aggiunto web searc tool implementata tramite Tavily

agent.py

@@ -13,7 +13,7 @@ from langgraph.graph import StateGraph, END
 from langchain_google_genai import ChatGoogleGenerativeAI
 
 # Local imports
-from tools import get_search_tool, get_wikipedia_tool, wikipedia_search, wikipedia_search_3, execute_python_code_from_file, download_taskid_file
+from tools import get_search_tool, get_tavily_search_tool, get_wikipedia_tool, wikipedia_search, wikipedia_search_3, execute_python_code_from_file, download_taskid_file
 
 # Nota: per i test in locale si usa il .env
 #       su HuggingFace invece si usano le variabili definite in Settings/"Variables and secrets"
@@ -54,7 +54,8 @@ chat = ChatGoogleGenerativeAI(
     temperature = GEMINI_TEMPERATURE)
 
 # Imposta i tool
-search_tool = get_search_tool()
+#search_tool = get_search_tool()
+search_tool = get_tavily_search_tool()
 #wikipedia_tool = get_wikipedia_tool()
 
 tools = [search_tool, wikipedia_search_3, execute_python_code_from_file, download_taskid_file]

requirements.txt

@@ -10,5 +10,6 @@ langchain-community
 langchain-openai
 langchain-huggingface
 langchain-google-genai
+langchain-tavily
 
 wikipedia

tools.py

@@ -7,6 +7,7 @@ from langchain_community.utilities import WikipediaAPIWrapper
 from langchain_community.tools import WikipediaQueryRun
 from langchain_community.document_loaders import WikipediaLoader
 import wikipedia
+from langchain_tavily import TavilySearch
 from langchain_core.tools import tool
 from langchain.tools import Tool
 
@@ -28,6 +29,24 @@ def get_search_tool():
     return search_tool
 
 
+def get_tavily_search_tool():
+
+    tavily_search_tool = TavilySearch(
+        max_results=5,
+        topic="general",
+        # include_answer=False,
+        # include_raw_content=False,
+        # include_images=False,
+        # include_image_descriptions=False,
+        # search_depth="basic",
+        # time_range="day",
+        # include_domains=None,
+        # exclude_domains=None
+    )
+
+    return tavily_search_tool
+
+
 # Wikipedia tool 1: usa WikipediaQueryRun dal package 'langchain_community.tools'
 # problema: sembra ottenere solo i summary
 def get_wikipedia_tool():