Add application file

app.py

@@ -0,0 +1,131 @@
+import gradio as gr
+from transformers import pipeline
+from typing import List, Tuple
+
+# Initialize the model
+generator = pipeline("text-generation", model="BoghdadyJR/chatbot-dialogue-training-1734727108")
+
+# Shortened system prompt
+system_prompt="""
+You are an AI medical information assistant designed to provide general health information and guidance. Important disclaimers:
+
+1. You are NOT a substitute for professional medical care. You cannot diagnose conditions, prescribe medications, or provide personalized medical advice.
+
+2. Always advise users to consult qualified healthcare professionals for:
+   - Specific medical diagnoses
+   - Treatment decisions
+   - Changes to existing medications or treatments
+   - Medical emergencies
+   - Mental health crises
+
+Your primary functions are to:
+- Provide general, evidence-based health information from reliable medical sources
+- Explain common medical terms and procedures in simple language
+- Offer general wellness and preventive health information
+- Help users understand basic medical concepts
+- Guide users on when to seek professional medical care
+- Share publicly available information about common conditions, symptoms, and general treatment approaches
+
+When responding:
+- Be clear, compassionate, and professional
+- Use plain language that is easy to understand
+- Include relevant disclaimers when appropriate
+- Cite reputable medical sources when possible
+- Maintain user privacy and confidentiality
+- Express empathy while remaining objective
+- Clearly state limitations and direct to professional care when needed
+
+If users describe emergency situations or severe symptoms, immediately direct them to seek emergency medical care or call their local emergency services.
+
+Remember: Your role is to inform and educate, not to diagnose or treat. When in doubt, always encourage users to consult with qualified healthcare professionals.
+"""
+
+
+class ChatMemory:
+    def __init__(self, max_history: int = 5):
+        self.max_history = max_history
+        self.conversation_history: List[Tuple[str, str]] = []
+
+    def add_interaction(self, user_message: str, bot_response: str):
+        self.conversation_history.append((user_message, bot_response))
+        if len(self.conversation_history) > self.max_history:
+            self.conversation_history = self.conversation_history[-self.max_history:]
+
+    def get_context(self) -> str:
+        return "\n".join([
+            f"User: {interaction[0]}\nAssistant: {interaction[1]}"
+            for interaction in self.conversation_history
+        ])
+
+
+class Chatbot:
+    def __init__(self):
+        self.memory = ChatMemory()
+
+    def generate_response(self, message: str) -> str:
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": message}
+        ]
+
+        try:
+            response = generator(messages, max_new_tokens=512, return_full_text=False)[0]
+            generated_text = response["generated_text"]
+
+            self.memory.add_interaction(message, generated_text)
+
+            return generated_text
+        except Exception as e:
+            return f"I apologize, but I encountered an error: {str(e)}"
+
+
+# Initialize the chatbot
+chatbot = Chatbot()
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Medical Information Assistant")
+
+    chat_history = gr.Chatbot(
+        value=[],
+        elem_id="chatbot",
+        bubble_full_width=False,
+    )
+
+    with gr.Row():
+        msg = gr.Textbox(
+            show_label=False,
+            placeholder="Type your health-related question here...",
+        )
+        submit_button = gr.Button("➤", scale=0.1)
+
+
+    def user(user_message: str, history: list) -> tuple:
+        if not user_message.strip():
+            return "", history
+        history = history + [[user_message, None]]
+        return "", history
+
+
+    def bot(history: list) -> list:
+        if not history:
+            return history
+
+        user_message = history[-1][0]
+        bot_message = chatbot.generate_response(user_message)
+        history[-1][1] = bot_message
+
+        return history
+
+
+    msg.submit(user, [msg, chat_history], [msg, chat_history], queue=False).then(
+        bot, chat_history, chat_history
+    )
+
+    submit_button.click(user, [msg, chat_history], [msg, chat_history], queue=False).then(
+        bot, chat_history, chat_history
+    )
+
+# Launch the interface
+if __name__ == "__main__":
+    demo.launch()