Now using Tavily for web searches. It's a lot more powerful than DuckDuckGo

agent_factory.py

@@ -1,3 +1,5 @@
+import datetime as dt
+import dotenv
 import re
 from typing import Any, Literal
 
@@ -6,6 +8,7 @@ from langchain_core.messages import SystemMessage, AnyMessage
 from langchain_core.runnables import Runnable
 from langchain_core.tools import BaseTool
 from langchain_ollama import ChatOllama
+from langchain_tavily import TavilySearch, TavilyExtract
 from langgraph.constants import START, END
 from langgraph.graph import MessagesState, StateGraph
 from langgraph.graph.graph import CompiledGraph
@@ -23,6 +26,9 @@ from tools import (
 )
 
 
+dotenv.load_dotenv()
+
+
 class AgentFactory:
     """
     A factory for the agent. It is assumed that an Ollama server is running
@@ -67,7 +73,9 @@ class AgentFactory:
         "again the same tool, by calling it again.\n"
         "You are advised to cycle between reasoning and tool calling also\n"
         "multiple times. Provide an answer only when you are sure you don't\n"
-        "have to call any tool again."
+        "have to call any tool again.\n"
+        "\n"
+        f"If you need it, the date today is {dt.date.today()}."
     )
 
     __llm: Runnable
@@ -90,31 +98,42 @@ class AgentFactory:
             num_ctx:        Size of the context window used to generate the
                             next token.
         """
-        search_tool = DuckDuckGoSearchResults(
-            description=(
-                "A wrapper around Duck Duck Go Search. Useful for when you "
-                "need to answer questions about information you can find on "
-                "the web. Input should be a search query. It is advisable to "
-                "use this tool to retrieve web page URLs and use another tool "
-                "to analyze the pages. If the web source is suggested by the "
-                "user query, prefer retrieving information from that source. "
-                "For example, the query may suggest to search on Wikipedia or "
-                "Medium. In those cases, prepend the query with "
-                "'site: <name of the source>'. For example: "
-                "'site: wikipedia.org'"
-            ),
-            output_format="list"
+        # search_tool = DuckDuckGoSearchResults(
+        #     description=(
+        #         "A wrapper around Duck Duck Go Search. Useful for when you "
+        #         "need to answer questions about information you can find on "
+        #         "the web. Input should be a search query. It is advisable to "
+        #         "use this tool to retrieve web page URLs and use another tool "
+        #         "to analyze the pages. If the web source is suggested by the "
+        #         "user query, prefer retrieving information from that source. "
+        #         "For example, the query may suggest to search on Wikipedia or "
+        #         "Medium. In those cases, prepend the query with "
+        #         "'site: <name of the source>'. For example: "
+        #         "'site: wikipedia.org'"
+        #     ),
+        #     output_format="list"
+        # )
+
+        search_tool = TavilySearch(
+            topic="general",
+            max_results=5,
+            include_answer="advanced",
+        )
+        # search_tool.with_retry()
+        extract_tool = TavilyExtract(
+            extract_depth="advanced",
+            include_images=False,
         )
-        search_tool.with_retry()
         self.__tools = [
             execute_python_script,
             get_excel_table_content,
             get_youtube_video_transcript,
             reverse_string,
             search_tool,
+            extract_tool,
             sum_list,
             transcribe_audio_file,
-            web_page_info_retriever,
+            # web_page_info_retriever,
             youtube_video_to_frame_captions
         ]
         self.__llm = ChatOllama(

requirements.txt

@@ -8,6 +8,7 @@ langchain
 langchain_community
 langchain-core
 langchain-ollama
+langchain-tavily
 langchain-unstructured[local]
 langgraph
 opencv-python

tests/tools/test_web_search.py

@@ -25,4 +25,4 @@ def test_web_search() -> None:
     answer = final_state["messages"][-1].content
 
     # then
-    assert answer == "2"
+    assert answer == "3"