Update app.py

app.py

@@ -10,14 +10,155 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+import os
+
+from typing import TypedDict, Annotated
+
+from duckduckgo_search import DDGS
+
+from langchain.tools import tool
+from langchain_core.messages import AnyMessage, HumanMessage
+from langgraph.graph import START, StateGraph
+from langgraph.graph.message import add_messages
+from langgraph.prebuilt import ToolNode, tools_condition
+
+from langchain_huggingface import (
+    HuggingFaceEndpoint,
+    ChatHuggingFace,
+)
+
+# =====================================================
+# HF TOKEN FROM SPACE SECRET
+# =====================================================
+
+HF_TOKEN = os.environ["HF_TOKEN"]
+
+# =====================================================
+# WEB SEARCH TOOL
+# =====================================================
+
+@tool
+def web_search(query: str) -> str:
+    """
+    Search the web and return useful snippets.
+    """
+
+    try:
+        with DDGS() as ddgs:
+            results = list(ddgs.text(query, max_results=5))
+
+        if not results:
+            return "No results found."
+
+        output = []
+
+        for r in results:
+            output.append(
+                f"""
+Title: {r.get("title","")}
+Snippet: {r.get("body","")}
+URL: {r.get("href","")}
+"""
+            )
+
+        return "\n".join(output)
+
+    except Exception as e:
+        return f"Search error: {e}"
+
+
+# =====================================================
+# LLM
+# =====================================================
+
+llm = HuggingFaceEndpoint(
+    repo_id="Qwen/Qwen2.5-Coder-32B-Instruct",
+    huggingfacehub_api_token=HF_TOKEN,
+    temperature=0.0,
+    max_new_tokens=1024,
+)
+
+chat = ChatHuggingFace(
+    llm=llm,
+    verbose=False,
+)
+
+tools = [web_search]
+
+chat_with_tools = chat.bind_tools(tools)
+
+# =====================================================
+# STATE
+# =====================================================
+
+class AgentState(TypedDict):
+    messages: Annotated[list[AnyMessage], add_messages]
+
+# =====================================================
+# ASSISTANT NODE
+# =====================================================
+
+def assistant(state: AgentState):
+
+    response = chat_with_tools.invoke(
+        state["messages"]
+    )
+
+    return {
+        "messages": [response]
+    }
+
+# =====================================================
+# GRAPH
+# =====================================================
+
+builder = StateGraph(AgentState)
+
+builder.add_node("assistant", assistant)
+builder.add_node("tools", ToolNode(tools))
+
+builder.add_edge(START, "assistant")
+
+builder.add_conditional_edges(
+    "assistant",
+    tools_condition
+)
+
+builder.add_edge(
+    "tools",
+    "assistant"
+)
+
+graph = builder.compile()
+
+# =====================================================
+# BASIC AGENT FOR HF COURSE
+# =====================================================
+
 class BasicAgent:
+
     def __init__(self):
-        print("BasicAgent initialized.")
+        self.graph = graph
+
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+
+        try:
+
+            result = self.graph.invoke(
+                {
+                    "messages": [
+                        HumanMessage(content=question)
+                    ]
+                },
+                config={
+                    "recursion_limit": 10
+                }
+            )
+
+            return result["messages"][-1].content
+
+        except Exception as e:
+            return f"Agent error: {e}"
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """