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+
diff --git a/ai_agent_tutorials/ai_3dpygame_r1/README.md b/ai_agent_tutorials/ai_3dpygame_r1/README.md
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+## 🎮 AI 3D PyGame Visualizer with R1
+This Project demonstrates R1's code capabilities with a PyGame code generator and visualizer with browser use. The system uses DeepSeek for reasoning, OpenAI for code extraction, and browser automation agents to visualize the code on Trinket.io.
+
+### Features
+
+- Generates PyGame code from natural language descriptions
+- Uses DeepSeek Reasoner for code logic and explanation
+- Extracts clean code using OpenAI GPT-4o
+- Automates code visualization on Trinket.io using browser agents
+- Provides a streamlined Streamlit interface
+- Multi-agent system for handling different tasks (navigation, coding, execution, viewing)
+
+### How to get Started?
+
+1. Clone the GitHub repository
+```bash
+git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+cd awesome-llm-apps/ai_agent_tutorials/ai_3dpygame_r1
+```
+
+2. Install the required dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+3. Get your API Keys
+- Sign up for [DeepSeek](https://platform.deepseek.com/) and obtain your API key
+- Sign up for [OpenAI](https://platform.openai.com/) and obtain your API key
+
+4. Run the AI PyGame Visualizer
+```bash
+streamlit run ai_3dpygame_r1.py
+```
+
+5. Browser use automatically opens your web browser and navigate to the URL provided in the console output to interact with the PyGame generator.
+
+### How it works?
+
+1. **Query Processing:** User enters a natural language description of the desired PyGame visualization.
+2. **Code Generation:** 
+   - DeepSeek Reasoner analyzes the query and provides detailed reasoning with code
+   - OpenAI agent extracts clean, executable code from the reasoning
+3. **Visualization:**
+   - Browser agents automate the process of running code on Trinket.io
+   - Multiple specialized agents handle different tasks:
+     - Navigation to Trinket.io
+     - Code input
+     - Execution
+     - Visualization viewing
+4. **User Interface:** Streamlit provides an intuitive interface for entering queries, viewing code, and managing the visualization process.
diff --git a/ai_agent_tutorials/ai_3dpygame_r1/ai_3dpygame_r1.py b/ai_agent_tutorials/ai_3dpygame_r1/ai_3dpygame_r1.py
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+import streamlit as st
+from openai import OpenAI
+from agno.agent import Agent as AgnoAgent
+from agno.models.openai import OpenAIChat as AgnoOpenAIChat
+from langchain_openai import ChatOpenAI 
+import asyncio
+from browser_use import Browser
+
+st.set_page_config(page_title="PyGame Code Generator", layout="wide")
+
+# Initialize session state
+if "api_keys" not in st.session_state:
+    st.session_state.api_keys = {
+        "deepseek": "",
+        "openai": ""
+    }
+
+# Streamlit sidebar for API keys
+with st.sidebar:
+    st.title("API Keys Configuration")
+    st.session_state.api_keys["deepseek"] = st.text_input(
+        "DeepSeek API Key",
+        type="password",
+        value=st.session_state.api_keys["deepseek"]
+    )
+    st.session_state.api_keys["openai"] = st.text_input(
+        "OpenAI API Key",
+        type="password",
+        value=st.session_state.api_keys["openai"]
+    )
+    
+    st.markdown("---")
+    st.info("""
+    📝 How to use:
+    1. Enter your API keys above
+    2. Write your PyGame visualization query
+    3. Click 'Generate Code' to get the code
+    4. Click 'Generate Visualization' to:
+       - Open Trinket.io PyGame editor
+       - Copy and paste the generated code
+       - Watch it run automatically
+    """)
+
+# Main UI
+st.title("AI 3D Visualizer with R1")
+example_query = "Create a particle system simulation where 100 particles emit from the mouse position and respond to keyboard-controlled wind forces"
+query = st.text_area(
+    "Enter your PyGame query:",
+    height=70,
+    placeholder=f"e.g.: {example_query}"
+)
+
+# Split the buttons into columns
+col1, col2 = st.columns(2)
+generate_code_btn = col1.button("Generate Code")
+generate_vis_btn = col2.button("Generate Visualization")
+
+if generate_code_btn and query:
+    if not st.session_state.api_keys["deepseek"] or not st.session_state.api_keys["openai"]:
+        st.error("Please provide both API keys in the sidebar")
+        st.stop()
+
+    # Initialize Deepseek client
+    deepseek_client = OpenAI(
+        api_key=st.session_state.api_keys["deepseek"],
+        base_url="https://api.deepseek.com"
+    )
+
+    system_prompt = """You are a Pygame and Python Expert that specializes in making games and visualisation through pygame and python programming. 
+    During your reasoning and thinking, include clear, concise, and well-formatted Python code in your reasoning. 
+    Always include explanations for the code you provide."""
+
+    try:
+        # Get reasoning from Deepseek
+        with st.spinner("Generating solution..."):
+            deepseek_response = deepseek_client.chat.completions.create(
+                model="deepseek-reasoner",
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": query}
+                ],
+                max_tokens=1  
+            )
+
+        reasoning_content = deepseek_response.choices[0].message.reasoning_content
+        print("\nDeepseek Reasoning:\n", reasoning_content)
+        with st.expander("R1's Reasoning"):      
+            st.write(reasoning_content)
+
+        # Initialize Claude agent (using PhiAgent)
+        openai_agent = AgnoAgent(
+            model=AgnoOpenAIChat(
+                id="gpt-4o",
+                api_key=st.session_state.api_keys["openai"]
+            ),
+            show_tool_calls=True,
+            markdown=True
+        )
+
+        # Extract code
+        extraction_prompt = f"""Extract ONLY the Python code from the following content which is reasoning of a particular query to make a pygame script. 
+        Return nothing but the raw code without any explanations, or markdown backticks:
+        {reasoning_content}"""
+
+        with st.spinner("Extracting code..."):
+            code_response = openai_agent.run(extraction_prompt)
+            extracted_code = code_response.content
+
+        # Store the generated code in session state
+        st.session_state.generated_code = extracted_code
+        
+        # Display the code
+        with st.expander("Generated PyGame Code", expanded=True):      
+            st.code(extracted_code, language="python")
+            
+        st.success("Code generated successfully! Click 'Generate Visualization' to run it.")
+
+    except Exception as e:
+        st.error(f"An error occurred: {str(e)}")
+
+elif generate_vis_btn:
+    if "generated_code" not in st.session_state:
+        st.warning("Please generate code first before visualization")
+    else:
+        async def run_pygame_on_trinket(code: str) -> None:
+            browser = Browser()
+            from browser_use import Agent 
+            async with await browser.new_context() as context:
+                model = ChatOpenAI(
+                    model="gpt-4o", 
+                    api_key=st.session_state.api_keys["openai"]
+                )
+                
+                agent1 = Agent(
+                    task='Go to https://trinket.io/features/pygame, thats your only job.',
+                    llm=model,
+                    browser_context=context,
+                )
+                
+                executor = Agent(
+                    task='Executor. Execute the code written by the User by clicking on the run button on the right. ',
+                    llm=model,
+                    browser_context=context
+                )
+
+                coder = Agent(
+                    task='Coder. Your job is to wait for the user for 10 seconds to write the code in the code editor.',
+                    llm=model,
+                    browser_context=context
+                )
+                
+                viewer = Agent(
+                    task='Viewer. Your job is to just view the pygame window for 10 seconds.',
+                    llm=model,
+                    browser_context=context,
+                )
+
+                with st.spinner("Running code on Trinket..."):
+                    try:
+                        await agent1.run()
+                        await coder.run()
+                        await executor.run()
+                        await viewer.run()
+                        st.success("Code is running on Trinket!")
+                    except Exception as e:
+                        st.error(f"Error running code on Trinket: {str(e)}")
+                        st.info("You can still copy the code above and run it manually on Trinket")
+
+        # Run the async function with the stored code
+        asyncio.run(run_pygame_on_trinket(st.session_state.generated_code))
+
+elif generate_code_btn and not query:
+    st.warning("Please enter a query before generating code")
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diff --git a/ai_agent_tutorials/ai_3dpygame_r1/requirements.txt b/ai_agent_tutorials/ai_3dpygame_r1/requirements.txt
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+agno
+langchain-openai
+browser-use
+streamlit
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