app.py

import gradio as gr
from transformers import pipeline

# Load a more capable open-source model
strategy_generator = pipeline("text2text-generation", model="google/flan-t5-large")

# Function to clean up repetitive or irrelevant sentences in generated text
def clean_output(text):
    sentences = text.split(". ")
    seen = set()
    cleaned_sentences = []
    for sentence in sentences:
        if sentence.strip() not in seen:
            seen.add(sentence.strip())
            cleaned_sentences.append(sentence.strip())
    return ". ".join(cleaned_sentences)

# Function to generate a business strategy
def generate_strategy(industry, challenge, goals):
    prompt = f"""
    You are a business consultant with expertise in the {industry} industry.
    The company faces the following challenge: {challenge}.
    The company's goal is to achieve: {goals}.
    Provide a detailed strategy that includes:
    1. Three to five actionable steps.
    2. For each step, explain WHY it is recommended and HOW to implement it.
    Example format:
    1. Actionable Step: Description
       - Why: Reasoning for this step.
       - How: Implementation details.
    """
    try:
        response = strategy_generator(prompt, max_length=500, num_return_sequences=1, temperature=0.7, top_p=0.9)
        cleaned_response = clean_output(response[0]['generated_text'])
        return cleaned_response
    except Exception as e:
        return f"Error generating strategy: {e}"

# Function to perform a SWOT analysis
def swot_analysis(strengths, weaknesses, opportunities, threats):
    prompt = f"""
    You are a business consultant performing a SWOT analysis for a company.
    - Strengths: {strengths}
    - Weaknesses: {weaknesses}
    - Opportunities: {opportunities}
    - Threats: {threats}
    Provide detailed insights for each category, and include specific recommendations for improvement.
    """
    try:
        response = strategy_generator(prompt, max_length=300, num_return_sequences=1, temperature=0.7, top_p=0.9)
        cleaned_response = clean_output(response[0]['generated_text'])
        return cleaned_response
    except Exception as e:
        return f"Error generating SWOT analysis: {e}"

# Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# AI Business Strategy Generator")
    gr.Markdown("Generate actionable business strategies and SWOT analyses using AI.")

    # Tab 1: Generate Business Strategy
    with gr.Tab("Generate Strategy"):
        gr.Markdown("### Input Information to Generate a Business Strategy")
        industry_input = gr.Textbox(label="Industry", placeholder="E.g., E-commerce, Healthcare")
        challenge_input = gr.Textbox(label="Key Challenge", placeholder="E.g., Low customer retention")
        goals_input = gr.Textbox(label="Goals", placeholder="E.g., Increase sales by 20% in 6 months")
        strategy_button = gr.Button("Generate Strategy")
        strategy_output = gr.Textbox(label="Generated Strategy", lines=10)

        strategy_button.click(
            generate_strategy,
            inputs=[industry_input, challenge_input, goals_input],
            outputs=[strategy_output]
        )

    # Tab 2: SWOT Analysis
    with gr.Tab("SWOT Analysis"):
        gr.Markdown("### Input Information to Perform a SWOT Analysis")
        strengths_input = gr.Textbox(label="Strengths", placeholder="E.g., Strong brand presence")
        weaknesses_input = gr.Textbox(label="Weaknesses", placeholder="E.g., Limited market reach")
        opportunities_input = gr.Textbox(label="Opportunities", placeholder="E.g., Emerging markets")
        threats_input = gr.Textbox(label="Threats", placeholder="E.g., Rising competition")
        swot_button = gr.Button("Perform SWOT Analysis")
        swot_output = gr.Textbox(label="Generated SWOT Analysis", lines=10)

        swot_button.click(
            swot_analysis,
            inputs=[strengths_input, weaknesses_input, opportunities_input, threats_input],
            outputs=[swot_output]
        )

# Launch the Gradio app
demo.launch()