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Create app.py
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app.py
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import os
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import gradio as gr
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from crewai import Agent, Task, Crew, Process
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from crewai_tools import SerperDevTool
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from langchain_groq import ChatGroq
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# Set up environment variables
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os.environ["GROQ_API_KEY"] = "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"
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os.environ["SERPER_API_KEY"] = "206256c6acfbcd5a46195f3312aaa7e8ed38ae5f"
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# Initialize Groq LLM
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groq_llm = ChatGroq(
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model_name="mixtral-8x7b-32768",
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temperature=0.7,
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max_tokens=32768
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)
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# Initialize search tool
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search_tool = SerperDevTool()
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# Define agents
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researcher = Agent(
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role='Senior Research Analyst',
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goal='Uncover cutting-edge developments in AI and data science',
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backstory="""You work at a leading tech think tank.
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Your expertise lies in identifying emerging trends.
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You have a knack for dissecting complex data and presenting actionable insights.""",
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verbose=True,
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allow_delegation=False,
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llm=groq_llm,
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tools=[search_tool]
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)
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writer = Agent(
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role='Tech Content Strategist',
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goal='Craft compelling content on tech advancements',
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backstory="""You are a renowned Content Strategist, known for your insightful and engaging articles.
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You transform complex concepts into compelling narratives.""",
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verbose=True,
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allow_delegation=True,
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llm=groq_llm
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)
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def run_agents(research_topic):
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# Create tasks
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task1 = Task(
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description=f"""Conduct a comprehensive analysis of the latest advancements in {research_topic} in 2024.
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Identify key trends, breakthrough technologies, and potential industry impacts.""",
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expected_output="Full analysis report in bullet points",
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agent=researcher
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)
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task2 = Task(
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description="""Using the insights provided, develop an engaging blog
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post that highlights the most significant advancements.
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Your post should be informative yet accessible, catering to a tech-savvy audience.
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Make it sound cool, avoid complex words so it doesn't sound like AI.""",
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expected_output="Full blog post of at least 4 paragraphs",
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agent=writer
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)
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# Instantiate crew
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crew = Crew(
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agents=[researcher, writer],
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tasks=[task1, task2],
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verbose=2,
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process=Process.sequential
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)
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# Run the crew
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result = crew.kickoff()
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return result
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# Define Gradio interface
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iface = gr.Interface(
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fn=run_agents,
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inputs=gr.Textbox(label="Enter a research topic (e.g., 'AI', 'Machine Learning', 'Data Science')"),
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outputs=gr.Textbox(label="Results"),
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title="AI Research and Blog Post Generator",
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description="Enter a research topic to generate an analysis and blog post about recent advancements."
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)
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# Launch the Gradio interface
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iface.launch()
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