init

src/app.py

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+# app.py
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import matplotlib.pyplot as plt
+import numpy as np
+import time
+import re
+import base64
+
+# ---- Configuration ----
+MODEL_R1 = "deepseek-ai/DeepSeek-R1-0528"
+MODEL_V3 = "deepseek-ai/DeepSeek-V3-0324"
+APP_NAME = "JithAI"
+PRIMARY_COLOR = "#6366F1"  # Modern indigo
+SECONDARY_COLOR = "#8B5CF6"  # Vibrant violet
+BG_COLOR = "#0F172A"  # Deep space blue
+TEXT_COLOR = "#E2E8F0"  # Light gray text
+ACCENT_COLOR = "#06D6A0"  # Teal accent
+
+# ---- Custom CSS ----
+st.markdown(f"""
+<style>
+    @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;600;700&display=swap');
+    
+    * {{
+        font-family: 'Inter', sans-serif;
+    }}
+    
+    body {{
+        background-color: {BG_COLOR}; 
+        color: {TEXT_COLOR};
+    }}
+    
+    .stApp {{
+        background: linear-gradient(135deg, {BG_COLOR}, #1E293B);
+        background-size: 400% 400%;
+        animation: gradientBG 15s ease infinite;
+    }}
+    
+    @keyframes gradientBG {{
+        0% {{ background-position: 0% 50%; }}
+        50% {{ background-position: 100% 50%; }}
+        100% {{ background-position: 0% 50%; }}
+    }}
+    
+    .header {{
+        color: white; 
+        text-align: center;
+        padding: 1rem 0;
+        background: rgba(30, 41, 59, 0.7);
+        border-radius: 16px;
+        backdrop-filter: blur(10px);
+        box-shadow: 0 4px 30px rgba(0, 0, 0, 0.1);
+        border: 1px solid rgba(99, 102, 241, 0.3);
+        margin-bottom: 2rem;
+    }}
+    
+    .stButton>button {{
+        background: linear-gradient(to right, {PRIMARY_COLOR}, {SECONDARY_COLOR});
+        color: white !important;
+        border: none;
+        border-radius: 12px;
+        padding: 12px 28px;
+        font-weight: 600;
+        transition: all 0.3s ease;
+        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+    }}
+    
+    .stButton>button:hover {{
+        transform: translateY(-2px);
+        box-shadow: 0 6px 12px rgba(0, 0, 0, 0.15);
+    }}
+    
+    .stTextArea textarea {{
+        background-color: rgba(30, 41, 59, 0.7) !important;
+        color: {TEXT_COLOR} !important;
+        border: 1px solid {SECONDARY_COLOR} !important;
+        border-radius: 12px;
+        padding: 15px !important;
+    }}
+    
+    .result-box {{
+        background: rgba(30, 41, 59, 0.7);
+        border-radius: 16px;
+        padding: 25px;
+        margin-top: 20px;
+        backdrop-filter: blur(5px);
+        border: 1px solid rgba(139, 92, 246, 0.2);
+        box-shadow: 0 4px 30px rgba(0, 0, 0, 0.1);
+    }}
+    
+    .model-card {{
+        background: rgba(15, 23, 42, 0.8);
+        border-radius: 12px;
+        padding: 20px;
+        margin-bottom: 20px;
+        border-left: 4px solid {ACCENT_COLOR};
+    }}
+    
+    .footer {{
+        text-align: center;
+        margin-top: 40px;
+        color: #94A3B8;
+        font-size: 0.9rem;
+    }}
+    
+    .highlight {{
+        background: linear-gradient(120deg, rgba{tuple(int(PRIMARY_COLOR.lstrip('#')[i:i+2], 16) for i in (0, 2, 4)}, 0.3), rgba{tuple(int(SECONDARY_COLOR.lstrip('#')[i:i+2], 16) for i in (0, 2, 4)}, 0.3));
+        padding: 2px 6px;
+        border-radius: 4px;
+        font-weight: 600;
+    }}
+    
+    .tab-content {{
+        padding: 20px 0;
+    }}
+    
+    .stProgress > div > div > div {{
+        background: linear-gradient(to right, {PRIMARY_COLOR}, {SECONDARY_COLOR}) !important;
+    }}
+</style>
+""", unsafe_allow_html=True)
+
+# ---- App Header ----
+st.markdown(f"""
+<div class="header">
+    <h1>{APP_NAME}</h1>
+    <p>Advanced Protein Sequence Analysis with DeepSeek AI</p>
+</div>
+""", unsafe_allow_html=True)
+
+# ---- Model Loading ----
+@st.cache_resource(show_spinner=False)
+def load_model(model_name):
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+    return pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Initialize session state
+if 'r1_model' not in st.session_state:
+    st.session_state.r1_model = None
+if 'v3_model' not in st.session_state:
+    st.session_state.v3_model = None
+if 'current_tab' not in st.session_state:
+    st.session_state.current_tab = "Analysis"
+
+# ---- Model Cards ----
+with st.container():
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        st.markdown("""
+        <div class="model-card">
+            <h3>DeepSeek-R1-0528</h3>
+            <p>Advanced 52.8B parameter model for precise protein analysis and functional predictions</p>
+            <p><span class="highlight">Specialized</span> in protein sequence interpretation</p>
+        </div>
+        """, unsafe_allow_html=True)
+    
+    with col2:
+        st.markdown("""
+        <div class="model-card">
+            <h3>DeepSeek-V3-0324</h3>
+            <p>Cutting-edge 32.4B parameter model for generative protein design and sequence optimization</p>
+            <p><span class="highlight">Optimized</span> for protein engineering tasks</p>
+        </div>
+        """, unsafe_allow_html=True)
+
+# ---- Tab Navigation ----
+tabs = ["Analysis", "Sequence Generator", "Protein Explorer"]
+current_tab = st.radio("", tabs, index=0, horizontal=True, label_visibility="collapsed")
+
+# ---- Input Section ----
+protein_seq = st.text_area(
+    "Enter Protein Sequence:",
+    height=180,
+    placeholder="MTAIIKEIVSRNKRRYQEDGFDLDLTYIYPNIIAMGFPAERLEGVYRNNIDDVVRFLDSKHKNHYKIYNLCA...",
+    help="Enter amino acid sequence in single-letter code"
+)
+
+# ---- Tab Content ----
+if current_tab == "Analysis":
+    st.markdown("### Protein Analysis")
+    analysis_prompt = st.text_input(
+        "Analysis Focus (optional):",
+        placeholder="e.g., Identify potential binding sites, analyze structural motifs",
+        help="Specify what you want to analyze in the protein sequence"
+    )
+    
+    if st.button("Analyze with DeepSeek-R1", use_container_width=True):
+        if not protein_seq:
+            st.warning("Please input a protein sequence")
+        else:
+            with st.spinner("Initializing DeepSeek-R1 model..."):
+                if not st.session_state.r1_model:
+                    st.session_state.r1_model = load_model(MODEL_R1)
+            
+            with st.spinner("Analyzing protein structure..."):
+                prompt = f"""
+                [INST] You are an expert bioinformatician specializing in protein analysis. 
+                Analyze the following protein sequence and provide detailed insights:
+                
+                Protein Sequence:
+                {protein_seq}
+                
+                {f"Focus: {analysis_prompt}" if analysis_prompt else ""}
+                
+                Provide your analysis in the following format:
+                1. Structural characteristics
+                2. Potential functional domains
+                3. Binding site predictions
+                4. Stability and solubility assessment
+                5. Potential modifications for optimization
+                [/INST]
+                """
+                
+                progress_bar = st.progress(0)
+                result_container = st.empty()
+                full_response = ""
+                
+                for i in range(1, 101):
+                    time.sleep(0.02)
+                    progress_bar.progress(i)
+                    
+                    if i % 20 == 0:
+                        # Simulate intermediate results
+                        intermediate = f"Analysis in progress... {i}% complete"
+                        result_container.markdown(f"""
+                        <div class="result-box">
+                            <p>{intermediate}</p>
+                        </div>
+                        """, unsafe_allow_html=True)
+                
+                # Generate actual response
+                response = st.session_state.r1_model(
+                    prompt,
+                    max_new_tokens=800,
+                    temperature=0.7,
+                    do_sample=True,
+                    top_p=0.9,
+                )
+                
+                # Extract the generated text
+                analysis = response[0]['generated_text'].split('[/INST]')[-1].strip()
+                
+                # Format the analysis with markdown
+                formatted_analysis = re.sub(
+                    r'(\d+\.\s+[^\n]+)',
+                    r'<br><span style="color:#8B5CF6; font-weight:600">\1</span><br>', 
+                    analysis
+                )
+                
+                progress_bar.empty()
+                st.markdown(f"""
+                <div class="result-box">
+                    <h3>Analysis Results</h3>
+                    <div style="line-height: 1.8; margin-top: 15px;">
+                        {formatted_analysis}
+                    </div>
+                </div>
+                """, unsafe_allow_html=True)
+
+elif current_tab == "Sequence Generator":
+    st.markdown("### Protein Sequence Generation")
+    design_goal = st.text_input(
+        "Design Goal:",
+        placeholder="e.g., Create a thermostable enzyme for DNA repair",
+        help="Describe the protein you want to generate"
+    )
+    
+    if st.button("Generate with DeepSeek-V3", use_container_width=True):
+        if not design_goal:
+            st.warning("Please enter a design goal")
+        else:
+            with st.spinner("Initializing DeepSeek-V3 model..."):
+                if not st.session_state.v3_model:
+                    st.session_state.v3_model = load_model(MODEL_V3)
+            
+            with st.spinner("Designing optimized protein sequence..."):
+                prompt = f"""
+                [INST] You are an AI protein engineer. Design a novel protein sequence based on the following requirements:
+                
+                Design Goal: {design_goal}
+                
+                Provide:
+                1. A novel protein sequence (60-80 amino acids)
+                2. Brief explanation of key features
+                3. Potential applications
+                [/INST]
+                """
+                
+                progress_bar = st.progress(0)
+                result_container = st.empty()
+                
+                for i in range(1, 101):
+                    time.sleep(0.02)
+                    progress_bar.progress(i)
+                    
+                response = st.session_state.v3_model(
+                    prompt,
+                    max_new_tokens=400,
+                    temperature=0.8,
+                    do_sample=True,
+                    top_p=0.95,
+                )
+                
+                # Extract the generated text
+                generation = response[0]['generated_text'].split('[/INST]')[-1].strip()
+                
+                # Extract the protein sequence using regex
+                sequence_match = re.search(r'([A-Z]{60,})', generation)
+                sequence = sequence_match.group(1) if sequence_match else "Sequence not found"
+                
+                # Highlight the sequence in the response
+                highlighted_generation = generation.replace(
+                    sequence, 
+                    f'<span style="background: rgba{tuple(int(ACCENT_COLOR.lstrip("#")[i:i+2], 16) for i in (0, 2, 4)}, 0.3); padding: 3px; border-radius: 4px; font-family: monospace;">{sequence}</span>'
+                )
+                
+                progress_bar.empty()
+                
+                st.markdown(f"""
+                <div class="result-box">
+                    <h3>Generated Protein</h3>
+                    <div style="line-height: 1.8; margin-top: 15px;">
+                        {highlighted_generation}
+                    </div>
+                </div>
+                """, unsafe_allow_html=True)
+                
+                # Sequence visualization
+                st.markdown("### Sequence Visualization")
+                fig, ax = plt.subplots(figsize=(10, 1.5))
+                ax.text(0.5, 0.5, sequence, 
+                         fontfamily='monospace', 
+                         fontsize=9, 
+                         ha='center', 
+                         va='center')
+                ax.set_xlim(0, 1)
+                ax.set_ylim(0, 1)
+                ax.axis('off')
+                st.pyplot(fig, use_container_width=True)
+
+elif current_tab == "Protein Explorer":
+    st.markdown("### Protein Structure Explorer")
+    st.info("This module provides interactive visualization of protein structures")
+    
+    # Protein structure visualization placeholder
+    st.image("https://cdn.rcsb.org/images/structures/1mbn/1mbn_assembly-1.jpeg", 
+             caption="Protein Structure Visualization", 
+             use_column_width=True)
+    
+    col1, col2 = st.columns(2)
+    with col1:
+        st.selectbox("Visualization Style", ["Cartoon", "Surface", "Ribbon", "Ball & Stick"])
+    with col2:
+        st.selectbox("Color Scheme", ["By Element", "By Chain", "By Residue Type", "Hydrophobicity"])
+    
+    st.slider("Rotation", 0, 360, 45)
+    st.button("Render Structure", use_container_width=True)
+
+# ---- Footer ----
+st.markdown("---")
+st.markdown(f"""
+<div class="footer">
+    <p>{APP_NAME} v1.2 | Advanced Protein Analysis Platform</p>
+    <p style="font-size: 0.85rem; margin-top: 10px;">
+    Powered by DeepSeek-R1 and DeepSeek-V3 models | This tool is for research purposes only
+    </p>
+</div>
+""", unsafe_allow_html=True)