updated code space

agent.py

@@ -13,10 +13,8 @@ from dotenv import load_dotenv
 # Load environment variables from .env
 load_dotenv()
 
-
 # Initialize LLM
 def initialize_llm():
-    """Initializes the ChatGroq LLM."""
     llm = ChatGroq(
         temperature=0,
         model_name="qwen-qwq-32b",
@@ -26,27 +24,20 @@ def initialize_llm():
 
 # Initialize Tavily Search Tool
 def initialize_search_tool():
-    """Initializes the TavilySearchResults tool."""
-    search_tool = TavilySearchResults()
-    return search_tool
-
+    return TavilySearchResults()
 
-
-# Define Tools
+# Weather tool
 def get_weather(location: str, search_tool: TavilySearchResults = None) -> str:
-    """Fetch the current weather information for a given location using Tavily search."""
     if search_tool is None:
         search_tool = initialize_search_tool()
     query = f"current weather in {location}"
-    results = search_tool.run(query)
-    return results
-
+    return search_tool.run(query)
 
+# Recommendation chain
 def initialize_recommendation_chain(llm: ChatGroq) -> Runnable:
-    """Initializes the recommendation chain."""
     recommendation_prompt = ChatPromptTemplate.from_template("""
     You are a helpful assistant that gives weather-based advice.
-
+    
     Given the current weather condition: "{weather_condition}", provide:
     1. Clothing or activity recommendations suited for this weather.
     2. At least one health tip to stay safe or comfortable in this condition.
@@ -55,73 +46,104 @@ def initialize_recommendation_chain(llm: ChatGroq) -> Runnable:
     """)
     return recommendation_prompt | llm
 
-
-
 def get_recommendation(weather_condition: str, recommendation_chain: Runnable = None) -> str:
-    """Give activity/clothing recommendations and health tips based on the weather condition using an LLM."""
     if recommendation_chain is None:
         llm = initialize_llm()
         recommendation_chain = initialize_recommendation_chain(llm)
     return recommendation_chain.invoke({"weather_condition": weather_condition})
 
-
-
+# Math tools
+@tool
+def add(x: int, y: int) -> int:
+    return x + y
+
+@tool
+def subtract(x: int, y: int) -> int:
+    return x - y
+
+@tool
+def multiply(x: int, y: int) -> int:
+    return x * y
+
+@tool
+def divide(x: int, y: int) -> float:
+    if y == 0:
+        raise ValueError("Cannot divide by zero.")
+    return x / y
+
+@tool
+def square(x: int) -> int:
+    return x * x
+
+@tool
+def cube(x: int) -> int:
+    return x * x * x
+
+@tool
+def power(x: int, y: int) -> int:
+    return x ** y
+
+@tool
+def factorial(n: int) -> int:
+    if n < 0:
+        raise ValueError("Factorial is not defined for negative numbers.")
+    if n == 0 or n == 1:
+        return 1
+    result = 1
+    for i in range(2, n + 1):
+        result *= i
+    return result
+
+@tool
+def mean(numbers: list) -> float:
+    if not numbers:
+        raise ValueError("The list is empty.")
+    return sum(numbers) / len(numbers)
+
+@tool
+def standard_deviation(numbers: list) -> float:
+    if not numbers:
+        raise ValueError("The list is empty.")
+    mean_value = mean(numbers)
+    variance = sum((x - mean_value) ** 2 for x in numbers) / len(numbers)
+    return variance ** 0.5
+
+# Build the LangGraph
 def build_graph():
-    """Build the graph using Groq and custom prompt/tools setup"""
-
-    # Initialize the LLM
     llm = initialize_llm()
-
-    # Initialize Tavily tool
     search_tool = initialize_search_tool()
-
-
-    # Initialize the recommendation chain
     recommendation_chain = initialize_recommendation_chain(llm)
 
-    # Define tools
     @tool
     def weather_tool(location: str) -> str:
-        """Fetch the current weather information for a given location."""
-        return get_weather(location, search_tool)  # Pass the search tool
+        return get_weather(location, search_tool)
 
     @tool
     def recommendation_tool(weather_condition: str) -> str:
-        """Get recommendations based on weather."""
         return get_recommendation(weather_condition, recommendation_chain)
 
-    tools = [weather_tool, recommendation_tool]
+    tools = [weather_tool, recommendation_tool, add, subtract, multiply, divide, square, cube, power, factorial, mean, standard_deviation]
 
-    # Bind tools to LLM
     llm_with_tools = llm.bind_tools(tools)
 
-    # Define assistant node
     def assistant(state: MessagesState):
-        """Assistant node"""
         print("Entering assistant node...")
         response = llm_with_tools.invoke(state["messages"])
         print(f"Assistant says: {response.content}")
         return {"messages": [response]}
 
-    # Create graph
     builder = StateGraph(MessagesState)
     builder.add_node("assistant", assistant)
     builder.add_node("tools", ToolNode(tools))
     builder.set_entry_point("assistant")
     builder.add_conditional_edges("assistant", tools_condition)
     builder.add_edge("tools", "assistant")
-    graph = builder.compile()
-
-    return graph
-
-
+    return builder.compile()
 
-# Main execution
 if __name__ == "__main__":
-    # Build and run the graph
     graph = build_graph()
-    question = "What are the Upanishads?"
+    question = "What is the factorial of 6 and can you also tell me the weather in Paris?"
     messages = [HumanMessage(content=question)]
-    messages = graph.invoke({"messages": messages})
-    for m in messages["messages"]:
-        m.pretty_print()
+    result = graph.invoke({"messages": messages})
+    for msg in result["messages"]:
+        msg.pretty_print()

chroma_db/b4f29986-cfbe-4e28-871d-c988b39d1992/data_level0.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:23add52afbe7588391f32d3deffb581b2663d2e2ad8851aba7de25e6b3f66761
-size 32120000

chroma_db/b4f29986-cfbe-4e28-871d-c988b39d1992/header.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f8c7f00b4415698ee6cb94332eff91aedc06ba8e066b1f200e78ca5df51abb57
-size 100

chroma_db/b4f29986-cfbe-4e28-871d-c988b39d1992/length.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e7e2dcff542de95352682dc186432e98f0188084896773f1973276b0577d5305
-size 40000