Update app.py

app.py

@@ -1,34 +1,33 @@
 import streamlit as st
-from dotenv import load_dotenv
 import os
-from crewai import Agent, Task, Crew
-from langchain_google_genai import ChatGoogleGenerativeAI
+from dotenv import load_dotenv
+import google.generativeai as genai
 
 # Load environment variables
 load_dotenv()
 GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
 
-# API key validation
+# Validate API Key
 if not GOOGLE_API_KEY:
-    st.error("Google Gemini API key not found. Please set it in the .env file.")
+    st.error("Google Gemini API key not found. Please set GOOGLE_API_KEY in your .env file.")
     st.stop()
 
-# Streamlit config
+# Configure Gemini
+genai.configure(api_key=GOOGLE_API_KEY)
+
+# Streamlit page setup
 st.set_page_config(page_title="NeuraNexus: AI-Powered ML Assistant", page_icon="🧠", layout="wide")
 
-# ==========================
-# CSS & Animation
-# ==========================
+# ==============================
+# Custom CSS (include your full CSS here)
+# ==============================
 st.markdown("""
 <style>
-/* (Only showing part of the long CSS here to avoid repetition. Replace with your full custom CSS/JS from the previous version) */
-
 body {
     background-color: #0F1C2E;
-    color: #FFFFFF;
+    color: white;
     font-family: 'Roboto', sans-serif;
 }
-
 h1 {
     font-family: 'Orbitron', sans-serif;
     color: #FF6B6B;
@@ -36,18 +35,16 @@ h1 {
     font-size: 2.5em;
     text-shadow: 0 0 10px rgba(255, 107, 107, 0.7);
 }
-
 .result-container {
     background: rgba(255, 255, 255, 0.05);
     border: 1px solid rgba(74, 144, 226, 0.2);
     border-radius: 15px;
     padding: 20px;
     margin-top: 30px;
-    color: #FFFFFF;
+    color: white;
     box-shadow: 0 8px 32px 0 rgba(31, 38, 135, 0.2);
     backdrop-filter: blur(10px);
 }
-
 .by-theaimart {
     text-align: center;
     font-size: 20px;
@@ -56,110 +53,57 @@ h1 {
     font-weight: bold;
 }
 </style>
-
-<!-- Optional neural animation background -->
-<div class="neural-network" id="neuralNetwork"></div>
-<script>
-function createNeuralNetwork() {
-    const container = document.getElementById('neuralNetwork');
-    const numNeurons = 20;
-    const numSynapses = 30;
-    for (let i = 0; i < numNeurons; i++) {
-        const neuron = document.createElement('div');
-        neuron.classList.add('neuron');
-        neuron.style.left = `${Math.random() * 100}%`;
-        neuron.style.top = `${Math.random() * 100}%`;
-        neuron.style.width = `${Math.random() * 10 + 5}px`;
-        neuron.style.height = neuron.style.width;
-        container.appendChild(neuron);
-    }
-    for (let i = 0; i < numSynapses; i++) {
-        const synapse = document.createElement('div');
-        synapse.classList.add('synapse');
-        synapse.style.left = `${Math.random() * 100}%`;
-        synapse.style.top = `${Math.random() * 100}%`;
-        synapse.style.width = `${Math.random() * 200 + 50}px`;
-        synapse.style.transform = `rotate(${Math.random() * 360}deg)`;
-        container.appendChild(synapse);
-    }
-}
-document.addEventListener('DOMContentLoaded', createNeuralNetwork);
-</script>
 """, unsafe_allow_html=True)
 
-# ==========================
-# UI
-# ==========================
+# ==============================
+# App UI
+# ==============================
 st.markdown('<h1 class="glow">NeuraNexus: AI-Powered ML Assistant</h1>', unsafe_allow_html=True)
 st.markdown('<h3 style="text-align:center;">Describe your ML challenge, and let NeuraNexus craft an innovative solution.</h3>', unsafe_allow_html=True)
 
-problem_description = st.text_area("", height=150, placeholder="Enter your ML challenge here...")
-analyze_button = st.button("SYNTHESIZE")
+# Input from user
+user_prompt = st.text_area("Your ML Challenge", height=150, placeholder="Enter your machine learning challenge here...")
 
-if 'analysis_result' not in st.session_state:
-    st.session_state.analysis_result = ""
+if 'response' not in st.session_state:
+    st.session_state.response = ""
 
-# ==========================
-# Handle Analysis
-# ==========================
-if analyze_button:
-    if not problem_description:
-        st.warning("Please describe your ML challenge before synthesizing.")
+# Generate button
+if st.button("SYNTHESIZE"):
+    if not user_prompt.strip():
+        st.warning("Please describe your ML challenge first.")
     else:
-        with st.spinner("NeuraNexus is synthesizing your solution..."):
+        with st.spinner("NeuraNexus is thinking..."):
             try:
-                # Gemini LLM via LangChain
-                llm = ChatGoogleGenerativeAI(
-                    model="gemini-pro",
-                    google_api_key=GOOGLE_API_KEY,
-                    temperature=0.2
-                )
-
-                # Define Agent
-                agent = Agent(
-                    role="NeuraNexus - ML Architect",
-                    goal="Design innovative ML strategies",
-                    backstory="You are an advanced AI agent trained in modern and futuristic machine learning problem-solving.",
-                    verbose=True,
-                    allow_delegation=False,
-                    llm=llm
-                )
-
-                # Define Task
-                task = Task(
-                    description=f"Analyze the following ML challenge and provide a detailed solution strategy: {problem_description}",
-                    expected_output="An innovative, clear, and actionable ML solution strategy.",
-                    agent=agent
-                )
-
-                # Crew
-                crew = Crew(
-                    agents=[agent],
-                    tasks=[task],
-                    verbose=False
-                )
-
-                result = crew.kickoff()
-                st.session_state.analysis_result = str(result)
+                model = genai.GenerativeModel("gemini-pro")
+                chat = model.start_chat()
+
+                system_prompt = "You are NeuraNexus, an AI specialized in designing innovative and actionable ML strategies. Provide expert-level solutions to the given ML challenge."
+
+                full_prompt = f"{system_prompt}\n\nUser Problem:\n{user_prompt}"
+
+                response = chat.send_message(full_prompt)
+                st.session_state.response = response.text
                 st.success("Synthesis complete!")
 
             except Exception as e:
-                st.session_state.analysis_result = f"❌ Error: {str(e)}"
+                st.session_state.response = f"❌ Error: {e}"
                 st.error("Gemini synthesis failed.")
 
-# ==========================
-# Display Output
-# ==========================
-if st.session_state.analysis_result:
+# ==============================
+# Show result
+# ==============================
+if st.session_state.response:
     st.markdown("### NeuraNexus Synthesis Result")
     st.markdown(f"""
     <div class="result-container">
-        {st.session_state.analysis_result}
+        {st.session_state.response}
     </div>
     """, unsafe_allow_html=True)
 
+# Footer
 st.markdown('<p class="by-theaimart">By Theaimart</p>', unsafe_allow_html=True)
 
+# Run wrapper
 def main():
     pass