I'll help you design an agentic AI solution to create games based on user input using Azure GPT-4 and Streamlit. Here's a comprehensive architecture:

### Solution Architecture
```mermaid
graph TD
    A[User Input] --> B(Orchestrator Agent)
    B --> C1(Requirement Analyzer)
    B --> C2(Game Designer)
    B --> C3(Component Generator)
    B --> C4(Code Assembler)
    B --> C5(Streamlit Integrator)
    C1 --> D[Game Spec]
    C2 --> E[Game Design]
    C3 --> F[Code Modules]
    C4 --> G[Full Codebase]
    C5 --> H[Streamlit App]
    H --> I[Playable Game]
```

### Agent System Components

1. **Orchestrator Agent** (Azure GPT-4)
   - Manages workflow and communication
   - Coordinates task sequencing
   - Validates final output

2. **Requirement Analyzer Agent**
   - Input: User request ("Create a Mario-like game")
   - Output: Structured requirements:
     ```json
     {
       "core_mechanics": ["platforming", "jumping", "collision"],
       "assets": ["player", "enemies", "coins", "platforms"],
       "rules": ["score system", "lives system"],
       "visuals": ["2D side-scroller"]
     }
     ```

3. **Game Designer Agent**
   - Creates game design document
   - Sample output:
     ```markdown
     ## Game Elements
     - Player: Moves with ← → keys, jumps with SPACE
     - Enemies: Move horizontally, reset on collision
     - Coins: Collectible (+10 points)
     - Platforms: Collidable surfaces
     
     ## Game Loop
     1. Render scene
     2. Process input
     3. Update positions
     4. Check collisions
     5. Update score
     ```

4. **Component Generator Agent**
   - Generates modular code using Azure GPT-4
   - Creates:
     - `player.py`: Movement logic
     - `physics.py`: Collision detection
     - `game_objects.py`: Coin/enemy classes
     - `level.py`: Platform layout

5. **Code Assembler Agent**
   - Combines modules into playable prototype
   - Ensures component compatibility
   - Adds game loop structure

6. **Streamlit Integrator Agent**
   - Creates UI wrapper:
     ```python
     import streamlit as st
     import pygame_wrapper  # Generated game module

     st.title("Mario-like Platformer")
     if st.button("Start Game"):
         pygame_wrapper.run_game()
     ```

### Technical Implementation

**Core Dependencies:**
```python
# requirements.txt
streamlit==1.32.0
openai==1.30.1
pygame==2.5.0  # For game rendering
```

**Orchestrator Workflow:**
```python
from openai import AzureOpenAI

def generate_with_gpt(prompt, system_role):
    client = AzureOpenAI(
        api_key="YOUR_AZURE_KEY",
        api_version="2024-02-01",
        azure_endpoint="https://YOUR_RESOURCE.openai.azure.com"
    )
    
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": system_role},
            {"role": "user", "content": prompt}
        ],
        temperature=0.3
    )
    return response.choices[0].message.content
```

**Agent Execution Sequence:**
```python
def create_game(user_input):
    # Step 1: Analyze requirements
    requirements = generate_with_gpt(
        user_input, 
        "You are a game requirements analyzer. Extract mechanics, assets, and rules."
    )
    
    # Step 2: Design game
    design_doc = generate_with_gpt(
        requirements,
        "You are a game designer. Create detailed mechanics and level design."
    )
    
    # Step 3: Generate components
    components = {}
    for component in ["player", "physics", "objects", "levels"]:
        components[component] = generate_with_gpt(
            design_doc,
            f"You are a game programmer. Write Pygame code for {component} module."
        )
    
    # Step 4: Assemble game
    game_code = generate_with_gpt(
        str(components),
        "Integrate these Pygame modules into a single runnable file."
    )
    
    # Step 5: Create Streamlit wrapper
    streamlit_code = generate_with_gpt(
        game_code,
        "Create a Streamlit app that embeds this Pygame code using stpygame."
    )
    
    return streamlit_code
```

### Streamlit Deployment
1. **Game Containerization:**
```python
# main.py
import streamlit as st
from stpygame import stpygame
import generated_game  # AI-created module

st.set_page_config(layout="wide")
st.title("AI-Generated Platformer")

if st.sidebar.button("Generate New Game"):
    with st.spinner("Creating your game..."):
        game_code = create_game(st.session_state.user_input)
        exec(game_code, globals())

if 'game_code' in st.session_state:
    stpygame(st.session_state.game_code)
```

2. **Run with:**
```bash
streamlit run main.py
```

### Key Features
1. **Dynamic Asset Generation:**
   - Use DALL-E for character/enemy sprites
   - Generate sound effects with Azure TTS

2. **Progressive Enhancement:**
   - Add levels through iterative prompts
   - Implement power-ups via chat suggestions

3. **Testing Framework:**
   - Automated collision tests
   - Playability score metrics

### Optimization Strategies
1. **Caching:** Store generated components to avoid redundant API calls
2. **Validation:** Add sanity checks for game physics before execution
3. **Modular Design:** Allow swapping game engines (PyGame, Arcade)

### Security Considerations
1. Sandbox code execution with `restrictedpython`
2. Validate generated code with AST parsing
3. Implement rate limiting for Azure API calls

This architecture creates a production-ready solution where:
1. Non-technical users can create games via natural language
2. Agents handle specialized development tasks
3. Streamlit provides instant playable interface
4. Azure GPT-4 ensures high-quality game generation
can you give em full code for each component also tell me how to do that where to code