Codespace sturdy winner rp9qwxw5wjpf5xrq

agents/.python-version

@@ -0,0 +1 @@
+3.10

agents/crew_zaai/main.py

@@ -0,0 +1,6 @@
+def main():
+    print("Hello from crew-zaai!")
+
+
+if __name__ == "__main__":
+    main()

agents/crew_zaai/pyproject.toml

@@ -0,0 +1,7 @@
+[project]
+name = "crew-zaai"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = []

agents/crew_zaai/src/crew_zaai/config/agents.yaml

@@ -19,12 +19,13 @@ summarizer:
     You're known for your ability to summarize and retrive facts, references, quotes
     and recommend the most useful surprising information about the {topic}.
 
-blog_writer:
+linkedin_post_writer:
   role: >
-    {topic} Blog Writer
+    {topic} LinkedIn Engagement Specialist
   goal: >
-    Create detailed blog posts based on {topic} research findings
+    Craft high-impact LinkedIn posts about {topic} to maximize engagement and professional reach.Note: Please shorten your post and try again. Max 3000 characters
   backstory: >
-    You're a meticulous writer with a keen eye for detail.
-    You're known for your ability to turn complex topics into clear and concise blog posts,
-    making it easy for others to understand and act on the information you provide.
+    You are a seasoned social media strategist with a specialty in LinkedIn.
+    You understand the nuances of the LinkedIn algorithm and what content resonates with professionals.
+    Your expertise lies in creating concise, engaging posts that spark conversations, build thought leadership, and expand professional networks around key topics.
+    Note: Please shorten your post and try again. Max 3000 characters

agents/crew_zaai/src/crew_zaai/config/tasks.yaml

@@ -2,10 +2,10 @@ research_task:
   description: >
     Conduct a thorough research about {topic}
     Make sure you find any interesting and relevant youtube links given
-    the current year is 2024.
+    the current year is 2025.
   expected_output: >
     A list with youtube URLs that cover {topic} and the respective description
-    with the most relevant information about {topic}. Ignore any links that don't
+    with the most relevant information about {topic}. and do have subtitles enabled.Ignore any links that don't
     start with "https://www.youtube.com".
   agent: researcher
 
@@ -22,12 +22,19 @@ summarize_task:
 
 write_task:
   description: >
-    Review the context you got and expand each topic into a full section for a blog post.
-    Make sure the blog post is detailed and contains any and all relevant information.
-    The blog post must contain an introduction, a body, a code example and a conclusion section.
+    Review the context you got and craft engaging LinkedIn posts for each key topic.
+    Each post should be concise, insightful, and tailored for a professional audience on LinkedIn.
+    The LinkedIn post series must include an introductory post, several posts covering each main topic, a post with a code example (if relevant and simplified for LinkedIn), and a concluding post.
   expected_output: >
-    A fully-fledged blog post with the main topics, each presented as a complete section of information.
-    Format it as HTML without using '```'. Make it look like a professional tech blog website,
-    including a navbar, menu, and styling. Incorporate YouTube links as clickable references within
-    the text and at the end.
-  agent: blog_writer
+    A series of structured LinkedIn post drafts, one for each topic.
+    Format each post as text, optimized for LinkedIn's platform.
+    Note: Please shorten your post and try again. Max 3000 characters.
+    Focus on:
+      - Engaging opening lines to grab attention.
+      - Concise bullet points or short paragraphs for key information.
+      - Relevant hashtags for discoverability.
+      - A professional yet approachable tone.
+      - A clear call to action or question to encourage engagement (optional).
+    Avoid using '```' and aim for a professional, LinkedIn-style presentation.
+  agent: linkedin_post_writer # Agent designed to write LinkedIn posts
+

agents/crew_zaai/src/crew_zaai/crew.py

@@ -1,8 +1,11 @@
-import os
 from crewai import Agent, Crew, Process, Task
 from crewai.project import CrewBase, agent, crew, task
-from crew_zaai.src.crew_zaai.tools.searx import SearxSearchTool
-from crew_zaai.src.crew_zaai.tools.youtube import YouTubeTranscriptTool
+import sys
+import os
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) # Add current directory of crew.py to path
+sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), '..')) # Add parent directory (src) to path, assuming 'tools' is in 'src'
+from tools.searx import SearxSearchTool
+from tools.youtube import YouTubeTranscriptTool
 
 
 @CrewBase
@@ -31,8 +34,8 @@ def summarizer(self) -> Agent:
         )
 
     @agent
-    def blog_writer(self) -> Agent:
-        return Agent(config=self.agents_config["blog_writer"], verbose=True)
+    def linkedin_post_writer(self) -> Agent:
+        return Agent(config=self.agents_config["linkedin_post_writer"], verbose=True)
 
     @task
     def research_task(self) -> Task:

agents/crew_zaai/src/crew_zaai/streamlit_app.py

@@ -0,0 +1,56 @@
+import streamlit as st
+import warnings
+from dotenv import load_dotenv
+from src.crew_zaai.crew import CrewZaai
+import sys
+import os
+
+# Assuming your crew.py and CrewZaai class are correctly set up in crew_zaai package
+# Get the directory where your streamlit_app.py is located
+current_dir = os.path.dirname(os.path.abspath(__file__))
+src_dir = os.path.join(current_dir, "src") # Assuming 'src' is in the same directory as streamlit_app.py
+if os.path.exists(src_dir):
+    sys.path.insert(0, src_dir) # Add 'src' directory to Python path
+else:
+    src_dir_parent = os.path.dirname(current_dir) # Check if 'src' is in the parent directory
+    src_dir_parent_check = os.path.join(src_dir_parent, "src")
+    if os.path.exists(src_dir_parent_check):
+        sys.path.insert(0, src_dir_parent_check) # Add parent 'src' if found
+    else:
+        print(f"Warning: 'src' directory not found in '{current_dir}' or parent directory. Import errors may occur.")
+
+
+warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
+load_dotenv()
+
+def run_crew_zaai(topic):
+    """Runs the CrewZaai crew with the given topic and returns the output."""
+    try:
+        crew_instance = CrewZaai() # Instantiate CrewZaai class
+        crew = crew_instance.crew() # Get the crew object
+        result = crew.kickoff(inputs={"topic": topic}) # Run kickoff and capture the result
+        return result
+    except Exception as e:
+        return {"error": f"An error occurred while running the crew: {e}"}
+
+def main():
+    st.title("CrewZaai AI Agent Runner")
+
+    topic = st.text_input("Enter a Topic for the AI Agents to Explore:", "AI Agents 2024")
+
+    if st.button("Run Crew"):
+        if not topic:
+            st.warning("Please enter a topic.")
+        else:
+            with st.spinner(text="Running CrewZaai..."):
+                output = run_crew_zaai(topic)
+
+            st.subheader("CrewZaai Output:")
+            if "error" in output:
+                st.error(output["error"])
+            else:
+                # Assuming the output is a dictionary or string that can be displayed
+                st.write(output) # You might need to format this output better depending on its structure
+
+if __name__ == "__main__":
+    main()

agents/crew_zaai/src/crew_zaai/tools/youtube.py

@@ -64,7 +64,7 @@ def _run(
         Runs the YouTubeTranscriptTool with the given parameters.
 
         Args:
-            video_url (list[str]): The list of YouTube video URLs to fetch the transcript for.
+            video_url (list[str]): The list of YouTube video URLs to fetch the transcript for and do have subtitles enabled.
             language (Optional[str]): The language code for the transcript (e.g., 'en' for English).
 
         Returns:

agents/crew_zaai/src/streamlit_app.py

@@ -0,0 +1,76 @@
+import streamlit as st
+import warnings
+from dotenv import load_dotenv
+from crew_zaai.crew import CrewZaai
+import sys
+import os
+import json
+
+# Assuming your crew.py and CrewZaai class are correctly set up in crew_zaai package
+# Get the directory where your streamlit_app.py is located
+current_dir = os.path.dirname(os.path.abspath(__file__))
+src_dir = os.path.join(current_dir, "src") # Assuming 'src' is in the same directory as streamlit_app.py
+if os.path.exists(src_dir):
+    sys.path.insert(0, src_dir) # Add 'src' directory to Python path
+else:
+    src_dir_parent = os.path.dirname(current_dir) # Check if 'src' is in the parent directory
+    src_dir_parent_check = os.path.join(src_dir_parent, "src")
+    if os.path.exists(src_dir_parent_check):
+        sys.path.insert(0, src_dir_parent_check) # Add parent 'src' if found
+    else:
+        print(f"Warning: 'src' directory not found in '{current_dir}' or parent directory. Import errors may occur.")
+
+
+warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
+load_dotenv()
+
+def run_crew_zaai(topic):
+    """Runs the CrewZaai crew with the given topic and returns the output."""
+    try:
+        crew_instance = CrewZaai() # Instantiate CrewZaai class
+        crew = crew_instance.crew() # Get the crew object
+        result = crew.kickoff(inputs={"topic": topic}) # Run kickoff and capture the result
+        return result
+    except Exception as e:
+        return {"error": f"An error occurred while running the crew: {e}"}
+
+def main():
+    st.title("Multi Agents AI for research/Summarizer and Linkindin post") # Updated title
+
+    topic = st.text_input("Enter a Topic for the AI Agents to Explore:", "Agentic AI 2025")
+
+    if st.button("Button"):
+        if not topic:
+            st.warning("Please enter a topic.")
+        else:
+            with st.spinner(text="Running ..."):
+                output = run_crew_zaai(topic)
+
+            st.subheader("Task Outputs:") # Updated subheader
+
+            if "error" in output:
+                st.error(output["error"])
+            else:
+                if isinstance(output, dict) and "tasks_output" in output:
+                    tasks_output_list = output["tasks_output"] # Get the list of TaskOutput objects
+
+                    for i, task_output in enumerate(tasks_output_list):
+                        st.subheader(f"Task {i+1}: {task_output.summary}") # Display task summary as subheader
+
+                        try:
+                            # Try to parse task_output.raw as JSON (dictionary)
+                            raw_dict = json.loads(task_output.raw)
+                            st.json(raw_dict) # Display as JSON if parsing is successful
+                        except json.JSONDecodeError:
+                            # If JSON parsing fails, display as plain text
+                            st.text_area(f"Task {i+1} Output (Plain Text)", value=task_output.raw, height=1500)
+                        except TypeError: # Handle cases where task_output.raw might not be a string
+                            st.text_area(f"Task {i+1} Output (Plain Text, Non-String Raw)", value=str(task_output.raw), height=1500)
+
+
+                else:
+                    st.write(output) # Fallback to raw output if format is unexpected
+
+
+if __name__ == "__main__":
+    main()

agents/main.py

@@ -0,0 +1,6 @@
+def main():
+    print("Hello from agents!")
+
+
+if __name__ == "__main__":
+    main()

agents/pyproject.toml

@@ -0,0 +1,10 @@
+[project]
+name = "agents"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = []
+
+[tool.uv.workspace]
+members = ["crew_zaai"]