Create agent.py

agent.py

@@ -0,0 +1,54 @@
+# agent.py
+
+import os
+from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+from llama_index.core.agent.workflow import AgentWorkflow, ReActAgent
+from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec
+from llama_index.core.tools import FunctionTool
+
+class BasicAgent:
+    def __init__(self):
+        print("Initializing BasicAgent...")
+
+        # Define tools
+        def add(a: int, b: int) -> int:
+            return a + b
+
+        def multiply(a: int, b: int) -> int:
+            return a * b
+
+        add_tool = FunctionTool.from_defaults(fn=add)
+        multiply_tool = FunctionTool.from_defaults(fn=multiply)
+
+        # Load web search tool
+        tool_spec = DuckDuckGoSearchToolSpec()
+        search_tools = tool_spec.to_tool_list()
+
+        all_tools = [add_tool, multiply_tool] + search_tools
+
+        # Load LLM
+        hf_token = os.getenv("HF_TOKEN")
+        self.llm = HuggingFaceInferenceAPI(
+            model_name="Qwen/Qwen2.5-Coder-32B-Instruct",
+            token=hf_token,
+        )
+
+        # Create the agent
+        self.agent = ReActAgent(
+            name="universal_agent",
+            description="An assistant that can search the web and do math.",
+            system_prompt="You are a helpful assistant with access to tools.",
+            tools=all_tools,
+            llm=self.llm,
+        )
+
+        # Setup workflow
+        self.workflow = AgentWorkflow(
+            agents=[self.agent],
+            root_agent="universal_agent",
+        )
+
+    async def __call__(self, question: str) -> str:
+        print(f"[BasicAgent] Received question: {question}")
+        response = await self.workflow.run(user_msg=question)
+        return str(response)