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Update app.py

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  1. app.py +3 -6
app.py CHANGED
@@ -7,11 +7,8 @@ It exposes the following tools:
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  """
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  import os
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- from dotenv import load_dotenv
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- load_dotenv() # Load environment variables
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-
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- import gradio as gr
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  import requests
 
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  def search_knowledge_base_for_context(query: str) -> str:
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  """
@@ -80,11 +77,11 @@ with gr.Blocks() as server_info:
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  # πŸ‘ MCP Powered RAG and Research Topic 🌍
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  I present to you an MCP-powered RAG and Research Topic.
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- The Tools are hosted and executed on **Modal Labs**.
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  RAG Tool uses the **GroundX** storage by **eyelevel.ai** 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.
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- The Research Tool is implemented using a multi-agent workflow using **LlamaIndex**.
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  <br>
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  The Agents use **Nebius** provided LLM.
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  """
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  import os
 
 
 
 
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  import requests
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+ import gradio as gr
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  def search_knowledge_base_for_context(query: str) -> str:
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  """
 
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  # πŸ‘ MCP Powered RAG and Research Topic 🌍
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  I present to you an MCP-powered RAG and Research Topic.
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+ The Tools are hosted and executed on **Modal Labs** platform.
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  RAG Tool uses the **GroundX** storage by **eyelevel.ai** 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.
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+ The Research Tool is implemented using a Multi-Agent Workflow using **LlamaIndex**.
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  <br>
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  The Agents use **Nebius** provided LLM.
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