Upload app.py

app.py

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+import streamlit as st
+from langchain_ollama import ChatOllama
+from langchain_core.output_parsers import StrOutputParser
+
+from langchain_core.prompts import (
+    SystemMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+    AIMessagePromptTemplate,
+    ChatPromptTemplate
+)
+# Custom CSS styling
+st.markdown("""
+<style>
+    /* Existing styles */
+    .main {
+        background-color: #1a1a1a;
+        color: #ffffff;
+    }
+    .sidebar .sidebar-content {
+        background-color: #2d2d2d;
+    }
+    .stTextInput textarea {
+        color: #ffffff !important;
+    }
+    
+    /* Add these new styles for select box */
+    .stSelectbox div[data-baseweb="select"] {
+        color: white !important;
+        background-color: #3d3d3d !important;
+    }
+    
+    .stSelectbox svg {
+        fill: white !important;
+    }
+    
+    .stSelectbox option {
+        background-color: #2d2d2d !important;
+        color: white !important;
+    }
+    
+    /* For dropdown menu items */
+    div[role="listbox"] div {
+        background-color: #2d2d2d !important;
+        color: white !important;
+    }
+</style>
+""", unsafe_allow_html=True)
+st.title("🧠 DeepSeek Code Companion")
+st.caption("🚀 Your AI Pair Programmer with Debugging Superpowers")
+
+# Sidebar configuration
+with st.sidebar:
+    st.header("⚙️ Configuration")
+    selected_model = st.selectbox(
+        "Choose Model",
+        ["deepseek-r1:1.5b", "deepseek-r1:3b"],
+        index=0
+    )
+    st.divider()
+    st.markdown("### Model Capabilities")
+    st.markdown("""
+    - 🐍 Python Expert
+    - 🐞 Debugging Assistant
+    - 📝 Code Documentation
+    - 💡 Solution Design
+    """)
+    st.divider()
+    st.markdown("Built with [Ollama](https://ollama.ai/) | [LangChain](https://python.langchain.com/)")
+
+
+# initiate the chat engine
+
+llm_engine=ChatOllama(
+    model=selected_model,
+    base_url="http://localhost:11434",
+
+    temperature=0.3
+
+)
+
+# System prompt configuration
+system_prompt = SystemMessagePromptTemplate.from_template(
+    "You are an expert AI coding assistant. Provide concise, correct solutions "
+    "with strategic print statements for debugging. Always respond in English."
+)
+
+# Session state management
+if "message_log" not in st.session_state:
+    st.session_state.message_log = [{"role": "ai", "content": "Hi! I'm DeepSeek. How can I help you code today? 💻"}]
+
+# Chat container
+chat_container = st.container()
+
+# Display chat messages
+with chat_container:
+    for message in st.session_state.message_log:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+# Chat input and processing
+user_query = st.chat_input("Type your coding question here...")
+
+def generate_ai_response(prompt_chain):
+    processing_pipeline=prompt_chain | llm_engine | StrOutputParser()
+    return processing_pipeline.invoke({})
+
+def build_prompt_chain():
+    prompt_sequence = [system_prompt]
+    for msg in st.session_state.message_log:
+        if msg["role"] == "user":
+            prompt_sequence.append(HumanMessagePromptTemplate.from_template(msg["content"]))
+        elif msg["role"] == "ai":
+            prompt_sequence.append(AIMessagePromptTemplate.from_template(msg["content"]))
+    return ChatPromptTemplate.from_messages(prompt_sequence)
+
+if user_query:
+    # Add user message to log
+    st.session_state.message_log.append({"role": "user", "content": user_query})
+    
+    # Generate AI response
+    with st.spinner("🧠 Processing..."):
+        prompt_chain = build_prompt_chain()
+        ai_response = generate_ai_response(prompt_chain)
+    
+    # Add AI response to log
+    st.session_state.message_log.append({"role": "ai", "content": ai_response})
+    
+    # Rerun to update chat display
+    st.rerun()