Initial version of agent with math and search tools

.gitignore

@@ -0,0 +1 @@
+.env

.python-version

@@ -0,0 +1 @@
+3.12

agent.py

@@ -0,0 +1,52 @@
+import os
+from dotenv import load_dotenv
+from langgraph.graph import START, StateGraph, MessagesState
+from langgraph.prebuilt import tools_condition
+from langgraph.prebuilt import ToolNode
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_core.messages import SystemMessage, HumanMessage
+from langchain_core.tools import tool
+from tools.math_tools import add, subtract, multiply, divide, modulus, power, sqrt
+from tools.search_tools import search_wikipedia, web_search
+
+load_dotenv()
+
+def build_graph():
+
+    llm = ChatGoogleGenerativeAI(
+        model="gemini-2.0-flash-001",
+        temperature=0.8,
+        max_tokens=None,
+        timeout=None,
+        max_retries=2,
+        )
+    tools = [add, subtract, multiply, divide, modulus, power, sqrt, web_search, search_wikipedia]
+
+    llm_with_tools = llm.bind_tools(tools)
+
+    def assistant(state: MessagesState):
+        """Assistant node for invoking the LLM."""
+        return {"messages": [llm_with_tools.invoke(state["messages"])]}
+
+    builder = StateGraph(MessagesState)
+    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")
+
+    # Compile graph
+    return builder.compile()
+
+if __name__ == "__main__":
+    question = "Give me a summary of the wikipedia page for photosynthesis"
+    # Build the graph
+    graph = build_graph()
+    # Run the graph
+    messages = [HumanMessage(content=question)]
+    messages = graph.invoke({"messages": messages})
+    for m in messages["messages"]:
+        m.pretty_print()

app.py

@@ -3,6 +3,8 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from langchain_core.messages import HumanMessage
+from agent import build_graph
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -12,12 +14,29 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
+        self.graph = build_graph()
         print("BasicAgent initialized.")
     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
+        messages = [HumanMessage(content=question)]
+        try:
+            result = self.graph.invoke({"messages": messages})
+
+            if not result.get("messages") or len(result["messages"]) == 0:
+                raise ValueError("No messages returned from the graph")
+
+            last_message = result["messages"][-1].content
+
+            if "final answer" in last_message.lower():
+                split_final_answer = last_message.lower().split("final answer")
+                final_answer = split_final_answer[1].strip()
+            else:
+                final_answer = last_message
+            return final_answer
+        except Exception as e: 
+            print("Agent processing failed")
+            return
+            
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """

main.py

@@ -0,0 +1,6 @@
+def main():
+    print("Hello from final-assignment-template!")
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

@@ -0,0 +1,17 @@
+[project]
+name = "final-assignment-template"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "dotenv>=0.9.9",
+    "gradio>=5.29.0",
+    "langchain-community>=0.3.23",
+    "langchain-core>=0.3.59",
+    "langchain-google-genai>=2.1.4",
+    "langgraph>=0.4.3",
+    "pandas>=2.2.3",
+    "requests>=2.32.3",
+    "wikipedia>=1.4.0",
+]

tools/math_tools.py

@@ -0,0 +1,85 @@
+"""This module contains tools for performing mathematical operations."""
+from langchain_core.tools import tool
+
+@tool
+def add(x: float, y: float) -> float:
+    """
+    Adds two numbers.
+
+    Args: 
+        x (float): the first number
+        y (float): the second number
+    """
+    return x + y
+
+@tool
+def subtract(x: float, y: float) -> float:
+    """
+    Subtracts two numbers.
+
+    Args:
+        x (float): the first number 
+        y (float): the second number
+    """
+    return x - y
+
+@tool
+def multiply(x: float, y: float) -> float:
+    """
+    Multiplies two numbers.
+
+    Args:
+        x (float): the first number
+        y (float): the second number
+    """
+    return x * y
+
+@tool
+def divide(x: float, y: float) -> float:
+    """
+    Divides two numbers.
+
+    Args:
+        x (float): the first number
+        y (float): the second number to divide by
+    """
+    if y == 0:
+        raise ValueError("Cannot divide by zero")
+    return x / y
+
+@tool
+def modulus(x: float, y: float) -> float:
+    """
+    Returns the remainder when x is divided by y.
+
+    Args:
+        x (float): the dividend
+        y (float): the divisor
+    """
+    if y == 0:
+        raise ValueError("Cannot compute modulus with zero divisor")
+    return x % y
+
+@tool
+def power(x: float, y: float) -> float:
+    """
+    Raises x to the power of y.
+
+    Args:
+        x (float): the base number
+        y (float): the exponent
+    """
+    return x ** y
+
+@tool
+def sqrt(x: float) -> float:
+    """
+    Returns the square root of x.
+
+    Args:
+        x (float): the number to find the square root of
+    """
+    if x < 0:
+        raise ValueError("Cannot compute square root of negative number")
+    return x ** 0.5
+

tools/search_tools.py

@@ -0,0 +1,42 @@
+"""This module contains tools for searching external sources."""
+from langchain_core.tools import tool
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_community.document_loaders import WikipediaLoader
+
+
+@tool
+def web_search(query: str) -> str:
+    """Search the web via Tavily for a given query and return maximum 3 results.
+    
+    Args:
+        query (str): The search query
+
+    Returns:
+        str: Content from the Tavily search
+    """
+    search_results = TavilySearchResults(max_results=3).invoke(query=query)
+    return {"web_results": search_results}
+
+@tool
+def search_wikipedia(query: str) -> str:
+    """
+    Searches Wikipedia and returns content from the topic.
+
+    Args:
+        query (str): The search query/topic to look up on Wikipedia
+        
+    Returns:
+        str: Content from the Wikipedia article for the query
+        
+    Raises:
+        ValueError: If no matching page is found
+    """
+    try:
+        loader = WikipediaLoader(query=query, load_max_docs=1)
+        docs = loader.load()
+        if not docs:
+            return f"No Wikipedia page found for '{query}'"
+        return docs[0].page_content
+    except Exception as e:
+        return f"Error searching Wikipedia: {str(e)}"
+