app.py

import gradio as gr
import os
from crewai import Agent, Task, Crew, Process
from langchain_groq import ChatGroq
from langchain.schema import HumanMessage
import time

# Initialize the GROQ language model
try:
    groq_llm = ChatGroq(
        groq_api_key=os.environ["GROQ_API_KEY"],
        model_name="mixtral-8x7b-32768"
    )
except Exception as e:
    print(f"Error initializing GROQ LLM: {e}")
    groq_llm = None

def simple_groq_query(query):
    try:
        response = groq_llm([HumanMessage(content=query)])
        return response.content
    except Exception as e:
        print(f"Error in simple GROQ query: {e}")
        return f"I apologize, but I'm having trouble processing your request at the moment. Here's what I can say: {query} is an interesting topic. Could you please try again in a moment?"

# Create agents
def create_agent(role, goal, backstory):
    return Agent(
        role=role,
        goal=goal,
        backstory=backstory,
        verbose=True,
        allow_delegation=False,
        llm=groq_llm
    )

researcher = create_agent(
    'Senior Researcher',
    'Conduct thorough research on given topics',
    'You are an experienced researcher with a keen eye for detail and the ability to find relevant information quickly.'
)

writer = create_agent(
    'Content Writer',
    'Create engaging and informative content based on research',
    'You are a skilled writer capable of turning complex information into easily understandable and engaging content.'
)

editor = create_agent(
    'Editor',
    'Refine and improve the written content',
    'You are a meticulous editor with a strong command of language and an eye for clarity and coherence.'
)

def create_crew(query):
    # Create tasks
    research_task = Task(
        description=f"Research the following topic thoroughly: {query}",
        agent=researcher
    )

    writing_task = Task(
        description="Write an informative article based on the research conducted",
        agent=writer
    )

    editing_task = Task(
        description="Review and refine the written article, ensuring clarity, coherence, and engagement",
        agent=editor
    )

    # Create the crew
    crew = Crew(
        agents=[researcher, writer, editor],
        tasks=[research_task, writing_task, editing_task],
        verbose=2,
        process=Process.sequential
    )

    return crew

def process_query(query, max_tokens=500):
    try:
        if not groq_llm:
            raise Exception("GROQ LLM not initialized")
        
        crew = create_crew(query)
        result = crew.kickoff()
        return result
    except Exception as e:
        print(f"Error in process_query: {e}")
        return simple_groq_query(query)

# Create the Gradio interface
iface = gr.Interface(
    fn=process_query,
    inputs=[
        gr.Textbox(lines=5, label="Enter your query"),
        gr.Slider(minimum=100, maximum=1000, value=500, step=50, label="Max Tokens")
    ],
    outputs=gr.Textbox(lines=10, label="AI Agent Response"),
    title="CrewAI-powered Chatbot using GROQ and LangChain",
    description="Enter a query and get a researched, written, and edited response using CrewAI, GROQ API, and LangChain."
)

iface.launch()