committing the project AI Design Agent Team

ai_agent_tutorials/ai_multimodal_design_agent/README.md

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+# Multimodal AI Design Agent Team
+
+A multimodal design analysis tool powered by Google's Gemini 2.0 multimodal capabilities. This application leverages multiple specialized AI agents to provide comprehensive analysis of UI/UX designs of your product and your competitors, combining visual understanding, user experience evaluation, and market research insights.
+
+## Demo
+
+
+## About
+
+The Design Agent Team utilizes Gemini 2.0's advanced multimodal capabilities to analyze design assets from multiple perspectives:
+
+- 🎨 **Visual Design Analysis**: Evaluates design elements, patterns, color schemes, typography, and visual hierarchy
+- 🔄 **UX Analysis**: Assesses user flows, interaction patterns, usability, and accessibility
+- 📊 **Market Analysis**: Provides market insights, competitor analysis, and positioning recommendations
+
+## Features
+
+- **Multiple Analysis Types**: Choose from Visual Design, UX, and Market Analysis
+- **Comparative Analysis**: Upload competitor designs for comparative insights
+- **Customizable Focus Areas**: Select specific aspects for detailed analysis
+- **Context-Aware**: Provide additional context for more relevant insights
+- **Real-time Processing**: Get instant analysis with progress indicators
+- **Structured Output**: Receive well-organized, actionable insights
+
+## How to Run
+
+1. **Setup Environment**
+   ```bash
+   # Clone the repository
+   git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+   cd ai_agent_tutorials/ai_multimodal_design_agent
+
+   # Create and activate virtual environment (optional)
+   python -m venv venv
+   source venv/bin/activate  # On Windows: venv\Scripts\activate
+
+   # Install dependencies
+   pip install -r requirements.txt
+   ```
+
+2. **Get API Key**
+   - Visit [Google AI Studio](https://makersuite.google.com/app/apikey)
+   - Create or select a project
+   - Generate an API key
+
+3. **Run the Application**
+   ```bash
+   streamlit run design_agent_team.py
+   ```
+
+4. **Use the Application**
+   - Enter your Gemini API key in the sidebar
+   - Upload design files (supported formats: JPG, JPEG, PNG)
+   - Select analysis types and focus areas
+   - Add context if needed
+   - Click "Run Analysis" to get insights
+
+
+## Technical Stack
+
+- **Frontend**: Streamlit
+- **AI Model**: Google Gemini 2.0
+- **Image Processing**: Pillow
+- **Market Research**: DuckDuckGo Search API
+- **Framework**: Phidata for agent orchestration
+
+## Tips for Best Results
+
+- Upload clear, high-resolution images
+- Include multiple views/screens for better context
+- Add competitor designs for comparative analysis
+- Provide specific context about your target audience
+

ai_agent_tutorials/ai_multimodal_design_agent/design_agent_team.py

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+from phi.agent import Agent
+from phi.model.google import Gemini
+from phi.tools.duckduckgo import DuckDuckGo
+import streamlit as st
+from PIL import Image
+from typing import List, Optional
+
+def initialize_agents(api_key: str) -> tuple[Agent, Agent, Agent]:
+    try:
+        model = Gemini(id="gemini-2.0-flash-exp", api_key=api_key)
+
+        vision_agent = Agent(
+            model=model,
+            instructions=[
+                "You are a visual analysis expert that:",
+                "1. Identifies design elements, patterns, and visual hierarchy",
+                "2. Analyzes color schemes, typography, and layouts",
+                "3. Detects UI components and their relationships",
+                "4. Evaluates visual consistency and branding",
+                "Be specific and technical in your analysis"
+            ],
+            markdown=True
+        )
+
+        ux_agent = Agent(
+            model=model,
+            instructions=[
+                "You are a UX analysis expert that:",
+                "1. Evaluates user flows and interaction patterns",
+                "2. Identifies usability issues and opportunities",
+                "3. Suggests UX improvements based on best practices",
+                "4. Analyzes accessibility and inclusive design",
+                "Focus on user-centric insights and practical improvements"
+            ],
+            markdown=True
+        )
+
+        market_agent = Agent(
+            model=model,
+            tools=[DuckDuckGo(search=True)],
+            instructions=[
+                "You are a market research expert that:",
+                "1. Identifies market trends and competitor patterns",
+                "2. Analyzes similar products and features",
+                "3. Suggests market positioning and opportunities",
+                "4. Provides industry-specific insights",
+                "Focus on actionable market intelligence"
+            ],
+            markdown=True
+        )
+
+        return vision_agent, ux_agent, market_agent
+    except Exception as e:
+        st.error(f"Error initializing agents: {str(e)}")
+        return None, None, None
+
+# Sidebar for API key input
+with st.sidebar:
+    st.header("🔑 API Configuration")
+
+    if "api_key_input" not in st.session_state:
+        st.session_state.api_key_input = ""
+
+    api_key = st.text_input(
+        "Enter your Gemini API Key",
+        value=st.session_state.api_key_input,
+        type="password",
+        help="Get your API key from Google AI Studio",
+        key="api_key_widget"  
+    )
+
+    if api_key != st.session_state.api_key_input:
+        st.session_state.api_key_input = api_key
+
+    if api_key:
+        st.success("API Key provided! ✅")
+    else:
+        st.warning("Please enter your API key to proceed")
+        st.markdown("""
+        To get your API key:
+        1. Go to [Google AI Studio](https://makersuite.google.com/app/apikey)
+        """)
+
+st.title("Multimodal AI Design Agent Team")
+
+if st.session_state.api_key_input:
+    vision_agent, ux_agent, market_agent = initialize_agents(st.session_state.api_key_input)
+
+    if all([vision_agent, ux_agent, market_agent]):
+        # File Upload Section
+        st.header("📤 Upload Content")
+        col1, space, col2 = st.columns([1, 0.1, 1])
+
+        with col1:
+            design_files = st.file_uploader(
+                "Upload UI/UX Designs",
+                type=["jpg", "jpeg", "png"],
+                accept_multiple_files=True,
+                key="designs"
+            )
+
+            if design_files:
+                for file in design_files:
+                    image = Image.open(file)
+                    st.image(image, caption=file.name, use_container_width=True)
+
+        with col2:
+            competitor_files = st.file_uploader(
+                "Upload Competitor Designs (Optional)",
+                type=["jpg", "jpeg", "png"],
+                accept_multiple_files=True,
+                key="competitors"
+            )
+
+            if competitor_files:
+                for file in competitor_files:
+                    image = Image.open(file)
+                    st.image(image, caption=f"Competitor: {file.name}", use_container_width=True)
+
+        # Analysis Configuration
+        st.header("🎯 Analysis Configuration")
+
+        analysis_types = st.multiselect(
+            "Select Analysis Types",
+            ["Visual Design", "User Experience", "Market Analysis"],
+            default=["Visual Design"]
+        )
+
+        specific_elements = st.multiselect(
+            "Focus Areas",
+            ["Color Scheme", "Typography", "Layout", "Navigation", 
+             "Interactions", "Accessibility", "Branding", "Market Fit"]
+        )
+
+        context = st.text_area(
+            "Additional Context",
+            placeholder="Describe your product, target audience, or specific concerns..."
+        )
+
+        # Analysis Process
+        if st.button("🚀 Run Analysis", type="primary"):
+            if design_files:
+                try:
+                    st.header("📊 Analysis Results")
+
+                    # Process images once
+                    def process_images(files):
+                        processed_images = []
+                        for file in files:
+                            try:
+                                # Create a temporary file path for the image
+                                import tempfile
+                                import os
+
+                                temp_dir = tempfile.gettempdir()
+                                temp_path = os.path.join(temp_dir, f"temp_{file.name}")
+
+                                # Save the uploaded file to temp location
+                                with open(temp_path, "wb") as f:
+                                    f.write(file.getvalue())
+
+                                # Add the path to processed images
+                                processed_images.append(temp_path)
+
+                            except Exception as e:
+                                st.error(f"Error processing image {file.name}: {str(e)}")
+                                continue
+                        return processed_images
+
+                    design_images = process_images(design_files)
+                    competitor_images = process_images(competitor_files) if competitor_files else []
+                    all_images = design_images + competitor_images
+
+                    # Visual Design Analysis
+                    if "Visual Design" in analysis_types and design_files:
+                        with st.spinner("🎨 Analyzing visual design..."):
+                            if all_images:
+                                vision_prompt = f"""
+                                Analyze these designs focusing on: {', '.join(specific_elements)}
+                                Additional context: {context}
+                                Provide specific insights about visual design elements.
+                                
+                                Please format your response with clear headers and bullet points.
+                                Focus on concrete observations and actionable insights.
+                                """
+
+                                response = vision_agent.run(
+                                    message=vision_prompt,
+                                    images=all_images
+                                )
+
+                                st.subheader("🎨 Visual Design Analysis")
+                                st.markdown(response.content)
+
+                    # UX Analysis
+                    if "User Experience" in analysis_types:
+                        with st.spinner("🔄 Analyzing user experience..."):
+                            if all_images:
+                                ux_prompt = f"""
+                                Evaluate the user experience considering: {', '.join(specific_elements)}
+                                Additional context: {context}
+                                Focus on user flows, interactions, and accessibility.
+                                
+                                Please format your response with clear headers and bullet points.
+                                Focus on concrete observations and actionable improvements.
+                                """
+
+                                response = ux_agent.run(
+                                    message=ux_prompt,
+                                    images=all_images
+                                )
+
+                                st.subheader("🔄 UX Analysis")
+                                st.markdown(response.content)
+
+                    # Market Analysis
+                    if "Market Analysis" in analysis_types:
+                        with st.spinner("📊 Conducting market analysis..."):
+                            market_prompt = f"""
+                            Analyze market positioning and trends based on these designs.
+                            Context: {context}
+                            Compare with competitor designs if provided.
+                            Suggest market opportunities and positioning.
+                            
+                            Please format your response with clear headers and bullet points.
+                            Focus on concrete market insights and actionable recommendations.
+                            """
+
+                            response = market_agent.run(
+                                message=market_prompt,
+                                images=all_images
+                            )
+
+                            st.subheader("📊 Market Analysis")
+                            st.markdown(response.content)
+
+                    # Combined Insights
+                    if len(analysis_types) > 1:
+                        st.subheader("🎯 Key Takeaways")
+                        st.info("""
+                        Above you'll find detailed analysis from multiple specialized AI agents, each focusing on their area of expertise:
+                        - Visual Design Agent: Analyzes design elements and patterns
+                        - UX Agent: Evaluates user experience and interactions
+                        - Market Research Agent: Provides market context and opportunities
+                        """)
+
+                except Exception as e:
+                    st.error(f"An error occurred during analysis: {str(e)}")
+                    st.error("Please check your API key and try again.")
+            else:
+                st.warning("Please upload at least one design to analyze.")
+    else:
+        st.info("👈 Please enter your API key in the sidebar to get started")
+else:
+    st.info("👈 Please enter your API key in the sidebar to get started")
+
+# Footer with usage tips
+st.markdown("---")
+st.markdown("""
+<div style='text-align: center'>
+    <h4>Tips for Best Results</h4>
+    <p>
+    • Upload clear, high-resolution images<br>
+    • Include multiple views/screens for better context<br>
+    • Add competitor designs for comparative analysis<br>
+    • Provide specific context about your target audience
+    </p>
+</div>
+""", unsafe_allow_html=True) 

ai_agent_tutorials/ai_multimodal_design_agent/requirements.txt

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+google-generativeai==0.8.3
+streamlit==1.30.0
+phidata==2.7.2
+Pillow==11.0.0
+duckduckgo-search==6.3.7
+