name of the agent changed

.python-version

@@ -1 +1 @@
-3.13
+3.11

README.md

@@ -1,6 +1,6 @@
 ---
-title: Agent Chatbot Demo
-emoji: 🔥
+title: LlamaIndex Report Generation Agent
+emoji: 🤖
 colorFrom: blue
 colorTo: blue
 sdk: gradio
@@ -9,7 +9,11 @@ app_file: app.py
 pinned: false
 license: apache-2.0
 python_version: "3.13.3"
-short_description: Demo Template for Agentic Chatbot
+short_description: LlamaIndex-based report generation agent using teacher-student methodology
 ---
 
+# LlamaIndex Report Generation Agent
+
+A multi-agent workflow built with LlamaIndex that uses teacher-student methodology to generate comprehensive reports. The system employs three specialized agents (Research, Write, Review) that collaborate to research topics, write reports, and ensure quality through iterative feedback.
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

agent.py

@@ -10,7 +10,7 @@ from llama_index.core.workflow import Context
 
 load_dotenv(os.path.join(os.path.dirname(__file__), 'env.local'))
 
-class TeacherStudentAgentWorkflow:
+class LlamaIndexReportAgent:
     def __init__(self):
         self.llm = HuggingFaceInferenceAPI(
             model_name="microsoft/Phi-3.5-mini-instruct",
@@ -167,7 +167,7 @@ class TeacherStudentAgentWorkflow:
 
 if __name__ == "__main__":
     import asyncio
-    agent = TeacherStudentAgentWorkflow()
+    agent = LlamaIndexReportAgent()
     user_msg = input("Enter the topic or instructions for the report (leave blank for default): ").strip()
     if not user_msg:
         user_msg = None

app.py

@@ -4,7 +4,7 @@ import asyncio
 import json
 import hashlib
 from datetime import datetime
-from agent import TeacherStudentAgentWorkflow
+from agent import LlamaIndexReportAgent
 from tools.simple_tools import get_workflow_state
 from llama_index.core.agent.workflow import (
     AgentInput,
@@ -21,7 +21,7 @@ agent_workflow = None
 def get_agent_workflow():
     global agent_workflow
     if agent_workflow is None:
-        agent_workflow = TeacherStudentAgentWorkflow()
+        agent_workflow = LlamaIndexReportAgent()
     return agent_workflow
 
 async def chat_with_agent(message, history):
@@ -199,16 +199,16 @@ def format_structured_report_display(structured_report_data):
     )
 
 # Create the Gradio interface
-with gr.Blocks(title="Teacher-Student Agent Workflow", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="LlamaIndex Report Generation Agent", theme=gr.themes.Soft()) as demo:
     gr.Markdown("""
-    # 🤖 Teacher-Student Agent Workflow
+    # 🤖 LlamaIndex Report Generation Agent
     
-    This demo showcases a multi-agent workflow with three specialized agents:
-    - **ResearchAgent**: Searches the web and records notes
-    - **WriteAgent**: Writes reports based on research
-    - **ReviewAgent**: Reviews and provides feedback on reports
+    A multi-agent workflow built with LlamaIndex that uses teacher-student methodology to generate comprehensive reports. The system employs three specialized agents that collaborate step by step:
+    - **ResearchAgent**: Searches the web and records research notes
+    - **WriteAgent**: Creates structured reports based on research findings
+    - **ReviewAgent**: Reviews reports and provides iterative feedback for improvement
     
-    Enter a topic or request below to see the agents collaborate step by step!
+    Enter any topic below to see the LlamaIndex agents collaborate using teacher-student methodology!
     """)
     
     chatbot = gr.Chatbot(
@@ -250,13 +250,13 @@ with gr.Blocks(title="Teacher-Student Agent Workflow", theme=gr.themes.Soft()) a
     )
     
     gr.Markdown("""
-    ### How it works:
-    1. **ResearchAgent** searches for information and takes notes
-    2. **WriteAgent** creates a report based on the research
-    3. **ReviewAgent** reviews the report and provides feedback
-    4. The process continues until the report is approved
+    ### How the LlamaIndex Teacher-Student Agent Works:
+    1. **ResearchAgent** searches for information and takes comprehensive notes
+    2. **WriteAgent** creates a structured report based on the research findings
+    3. **ReviewAgent** reviews the report and provides constructive feedback
+    4. The process iterates until the report meets quality standards
     
-    Watch the real-time collaboration between agents as they work together!
+    Watch the real-time collaboration between LlamaIndex agents as they employ teacher-student methodology!
     """)
 
     # Event handlers

pyproject.toml

@@ -3,7 +3,7 @@ name = "teacher-student-agent"
 version = "0.1.0"
 description = "Add your description here"
 readme = "README.md"
-requires-python = ">=3.13"
+requires-python = ">=3.11,<3.12"
 dependencies = [
     "asyncio>=3.4.3",
     "dotenv>=0.9.9",
@@ -12,3 +12,8 @@ dependencies = [
     "llama-index-llms-huggingface-api>=0.5.0",
     "tavily-python>=0.7.5",
 ]
+
+[tool.uv]
+# Configure uv for faster builds in cloud environments
+no-cache = true
+index-strategy = "unsafe-best-match"

runtime.txt

@@ -0,0 +1 @@
+python-3.11.10