clean code - few features to ad
This commit is contained in:
Madhu
parent
0aa4db198c
commit
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3 changed files with 154 additions and 158 deletions
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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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# 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 (optional):")
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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-4", 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-4", 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=2,
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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=2
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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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structured_info = firecrawl_agent.run(
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f"""Extract the following information from the crawled data:
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- Product pricing and features: Extract exact pricing numbers from their pricing page.
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- Technology stack information
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- Marketing messaging/positioning
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- Customer testimonials/case studies
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- Latest news and developments (use DuckDuckGo to search for the latest news and developments)
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Crawled Data:
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{crawled_data}
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"""
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)
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return {
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"competitor": competitor_url,
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"data": structured_info.content
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}
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except Exception as 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_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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with st.spinner("Generating analysis report..."):
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analysis_report = generate_analysis_report(competitor_data)
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st.success("Analysis complete!")
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st.subheader("Competitor Analysis Report")
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st.markdown(analysis_report)
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else:
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st.error("Please provide either a URL or a description.")
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@ -1,41 +0,0 @@
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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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firecrawl_tools = FirecrawlTools(
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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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agent = Agent(
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model=OpenAIChat(id="gpt-4o-mini", api_key=""),
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tools=[firecrawl_tools],
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show_tool_calls=True,
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markdown=True
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)
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def extract_competitor_info(competitor_url: str):
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crawl_response = agent.run(f"Crawl and summarize {competitor_url}")
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crawled_data = crawl_response.content
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structured_info = agent.run(
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f"""Extract the following information from the crawled data:
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- Product pricing and features - exact pricing numbers from their pricing page
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- Technology stack information
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- Marketing messaging/positioning
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- Customer testimonials/case studies
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Crawled Data:
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{crawled_data}
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"""
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)
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return structured_info.content
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if __name__ == "__main__":
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competitor_url = "https://www.equal.in"
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competitor_info = extract_competitor_info(competitor_url)
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print(f"Competitor: {competitor_url}")
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print(competitor_info)
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@ -1,117 +0,0 @@
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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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exa = Exa(api_key="")
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firecrawl_tools = FirecrawlTools(
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api_key="fc-",
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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="sk-proj-"),
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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="sk-proj-"),
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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=2,
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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=2
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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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structured_info = firecrawl_agent.run(
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f"""Extract the following information from the crawled data:
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- Product pricing and features: Extract exact pricing numbers from their pricing page.
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- Technology stack information
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- Marketing messaging/positioning
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- Customer testimonials/case studies
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- Latest news and developements (use DuckDuckGo to search for the latest news and developements)
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Crawled Data:
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{crawled_data}
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"""
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)
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return {
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"competitor": competitor_url,
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"data": structured_info.content
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}
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except Exception as 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_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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def main():
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competitor_urls = get_competitor_urls(url="https://www.harvey.ai")
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print(f"Competitor URLs: {competitor_urls}")
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competitor_data = []
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for url in competitor_urls:
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print(f"\nAnalyzing 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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analysis_report = generate_analysis_report(competitor_data)
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print("\nCompetitor Analysis Report:")
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print(analysis_report)
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if __name__ == "__main__":
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main()
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