Update app.py

app.py

@@ -1,41 +1,43 @@
 import streamlit as st
-from crewai import Task, Agent, Crew, Process
+from crewai import Agent, Task, Crew
 from crewai_tools import YoutubeChannelSearchTool
+from langchain_google_genai import ChatGoogleGenerativeAI
 from dotenv import load_dotenv
 import os
-import asyncio
-from langchain_google_genai import ChatGoogleGenerativeAI
 import nest_asyncio
+
 # Load environment variables
 load_dotenv()
+
+# Apply nest_asyncio to allow nested event loops
+nest_asyncio.apply()
+
+# Initialize Google Gemini AI
 llm = ChatGoogleGenerativeAI(
     api_key=os.getenv('GOOGLE_API_KEY'),
     model="models/gemini-pro"  # Replace with the correct model name
 )
+
 # Initialize the YoutubeChannelSearchTool with a specific Youtube channel handle to target your search
 yt_tool = YoutubeChannelSearchTool(youtube_channel_handle='@krishnaik06')
 
-# Define agents
-## Create a senior blog content researcher
+# Define Agents
 blog_researcher = Agent(
     role='Blog Researcher from Youtube Videos',
     goal='Get the relevant video transcription for the topic {topic} from the provided YT channel',
-    verbose=True,
-    memory=True,
     backstory=(
        "Expert in understanding videos in AI, Data Science, Machine Learning, and Gen AI and providing suggestions."
     ),
     llm=llm,
     tools=[yt_tool],
-    allow_delegation=True
+    allow_delegation=True,
+    verbose=True,
+    memory=True
 )
 
-## Create a senior blog writer agent with YT tool
 blog_writer = Agent(
     role='Blog Writer',
     goal='Narrate compelling tech stories about the video {topic} from YT video',
-    verbose=True,
-    memory=True,
     backstory=(
         "With a flair for simplifying complex topics, you craft"
         "engaging narratives that captivate and educate, bringing new"
@@ -43,61 +45,48 @@ blog_writer = Agent(
     ),
     llm=llm,
     tools=[yt_tool],
-    allow_delegation=False
+    allow_delegation=False,
+    verbose=True,
+    memory=True
 )
 
-# Define tasks
-## Research Task
+# Define Tasks
 research_task = Task(
-  description=(
-    "Identify the video {topic}."
-    "Get detailed information about the video from the channel video."
-  ),
-  expected_output='A comprehensive 3 paragraphs long report based on the {topic} of video content.',
-  tools=[yt_tool],
-  agent=blog_researcher,
+    description=(
+        "Identify the video {topic}. "
+        "Get detailed information about the video from the channel video."
+    ),
+    expected_output='A comprehensive 3 paragraphs long report based on the {topic} of video content.',
+    agent=blog_researcher,
+    tools=[yt_tool]
 )
 
-# Writing task with language model configuration
 write_task = Task(
-  description=(
-    "get the info from the youtube channel on the topic {topic}."
-  ),
-  expected_output='Summarize the info from the youtube channel video on the topic {topic} and create the content for the blog',
-  tools=[yt_tool],
-  agent=blog_writer,
-  async_execution=False,
-  output_file='new-blog-post.md'  # Example of output customization
+    description=(
+        "Get the info from the YouTube channel on the topic {topic}."
+    ),
+    expected_output='Summarize the info from the YouTube channel video on the topic {topic} and create the content for the blog',
+    agent=blog_writer,
+    tools=[yt_tool],
+    async_execution=False,
+    output_file='new-blog-post.md'
 )
 
-# Forming the tech-focused crew with some enhanced configurations
+# Define Crew
 crew = Crew(
-  agents=[blog_researcher, blog_writer],
-  tasks=[research_task, write_task],
-  process=Process.sequential,  # Optional: Sequential task execution is default
-  memory=True,
-  cache=True,
-  max_rpm=100,
-  share_crew=True
+    agents=[blog_researcher, blog_writer],
+    tasks=[research_task, write_task],
+    verbose=2,
+    memory=True,
+    cache=True,
+    max_rpm=100,
+    share_crew=True
 )
 
-async def run_task_async(topic):
-    # Start the task execution process with enhanced feedback
-    result = await crew.kickoff(inputs={'topic': topic})
-    with open('new-blog-post.md', 'r') as file:
-        blog_content = file.read()
-    return blog_content
-
-def run_task(topic):
-    loop = asyncio.new_event_loop()
-    asyncio.set_event_loop(loop)
-    result = loop.run_until_complete(run_task_async(topic))
-    loop.close()
-    return result
-
+# Streamlit App
 def main():
     st.set_page_config(page_title="AI Blog Generator", page_icon="📝")
-    
+
     st.title("AI Blog Generator")
     st.write("Enter a topic to generate a blog post based on YouTube videos.")
     
@@ -105,11 +94,15 @@ def main():
     if st.button("Generate Blog Post"):
         if topic:
             with st.spinner("Generating blog post..."):
-                result = run_task(topic)
-                st.success("Blog post generated!")
-                st.markdown(result)
+                try:
+                    result = crew.kickoff(inputs={'topic': topic})
+                    with open('new-blog-post.md', 'r') as file:
+                        blog_content = file.read()
+                    st.markdown(blog_content)
+                except Exception as e:
+                    st.error(f"An error occurred: {e}")
         else:
             st.error("Please enter a topic to continue.")
-            
+
 if __name__ == "__main__":
     main()