updated app

app.py

@@ -3,6 +3,7 @@ import spaces
 import torch
 from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
 import os
+from datetime import datetime
 
 # Model setup
 processor = AutoProcessor.from_pretrained("deepguess/weather-vlm-qwen2.5-7b", trust_remote_code=True)
@@ -14,61 +15,72 @@ model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
 model.eval()
 
 # Title and description
-TITLE = "🌦️ Weather Vision-Language Model (Qwen2.5-VL-7B Fine-tuned)"
+TITLE = "🌦️ Weather Analysis VLM (Qwen2.5-VL-7B Fine-tuned)"
 
 DESCRIPTION = """
-## About This Model
+## Advanced Weather Image Analysis
 
-This is a **fine-tuned Qwen2.5-VL-7B** model specialized for meteorological image analysis. It has been trained on weather-related visual data to provide detailed analysis of various weather phenomena.
+This model specializes in analyzing weather data including:
+- **Model Outputs**: GFS, HRRR, ECMWF, NAM analysis
+- **Soundings**: Skew-T diagrams, hodographs, SHARPpy analysis
+- **Observations**: Surface obs, satellite, radar imagery
+- **Forecasts**: Deterministic and ensemble model outputs
+- **Severe Weather**: Convective parameters, SPC outlooks
 
-### ⚠️ Important Disclaimer
-**This is an experimental small-scale fine-tuned model and should NEVER be used for:**
-- Making real meteorological decisions
-- Emergency weather warnings
-- Flight planning or navigation
-- Any safety-critical applications
-- Professional weather forecasting
-
-**This model is for educational and research purposes only.**
-
-### Model Details
-- **Base Model**: Qwen2.5-VL-7B-Instruct
-- **Fine-tuning**: LoRA (r=32, alpha=32)
-- **Training**: Custom weather image dataset
-- **Parameters**: 8.29B
-- **Precision**: BF16
-
-### What it can analyze:
-- ☁️ Cloud types and formations
-- 🌧️ Precipitation patterns
-- 🌪️ Storm systems
-- 📡 Satellite imagery
-- 📊 Weather maps and charts
-- 🌈 Atmospheric phenomena
+### ⚠️ Disclaimer
+**For educational and research purposes only. Not for operational forecasting.**
 """
 
-# Predefined prompts for different analysis types
+# Enhanced prompts based on your data categories
 PROMPT_TEMPLATES = {
-    "General": "What's the weather in this image?",
-    "Clouds": "What cloud types are shown?",
-    "Storm": "Analyze any storms in this image.",
-    "Forecast": "What weather is likely coming?",
-    "Technical": "Give a technical weather analysis.",
-    "Simple": "Explain this weather simply.",
-    "Hazards": "What weather hazards are visible?",
+    "Quick Analysis": "Describe the weather in this image.",
+    "Model Output": "Analyze this model output. What patterns and features are shown?",
+    "Sounding Analysis": "Analyze this sounding. Discuss stability, shear, and severe potential.",
+    "Radar/Satellite": "Describe the features in this radar or satellite image.",
+    "Severe Weather": "Assess severe weather potential based on this image.",
+    "Technical Deep Dive": "Provide detailed technical analysis including parameters and meteorological significance.",
+    "Forecast Discussion": "Based on this image, what weather evolution is expected?",
+    "Pattern Recognition": "Identify synoptic patterns, jet streaks, troughs, ridges, and fronts.",
+    "Ensemble Analysis": "Analyze ensemble spread, uncertainty, and most likely scenarios.",
+    "Winter Weather": "Analyze precipitation type, accumulation potential, and impacts.",
+}
+
+# System prompts for different analysis modes
+SYSTEM_PROMPTS = {
+    "technical": """You are an expert meteorologist providing technical analysis. Focus on:
+- Specific parameter values and thresholds
+- Physical processes and dynamics
+- Pattern recognition and anomalies
+- Forecast confidence and uncertainty
+Use technical terminology appropriately.""",
+    
+    "educational": """You are a meteorology instructor. Explain concepts clearly while maintaining accuracy. 
+Point out key features and explain their significance. Use some technical terms but define them.""",
+    
+    "operational": """You are providing a weather briefing. Focus on:
+- Current conditions and trends
+- Expected evolution
+- Impacts and hazards
+- Timing of changes
+Be concise but thorough.""",
+    
+    "research": """You are analyzing meteorological data for research purposes. Discuss:
+- Interesting features or anomalies
+- Comparison to climatology
+- Physical mechanisms
+- Uncertainty quantification"""
 }
 
-# Example images setup
-EXAMPLES = [
-    ["examples/thunderstorm.jpg", "Storm", 0.7, 256],
-    ["examples/cumulus_clouds.jpg", "Clouds", 0.7, 256],
-    ["examples/satellite_hurricane.jpg", "Technical", 0.7, 384],
-    ["examples/fog_morning.jpg", "General", 0.7, 256],
-    ["examples/weather_map.jpg", "Forecast", 0.7, 384],
-] if os.path.exists("examples") else []
+# Analysis mode descriptions
+MODE_INFO = {
+    "technical": "Detailed technical analysis for meteorologists",
+    "educational": "Clear explanations for learning",
+    "operational": "Focused briefing style",
+    "research": "In-depth research perspective"
+}
 
-@spaces.GPU(duration=60)
-def analyze_weather_image(image, analysis_type, custom_prompt, temperature, max_tokens):
+@spaces.GPU(duration=90)
+def analyze_weather_image(image, analysis_type, custom_prompt, analysis_mode, temperature, max_tokens, top_p):
     if image is None:
         return "Please upload an image to analyze."
     
@@ -76,12 +88,15 @@ def analyze_weather_image(image, analysis_type, custom_prompt, temperature, max_
     model.cuda()
     
     # Use custom prompt if provided, otherwise use template
-    prompt = custom_prompt if custom_prompt.strip() else PROMPT_TEMPLATES.get(analysis_type, PROMPT_TEMPLATES["General"])
+    prompt = custom_prompt.strip() if custom_prompt.strip() else PROMPT_TEMPLATES.get(analysis_type, PROMPT_TEMPLATES["Quick Analysis"])
+    
+    # Select system prompt based on mode
+    system_content = SYSTEM_PROMPTS.get(analysis_mode, SYSTEM_PROMPTS["technical"])
     
     # Prepare messages
     messages = [{
         "role": "system",
-        "content": "You are a meteorological analysis assistant. Provide detailed, accurate analysis of weather images while clearly stating any limitations or uncertainties."
+        "content": system_content
     }, {
         "role": "user",
         "content": [
@@ -100,17 +115,27 @@ def analyze_weather_image(image, analysis_type, custom_prompt, temperature, max_
         max_new_tokens=max_tokens,
         temperature=temperature,
         do_sample=True,
-        top_p=0.95,
-        repetition_penalty=1.1
+        top_p=top_p,
+        repetition_penalty=1.05
     )
     
     # Decode response
     response = processor.batch_decode(outputs[:, inputs.input_ids.shape[1]:], skip_special_tokens=True)[0]
     
-    return response
+    # Add metadata
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S UTC")
+    metadata = f"\n\n---\n*Analysis completed: {timestamp} | Mode: {analysis_mode} | Type: {analysis_type}*"
+    
+    return response + metadata
 
 # Create Gradio interface
-with gr.Blocks(title=TITLE, theme=gr.themes.Base()) as demo:
+with gr.Blocks(title=TITLE, theme=gr.themes.Base(), css="""
+    .gradio-container { font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace; }
+    .markdown-text { font-size: 14px; }
+    #analysis-output { font-family: 'Monaco', 'Menlo', monospace; font-size: 13px; }
+    .gr-button-primary { background-color: #2563eb; }
+    .gr-button-primary:hover { background-color: #1e40af; }
+""") as demo:
     gr.Markdown(f"# {TITLE}")
     gr.Markdown(DESCRIPTION)
     
@@ -127,33 +152,57 @@ with gr.Blocks(title=TITLE, theme=gr.themes.Base()) as demo:
             analysis_type = gr.Dropdown(
                 label="Analysis Type",
                 choices=list(PROMPT_TEMPLATES.keys()),
-                value="General"
+                value="Quick Analysis",
+                info="Select the type of analysis you need"
+            )
+            
+            # Analysis mode selector
+            analysis_mode = gr.Radio(
+                label="Analysis Mode",
+                choices=list(MODE_INFO.keys()),
+                value="technical",
+                info="Choose the style and depth of analysis"
             )
             
+            # Mode description
+            mode_description = gr.Markdown(value=MODE_INFO["technical"], elem_id="mode-desc")
+            
             # Custom prompt option
             with gr.Accordion("Custom Prompt (Optional)", open=False):
                 custom_prompt = gr.Textbox(
-                    label="Enter your own prompt",
-                    placeholder="Leave empty to use the selected analysis type template",
+                    label="Enter your specific question or analysis request",
+                    placeholder="E.g., 'Focus on the 500mb vorticity patterns' or 'Explain the hodograph curvature'",
                     lines=3
                 )
             
             # Advanced settings
             with gr.Accordion("Advanced Settings", open=False):
-                temperature = gr.Slider(
-                    minimum=0.1,
-                    maximum=1.0,
-                    value=0.7,
-                    step=0.1,
-                    label="Temperature (creativity)"
-                )
+                with gr.Row():
+                    temperature = gr.Slider(
+                        minimum=0.1,
+                        maximum=1.0,
+                        value=0.7,
+                        step=0.05,
+                        label="Temperature",
+                        info="Lower = more focused, Higher = more varied"
+                    )
+                    
+                    top_p = gr.Slider(
+                        minimum=0.5,
+                        maximum=1.0,
+                        value=0.95,
+                        step=0.05,
+                        label="Top-p",
+                        info="Nucleus sampling threshold"
+                    )
                 
                 max_tokens = gr.Slider(
                     minimum=128,
-                    maximum=512,
-                    value=256,
-                    step=32,
-                    label="Max Output Length"
+                    maximum=1024,
+                    value=512,
+                    step=64,
+                    label="Max Output Length",
+                    info="Longer for detailed analysis"
                 )
             
             # Analyze button
@@ -163,47 +212,111 @@ with gr.Blocks(title=TITLE, theme=gr.themes.Base()) as demo:
             # Output area
             output = gr.Textbox(
                 label="Analysis Results",
-                lines=20,
-                max_lines=25,
-                show_copy_button=True
+                lines=25,
+                max_lines=30,
+                show_copy_button=True,
+                elem_id="analysis-output"
+            )
+    
+    # Common weather data categories for quick access
+    with gr.Accordion("📊 Quick Templates for Common Data Types", open=False):
+        gr.Markdown("""
+        ### Click to load analysis templates:
+        """)
+        with gr.Row():
+            gr.Button("500mb Analysis", size="sm").click(
+                lambda: "Analyze the 500mb height and wind patterns. Identify troughs, ridges, jet streaks, and vorticity.",
+                outputs=custom_prompt
+            )
+            gr.Button("Sounding Analysis", size="sm").click(
+                lambda: "Analyze this sounding for stability, CAPE, shear, LCL, LFC, and severe weather parameters.",
+                outputs=custom_prompt
+            )
+            gr.Button("Composite Reflectivity", size="sm").click(
+                lambda: "Analyze radar reflectivity patterns, storm structure, intensity, and movement.",
+                outputs=custom_prompt
+            )
+        with gr.Row():
+            gr.Button("Surface Analysis", size="sm").click(
+                lambda: "Analyze surface features including fronts, pressure centers, convergence, and boundaries.",
+                outputs=custom_prompt
+            )
+            gr.Button("Ensemble Spread", size="sm").click(
+                lambda: "Analyze ensemble spread, clustering, and probabilistic information.",
+                outputs=custom_prompt
+            )
+            gr.Button("Convective Parameters", size="sm").click(
+                lambda: "Analyze CAPE, CIN, SRH, bulk shear, and composite parameters for severe potential.",
+                outputs=custom_prompt
             )
     
     # Examples section
-    if EXAMPLES:
+    example_data = [
+        ["examples/500mb_heights.jpg", "Model Output", "technical", 0.7, 512],
+        ["examples/sounding.jpg", "Sounding Analysis", "educational", 0.7, 512],
+        ["examples/radar_composite.jpg", "Radar/Satellite", "operational", 0.7, 384],
+        ["examples/spc_outlook.jpg", "Severe Weather", "operational", 0.7, 512],
+        ["examples/ensemble_spaghetti.jpg", "Ensemble Analysis", "research", 0.8, 640],
+    ] if os.path.exists("examples") else []
+    
+    if example_data:
         gr.Examples(
-            examples=EXAMPLES,
-            inputs=[image_input, analysis_type, temperature, max_tokens],
+            examples=example_data,
+            inputs=[image_input, analysis_type, analysis_mode, temperature, max_tokens],
             outputs=output,
-            fn=lambda img, typ, temp, tok: analyze_weather_image(img, typ, "", temp, tok),
-            cache_examples=False
+            fn=lambda img, typ, mode, temp, tok: analyze_weather_image(img, typ, "", mode, temp, tok, 0.95),
+            cache_examples=False,
+            label="Example Analyses"
         )
     
     # Tips section
-    with gr.Accordion("📚 Usage Tips", open=False):
+    with gr.Accordion("💡 Pro Tips for Best Results", open=False):
         gr.Markdown("""
-        ### Getting the Best Results:
+        ### Image Guidelines:
+        - **Resolution**: Higher resolution images yield better analysis
+        - **Clarity**: Ensure text/contours are legible
+        - **Completeness**: Include colorbars, titles, valid times
+        
+        ### Analysis Tips by Data Type:
+        
+        **Model Output (GFS, HRRR, ECMWF, NAM):**
+        - Include initialization and valid times
+        - Specify if you want focus on particular features
+        - Ask about ensemble uncertainty if applicable
+        
+        **Soundings (Skew-T, Hodographs):**
+        - Ensure all parameters are visible
+        - Ask about specific levels or layers
+        - Request shear calculations or thermodynamic analysis
         
-        1. **Image Quality**: Use clear, high-resolution weather images
-        2. **Image Types**: Works best with:
-           - Satellite imagery
-           - Ground-based sky photos
-           - Weather radar images
-           - Weather maps and charts
-        3. **Analysis Types**: Choose the most relevant analysis type for your image
-        4. **Temperature**: Lower values (0.3-0.5) for factual analysis, higher (0.7-0.9) for more detailed descriptions
-        5. **Custom Prompts**: Be specific about what aspects you want analyzed
+        **Radar/Satellite:**
+        - Include timestamp and location
+        - Specify interest in particular features
+        - Ask about storm motion or development
         
-        ### Limitations:
-        - Cannot predict exact future weather
-        - May misidentify rare phenomena
-        - Not suitable for professional use
-        - Analysis quality depends on image clarity
+        **Surface/Upper Air Charts:**
+        - Ensure contours and labels are clear
+        - Ask about specific features or patterns
+        - Request frontal analysis or jet stream discussion
+        
+        ### Parameter Settings:
+        - **Temperature 0.3-0.5**: Factual, consistent analysis
+        - **Temperature 0.6-0.8**: Balanced analysis with some interpretation
+        - **Temperature 0.9-1.0**: More speculative, exploring possibilities
+        - **Max Tokens**: Use 256-384 for quick analysis, 512-768 for detailed
         """)
     
+    # Update mode description when mode changes
+    analysis_mode.change(
+        lambda mode: MODE_INFO[mode],
+        inputs=analysis_mode,
+        outputs=mode_description
+    )
+    
     # Set up event handler
     analyze_btn.click(
         fn=analyze_weather_image,
-        inputs=[image_input, analysis_type, custom_prompt, temperature, max_tokens],
+        inputs=[image_input, analysis_type, custom_prompt, analysis_mode, temperature, max_tokens, top_p],
         outputs=output
     )