Update app.py

app.py

@@ -4,15 +4,14 @@ import json
 from docx import Document
 from io import BytesIO
 import base64
-
+from urllib.parse import quote
 
 # Pollinations AI Configuration
-POLLINATIONS_API_URL = "https://text.pollinations.ai/openai/chat/completions"
-MODEL = "deepseek-r1"
-
+POLLINATIONS_API_URL = "https://text.pollinations.ai/openai"
+MODEL = "openai"  # Changed from "deepseek-r1" to a supported model
 
 def call_pollinations_ai(system_prompt, user_message):
-    """Call Pollinations AI API"""
+    """Call Pollinations AI API using OpenAI-compatible POST endpoint"""
     headers = {
         "Content-Type": "application/json"
     }
@@ -24,7 +23,7 @@ def call_pollinations_ai(system_prompt, user_message):
             {"role": "user", "content": user_message}
         ],
         "temperature": 0.1,
-        "max_tokens": 8000
+        # "max_tokens": 8000  # Remove if not supported by Pollinations
     }
     
     try:
@@ -35,7 +34,6 @@ def call_pollinations_ai(system_prompt, user_message):
     except Exception as e:
         return f"Error calling API: {str(e)}"
 
-
 def generate_diagnosis(symptoms, medical_history, age, gender, allergies, medications, family_history, lifestyle):
     """Generate medical diagnosis"""
     
@@ -43,29 +41,21 @@ def generate_diagnosis(symptoms, medical_history, age, gender, allergies, medica
 Provide evidence-based preliminary diagnoses using patient information. Be thorough and analytical."""
     
     user_message = f"""Analyze the patient's case and provide a preliminary diagnosis:
-
 PATIENT DEMOGRAPHICS:
 - Age: {age}
 - Gender: {gender}
-
 CURRENT SYMPTOMS:
 {symptoms}
-
 MEDICAL HISTORY:
 {medical_history}
-
 ALLERGIES:
 {allergies if allergies else 'None reported'}
-
 CURRENT MEDICATIONS:
 {medications if medications else 'None reported'}
-
 FAMILY HISTORY:
 {family_history if family_history else 'None reported'}
-
 LIFESTYLE FACTORS:
 {lifestyle if lifestyle else 'Not provided'}
-
 Please provide:
 1. Preliminary diagnosis with possible conditions
 2. List most likely conditions in order of probability
@@ -74,7 +64,6 @@ Please provide:
     
     return call_pollinations_ai(system_prompt, user_message)
 
-
 def generate_treatment_plan(symptoms, medical_history, age, gender, allergies, medications, family_history, diagnosis):
     """Generate treatment recommendations"""
     
@@ -82,26 +71,19 @@ def generate_treatment_plan(symptoms, medical_history, age, gender, allergies, m
 Consider patient history, comorbidities, and current medical best practices. Focus on safe and effective recommendations."""
     
     user_message = f"""Based on the following diagnosis and patient profile, create a comprehensive treatment plan:
-
 PATIENT DEMOGRAPHICS:
 - Age: {age}
 - Gender: {gender}
-
 PRELIMINARY DIAGNOSIS:
 {diagnosis}
-
 MEDICAL HISTORY:
 {medical_history}
-
 ALLERGIES:
 {allergies if allergies else 'None reported'}
-
 CURRENT MEDICATIONS:
 {medications if medications else 'None reported'}
-
 FAMILY HISTORY:
 {family_history if family_history else 'None reported'}
-
 Please provide:
 1. Pharmacological treatment (specific medications and dosages)
 2. Lifestyle modifications
@@ -113,7 +95,6 @@ Please provide:
     
     return call_pollinations_ai(system_prompt, user_message)
 
-
 def generate_docx_report(diagnosis, treatment_plan, patient_data):
     """Generate DOCX report"""
     doc = Document()
@@ -137,7 +118,6 @@ def generate_docx_report(diagnosis, treatment_plan, patient_data):
     bio.seek(0)
     return bio
 
-
 def process_medical_analysis(symptoms, medical_history, age, gender, allergies, medications, family_history, lifestyle):
     """Main processing function"""
     
@@ -163,7 +143,6 @@ def process_medical_analysis(symptoms, medical_history, age, gender, allergies,
     
     return diagnosis, treatment_plan, download_link
 
-
 # Gradio Interface
 with gr.Blocks(title="Medical AI Assistant", theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 🏥 Medical AI Assistant")
@@ -227,6 +206,5 @@ with gr.Blocks(title="Medical AI Assistant", theme=gr.themes.Soft()) as demo:
         outputs=[diagnosis_output, treatment_output, download_output]
     )
 
-
 if __name__ == "__main__":
     demo.launch(share=True, server_name="0.0.0.0", server_port=7860)