react agent in react agent

agents.py

@@ -3,9 +3,67 @@ from llama_index.core.agent.workflow import AgentWorkflow
 from llama_index.llms.openai import OpenAI
 from tools import (image_analyzer_tool, youtube_transcript_tool, calculator_tool, read_document_tool, search_tool)
 from llama_index.core.workflow import (Workflow, Context, step, Context, StartEvent, StopEvent, Event)
+from llama_index.core.agent import ReActAgent
 from dotenv import load_dotenv
 load_dotenv()
 
+# Alfred React Agent
+class AlfredReactAgent(ReActAgent):
+     def __init__(self, llm:OpenAI):
+          tools = [image_analyzer_tool, youtube_transcript_tool, calculator_tool, read_document_tool, search_tool]
+          system_prompt = """You are a helpful assistant that answers questions concisely.
+
+CRITICAL RULES:
+1. Answer with THE MINIMUM words possible
+2. For "how many" questions → just the number
+3. For "what is the name" → just the name
+4. For calculations → just the result
+5. Use tools ONLY when absolutely necessary
+6. After using a tool ONCE, provide answer and STOP
+7. If you can't find answer after ONE tool use, say "Unable to find" and STOP
+
+EXAMPLES:
+Q: "Capital of Japan?" 
+A: "Tokyo"
+
+Q: "20 * 20?"
+A: "400"
+
+Q: "Surname of X?"
+A: "Murakami"
+
+Q: "What video shows X?"
+Use youtube_transcript → "quote from video"
+
+Q: "Total from file.xlsx?"
+Use read_document → "$1234.56"
+
+BE EXTREMELY CONCISE. No explanations."""
+
+
+
+
+          self.agent = ReActAgent.from_tools(
+                tools,
+                llm = llm, 
+                verbose = False,
+                max_iterations = 8,
+                system_prompt = system_prompt    
+           )
+          
+          async def run(self, question: str) -> str:
+               try:
+                    response = await self.agent.achat(question)
+                    return str(response)
+               except Exception as e:
+                    return f"Error: {str(e)}"
+          
+
+
+
+
+
+
 # Events
 class RouteEvent(Event):
     question: str