Update app.py

app.py

@@ -1,140 +1,171 @@
 import gradio as gr
 import pandas as pd
 from datetime import datetime
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
 # ----------------------
-# Load Production Model
+# Mock Model Components
 # ----------------------
-model_name = "DARJYO/darjyo-AgriLLM-GRPO"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-agriculture_pipe = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    device=0 if torch.cuda.is_available() else -1
-)
+def get_crop_recommendation(soil_type, climate, history):
+    """Mock recommendation engine"""
+    recommendations = {
+        "Parameter": ["Soil Type", "Climate Zone", "Top Crop", "Alternative 1", "Alternative 2"],
+        "Value": [soil_type, climate, "Pepper (0.85)", "Tomato (0.76)", "Chilli (0.68)"],
+        "Recommendation": [
+            "Optimal for root development",
+            "Ideal temperature range",
+            "High market demand",
+            "Good disease resistance",
+            "Drought tolerant"
+        ]
+    }
+    return pd.DataFrame(recommendations)
 
-# ----------------------
-# Agricultural Analysis Engine
-# ----------------------
-def generate_agricultural_response(query):
-    system_prompt = """You are CropSeek AI, an expert agricultural assistant. 
-    Provide detailed, professional crop recommendations based on:
-    - Soil type
-    - Climate conditions
-    - Historical yield data
-    - Regional market trends
-    - Sustainability practices
-    
-    Structure responses with:
-    1. Top 3 recommended crops
-    2. Confidence percentages
-    3. Cultivation guidelines
-    4. Risk factors
-    5. Market outlook"""
-
-    prompt = f"""<s>[INST] <<SYS>>
-    {system_prompt}
-    <</SYS>>
-    
-    User Query: {query} [/INST]"""
-    
-    response = agriculture_pipe(
-        prompt,
-        max_new_tokens=512,
-        temperature=0.7,
-        repetition_penalty=1.1,
-        do_sample=True
-    )[0]['generated_text'].split('[/INST]')[-1].strip()
-    
+def analyze_conditions(query, history):
+    """Mock analysis engine"""
+    response = f"🌱 **CropAI Analysis**: Based on '{query}', optimal cultivation patterns suggest **Pepper** (85% confidence) followed by Tomato and Chilli. "
+    response += "Recommended practices: Drip irrigation with weekly pH monitoring."
     return response
 
 # ----------------------
-# Data Analysis Component
-# ----------------------
-def analyze_agricultural_data(soil_type, climate, farm_data):
-    # Generate text analysis using the LLM
-    query = f"""Analyze farming conditions for:
-    - Soil type: {soil_type}
-    - Climate: {climate}
-    - Farm data: {pd.read_csv(farm_data.name).describe() if farm_data else 'No data'}
-    
-    Provide recommendations in table format with columns:
-    Crop | Confidence | Planting Window | Water Needs | Fertilizer | Yield Potential"""
-    
-    response = generate_agricultural_response(query)
-    
-    # Convert response to structured data
-    try:
-        df = pd.DataFrame([x.split('|') for x in response.split('\n') if '|' in x],
-                         columns=["Crop", "Confidence", "Planting Window", "Water Needs", "Fertilizer", "Yield Potential"])
-        return df
-    except:
-        return response
-
-# ----------------------
-# Gradio Interface
+# UI Components
 # ----------------------
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald"), title="CropSeek AI") as demo:
-    # Header Section
+    # ----------------------
+    # Enhanced Header
+    # ----------------------
     gr.HTML("""
-    <div style="text-align:center; background: linear-gradient(to right, #2c5f2d, #97bc62); padding: 20px; border-radius: 10px;">
-        <h1 style="color: white; margin: 10px 0;">🌾 CropSeek AI</h1>
-        <h3 style="color: #fafafa;">Production-Grade Agricultural Intelligence</h3>
+    <div style="text-align:center; background: linear-gradient(to right, #2c5f2d, #97bc62); padding: 20px; border-radius: 10px; box-shadow: 0 4px 6px rgba(0,0,0,0.1);">
+        <img src="https://huggingface.co/spaces/DARJYO/CropSeek-LLM/resolve/main/assets/logo.png" 
+             style="height:100px; filter: drop-shadow(2px 2px 4px #00000060);">
+        <h1 style="color: white; margin: 10px 0; font-family: 'Arial Rounded MT Bold', sans-serif;">CropSeek AI</h1>
+        <h3 style="color: #fafafa; font-weight: 300;">Next-Gen Agricultural Intelligence Platform</h3>
     </div>
     """)
 
+    # ----------------------
     # Main Analysis Interface
-    with gr.Tab("🌱 Field Optimization Console"):
+    # ----------------------
+    with gr.Tab("🌱 Field Analysis Console"):
         with gr.Row():
             with gr.Column(scale=2):
-                analysis_display = gr.Chatbot(
-                    label="Agricultural Analysis History",
+                analysis_log = gr.Chatbot(
+                    label="Crop Diagnosis History",
                     avatar_images=("🧑🌾", "🤖"),
-                    height=500
+                    height=450,
+                    bubble_full_width=False
                 )
-            
+                
             with gr.Column(scale=1):
-                gr.Markdown("### 🌍 Environmental Parameters")
-                soil_input = gr.Dropdown(
-                    ["Loamy", "Clay", "Sandy", "Peaty", "Chalky"],
-                    label="Soil Composition"
+                gr.Markdown("### 🌦️ Environmental Parameters")
+                field_input = gr.Textbox(
+                    label="Describe Conditions:",
+                    placeholder="e.g. 'Clay soil in tropical climate with 1200mm rainfall...'",
+                    lines=3
+                )
+                
+                gr.Examples(
+                    examples=[
+                        ["Sandy loam soil with temperate climate and irrigation access"],
+                        ["Arid region with limited water resources and alkaline soil"],
+                        ["Volcanic soil in subtropical highland climate"]
+                    ],
+                    inputs=field_input,
+                    label="💡 Try Example Scenarios:"
                 )
-                climate_input = gr.Dropdown(
-                    ["Tropical", "Arid", "Temperate", "Continental", "Mediterranean"],
-                    label="Climate Zone"
+                
+                analyze_btn = gr.Button(
+                    "🔍 Analyze Agricultural Patterns", 
+                    variant="primary",
+                    size="lg"
                 )
-                farm_data = gr.File(label="Upload Field Data (CSV)")
-                analyze_btn = gr.Button("🚜 Generate Cultivation Plan", variant="primary")
 
-    # Data Processing
-    analyze_btn.click(
-        fn=analyze_agricultural_data,
-        inputs=[soil_input, climate_input, farm_data],
-        outputs=analysis_display
-    )
+        analyze_btn.click(
+            analyze_conditions, 
+            [field_input, analysis_log], 
+            [field_input, analysis_log]
+        )
 
-    # Footer
+    # ----------------------
+    # Data Analysis Interface
+    # ----------------------
+    with gr.Tab("📈 Yield Optimization Advisor"):
+        with gr.Row():
+            soil_dd = gr.Dropdown(
+                ["Loamy", "Clay", "Sandy", "Volcanic", "Peaty"],
+                label="Soil Composition",
+                info="USDA soil classification",
+                interactive=True
+            )
+            climate_dd = gr.Dropdown(
+                ["Tropical", "Temperate", "Arid", "Mediterranean", "Continental"],
+                label="Climate Profile",
+                info="Köppen climate classification",
+                interactive=True
+            )
+            
+        with gr.Row():
+            farm_data = gr.File(
+                label="Upload Field Sensor Data (CSV)",
+                file_types=[".csv"],
+                height=50
+            )
+            simulate_btn = gr.Button(
+                "🚜 Generate Cultivation Plan", 
+                variant="primary",
+                size="lg"
+            )
+            
+        results = gr.Dataframe(
+            headers=["Parameter", "Value", "Recommendation"],
+            interactive=False,
+            wrap=True,
+            datatype=["str", "markdown", "str"],
+            height=400
+        )
+
+        # ----------------------
+        # Data Validation
+        # ----------------------
+        @demo.load(inputs=farm_data, outputs=results)
+        def validate_data(file_input):
+            if file_input:
+                try:
+                    df = pd.read_csv(file_input.name)
+                    required_columns = ['pH', 'Nitrogen', 'Phosphorus', 'Potassium']
+                    if not all(col in df.columns for col in required_columns):
+                        raise ValueError("Missing required soil analysis columns")
+                    return df.head().style.set_properties(**{
+                        'background-color': '#f0f7e4',
+                        'color': '#2c5f2d',
+                        'border-color': '#97bc62'
+                    })
+                except Exception as e:
+                    raise gr.Error(f"⚠️ Data validation error: {str(e)}")
+            return pd.DataFrame()
+
+        simulate_btn.click(
+            fn=get_crop_recommendation,
+            inputs=[soil_dd, climate_dd, farm_data],
+            outputs=results
+        )
+
+    # ----------------------
+    # Footer & Status
+    # ----------------------
     gr.Markdown("---")
+    with gr.Row():
+        gr.Markdown(f"**Last Updated:** {datetime.now().strftime('%Y-%m-%d %H:%M')}")
+        gr.Markdown("**System Status:** 🟢 Operational")
+        gr.Markdown("**Version:** 2.1.0")
+        
     gr.Markdown("""
-    <div style="text-align: center; padding: 15px;">
-        <small>Powered by DARJYO/darjyo-AgriLLM-GRPO | 
-        <a href="https://huggingface.co/DARJYO/darjyo-AgriLLM-GRPO" target="_blank">Model Documentation</a></small>
+    <div style="text-align: center; padding: 15px; background-color: #f8f9fa; border-radius: 8px; margin-top: 20px;">
+        <small>© 2025 DARJYO AI CropSeek | Agricultural Intelligence Platform | Contact: [email protected]</small>
     </div>
     """)
 
 # ----------------------
-# Deployment Configuration
+# Launch Application
 # ----------------------
-requirements = """
-gradio>=4.0
-torch>=2.0
-transformers>=4.30
-pandas>=2.0
-accelerate
-"""
-
 if __name__ == "__main__":
-    demo.launch(debug=True)
+    demo.launch()