import os import gradio as gr from textwrap import dedent import google.generativeai as genai # Tool import from crewai.tools.gemini_tools import GeminiSearchTools from langchain.tools.yahoo_finance_news import YahooFinanceNewsTool from crewai.tools.browser_tools import BrowserTools from crewai.tools.sec_tools import SECTools from crewai.tools.mixtral_tools import MixtralSearchTools # Google Langchain 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') # 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) # Base Example with Gemini Search def crewai_process(research_topic): # Define your agents with roles and goals crazy1 = Agent( role='Homeless Person', goal=f'Discuss issue with {research_topic} and come to a deeper understanding', backstory="""Not doing well mentally living on the street""", verbose=True, allow_delegation=False, llm = gemini_llm, tools=[ MixtralSearchTools.mixtral_crazy, GeminiSearchTools.gemini_search ] ) crazy2 = Agent( role='Distressed Mom', goal='Resond to answers', backstory="""Struggling with depression and loss of a child""", verbose=True, allow_delegation=True, llm = gemini_llm, tools=[ MixtralSearchTools.mixtral_crazy, GeminiSearchTools.gemini_search ] # Add tools and other optional parameters as needed ) # Create tasks for your agents task1 = Task( description=f"""Discuss the {research_topic}. Use Mixtral do 10 rounds of chat with. react to crazy2 """, agent=crazy1 ) task2 = Task( description=f"""Discuss the {research_topic}. Use Mixtral do 10 rounds of chat with. react to crazy1 """, agent=crazy2 ) # Instantiate your crew with a sequential process crew = Crew( agents=[crazy1, crazy2], tasks=[task1, task2], verbose=2, process=Process.sequential ) # Get your crew to work! result = crew.kickoff() return result # Create a Gradio interface iface = gr.Interface( fn=crewai_process, inputs=gr.Textbox(lines=2, placeholder="Enter Research Topic Here..."), outputs="text", title="CrewAI on Gemini (Blog Post Writer)", description="Input a research topic to get a comprehensive analysis (in logs) and a blog post draft (in output). To learn more connect with Mike Lively on LinkedIn at https://www.linkedin.com/in/awsmulticloud/ or join his cloud Meetup at https://www.meetup.com/florence-aws-user-group-meetup/" ) # Launch the interface iface.launch(debug=True)