diff --git a/advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent/README.md b/advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent/README.md
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+# 🔍 AI Domain Deep Research Agent
+
+An advanced AI research agent built using the Agno Agent framework, Together AI's Qwen model, and Composio tools. This agent helps users conduct comprehensive research on any topic by generating research questions, finding answers through multiple search engines, and compiling professional reports with Google Docs integration.
+
+## Features
+
+- 🧠 **Intelligent Question Generation**:
+
+  - Automatically generates 5 specific research questions about your topic
+  - Tailors questions to your specified domain
+  - Focuses on creating yes/no questions for clear research outcomes
+- 🔎 **Multi-Source Research**:
+
+  - Uses Tavily Search for comprehensive web results
+  - Leverages Perplexity AI for deeper analysis
+  - Combines multiple sources for thorough research
+- 📊 **Professional Report Generation**:
+
+  - Compiles research findings into a McKinsey-style report
+  - Structures content with executive summary, analysis, and conclusion
+  - Creates a Google Doc with the complete report
+- 🖥️ **User-Friendly Interface**:
+
+  - Clean Streamlit UI with intuitive workflow
+  - Real-time progress tracking
+  - Expandable sections to view detailed results
+
+## How to Run
+
+1. **Setup Environment**
+
+   ```bash
+   # Clone the repository
+   git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+   cd advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent
+
+   # Install dependencies
+   pip install -r requirements.txt
+
+   composio add googledocs
+   composio add perplexityai
+   ```
+2. **Configure API Keys**
+
+   - Get Together AI API key from [Together AI](https://together.ai)
+   - Get Composio API key from [Composio](https://composio.ai)
+   - Add these to a `.env` file or enter them in the app sidebar
+3. **Run the Application**
+
+   ```bash
+   streamlit run ai_domain_deep_research_agent.py
+   ```
+
+## Usage
+
+1. Launch the application using the command above
+2. Enter your Together AI and Composio API keys in the sidebar
+3. Input your research topic and domain in the main interface
+4. Click "Generate Research Questions" to create specific questions
+5. Review the questions and click "Start Research" to begin the research process
+6. Once research is complete, click "Compile Final Report" to generate a professional report
+7. View the report in the app and access it in Google Docs
+
+## Technical Details
+
+- **Agno Framework**: Used for creating and orchestrating AI agents
+- **Together AI**: Provides the Qwen 3 235B model for advanced language processing
+- **Composio Tools**: Integrates search engines and Google Docs functionality
+- **Streamlit**: Powers the user interface with interactive elements
+
+## Example Use Cases
+
+- **Academic Research**: Quickly gather information on academic topics across various disciplines
+- **Market Analysis**: Research market trends, competitors, and industry developments
+- **Policy Research**: Analyze policy implications and historical context
+- **Technology Evaluation**: Research emerging technologies and their potential impact
+
+## Dependencies
+
+- agno
+- composio_agno
+- streamlit
+- python-dotenv
+
+## License
+
+This project is part of the awesome-llm-apps collection and is available under the MIT License.
diff --git a/advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent/ai_domain_deep_research_agent.py b/advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent/ai_domain_deep_research_agent.py
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+++ b/advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent/ai_domain_deep_research_agent.py
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+import os
+import asyncio
+import streamlit as st
+from dotenv import load_dotenv
+from agno.agent import Agent
+from composio_agno import ComposioToolSet, Action
+from agno.models.together import Together
+
+# Load environment variables
+load_dotenv()
+
+# Set page config
+st.set_page_config(
+    page_title="AI DeepResearch Agent",
+    page_icon="🔍",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Sidebar for API keys
+st.sidebar.header("⚙️ Configuration")
+
+# API key inputs
+together_api_key = st.sidebar.text_input(
+    "Together AI API Key", 
+    value=os.getenv("TOGETHER_API_KEY", ""),
+    type="password",
+    help="Get your API key from https://together.ai"
+)
+
+composio_api_key = st.sidebar.text_input(
+    "Composio API Key", 
+    value=os.getenv("COMPOSIO_API_KEY", ""),
+    type="password",
+    help="Get your API key from https://composio.ai"
+)
+
+# Sidebar info
+st.sidebar.markdown("---")
+st.sidebar.markdown("### About")
+st.sidebar.info(
+    "This AI DeepResearch Agent uses Together AI's Qwen model and Composio tools to perform comprehensive research on any topic. "
+    "It generates research questions, finds answers, and compiles a professional report."
+)
+
+st.sidebar.markdown("### Tools Used")
+st.sidebar.markdown("- 🔍 Tavily Search")
+st.sidebar.markdown("- 🧠 Perplexity AI")
+st.sidebar.markdown("- 📄 Google Docs Integration")
+
+# Initialize session state
+if 'questions' not in st.session_state:
+    st.session_state.questions = []
+if 'question_answers' not in st.session_state:
+    st.session_state.question_answers = []
+if 'report_content' not in st.session_state:
+    st.session_state.report_content = ""
+if 'research_complete' not in st.session_state:
+    st.session_state.research_complete = False
+
+# Main content
+st.title("🔍 AI DeepResearch Agent with Agno and Composio")
+
+# Function to initialize the LLM and tools
+def initialize_agents(together_key, composio_key):
+    # Initialize Together AI LLM
+    llm = Together(id="Qwen/Qwen3-235B-A22B-fp8-tput", api_key=together_key)
+    
+    # Set up Composio tools
+    toolset = ComposioToolSet(api_key=composio_key)
+    composio_tools = toolset.get_tools(actions=[
+        Action.COMPOSIO_SEARCH_TAVILY_SEARCH, 
+        Action.PERPLEXITYAI_PERPLEXITY_AI_SEARCH, 
+        Action.GOOGLEDOCS_CREATE_DOCUMENT_MARKDOWN
+    ])
+    
+    return llm, composio_tools
+
+# Function to create agents
+def create_agents(llm, composio_tools):
+    # Create the question generator agent
+    question_generator = Agent(
+        name="Question Generator",
+        model=llm,
+        instructions="""
+        You are an expert at breaking down research topics into specific questions.
+        Generate exactly 5 specific yes/no research questions about the given topic in the specified domain.
+        Respond ONLY with the text of the 5 questions formatted as a numbered list, and NOTHING ELSE.
+        """
+    )
+    
+    return question_generator
+
+# Function to extract questions after think tag
+def extract_questions_after_think(text):
+    if "</think>" in text:
+        return text.split("</think>", 1)[1].strip()
+    return text.strip()
+
+# Function to generate research questions
+def generate_questions(llm, composio_tools, topic, domain):
+    question_generator = create_agents(llm, composio_tools)
+    
+    with st.spinner("🤖 Generating research questions..."):
+        questions_task = question_generator.run(
+            f"Generate exactly 5 specific yes/no research questions about the topic '{topic}' in the domain '{domain}'."
+        )
+        questions_text = questions_task.content
+        questions_only = extract_questions_after_think(questions_text)
+        
+        # Extract questions into a list
+        questions_list = [q.strip() for q in questions_only.split('\n') if q.strip()]
+        st.session_state.questions = questions_list
+        return questions_list
+
+# Function to research a specific question
+def research_question(llm, composio_tools, topic, domain, question):
+    research_task = Agent(
+        model=llm,
+        tools=[composio_tools],
+        instructions=f"You are a sophisticated research assistant. Answer the following research question about the topic '{topic}' in the domain '{domain}':\n\n{question}\n\nUse the PERPLEXITYAI_PERPLEXITY_AI_SEARCH and COMPOSIO_SEARCH_TAVILY_SEARCH tools to provide a concise, well-sourced answer."
+    )
+    
+    research_result = research_task.run()
+    return research_result.content
+
+# Function to compile final report
+def compile_report(llm, composio_tools, topic, domain, question_answers):
+    with st.spinner("📝 Compiling final report and creating Google Doc..."):
+        qa_sections = "\n".join(
+            f"<h2>{idx+1}. {qa['question']}</h2>\n<p>{qa['answer']}</p>" 
+            for idx, qa in enumerate(question_answers)
+        )
+        
+        compile_report_task = Agent(
+            name="Report Compiler",
+            model=llm,
+            tools=[composio_tools],
+            instructions=f"""
+            You are a sophisticated research assistant. Compile the following research findings into a professional, McKinsey-style report. The report should be structured as follows:
+
+            1. Executive Summary/Introduction: Briefly introduce the topic and domain, and summarize the key findings.
+            2. Research Analysis: For each research question, create a section with a clear heading and provide a detailed, analytical answer. Do NOT use a Q&A format; instead, weave the answer into a narrative and analytical style.
+            3. Conclusion/Implications: Summarize the overall insights and implications of the research.
+
+            Use clear, structured HTML for the report.
+
+            Topic: {topic}
+            Domain: {domain}
+
+            Research Questions and Findings (for your reference):
+            {qa_sections}
+
+            Use the GOOGLEDOCS_CREATE_DOCUMENT_MARKDOWN tool to create a Google Doc with the report. The text should be in HTML format. You have to create the google document with all the compiled info. You have to do it.
+            """
+        )
+        
+        compile_result = compile_report_task.run()
+        st.session_state.report_content = compile_result.content
+        st.session_state.research_complete = True
+        return compile_result.content
+
+# Main application flow
+if together_api_key and composio_api_key:
+    # Initialize agents
+    llm, composio_tools = initialize_agents(together_api_key, composio_api_key)
+    
+    # Main content area
+    st.header("Research Topic")
+    
+    # Input fields
+    col1, col2 = st.columns(2)
+    with col1:
+        topic = st.text_input("What topic would you like to research?", placeholder="American Tariffs")
+    with col2:
+        domain = st.text_input("What domain is this topic in?", placeholder="Politics, Economics, Technology, etc.")
+    
+    # Generate questions section
+    if topic and domain and st.button("Generate Research Questions", key="generate_questions"):
+        # Generate questions
+        questions = generate_questions(llm, composio_tools, topic, domain)
+        
+        # Display the generated questions
+        st.header("Research Questions")
+        for i, question in enumerate(questions):
+            st.markdown(f"**{i+1}. {question}**")
+    
+    # Research section - only show if we have questions
+    if st.session_state.questions and st.button("Start Research", key="start_research"):
+        st.header("Research Results")
+        
+        # Reset answers
+        question_answers = []
+        
+        # Research each question
+        progress_bar = st.progress(0)
+        
+        for i, question in enumerate(st.session_state.questions):
+            # Update progress
+            progress_bar.progress((i) / len(st.session_state.questions))
+            
+            # Research the question
+            with st.spinner(f"🔍 Researching question {i+1}..."):
+                answer = research_question(llm, composio_tools, topic, domain, question)
+                question_answers.append({"question": question, "answer": answer})
+            
+            # Display the answer
+            st.subheader(f"Question {i+1}:")
+            st.markdown(f"**{question}**")
+            st.markdown(answer)
+            
+            # Update progress again
+            progress_bar.progress((i + 1) / len(st.session_state.questions))
+        
+        # Store the answers
+        st.session_state.question_answers = question_answers
+        
+        # Compile report button
+        if st.button("Compile Final Report", key="compile_report"):
+            report_content = compile_report(llm, composio_tools, topic, domain, question_answers)
+            
+            # Display the report content
+            st.header("Final Report")
+            st.success("Your report has been compiled and a Google Doc has been created.")
+            
+            # Show the full report content
+            with st.expander("View Full Report Content", expanded=True):
+                st.markdown(report_content)
+    
+    # Display previous results if available
+    if len(st.session_state.question_answers) > 0 and not st.session_state.research_complete:
+        st.header("Previous Research Results")
+        
+        # Display research results
+        for i, qa in enumerate(st.session_state.question_answers):
+            with st.expander(f"Question {i+1}: {qa['question']}"):
+                st.markdown(qa['answer'])
+    
+    # Display final report if available
+    if st.session_state.research_complete and st.session_state.report_content:
+        st.header("Final Report")
+        
+        # Display the report content
+        st.success("Your report has been compiled and a Google Doc has been created.")
+        
+        # Show the full report content
+        with st.expander("View Full Report Content", expanded=True):
+            st.markdown(st.session_state.report_content)
+
+else:
+    # API keys not provided
+    st.warning("⚠️ Please enter your Together AI and Composio API keys in the sidebar to get started.")
+    
+    # Example UI
+    st.header("How It Works")
+    
+    col1, col2, col3 = st.columns(3)
+    with col1:
+        st.subheader("1️⃣ Define Topic")
+        st.write("Enter your research topic and domain to begin the research process.")
+    
+    with col2:
+        st.subheader("2️⃣ Generate Questions")
+        st.write("The AI generates specific research questions to explore your topic in depth.")
+        
+    with col3:
+        st.subheader("3️⃣ Compile Report")
+        st.write("Research findings are compiled into a professional report and saved to Google Docs.")
diff --git a/advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent/requirements.txt b/advanced_ai_agents/single_agent_apps/ai_domain_deep_research_agent/requirements.txt
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+composio
+agno
+streamlit
+composio-agno
+together
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