Update app.py

app.py

@@ -10,39 +10,21 @@ from crewai.tools.browser_tools import BrowserTools
 from crewai.tools.sec_tools import SECTools
 
 # Google Langchain
-#from langchain_google_genai import ChatGoogleGenerativeAI
-
 from langchain_google_genai import GoogleGenerativeAI
 
+#Crew imports
 from crewai import Agent, Task, Crew, Process
 
 # Retrieve API Key from Environment Variable
 GOOGLE_AI_STUDIO = os.environ.get('GOOGLE_API_KEY')
 
-# os.environ["GOOGLE_API_KEY"] = 
-
 # Ensure the API key is available
 if not GOOGLE_AI_STUDIO:
     raise ValueError("API key not found. Please set the GOOGLE_AI_STUDIO2 environment variable.")
 
-
+# Set gemini_llm
 gemini_llm = GoogleGenerativeAI(model="gemini-pro", google_api_key=GOOGLE_AI_STUDIO)
 
-
-# os.environ["OPENAI_API_KEY"] = "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"
-
-# Crew Bot: https://chat.openai.com/g/g-qqTuUWsBY-crewai-assistant
-
-
-'''
-tools=[
-GeminiSearchTools.gemini_search,
-BrowserTools.scrape_and_summarize_website
-
-]
-'''
-
-#llm = ChatGoogleGenerativeAI(model=model),
 # Base Example with Gemini Search
 
 def crewai_process(research_topic):
@@ -115,193 +97,3 @@ iface = gr.Interface(
 # Launch the interface
 iface.launch()
 
-
-
-# Stock Evaluation
-    
-
-'''   
-from stock_analysis_agents import StockAnalysisAgents
-from stock_analysis_tasks import StockAnalysisTasks
-
-#from dotenv import load_dotenv
-
-#load_dotenv()
-
-def run_financial_analysis(company_name):
-    # Assuming StockAnalysisAgents and StockAnalysisTasks are defined elsewhere
-    agents = StockAnalysisAgents()
-    tasks = StockAnalysisTasks()
-
-    research_analyst_agent = agents.research_analyst()
-    financial_analyst_agent = agents.financial_analyst()
-    investment_advisor_agent = agents.investment_advisor()
-
-    research_task = tasks.research(research_analyst_agent, company_name)
-    financial_task = tasks.financial_analysis(financial_analyst_agent)
-    filings_task = tasks.filings_analysis(financial_analyst_agent)
-    recommend_task = tasks.recommend(investment_advisor_agent)
-
-    crew = Crew(
-        agents=[
-            research_analyst_agent,
-            financial_analyst_agent,
-            investment_advisor_agent
-        ],
-        tasks=[
-            research_task,
-            financial_task,
-            filings_task,
-            recommend_task
-        ],
-        verbose=True
-    )
-
-    result = crew.kickoff()
-    return result
-
-iface = gr.Interface(
-    fn=run_financial_analysis,
-    inputs=gr.Textbox(lines=2, placeholder="Enter Company Name Here"),
-    outputs="text",
-    title="CrewAI Financial Analysis",
-    description="Enter a company name to get financial analysis."
-)
-
-#if __name__ == "__main__":
-iface.launch()
-
-''' 
-
-
-# Therapy Group
-
-'''
-def run_therapy_session(group_size, topic):
-    participant_names = ['Alice', 'Bob', 'Charlie', 'Diana', 'Ethan', 'Fiona', 'George', 'Hannah', 'Ivan']
-    
-    if group_size > len(participant_names) + 1:  # +1 for the therapist
-        return "Group size exceeds the number of available participant names."
-
-    # Create the therapist agent
-    dr_smith = Agent(
-        role='Therapist', 
-        goal='Facilitate a supportive group discussion', 
-        backstory='An experienced therapist specializing in group dynamics.', 
-        verbose=True,
-        allow_delegation=False
-    )
-    # Create participant agents
-
-    participants = [Agent(
-        role=f'Group Therapy Participant - {name}', 
-        goal='Participate in group therapy', 
-        backstory=f'{name} is interested in sharing and learning from the group.', 
-        verbose=True,
-        allow_delegation=False)
-        for name in participant_names[:group_size - 1]]
-    participants.append(dr_smith)
-
-    # Define tasks for each participant
-    tasks = [Task(description=f'{participant.role.split(" - ")[-1]}, please share your thoughts on the topic: "{topic}".', agent=participant)
-         for participant in participants]
-
-    # Instantiate the crew with a sequential process
-    therapy_crew = Crew(
-        agents=participants,
-        tasks=tasks,
-        process=Process.sequential,
-        verbose=True
-    )
-
-    # Start the group therapy session
-    result = therapy_crew.kickoff()
-
-    # Simulating a conversation (placeholder, adjust based on CrewAI capabilities)
-    conversation = "\n".join([f"{participant.role.split(' - ')[-1]}: [Participant's thoughts on '{topic}']" for participant in participants])
-    
-    return result
-
-# Gradio interface
-iface = gr.Interface(
-    fn=run_therapy_session,
-    inputs=[
-        gr.Slider(minimum=2, maximum=10, label="Group Size", value=4),
-        gr.Textbox(lines=2, placeholder="Enter a topic or question for discussion", label="Discussion Topic")
-    ],
-    outputs="text"
-)
-
-# Launch the interface
-iface.launch()
-
-'''
-
-
-
-
-# Choosing topics
-
-'''
-def run_crew(topic):
-    # Define your agents
-    researcher = Agent(
-        role='Senior Research Analyst',
-        goal='Uncover cutting-edge developments',
-        backstory="""You are a Senior Research Analyst at a leading tech think tank...""",
-        verbose=True,
-        allow_delegation=False
-    )
-
-    writer = Agent(
-        role='Tech Content Strategist',
-        goal='Craft compelling content',
-        backstory="""You are a renowned Tech Content Strategist...""",
-        verbose=True,
-        allow_delegation=False
-    )
-
-    # Assign tasks based on the selected topic
-    if topic == "write short story":
-        task_description = "Write a captivating short story about a journey through a futuristic city."
-    elif topic == "write an article":
-        task_description = "Compose an insightful article on the latest trends in technology."
-    elif topic == "analyze stock":
-        task_description = "Perform a detailed analysis of recent trends in the stock market."
-    elif topic == "create a vacation":
-        task_description = "Plan a perfect vacation itinerary for a family trip to Europe."
-
-    task1 = Task(
-        description=task_description,
-        agent=researcher
-    )
-
-    task2 = Task(
-        description=f"Use the findings from the researcher's task to develop a comprehensive report on '{topic}'.",
-        agent=writer
-    )
-
-    # Instantiate your crew with a sequential process
-    crew = Crew(
-        agents=[researcher, writer],
-        tasks=[task1, task2],
-        verbose=2,
-        process=Process.sequential
-    )
-
-    # Get your crew to work!
-    result = crew.kickoff()
-    return result
-
-# Gradio Interface with Dropdown for Topic Selection
-iface = gr.Interface(
-    fn=run_crew,
-    inputs=gr.Dropdown(choices=["write short story", "write an article", "analyze stock", "create a vacation"], label="Select Topic"),
-    outputs="text",
-    title="AI Research and Writing Crew",
-    description="Select a topic and click the button to run the crew of AI agents."
-)
-
-iface.launch()
-
-'''