Update app.py

app.py

@@ -1,14 +1,12 @@
 import streamlit as st
 from crewai import Crew, Agent, Task, Process
+from langchain_core.tools import Tool  # Import Tool from langchain_core.tools
 from langchain_community.tools import DuckDuckGoSearchRun
-#from langchain_openai import ChatOpenAI  # Remove OpenAI
-from langchain_community.llms import HuggingFaceHub  # Import Hugging Face Hub
+from langchain_community.llms import HuggingFaceHub
 import datetime
 import os
 
 # --- Environment Setup ---
-#  Make sure to set your HUGGINGFACEHUB_API_TOKEN in your environment variables.
-
 huggingfacehub_api_token = os.environ.get("HUGGINGFACEHUB_API_TOKEN")
 
 
@@ -21,13 +19,19 @@ def get_date_range():
     return yesterday.strftime("%Y-%m-%d")
 
 
-
 # --- Agent and Task Definitions ---
 
 def create_ai_news_crew():
     """Creates the CrewAI crew, agents, and tasks."""
 
-    search_tool = DuckDuckGoSearchRun()
+    search_tool_instance = DuckDuckGoSearchRun()
+
+    # Wrap the DuckDuckGoSearchRun instance with the Tool class.
+    search_tool = Tool(
+        name="DuckDuckGo Search",
+        func=search_tool_instance.run,
+        description="Useful for searching the web for recent AI news articles.",
+    )
 
     # Define Agents
     researcher = Agent(
@@ -39,10 +43,10 @@ def create_ai_news_crew():
             tools effectively to find information.""",
         verbose=True,
         allow_delegation=False,
-        tools=[search_tool],
+        tools=[search_tool],  # Pass the wrapped tool
         llm=HuggingFaceHub(
-            repo_id="deepseek-ai/DeepSeek-Coder-33B-Instruct",  # Use the DeepSeek-Coder model (Instruct version is better for this task)
-            model_kwargs={"temperature": 0.5, "max_new_tokens": 1024, "repetition_penalty": 1.2}, # Added repetition penalty
+            repo_id="deepseek-ai/DeepSeek-Coder-33B-Instruct",
+            model_kwargs={"temperature": 0.5, "max_new_tokens": 1024, "repetition_penalty": 1.2},
             huggingfacehub_api_token=huggingfacehub_api_token,
         )
     )
@@ -57,12 +61,12 @@ def create_ai_news_crew():
         verbose=True,
         allow_delegation=False,
         llm=HuggingFaceHub(
-            repo_id="deepseek-ai/DeepSeek-Coder-33B-Instruct", #Use DeepSeek-Coder model
-            model_kwargs={"temperature": 0.2, "max_new_tokens": 1024, "repetition_penalty": 1.2},  # Lower temp, high rep penalty for concise output
+            repo_id="deepseek-ai/DeepSeek-Coder-33B-Instruct",
+            model_kwargs={"temperature": 0.2, "max_new_tokens": 1024, "repetition_penalty": 1.2},
             huggingfacehub_api_token=huggingfacehub_api_token,
         )
     )
-    
+
     # Define Tasks
     yesterday_str = get_date_range()
     research_task = Task(
@@ -73,29 +77,27 @@ def create_ai_news_crew():
             """,
         agent=researcher
     )
-    
+
     summarize_task = Task(
-      description="""Using the news articles identified, create a daily AI news 
+        description="""Using the news articles identified, create a daily AI news 
         briefing.  The briefing should be no more than 500 words and should
         cover the 3-5 most important AI news items from yesterday. Include 
         a very brief (1-2 sentence) summary of each item and, if possible, link to the source.
         Format the output using markdown for readability.
         """,
-      agent=summarizer
+        agent=summarizer
     )
 
     # Create Crew
     crew = Crew(
         agents=[researcher, summarizer],
         tasks=[research_task, summarize_task],
-        verbose=True,  # You can set it to 1 or 2 to different level of logs
-        process=Process.sequential  # Tasks are executed sequentially
+        verbose=True,
+        process=Process.sequential
     )
     return crew
 
 
-
-
 # --- Streamlit App ---
 
 def main():
@@ -114,7 +116,7 @@ def main():
         with st.spinner("Generating your daily AI news briefing..."):
             try:
                 crew = create_ai_news_crew()
-                result = crew.kickoff()  # Start the crew's work
+                result = crew.kickoff()
                 st.subheader("Your AI News Briefing:")
                 st.markdown(result)
 
@@ -123,7 +125,6 @@ def main():
                 st.error("Please check your API key and ensure you have set up the environment correctly.")
 
 
-
 if __name__ == "__main__":
     if not huggingfacehub_api_token:
         st.error("HUGGINGFACEHUB_API_TOKEN is not set.  Please set it as an environment variable.")