web search tools

agent.py

@@ -1,10 +1,14 @@
 import os
 from typing import TypedDict, List, Dict, Any, Optional
+from langchain_core import tools
 from langgraph.graph import StateGraph, START, END
 from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint, HuggingFacePipeline
 from langchain_core.messages import HumanMessage, AIMessage
+from langchain_core.tools import Tool
+from duckduckgo_search import DDGS
 from dotenv import load_dotenv
 
+
 load_dotenv()
 
 # Base Hugging Face LLM used by the chat wrapper
@@ -18,9 +22,33 @@ base_llm = HuggingFaceEndpoint(
 # Chat model that works with LangGraph
 model = ChatHuggingFace(llm=base_llm)
 
+@tools
+def web_search(keywords: str, max_results:int = 5) -> str:
+    """
+    Uses duckduckgo to search the web
+
+    Use cases:
+     - Identify personal information
+     - Information search
+     - Finding organisation information
+     - Obtain the latest news
+
+     Args:
+        keywords: keywords used to search the web
+        max_results: number of results to show after searching the web, defaults to 5
+
+    Returns:
+        Search result (Header + body + URL)
+    """
+    with DDGS() as ddgs:
+        # Perform a text search
+        results = ddgs.text(keywords, max_results)
+        print(results)
+
 
 class AgentState(TypedDict):
     messages: List[HumanMessage | AIMessage]
+    search_required: 
 
 
 def read_message(state: AgentState) -> AgentState:

requirements.txt

@@ -17,4 +17,5 @@ wikipedia
 pgvector
 python-dotenv
 pandas
-numpy
+numpy
+duckduckgo_search