Initialize P2

.gradio/certificate.pem

@@ -0,0 +1,31 @@
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README.md

@@ -10,3 +10,57 @@ pinned: false
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Medical Chat Bot
+   
+   ## Domain
+   [Your chosen domain]
+   
+   ## Setup Instructions
+   ### Prerequisites
+   - Python 3.14.4+
+   - [Ollama OR HuggingFace account]
+   
+   ### Installation
+1. Install Ollama 
+   ```bash
+    # Mac:
+     brew install ollama 
+    
+    # Windows: Download from https://ollama.ai 
+    
+    # Linux:
+    curl -fsSL https://ollama.com/install.sh | sh 
+   ```
+
+1. Download llama3.2:3b model:
+   ```bash
+   ollama pull llama3.2:3b
+   ```
+1. Install Python packages 
+   ```bash
+      pip install ollama gradio
+   ```
+   
+   ### Running
+```bash
+   python your_file.py
+```
+   
+   ## Features
+   - Feature 1: [Description]
+   - Feature 2: [Description]
+   
+   ## Technical Details
+   - Model: llama3.2:3b
+   - Framework: Ollama
+   - Special considerations: [Any important notes]
+   
+   ## Demo
+   [Link to video OR screenshots]
+   
+   ## Known Limitations
+   [What your chatbot cannot do]
+   
+   ## Future Improvements
+   [What you would add with more time]

app.py

@@ -0,0 +1,314 @@
+"""
+Medical Chatbot using Ollama and Gradio
+This template provides a complete chatbot with sections to customize.
+"""
+
+import ollama
+import gradio as gr
+
+# 1: Customize system prompt for either healthcare professional or patient based on a radio button selection
+
+import gradio as gr
+current_mode = "patient"  # default
+grExamples = None
+
+def switch_prompt(mode):
+    """Switch between patient and doctor mode"""
+    global current_mode, SYSTEM_PROMPT
+    current_mode = mode
+    
+    # patient mode
+    if mode == "patient":
+        SYSTEM_PROMPT = """You are a medical AI assistant specialized in medication questions and management for a patient.
+
+            Your role is to help the patient keep track of their medication schedule and provide information about their medications.
+
+            When answering:
+            - Tell them they can let you know about any changes in medications at any time.
+            - Let them know about any upcoming medication times.
+            - Ask what medications they have taken today so far.
+            - Be accurate and evidence-based.
+            - Use clear, simple language.
+
+            Remember: You provide educational information, not personal medical advice."""
+        
+        # Update the example prompts.
+    else:  # doctor mode
+        SYSTEM_PROMPT = """You are a medical AI assistant specialized in providing information to healthcare professionals about a patient's medications and management.
+
+        Your role is to inform the healthcare professional so they understand the patient's medication list, recent medication schedule, and any concerns the patient has asked about their medications.
+
+        When answering:
+        - Present the list of medications the patient is taking.
+        - Provide a summary of specific questions the patient has asked.
+        - Detail the schedule of the patient's medications as best as you know, and explain what you don't know.
+
+        Remember: You provide educational information, not personal medical advice."""
+    
+    
+    return f"Switched to {mode} mode"
+
+# =============================================
+# CONFIGURATION
+# =============================================
+
+# Model selection
+MODEL = 'llama3.2:3b' # x your Ollama model name here after downloading it
+
+# 2: Set your parameters (tune these for your domain!) try different values and see what works best
+PARAMS = {
+    'temperature': 0.1,     # Adjust (0.1 = focused, 0.9 = creative)
+    'top_p': 0.9,           # Adjust (0.85-0.95 recommended)
+    'num_predict': 300,     # Adjust max length
+    'repeat_penalty': 1.0   # Adjust if needed
+}
+
+# =============================================
+# MEMORY & STATE
+# =============================================
+
+# Conversation history (for Feature: Memory)
+conversation_history = []
+
+# =============================================
+# CORE FUNCTIONS
+# =============================================
+
+def chat(user_message):
+    """
+    Main chat function with conversation memory
+    
+    3: Add your custom logic here
+    Ideas:
+    - Pre-process user input
+    - Add domain-specific checks
+    - Format output in special ways
+    - Add citations or references
+    """
+    
+    # Validate input
+    if not user_message.strip():
+        return "Please ask a question!"
+    
+    # 4: Add any pre-processing here
+    
+    # If emergency is mentioned, instruct user to seek immediate help
+    if "emergency" in user_message.lower() or "immediate" in user_message.lower():
+        return "Please seek immediate help from a healthcare professional."
+    
+    # Add user message to history
+    conversation_history.append({
+        'role': 'user',
+        'content': user_message
+    })
+    
+    # Get AI response
+    try:
+        response = ollama.chat(
+            model=MODEL,
+            messages=[
+                {'role': 'system', 'content': SYSTEM_PROMPT}
+            ] + conversation_history,
+            options=PARAMS
+        )
+        
+        # Extract answer
+        answer = response['message']['content']
+        
+        # Add to history
+        conversation_history.append({
+            'role': 'assistant',
+            'content': answer
+        })
+        
+        # 5: Add any post-processing here
+        
+        # Add disclaimer
+        disclaimer = "\n\n" + "─"*50 + "\n**Disclaimer:** This is educational information only. Always consult qualified healthcare professionals for medical advice."
+        
+        return answer + disclaimer
+        
+    except Exception as e:
+        return f"Error: {str(e)}\n\nMake sure Ollama is running and the model is downloaded."
+
+def clear_conversation():
+    """Clear conversation history"""
+    global conversation_history
+    conversation_history = []
+    return "", "Conversation cleared! Start fresh."
+
+# 6: Add your custom feature functions here
+
+def switch_examples(mode):
+    """Switch example prompts based on mode"""
+    new_dataset = get_examples(mode)
+    print ("Switching examples to:", new_dataset.samples)
+    return new_dataset
+
+def export_conversation():
+    """Export chat history to text file"""
+    if not conversation_history:
+        return "No conversation to export!"
+    
+    text = ""
+    for msg in conversation_history:
+        role = msg['role'].upper()
+        content = msg['content']
+        text += f"{role}:\n{content}\n\n" + "─"*50 + "\n\n"
+
+    # Save to file
+    with open("conversation_export.txt", "w") as f:
+        f.write(text)
+
+    return "Exported to conversation_export.txt"
+
+# Create a dictionary to hold the raw lists
+EXAMPLE_SAMPLES = {
+    "patient": [
+        ["How should I manage my blood pressure medication schedule?"],
+        ["Why did my doctor change my dosage?"],
+        ["Is it normal to feel dizzy after starting this?"],
+        ["What are the side effects of my current medications?"],
+        ["Which medications should I take with food?"],
+        ["What are the interactions between my medications?"],
+    ],
+    "doctor": [
+        ["What is the patient's current medication list?"],
+        ["Can you provide a summary of the patient's recent medication schedule?"],
+        ["What are the patient's concerns about their medications?"],
+    ]
+}
+
+def get_examples(mode):
+    # Return the correct examples to the gradio component.
+    return gr.Dataset(samples=EXAMPLE_SAMPLES[mode])
+
+# =============================================
+# GRADIO INTERFACE
+# =============================================
+
+# 7: Customize your interface design
+with gr.Blocks(theme=gr.themes.Soft(), title="Medical Chatbot") as app:
+    
+    # Header
+    gr.Markdown(f"""
+    # Patient/Doctor Medication Chatbot
+    ### Patients can ask questions about their medications and schedule. Healthcare professionals can get summaries of the patient's medication experience.
+    
+    **Domain:** Medication Management 
+    **Powered by:** {MODEL} via Ollama
+    """)
+    
+    # Main interface
+    with gr.Row():
+        with gr.Column(scale=2):
+            # Input area
+            question = gr.Textbox(
+                label="💬 Your Question",
+                placeholder="Ask anything about your medications...",
+                lines=3
+            )
+            
+            # Buttons
+            with gr.Row():
+                submit_btn = gr.Button("🚀 Ask", variant="primary", size="lg")
+                clear_btn = gr.Button("🗑️ Clear", size="lg")
+            
+            # 8: Add your custom controls here
+            # Add button:
+            export_btn = gr.Button("Export Conversation")
+            export_status = gr.Textbox(label="Export Status")
+            export_btn.click(export_conversation, outputs=export_status)
+
+            with gr.Row():
+                with gr.Column(scale=2):
+                    # A selector for patient or doctor mode.
+                    mode_selector = gr.Radio(
+                        choices=["patient", "doctor"],
+                        value="patient",
+                        label="Mode"
+                )
+            
+        with gr.Column(scale=3):
+            # Response area
+            response = gr.Textbox(
+                label="🤖 AI Response",
+                lines=15,
+                interactive=False
+            )
+
+    grExamples = gr.Examples(
+        examples=EXAMPLE_SAMPLES[current_mode],
+        inputs=question,
+        label="💡 Try these examples:",
+        cache_examples=False # Required for dynamic swapping
+    )
+
+    mode_selector.change(switch_prompt, inputs=mode_selector)
+    mode_selector.change(switch_examples, inputs=mode_selector, outputs=grExamples.dataset)
+    
+    # 10: Add an "About" section
+    with gr.Accordion("ℹ️ About This Chatbot", open=False):
+        gr.Markdown("""
+        ### About
+        This chatbot is designed with two modes, patient and doctor, to assist patients and healthcare professionals with medication management. 
+        In patient mode, itt provides a patient information about medication schedules, side effects, interactions, and more based on their prompts.
+        In doctor mode, it provides the doctor or healthcare professional a summary of what the patient has asked about regarding their medications.
+        The chatbot will remember the conversation history to provide context-aware responses.
+   
+        ### Features
+        - Feature 1: Answer patient questions about medications and remembers history.
+        - Feature 2: Provide doctors with summaries of patient inquiries to help with medication management.
+        - Feature 3: Suggests prompts depending on the mode selected (different prompts for doctors and patients).
+        - Feature 4: Export conversation history for record-keeping or further analysis.
+        
+        ### Technical Details
+        - **Model:** {model}
+        - **Framework:** Ollama + Gradio
+        - **Temperature:** {temp}
+        - **Max Length:** {max_len} tokens
+        
+        ### Important Notes
+        ⚠️ This chatbot is for educational purposes only.  
+        ⚠️ It is NOT a substitute for professional medical advice.  
+        ⚠️ Always consult qualified healthcare providers for medical concerns.
+        
+        ### Creator
+        **Developed by:** Donnie Goodson
+        **Course:** Medical AI  
+        **Date:** April 18, 2026
+        """.format(
+            model=MODEL,
+            temp=PARAMS['temperature'],
+            max_len=PARAMS['num_predict']
+        ))
+    
+    # Connect buttons to functions
+    submit_btn.click(
+        fn=chat,
+        inputs=question,
+        outputs=response
+    )
+    
+    clear_btn.click(
+        fn=clear_conversation,
+        inputs=None,
+        outputs=[question, response]
+    )
+
+    # =============================================
+# LAUNCH
+# =============================================
+
+if __name__ == "__main__":
+    print("\n" + "="*60)
+    print("LAUNCHING MEDICAL CHATBOT")
+    print("="*60)
+    print(f"\nModel: {MODEL}")
+    print(f"Domain: Medication Management")
+    print(f"Parameters: {PARAMS}")
+    print("\nStarting server... Open the URL below in your browser.\n")
+    
+    app.launch(
+        share=True,  # Set to True to get public URL and False for local only
+          )

chatBotOllama.ipynb

@@ -0,0 +1,467 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 320,
+   "id": "31c47390",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"\n",
+    "Medical Chatbot using Ollama and Gradio\n",
+    "This template provides a complete chatbot with sections to customize.\n",
+    "\"\"\"\n",
+    "\n",
+    "import ollama\n",
+    "import gradio as gr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 321,
+   "id": "ccc77483",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 1: Customize system prompt for either healthcare professional or patient based on a radio button selection\n",
+    "\n",
+    "import gradio as gr\n",
+    "current_mode = \"patient\"  # default\n",
+    "grExamples = None\n",
+    "\n",
+    "def switch_prompt(mode):\n",
+    "    \"\"\"Switch between patient and doctor mode\"\"\"\n",
+    "    global current_mode, SYSTEM_PROMPT\n",
+    "    current_mode = mode\n",
+    "    \n",
+    "    # patient mode\n",
+    "    if mode == \"patient\":\n",
+    "        SYSTEM_PROMPT = \"\"\"You are a medical AI assistant specialized in medication questions and management for a patient.\n",
+    "\n",
+    "            Your role is to help the patient keep track of their medication schedule and provide information about their medications.\n",
+    "\n",
+    "            When answering:\n",
+    "            - Tell them they can let you know about any changes in medications at any time.\n",
+    "            - Let them know about any upcoming medication times.\n",
+    "            - Ask what medications they have taken today so far.\n",
+    "            - Be accurate and evidence-based.\n",
+    "            - Use clear, simple language.\n",
+    "\n",
+    "            Remember: You provide educational information, not personal medical advice.\"\"\"\n",
+    "        \n",
+    "        # Update the example prompts.\n",
+    "    else:  # doctor mode\n",
+    "        SYSTEM_PROMPT = \"\"\"You are a medical AI assistant specialized in providing information to healthcare professionals about a patient's medications and management.\n",
+    "\n",
+    "        Your role is to inform the healthcare professional so they understand the patient's medication list, recent medication schedule, and any concerns the patient has asked about their medications.\n",
+    "\n",
+    "        When answering:\n",
+    "        - Present the list of medications the patient is taking.\n",
+    "        - Provide a summary of specific questions the patient has asked.\n",
+    "        - Detail the schedule of the patient's medications as best as you know, and explain what you don't know.\n",
+    "\n",
+    "        Remember: You provide educational information, not personal medical advice.\"\"\"\n",
+    "    \n",
+    "    \n",
+    "    return f\"Switched to {mode} mode\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 322,
+   "id": "9e6e1435",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# =============================================\n",
+    "# CONFIGURATION\n",
+    "# =============================================\n",
+    "\n",
+    "# Model selection\n",
+    "MODEL = 'llama3.2:3b' # x your Ollama model name here after downloading it\n",
+    "\n",
+    "# 2: Set your parameters (tune these for your domain!) try different values and see what works best\n",
+    "PARAMS = {\n",
+    "    'temperature': 0.1,     # Adjust (0.1 = focused, 0.9 = creative)\n",
+    "    'top_p': 0.9,           # Adjust (0.85-0.95 recommended)\n",
+    "    'num_predict': 300,     # Adjust max length\n",
+    "    'repeat_penalty': 1.0   # Adjust if needed\n",
+    "}\n",
+    "\n",
+    "# =============================================\n",
+    "# MEMORY & STATE\n",
+    "# =============================================\n",
+    "\n",
+    "# Conversation history (for Feature: Memory)\n",
+    "conversation_history = []\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 323,
+   "id": "a49ae2ca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# =============================================\n",
+    "# CORE FUNCTIONS\n",
+    "# =============================================\n",
+    "\n",
+    "def chat(user_message):\n",
+    "    \"\"\"\n",
+    "    Main chat function with conversation memory\n",
+    "    \n",
+    "    3: Add your custom logic here\n",
+    "    Ideas:\n",
+    "    - Pre-process user input\n",
+    "    - Add domain-specific checks\n",
+    "    - Format output in special ways\n",
+    "    - Add citations or references\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    # Validate input\n",
+    "    if not user_message.strip():\n",
+    "        return \"Please ask a question!\"\n",
+    "    \n",
+    "    # 4: Add any pre-processing here\n",
+    "    \n",
+    "    # If emergency is mentioned, instruct user to seek immediate help\n",
+    "    if \"emergency\" in user_message.lower() or \"immediate\" in user_message.lower():\n",
+    "        return \"Please seek immediate help from a healthcare professional.\"\n",
+    "    \n",
+    "    # Add user message to history\n",
+    "    conversation_history.append({\n",
+    "        'role': 'user',\n",
+    "        'content': user_message\n",
+    "    })\n",
+    "    \n",
+    "    # Get AI response\n",
+    "    try:\n",
+    "        response = ollama.chat(\n",
+    "            model=MODEL,\n",
+    "            messages=[\n",
+    "                {'role': 'system', 'content': SYSTEM_PROMPT}\n",
+    "            ] + conversation_history,\n",
+    "            options=PARAMS\n",
+    "        )\n",
+    "        \n",
+    "        # Extract answer\n",
+    "        answer = response['message']['content']\n",
+    "        \n",
+    "        # Add to history\n",
+    "        conversation_history.append({\n",
+    "            'role': 'assistant',\n",
+    "            'content': answer\n",
+    "        })\n",
+    "        \n",
+    "        # 5: Add any post-processing here\n",
+    "        \n",
+    "        # Add disclaimer\n",
+    "        disclaimer = \"\\n\\n\" + \"─\"*50 + \"\\n**Disclaimer:** This is educational information only. Always consult qualified healthcare professionals for medical advice.\"\n",
+    "        \n",
+    "        return answer + disclaimer\n",
+    "        \n",
+    "    except Exception as e:\n",
+    "        return f\"Error: {str(e)}\\n\\nMake sure Ollama is running and the model is downloaded.\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 324,
+   "id": "181f4dd1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def clear_conversation():\n",
+    "    \"\"\"Clear conversation history\"\"\"\n",
+    "    global conversation_history\n",
+    "    conversation_history = []\n",
+    "    return \"\", \"Conversation cleared! Start fresh.\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 325,
+   "id": "b252a74f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 6: Add your custom feature functions here\n",
+    "\n",
+    "def switch_examples(mode):\n",
+    "    \"\"\"Switch example prompts based on mode\"\"\"\n",
+    "    new_dataset = get_examples(mode)\n",
+    "    print (\"Switching examples to:\", new_dataset.samples)\n",
+    "    return new_dataset\n",
+    "\n",
+    "def export_conversation():\n",
+    "    \"\"\"Export chat history to text file\"\"\"\n",
+    "    if not conversation_history:\n",
+    "        return \"No conversation to export!\"\n",
+    "    \n",
+    "    text = \"\"\n",
+    "    for msg in conversation_history:\n",
+    "        role = msg['role'].upper()\n",
+    "        content = msg['content']\n",
+    "        text += f\"{role}:\\n{content}\\n\\n\" + \"─\"*50 + \"\\n\\n\"\n",
+    "\n",
+    "    # Save to file\n",
+    "    with open(\"conversation_export.txt\", \"w\") as f:\n",
+    "        f.write(text)\n",
+    "\n",
+    "    return \"Exported to conversation_export.txt\"\n",
+    "\n",
+    "# Create a dictionary to hold the raw lists\n",
+    "EXAMPLE_SAMPLES = {\n",
+    "    \"patient\": [\n",
+    "        [\"How should I manage my blood pressure medication schedule?\"],\n",
+    "        [\"Why did my doctor change my dosage?\"],\n",
+    "        [\"Is it normal to feel dizzy after starting this?\"],\n",
+    "        [\"What are the side effects of my current medications?\"],\n",
+    "        [\"Which medications should I take with food?\"],\n",
+    "        [\"What are the interactions between my medications?\"],\n",
+    "    ],\n",
+    "    \"doctor\": [\n",
+    "        [\"What is the patient's current medication list?\"],\n",
+    "        [\"Can you provide a summary of the patient's recent medication schedule?\"],\n",
+    "        [\"What are the patient's concerns about their medications?\"],\n",
+    "    ]\n",
+    "}\n",
+    "\n",
+    "def get_examples(mode):\n",
+    "    # Return the correct examples to the gradio component.\n",
+    "    return gr.Dataset(samples=EXAMPLE_SAMPLES[mode])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 326,
+   "id": "96c34ddf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\donni\\AppData\\Local\\Temp\\ipykernel_29884\\4222941924.py:6: UserWarning: The parameters have been moved from the Blocks constructor to the launch() method in Gradio 6.0: theme. Please pass these parameters to launch() instead.\n",
+      "  with gr.Blocks(theme=gr.themes.Soft(), title=\"Medical Chatbot\") as app:\n"
+     ]
+    }
+   ],
+   "source": [
+    "# =============================================\n",
+    "# GRADIO INTERFACE\n",
+    "# =============================================\n",
+    "\n",
+    "# 7: Customize your interface design\n",
+    "with gr.Blocks(theme=gr.themes.Soft(), title=\"Medical Chatbot\") as app:\n",
+    "    \n",
+    "    # Header\n",
+    "    gr.Markdown(f\"\"\"\n",
+    "    # Patient/Doctor Medication Chatbot\n",
+    "    ### Patients can ask questions about their medications and schedule. Healthcare professionals can get summaries of the patient's medication experience.\n",
+    "    \n",
+    "    **Domain:** Medication Management \n",
+    "    **Powered by:** {MODEL} via Ollama\n",
+    "    \"\"\")\n",
+    "    \n",
+    "    # Main interface\n",
+    "    with gr.Row():\n",
+    "        with gr.Column(scale=2):\n",
+    "            # Input area\n",
+    "            question = gr.Textbox(\n",
+    "                label=\"💬 Your Question\",\n",
+    "                placeholder=\"Ask anything about your medications...\",\n",
+    "                lines=3\n",
+    "            )\n",
+    "            \n",
+    "            # Buttons\n",
+    "            with gr.Row():\n",
+    "                submit_btn = gr.Button(\"🚀 Ask\", variant=\"primary\", size=\"lg\")\n",
+    "                clear_btn = gr.Button(\"🗑️ Clear\", size=\"lg\")\n",
+    "            \n",
+    "            # 8: Add your custom controls here\n",
+    "            # Add button:\n",
+    "            export_btn = gr.Button(\"Export Conversation\")\n",
+    "            export_status = gr.Textbox(label=\"Export Status\")\n",
+    "            export_btn.click(export_conversation, outputs=export_status)\n",
+    "\n",
+    "            with gr.Row():\n",
+    "                with gr.Column(scale=2):\n",
+    "                    # A selector for patient or doctor mode.\n",
+    "                    mode_selector = gr.Radio(\n",
+    "                        choices=[\"patient\", \"doctor\"],\n",
+    "                        value=\"patient\",\n",
+    "                        label=\"Mode\"\n",
+    "                )\n",
+    "            \n",
+    "        with gr.Column(scale=3):\n",
+    "            # Response area\n",
+    "            response = gr.Textbox(\n",
+    "                label=\"🤖 AI Response\",\n",
+    "                lines=15,\n",
+    "                interactive=False\n",
+    "            )\n",
+    "\n",
+    "    grExamples = gr.Examples(\n",
+    "        examples=EXAMPLE_SAMPLES[current_mode],\n",
+    "        inputs=question,\n",
+    "        label=\"💡 Try these examples:\",\n",
+    "        cache_examples=False # Required for dynamic swapping\n",
+    "    )\n",
+    "\n",
+    "    mode_selector.change(switch_prompt, inputs=mode_selector)\n",
+    "    mode_selector.change(switch_examples, inputs=mode_selector, outputs=grExamples.dataset)\n",
+    "    \n",
+    "    # 10: Add an \"About\" section\n",
+    "    with gr.Accordion(\"ℹ️ About This Chatbot\", open=False):\n",
+    "        gr.Markdown(\"\"\"\n",
+    "        ### About\n",
+    "        This chatbot is designed with two modes, patient and doctor, to assist patients and healthcare professionals with medication management. \n",
+    "        In patient mode, itt provides a patient information about medication schedules, side effects, interactions, and more based on their prompts.\n",
+    "        In doctor mode, it provides the doctor or healthcare professional a summary of what the patient has asked about regarding their medications.\n",
+    "        The chatbot will remember the conversation history to provide context-aware responses.\n",
+    "   \n",
+    "        ### Features\n",
+    "        - Feature 1: Answer patient questions about medications and remembers history.\n",
+    "        - Feature 2: Provide doctors with summaries of patient inquiries to help with medication management.\n",
+    "        - Feature 3: Suggests prompts depending on the mode selected (different prompts for doctors and patients).\n",
+    "        - Feature 4: Export conversation history for record-keeping or further analysis.\n",
+    "        \n",
+    "        ### Technical Details\n",
+    "        - **Model:** {model}\n",
+    "        - **Framework:** Ollama + Gradio\n",
+    "        - **Temperature:** {temp}\n",
+    "        - **Max Length:** {max_len} tokens\n",
+    "        \n",
+    "        ### Important Notes\n",
+    "        ⚠️ This chatbot is for educational purposes only.  \n",
+    "        ⚠️ It is NOT a substitute for professional medical advice.  \n",
+    "        ⚠️ Always consult qualified healthcare providers for medical concerns.\n",
+    "        \n",
+    "        ### Creator\n",
+    "        **Developed by:** Donnie Goodson\n",
+    "        **Course:** Medical AI  \n",
+    "        **Date:** April 18, 2026\n",
+    "        \"\"\".format(\n",
+    "            model=MODEL,\n",
+    "            temp=PARAMS['temperature'],\n",
+    "            max_len=PARAMS['num_predict']\n",
+    "        ))\n",
+    "    \n",
+    "    # Connect buttons to functions\n",
+    "    submit_btn.click(\n",
+    "        fn=chat,\n",
+    "        inputs=question,\n",
+    "        outputs=response\n",
+    "    )\n",
+    "    \n",
+    "    clear_btn.click(\n",
+    "        fn=clear_conversation,\n",
+    "        inputs=None,\n",
+    "        outputs=[question, response]\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 327,
+   "id": "2196dac3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "============================================================\n",
+      "LAUNCHING MEDICAL CHATBOT\n",
+      "============================================================\n",
+      "\n",
+      "Model: llama3.2:3b\n",
+      "Domain: Medication Management\n",
+      "Parameters: {'temperature': 0.1, 'top_p': 0.9, 'num_predict': 300, 'repeat_penalty': 1.0}\n",
+      "\n",
+      "Starting server... Open the URL below in your browser.\n",
+      "\n",
+      "* Running on local URL:  http://127.0.0.1:7883\n",
+      "* Running on public URL: https://058deb7a179b2a769c.gradio.live\n",
+      "\n",
+      "This share link expires in 1 week. 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://058deb7a179b2a769c.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"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\donni\\AppData\\Local\\Python\\pythoncore-3.14-64\\Lib\\site-packages\\gradio\\blocks.py:1851: UserWarning: A function (switch_prompt) returned too many output values (needed: 0, returned: 1). Ignoring extra values.\n",
+      "    Output components:\n",
+      "        []\n",
+      "    Output values returned:\n",
+      "        [\"Switched to doctor mode\"]\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Switching examples to: [[], [], []]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# =============================================\n",
+    "# LAUNCH\n",
+    "# =============================================\n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    print(\"\\n\" + \"=\"*60)\n",
+    "    print(\"LAUNCHING MEDICAL CHATBOT\")\n",
+    "    print(\"=\"*60)\n",
+    "    print(f\"\\nModel: {MODEL}\")\n",
+    "    print(f\"Domain: Medication Management\")\n",
+    "    print(f\"Parameters: {PARAMS}\")\n",
+    "    print(\"\\nStarting server... Open the URL below in your browser.\\n\")\n",
+    "    \n",
+    "    app.launch(\n",
+    "        share=True,  # Set to True to get public URL and False for local only\n",
+    "          )"
+   ]
+  }
+ ],
+ "metadata": {
+  "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": "3.14.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}