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from serp_tool import search_google
from llm_tool import analyze_data
def run_analysis(input_type, query):
"""
Core agent logic to handle different analysis types
"""
if input_type == "Competitor Analysis":
raw_data = search_google(f"site:{query} reviews pricing features")
prompt = f"""Analyze competitor {query} using these reviews and features: {raw_data}
Generate a detailed SWOT analysis:
1. Strengths
2. Weaknesses
3. Opportunities
4. Threats
Include pricing strategy insights and customer sentiment summary."""
elif input_type == "Keyword Research":
raw_data = search_google(f"best keywords for {query}")
prompt = f"""Generate SEO keyword report for "{query}" using: {raw_data}
List:
1. Top 5 keywords (with search volume and CPC)
2. Content gap opportunities
3. Backlink strategies
4. Competitor keyword analysis"""
elif input_type == "Trend Discovery":
raw_data = search_google(f"latest trends in {query} 2024")
prompt = f"""Identify emerging trends in "{query}" using: {raw_data}
Report:
1. Top 3 trends
2. Viral content patterns
3. Customer pain points
4. Opportunity areas"""
elif input_type == "Idea Validation":
raw_data = search_google(f"market demand for {query}")
prompt = f"""Validate business idea "{query}" using market data: {raw_data}
Assess:
1. Market demand score (1-10)
2. Competitor saturation
3. Pricing benchmarks
4. Go-to-market strategy"""
else:
return "Invalid analysis type selected"
return analyze_data(prompt) |