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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)