Update blog_title_generator.py

blog_title_generator.py

@@ -1,6 +1,10 @@
+
+import os
 import time
 import json
+from dotenv import load_dotenv
 from langchain_community.tools import DuckDuckGoSearchRun
+from langchain_community.tools import TavilySearchResults
 from langgraph.graph import MessagesState
 from langchain_core.prompts import PromptTemplate
 from langchain_core.messages import HumanMessage, SystemMessage
@@ -9,14 +13,19 @@ from langgraph.prebuilt import tools_condition
 from langgraph.prebuilt import ToolNode
 from langgraph.graph.state import CompiledStateGraph
 
+# Secret Key
+load_dotenv(override=True)
+tavily_api_key = os.getenv("TAVILY_API_KEY")
+
 
 def blog_titles_agent(llm, state):
   
   queries = state["search_queries"]
+
   
-  def duckduckgo_search(query: str) -> str:
+  def tavily_search(query: str) -> str:
     """
-    Performs a search on DuckDuckGo using the provided query.
+    Performs a search on Tavily using the provided query.
 
     Args:
         query (str): The search query to be executed.
@@ -24,13 +33,19 @@ def blog_titles_agent(llm, state):
     Returns:
         str: The result of the search query.
     """
-    search = DuckDuckGoSearchRun()
-    result = search.invoke(query)
+    tavily = TavilySearchResults(
+    max_results=5,
+    search_depth="advanced",
+    include_answer=True,
+    include_raw_content=True,
+    )
+    
+    text = tavily.invoke({"query": f"{query}"})
     print("Tool Call")
-    return result
-  
-  
-  tool = [duckduckgo_search]
+    return text
+    
+    
+  tool = [tavily_search]
   
   llm_with_tools = llm.bind_tools(tool)
   
@@ -50,7 +65,7 @@ def blog_titles_agent(llm, state):
   Context:
   - Generate only 3 Blog Titles.
   - The blog Title should be engaging.
-  - Always Use the attached tool duckduckgo_search to get the latest information about the Topic.
+  - Always Use the attached tool tavily_search to get the latest information about the Topic.
 
   Constraints:
   - Dont include any punctuation mark in the Title.
@@ -86,6 +101,7 @@ def blog_titles_agent(llm, state):
     time.sleep(5)
     messages = [HumanMessage(content=f"Search this query: {q}")]
     messages = react_graph.invoke({"messages": messages})
+    print("\n",messages)
     t = messages['messages'][-1].content
     t = t.replace("json", "").replace("```", "").strip()
     t = json.loads(t)
@@ -97,9 +113,7 @@ def blog_titles_agent(llm, state):
 
 
 def blog_titles_llm(llm, state):
-    
   topic = state["topic"]
-    
   blog_titles_prompt_template = PromptTemplate.from_template("""
   Task: You are an expert Blog Titles generator. Generate a blog Title on the Category given to you by using the examples below as a guide.
 
@@ -133,35 +147,4 @@ def blog_titles_llm(llm, state):
   titles = content.replace("json", "").replace("```", "").strip() # type: ignore
   titles = json.loads(titles)
   print(titles) 
-  return {"blog_topics": titles}
-
-
-
-
-
-
-
-
-
-# from langchain_community.tools import DuckDuckGoSearchResults
-# import time
-
-# def search_topics(queries):
-#   titles = []
-#   search = DuckDuckGoSearchResults(output_format="list")
-#   for query in queries:
-#     time.sleep(5)
-#     response = search.invoke(query)
-#     for r in response:
-#       titles.append(r['title'])
-
-#   return titles
-
-# from langchain_community.tools import DuckDuckGoSearchRun
-
-# def searched_blog_topics(state):
-#   queries = state["search_queries"]
-#   topics = search_topics(queries)
-#   return {"blog_topics": topics}
- 
-  
+  return {"blog_topics": titles}