Upload thai_maternal_health.py

thai_maternal_health.py

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+# -*- coding: utf-8 -*-
+"""thai maternal health.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1sk8TdnCQ8qOKCkzn_hPmCj8uU6xaV3HM
+"""
+
+# Simple Chatbot Gradio + Google Gemini API 🚀
+
+#@title Mostrar Imagen
+from IPython.display import Image
+url = 'https://github.com/AleNunezArroyo/Medium/blob/main/img/BannerM4.png?raw=true'
+Image(url=url, width=800)
+
+# Install the Python SDK
+!pip install -q -U google-generativeai
+
+# The library and API Key information is added
+import google.generativeai as genai
+import time  # Import the time module
+
+# Replace with your actual Google API key
+GOOGLE_API_KEY = "AIzaSyDw4vZTtNZrHN32Ekv5sS-FTvgp3KkqQhk"
+genai.configure(api_key=GOOGLE_API_KEY)
+
+# Model configuration
+model = genai.GenerativeModel('gemini-pro')
+
+# Chat conversations
+chat = model.start_chat(history=[])
+
+# Prompt tuning for maternal health
+def maternal_health_prompt(language_code):
+    return f"""You are a knowledgeable and compassionate maternal health expert.
+    Provide accurate, clear, and culturally sensitive information about maternal health,
+    pregnancy, childbirth, and postpartum care. Respond in the language corresponding to the language code: {language_code}.
+    Keep responses concise, friendly, and focused on evidence-based medical information.
+    If you're unsure about anything, recommend consulting a healthcare provider."""
+
+# Transform Gradio history to Gemini format
+def transform_history(history):
+    new_history = []
+    for chat in history:
+        new_history.append({"parts": [{"text": chat[0]}], "role": "user"})
+        new_history.append({"parts": [{"text": chat[1]}], "role": "model"})
+    return new_history
+
+# Response function
+def response(message, history, language_code):
+    global chat
+    # Update the chat history in the Gemini format
+    chat.history = transform_history(history)
+
+    # Use the prompt tuning for the maternal health expert context
+    prompt = maternal_health_prompt(language_code) + f"\n\nUser: {message}"
+
+    # Send the message and get the response
+    response = chat.send_message(prompt)
+    response.resolve()
+
+    # Each character of the answer is displayed
+    for i in range(len(response.text)):
+        time.sleep(0.05)
+        yield response.text[: i + 1]
+
+# Gradio interface
+import gradio as gr
+
+# Set up Gradio interface
+language_code = "th-TH"  # Change this to the desired language code
+gr.ChatInterface(response,
+                 title='Maternal Health Chatbot',
+                 textbox=gr.Textbox(placeholder="Ask your question about maternal health")).launch(debug=True)
+
+# Save chat history if necessary
+# chat.history can be accessed to save conversation history if required.