Merge pull request #82 from Madhuvod/ai-competitor-search
Added new demo: AI Competitor Intelligence Agent
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Shubham Saboo
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ai_agent_tutorials/ai_competitors_analysis_team/README.md
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ai_agent_tutorials/ai_competitors_analysis_team/README.md
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# AI Competitor Intelligence Agent 🔍
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The AI Competitor Intelligence Agent is a powerful competitor analysis tool powered by Firecrawl and Phidata's AI Agent framework. This app helps businesses analyze their competitors by extracting structured data from competitor websites and generating actionable insights using AI.
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## Features
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- **Multi-Agent System**
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- **Firecrawl Agent**: Specializes in crawling and summarizing competitor websites
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- **Analysis Agent**: Generates detailed competitive analysis reports
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- **Comparison Agent**: Creates structured comparisons between competitors
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- **Competitor Discovery**:
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- Finds similar companies using URL matching with Exa AI
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- Discovers competitors based on business descriptions
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- Automatically extracts relevant competitor URLs
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- **Comprehensive Analysis**:
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- Provides structured analysis reports with:
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- Market gaps and opportunities
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- Competitor weaknesses
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- Recommended features
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- Pricing strategies
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- Growth opportunities
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- Actionable recommendations
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- **Interactive Analysis**: Users can input either their company URL or description for analysis
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## Requirements
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The application requires the following Python libraries:
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- `phidata`
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- `exa-py`
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- `streamlit`
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- `pandas`
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- `firecrawl-py`
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You'll also need API keys for:
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- OpenAI
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- Firecrawl
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- Exa
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## How to Run
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Follow these steps to set up and run the application:
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1. **Clone the Repository**:
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```bash
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git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
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cd ai_agent_tutorials/ai_competitors_analysis_team
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```
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2. **Install the dependencies**:
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```bash
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pip install -r requirements.txt
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```
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3. **Set up your API keys**:
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- Get an OpenAI API key from: https://platform.openai.com/api-keys
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- Get a Firecrawl API key from: [Firecrawl website](https://www.firecrawl.dev/app/api-keys)
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- Get an Exa API key from: [Exa website](https://dashboard.exa.ai/api-keys)
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4. **Run the Streamlit app**:
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```bash
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streamlit run ai_competitor_analyser.py
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```
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## Usage
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1. Enter your API keys in the sidebar
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2. Input either:
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- Your company's website URL
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- A description of your company
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3. Click "Analyze Competitors" to generate:
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- Competitor comparison table
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- Detailed analysis report
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- Strategic recommendations
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import streamlit as st
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from exa_py import Exa
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from phi.agent import Agent
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from phi.tools.firecrawl import FirecrawlTools
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from phi.model.openai import OpenAIChat
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from phi.tools.duckduckgo import DuckDuckGo
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import pandas as pd
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# Streamlit UI
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st.set_page_config(page_title="AI Competitor Intelligence Agent", layout="wide")
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# Sidebar for API keys
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st.sidebar.title("API Keys")
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openai_api_key = st.sidebar.text_input("OpenAI API Key", type="password")
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firecrawl_api_key = st.sidebar.text_input("Firecrawl API Key", type="password")
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exa_api_key = st.sidebar.text_input("Exa API Key", type="password")
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# Store API keys in session state
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if openai_api_key and firecrawl_api_key and exa_api_key:
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st.session_state.openai_api_key = openai_api_key
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st.session_state.firecrawl_api_key = firecrawl_api_key
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st.session_state.exa_api_key = exa_api_key
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else:
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st.sidebar.warning("Please enter all API keys to proceed.")
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# Main UI
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st.title("AI Competitor Intelligence Agent")
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st.info(
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"""
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This app helps businesses analyze their competitors by extracting structured data from competitor websites and generating insights using AI.
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- Provide a **URL** or a **description** of your company.
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- The app will fetch competitor URLs, extract relevant information, and generate a detailed analysis report.
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"""
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)
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# Input fields for URL and description
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url = st.text_input("Enter your company URL :")
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description = st.text_area("Enter a description of your company (if URL is not available):")
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# Initialize API keys and tools
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if "openai_api_key" in st.session_state and "firecrawl_api_key" in st.session_state and "exa_api_key" in st.session_state:
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exa = Exa(api_key=st.session_state.exa_api_key)
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firecrawl_tools = FirecrawlTools(
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api_key=st.session_state.firecrawl_api_key,
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scrape=False,
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crawl=True,
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limit=5
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)
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firecrawl_agent = Agent(
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model=OpenAIChat(id="gpt-4o-mini", api_key=st.session_state.openai_api_key),
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tools=[firecrawl_tools, DuckDuckGo()],
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show_tool_calls=True,
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markdown=True
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)
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analysis_agent = Agent(
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model=OpenAIChat(id="gpt-4o-mini", api_key=st.session_state.openai_api_key),
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show_tool_calls=True,
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markdown=True
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)
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# New agent for comparing competitor data
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comparison_agent = Agent(
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model=OpenAIChat(id="gpt-4o-mini", api_key=st.session_state.openai_api_key),
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show_tool_calls=True,
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markdown=True
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)
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def get_competitor_urls(url=None, description=None):
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if url:
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result = exa.find_similar(
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url=url,
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num_results=3,
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exclude_source_domain=True,
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category="company"
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)
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elif description:
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result = exa.search(
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description,
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type="neural",
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category="company",
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use_autoprompt=True,
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num_results=3
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)
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else:
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raise ValueError("Please provide either a URL or a description.")
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competitor_urls = [item.url for item in result.results]
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return competitor_urls
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def extract_competitor_info(competitor_url: str):
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try:
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crawl_response = firecrawl_agent.run(f"Crawl and summarize {competitor_url}")
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crawled_data = crawl_response.content
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return {
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"competitor": competitor_url,
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"data": crawled_data
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}
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except Exception as e:
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st.error(f"Error extracting info for {competitor_url}: {e}")
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return {
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"competitor": competitor_url,
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"error": str(e)
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}
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def generate_comparison_report(competitor_data: list) -> None:
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"""
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Generate and display a comparison report of competitor data.
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Args:
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competitor_data: List of dictionaries containing competitor information
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"""
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# Combine all competitor data into a single string
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combined_data = "\n\n".join([str(data) for data in competitor_data])
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# Updated system prompt for more structured output
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system_prompt = """
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As an expert business analyst, analyze the competitor data and create a structured comparison table.
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Format the data in EXACTLY this markdown table structure:
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| Company | Pricing | Key Features | Tech Stack | Marketing Focus | Customer Feedback |
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|---------|---------|--------------|------------|-----------------|-------------------|
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| [Company Name 1] | ... | ... | ... | ... | ... |
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| [Company Name 2] | ... | ... | ... | ... | ... |
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| [Company Name 3] | ... | ... | ... | ... | ... |
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Rules:
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1. Always include all columns
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2. Use the exact column names specified above
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3. Keep entries concise but informative
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4. Use pipe symbols (|) to separate columns
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5. Include the separator row (|---|) after headers
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Competitor Data:
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{combined_data}
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"""
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# Get comparison table from agent
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comparison_response = comparison_agent.run(
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system_prompt.format(combined_data=combined_data)
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)
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# Display the raw markdown table first
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st.subheader("Competitor Comparison")
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st.markdown(comparison_response.content)
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try:
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# Split the markdown table into lines and clean them
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table_lines = [
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line.strip()
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for line in comparison_response.content.split('\n')
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if line.strip() and '|' in line
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]
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# Extract headers (first row)
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headers = [
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col.strip()
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for col in table_lines[0].split('|')
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if col.strip()
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]
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# Extract data rows (skip header and separator rows)
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data_rows = []
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for line in table_lines[2:]: # Skip header and separator rows
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row_data = [
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cell.strip()
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for cell in line.split('|')
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if cell.strip()
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]
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if len(row_data) == len(headers):
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data_rows.append(row_data)
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# Create DataFrame with explicit index
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df = pd.DataFrame(
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data_rows,
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columns=headers,
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index=range(len(data_rows))
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)
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# # Display the DataFrame
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# st.subheader("Competitor Comparison Table")
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# st.table(df)
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except Exception as e:
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st.error(f"Error converting table to DataFrame: {str(e)}")
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st.write("Raw table data for debugging:", table_lines)
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def generate_analysis_report(competitor_data: list):
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combined_data = "\n\n".join([str(data) for data in competitor_data])
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report = analysis_agent.run(
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f"""Analyze the following competitor data and identify market opportunities to improve my own company:
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{combined_data}
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Tasks:
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1. Identify market gaps and opportunities based on competitor offerings
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2. Analyze competitor weaknesses that we can capitalize on
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3. Recommend unique features or capabilities we should develop
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4. Suggest pricing and positioning strategies to gain competitive advantage
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5. Outline specific growth opportunities in underserved market segments
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6. Provide actionable recommendations for product development and go-to-market strategy
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Focus on finding opportunities where we can differentiate and do better than competitors.
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Highlight any unmet customer needs or pain points we can address.
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"""
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)
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return report.content
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# Run analysis when the user clicks the button
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if st.button("Analyze Competitors"):
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if url or description:
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with st.spinner("Fetching competitor URLs..."):
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competitor_urls = get_competitor_urls(url=url, description=description)
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st.write(f"Competitor URLs: {competitor_urls}")
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competitor_data = []
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for url in competitor_urls:
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with st.spinner(f"Analyzing Competitor: {url}..."):
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competitor_info = extract_competitor_info(url)
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competitor_data.append(competitor_info)
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# Generate and display comparison report
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with st.spinner("Generating comparison table..."):
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generate_comparison_report(competitor_data)
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# Generate and display final analysis report
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with st.spinner("Generating analysis report..."):
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analysis_report = generate_analysis_report(competitor_data)
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st.subheader("Competitor Analysis Report")
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st.markdown(analysis_report)
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st.success("Analysis complete!")
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else:
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st.error("Please provide either a URL or a description.")
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@ -0,0 +1,5 @@
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exa-py==1.7.1
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firecrawl-py==1.9.0
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duckduckgo-search==7.2.1
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phidata==2.7.3
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streamlit==1.41.1
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