "    {\n",
+      "      \"name\": \"Ung resorcim comp\",\n",
+      "      \"strength\": \"3T\",\n",
+      "      \"dosage_frequency\": null,\n",
+      "      \"duration\": null\n",
+      "    }\n",
+      "  ],\n",
+      "  \"notes\": \"Apply 3 times a day\"\n",
+      "}\n",
+      "```\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Ask Gemini to understand image\n",
+    "def is_valid_image(image_path):\n",
+    "    try:\n",
+    "        img = cv2.imread(image_path)\n",
+    "        return img is not None\n",
+    "    except Exception as e:\n",
+    "        print(f\"Failed to load image: {image_path}, error: {e}\")\n",
+    "        return False\n",
+    "\n",
+    "# Example OCR on an uploaded image\n",
+    "if is_valid_image(image_path):\n",
+    "    response = client.models.generate_content(\n",
+    "        model=\"gemini-2.0-flash\",\n",
+    "        contents=[\n",
+    "            prompt,\n",
+    "            image])\n",
+    "    print(response.text) \n",
+    "else:\n",
+    "    print(f\"Skipping corrupted image: {image_path}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f8bf9db",
+   "metadata": {
+    "papermill": {
+     "duration": 0.03661,
+     "end_time": "2025-04-10T12:41:44.315470",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:44.278860",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Step 5: Trying out Chat Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "fd770528",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:41:44.391332Z",
+     "iopub.status.busy": "2025-04-10T12:41:44.390927Z",
+     "iopub.status.idle": "2025-04-10T12:41:45.896031Z",
+     "shell.execute_reply": "2025-04-10T12:41:45.895171Z"
+    },
+    "papermill": {
+     "duration": 1.545711,
+     "end_time": "2025-04-10T12:41:45.897584",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:44.351873",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "Okay!\n",
+       "\n",
+       "*   **Azithromycin** is an antibiotic. It's used to treat a variety of bacterial infections, such as respiratory infections (like bronchitis or pneumonia), skin infections, and sexually transmitted infections.\n",
+       "\n",
+       "*   **Cetirizine** is an antihistamine. It's commonly used to relieve allergy symptoms such as runny nose, sneezing, itchy eyes, and skin rashes.\n",
+       "\n",
+       "So, it sounds like you may have a bacterial infection and are experiencing allergy symptoms.\n",
+       "\n",
+       "Please consult a licensed medical professional before taking any medication.\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Load Gemini Chat Model\n",
+    "chat = client.chats.create(model=\"gemini-2.0-flash\")\n",
+    "\n",
+    "# Define few-shot prompt to guide the agent\n",
+    "system_prompt = \"\"\"\n",
+    "You are a friendly and knowledgeable AI medical assistant named MediSync.\n",
+    "You help patients understand their prescriptions, medications, and basic symptoms.\n",
+    "\n",
+    "Example Q&A:\n",
+    "\n",
+    "Q: I was prescribed Paracetamol 650mg. What is it for?\n",
+    "A: Paracetamol is used to relieve fever and mild to moderate pain, such as headaches or body aches.\n",
+    "\n",
+    "Q: My prescription has Amoxicillin and Clavulanic acid. What condition could this be?\n",
+    "A: That combination is often used to treat bacterial infections like sinusitis, throat infections, or bronchitis.\n",
+    "\n",
+    "Q: What medicine should I take for acidity?\n",
+    "A: Over-the-counter medicines like Pantoprazole or Ranitidine are commonly used for acidity. Please consult a doctor before taking any medication.\n",
+    "\n",
+    "Always include a disclaimer like: \"Please consult a licensed medical professional before taking any medication.\"\n",
+    "\n",
+    "Start interacting now.\n",
+    "\"\"\"\n",
+    "\n",
+    "# Send system prompt to chat session\n",
+    "chat.send_message(system_prompt)\n",
+    "\n",
+    "# Example chat interaction\n",
+    "user_question = \"I was prescribed Azithromycin and Cetirizine. What are they used for?\"\n",
+    "response = chat.send_message(user_question)\n",
+    "\n",
+    "Markdown(response.text)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53ddb8ca",
+   "metadata": {
+    "papermill": {
+     "duration": 0.037569,
+     "end_time": "2025-04-10T12:41:45.972235",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:45.934666",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "source": [
+    "## Step 6: Building Gradio Interface"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f7136439",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2025-04-10T12:41:46.053703Z",
+     "iopub.status.busy": "2025-04-10T12:41:46.053388Z",
+     "iopub.status.idle": "2025-04-10T12:41:51.808620Z",
+     "shell.execute_reply": "2025-04-10T12:41:51.807705Z"
+    },
+    "papermill": {
+     "duration": 5.798177,
+     "end_time": "2025-04-10T12:41:51.810261",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:46.012084",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_13/1192573786.py:72: UserWarning: You have not specified a value for the `type` parameter. Defaulting to the 'tuples' format for chatbot messages, but this is deprecated and will be removed in a future version of Gradio. Please set type='messages' instead, which uses openai-style dictionaries with 'role' and 'content' keys.\n",
+      "  chatbot=gr.Chatbot(label=\"MediSync\"),\n",
+      "/usr/local/lib/python3.11/dist-packages/gradio/blocks.py:1115: UserWarning: Cannot load compact. Caught Exception: 404 Client Error: Not Found for url: https://huggingface.co/api/spaces/compact (Request ID: Root=1-67f7bc8d-299c34a7360aed6e6d6ab95b;708ae4ba-5fb8-4ce9-941b-4dbf872a2ed8)\n",
+      "\n",
+      "Sorry, we can't find the page you are looking for.\n",
+      "  warnings.warn(f\"Cannot load {theme}. Caught Exception: {str(e)}\")\n",
+      "/usr/local/lib/python3.11/dist-packages/gradio/chat_interface.py:314: UserWarning: The type of the gr.Chatbot does not match the type of the gr.ChatInterface.The type of the gr.ChatInterface, 'messages', will be used.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "* Running on local URL:  http://127.0.0.1:7860\n",
+      "Kaggle notebooks require sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
+      "\n",
+      "* Running on public URL: https://35c21101bf8d390fde.gradio.live\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://35c21101bf8d390fde.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "from PIL import Image\n",
+    "from google import genai\n",
+    "\n",
+    "# Function to handle image input\n",
+    "def extract_prescription(image):\n",
+    "    if image is None:\n",
+    "        return \"Please upload an image.\"\n",
+    "\n",
+    "    response = client.models.generate_content(\n",
+    "        model=\"gemini-2.0-flash\",\n",
+    "        contents=[\n",
+    "            prompt,\n",
+    "            image\n",
+    "        ]\n",
+    "    )\n",
+    "    text = response.text.strip()\n",
+    "\n",
+    "    # Remove markdown formatting if any\n",
+    "    if text.startswith(\"```json\"):\n",
+    "        text = re.sub(r\"```json|```\", \"\", text).strip()\n",
+    "\n",
+    "    try:\n",
+    "        data = json.loads(text)\n",
+    "\n",
+    "        # Format nicely\n",
+    "        output = f\"### 👩‍⚕️ Prescription Summary\\n\"\n",
+    "        output += f\"- **Patient Name:** {data.get('patient_name', 'N/A') or 'N/A'}\\n\"\n",
+    "        output += f\"- **Medicines Prescribed:**\\n\"\n",
+    "\n",
+    "        for med in data.get(\"medicines\", []):\n",
+    "            name = med.get(\"name\") or \"Unknown\"\n",
+    "            strength = med.get(\"strength\") or \"N/A\"\n",
+    "            freq = med.get(\"dosage_frequency\") or \"N/A\"\n",
+    "            duration = med.get(\"duration\") or \"N/A\"\n",
+    "            output += f\"  - 💊 **{name}** – {strength} – Dosage: {freq} – Duration: {duration}\\n\"\n",
+    "\n",
+    "        notes = data.get(\"notes\") or \"None\"\n",
+    "        output += f\"- **Notes:** {notes}\\n\"\n",
+    "\n",
+    "        return output\n",
+    "\n",
+    "    except Exception as e:\n",
+    "        return f\"❌ Error parsing response:\\n{text}\"\n",
+    "\n",
+    "\n",
+    "# Chatbot function\n",
+    "def chat_with_medisync(user_question, history):\n",
+    "    try:\n",
+    "        response = chat.send_message(user_question)\n",
+    "        return response.text\n",
+    "    except Exception as e:\n",
+    "        return f\"❌ Error: {e}\"\n",
+    "\n",
+    "# Gradio Interface\n",
+    "with gr.Blocks() as MediSyncAI:\n",
+    "    gr.Markdown(\"## 🧠 MediSync.AI - Prescription Reader + Chatbot\")\n",
+    "\n",
+    "    with gr.Tab(\"📸 Upload Prescription\"):\n",
+    "        with gr.Row():\n",
+    "            image_input = gr.Image(type=\"pil\", label=\"Upload Prescription Image\")\n",
+    "            json_output = gr.Markdown(label=\"Prescription Summary\")\n",
+    "\n",
+    "        extract_btn = gr.Button(\"Extract Info\")\n",
+    "        extract_btn.click(fn=extract_prescription, inputs=image_input, outputs=json_output)\n",
+    "\n",
+    "    with gr.Tab(\"💬 Chat with MediSync\"):\n",
+    "        chatbot = gr.ChatInterface(\n",
+    "            fn=chat_with_medisync,\n",
+    "            type=\"messages\",\n",
+    "            title=\"MediSync-AI Chatbot\",\n",
+    "            chatbot=gr.Chatbot(label=\"MediSync\"),\n",
+    "            textbox=gr.Textbox(placeholder=\"Type your medical question here...\", label=\"Your question\"),\n",
+    "            theme=\"compact\",\n",
+    "        )\n",
+    "\n",
+    "MediSyncAI.launch()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8e301983",
+   "metadata": {
+    "papermill": {
+     "duration": 0.037968,
+     "end_time": "2025-04-10T12:41:51.886595",
+     "exception": false,
+     "start_time": "2025-04-10T12:41:51.848627",
+     "status": "completed"
+    },
+    "tags": []
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kaggle": {
+   "accelerator": "none",
+   "dataSources": [
+    {
+     "datasetId": 7102462,
+     "sourceId": 11350664,
+     "sourceType": "datasetVersion"
+    }
+   ],
+   "dockerImageVersionId": 31012,
+   "isGpuEnabled": false,
+   "isInternetEnabled": true,
+   "language": "python",
+   "sourceType": "notebook"
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.11"
+  },
+  "papermill": {
+   "default_parameters": {},
+   "duration": 140.358489,
+   "end_time": "2025-04-10T12:41:54.546120",
+   "environment_variables": {},
+   "exception": null,
+   "input_path": "__notebook__.ipynb",
+   "output_path": "__notebook__.ipynb",
+   "parameters": {},
+   "start_time": "2025-04-10T12:39:34.187631",
+   "version": "2.6.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

requirements.txt

@@ -0,0 +1,73 @@
+aiofiles==24.1.0
+annotated-types==0.7.0
+anyio==4.9.0
+audioop-lts==0.2.1
+cachetools==5.5.2
+certifi==2025.1.31
+charset-normalizer==3.4.1
+click==8.1.8
+fastapi==0.115.12
+ffmpy==0.5.0
+filelock==3.18.0
+fsspec==2025.3.2
+google-ai-generativelanguage==0.6.15
+google-api-core==2.24.2
+google-api-python-client==2.166.0
+google-auth==2.38.0
+google-auth-httplib2==0.2.0
+google-generativeai==0.8.4
+googleapis-common-protos==1.69.2
+gradio==5.25.0
+gradio_client==1.8.0
+groovy==0.1.2
+grpcio==1.72.0rc1
+grpcio-status==1.71.0
+h11==0.14.0
+httpcore==1.0.8
+httplib2==0.22.0
+httpx==0.28.1
+huggingface-hub==0.30.2
+idna==3.10
+Jinja2==3.1.6
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+mdurl==0.1.2
+numpy==2.2.4
+orjson==3.10.16
+packaging==24.2
+pandas==2.2.3
+pillow==11.1.0
+proto-plus==1.26.1
+protobuf==5.29.4
+pyasn1==0.6.1
+pyasn1_modules==0.4.2
+pydantic==2.11.3
+pydantic_core==2.33.1
+pydub==0.25.1
+Pygments==2.19.1
+pyparsing==3.2.3
+python-dateutil==2.9.0.post0
+python-dotenv==1.1.0
+python-multipart==0.0.20
+pytz==2025.2
+PyYAML==6.0.2
+requests==2.32.3
+rich==14.0.0
+rsa==4.9
+ruff==0.11.5
+safehttpx==0.1.6
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+starlette==0.46.1
+tomlkit==0.13.2
+tqdm==4.67.1
+typer==0.15.2
+typing-inspection==0.4.0
+typing_extensions==4.13.2
+tzdata==2025.2
+uritemplate==4.1.1
+urllib3==2.4.0
+uvicorn==0.34.0
+websockets==15.0.1