Added app.py

app.py

@@ -0,0 +1,151 @@
+"""
+This file is the main file for the hackathon.
+It contains the Gradio interface for the hackathon as a MCP server.
+It exposes the following tools:
+- search_knowledge_base_for_context
+- research_write_review_topic
+
+"""
+from dotenv import load_dotenv
+load_dotenv()  # Load environment variables from .env file
+
+import logging
+
+# Configure logging to write to a file instead of stdout/stderr
+# This avoids interference with the MCP communication channel
+logging.basicConfig(
+    filename='hackathon-mcp.log',  # Log to a file instead of stdout/stderr
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+import gradio as gr
+from tools.rag_tools import search_groundx_for_rag_context
+from tools.multi_agent_workflow_for_research import run_research_workflow
+
+def search_knowledge_base_for_context(query: str) -> str:
+    """
+    Searches and retrieves relevant context from a knowledge base (GroundX),
+    based on the user's query.
+
+     Example queries:
+     - "What are the main features of fuel system of SU-35."
+     - "What are the combat potential of SU-35."
+
+    Args:
+        query: The search query supplied by the user.
+
+    Returns:
+        str: Relevant text content that can be used by the LLM to answer the query.
+    """
+    logger.info(f"Searching document for RAG context {query}")
+    response = search_groundx_for_rag_context(query)
+    logger.info(f"RAG Response: {response}")
+    return response
+
+def research_write_review_topic(query: str) -> str:
+    """
+    Helps with writing a report with research, writing, and review on any topic.
+    Returns a reviewed topic.
+
+    The query is a string that contains the topic to be researched and reviewed.
+
+    Example queries:
+    - "Write me a report on the history of the internet."
+    - "Write me a report on origin of the universe."
+    - "Write me a report on the impact of climate change on polar bears."
+    - "Write me a report on the benefits of meditation."
+    - "Write me a report on the future of artificial intelligence."
+    - "Write me a report on the effects of social media on mental health."
+
+    Args:
+        query (str): The query to research, write and review .
+
+    Returns:
+        str: A nicely formatted string.
+    """
+    try:
+        logger.info(f"Researching the topic: {query}")
+        result = run_research_workflow(query)
+        return result or "Research completed, but no content was generated."
+    except Exception as e:
+        return f"Error: {e}"
+
+with gr.Blocks() as server_info:
+    gr.Markdown("""
+    # MCP powered RAG and Research
+
+    I present to you a MCP powered RAG and Research.
+
+    RAG Tool uses GroundX service to fetch the knowledge base. The knowledge base is a document that contains information about the SU-35 aircraft, including its features, capabilities, and specifications.
+    Please check [this PDF](https://airgroup2000.com/gallery/albums/userpics/32438/SU-35_TM_eng.pdf) to formulate queries on Sukhoi.
+
+    The Research Tool is implemented using multi-agent workflow using LlamaIndex (ResearchAgent, WriteAgent, and ReviewAgent).
+
+    ## Available Tools
+
+    ### search_knowledge_base_for_context
+    - **Description**: Searches and retrieves relevant context from a knowledge base based on the user's query.
+    - **Example Queries**:
+        - "What are the main features of fuel system of SU-35."
+        - "What are the combat potential of SU-35."
+
+    ### research_write_review_topic
+    - **Description**: Helps with writing a report with research, writing, and review on any topic.
+    - **Example Queries**:
+        - "Write me a report on the history of the internet."
+        - "Write me a report on origin of the universe."
+        - "Write me a report on the impact of climate change on polar bears."
+
+    ## How to Use
+    - Use the MCP RAG Tool tab above to query the knowledge base.
+    - Use the Research Tool tab above to write report on any topic.
+
+    ## Demo Link
+    [Link to Demo on Youtube](https://www.youtube.com/mcp-rag-research)
+    """)
+
+mcp_rag_tool = gr.Interface(
+    fn=search_knowledge_base_for_context,
+    inputs=["text"],
+    outputs=[gr.Textbox(label="Knowledge Base", max_lines=10)],
+    title="MCP RAG Tool",
+    description="Searches and retrieves relevant context from a knowledge base"
+)
+
+research_tool = gr.Interface(
+    fn=research_write_review_topic,
+    inputs=["text"],
+    outputs=[gr.Textbox(label="Reviewed Topic", max_lines=10)],
+    title="Research Tool",
+    description="Helps with report writing with research, writing, and review agents on any topic. ",
+    concurrency_limit=10
+)
+
+named_interfaces = {
+    "Project Information": server_info,
+    "RAG - Tool": mcp_rag_tool,
+    "Research a Topic - Tool": research_tool
+}
+
+# Tab names and interfaces
+tab_names = list(named_interfaces.keys())
+interface_list = list(named_interfaces.values())
+
+mcp_server = gr.TabbedInterface(
+    interface_list,
+    tab_names=tab_names,
+    title="👁 MCP powered RAG and Research 🌍"
+)
+
+# Launch the MCP Server
+if __name__ == "__main__":
+    mcp_server.queue(default_concurrency_limit=10)
+    mcp_server.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        debug=False,
+        mcp_server=True
+    )