clean code - few features to ad
This commit is contained in:
Madhu
parent
0aa4db198c
commit
d161adc3a0
3 changed files with 154 additions and 158 deletions
|
|
@ -0,0 +1,154 @@
|
||||||
|
import streamlit as st
|
||||||
|
from exa_py import Exa
|
||||||
|
from phi.agent import Agent
|
||||||
|
from phi.tools.firecrawl import FirecrawlTools
|
||||||
|
from phi.model.openai import OpenAIChat
|
||||||
|
from phi.tools.duckduckgo import DuckDuckGo
|
||||||
|
|
||||||
|
# Streamlit UI
|
||||||
|
st.set_page_config(page_title="AI Competitor Intelligence Agent", layout="wide")
|
||||||
|
|
||||||
|
# Sidebar for API keys
|
||||||
|
st.sidebar.title("API Keys")
|
||||||
|
openai_api_key = st.sidebar.text_input("OpenAI API Key", type="password")
|
||||||
|
firecrawl_api_key = st.sidebar.text_input("Firecrawl API Key", type="password")
|
||||||
|
exa_api_key = st.sidebar.text_input("Exa API Key", type="password")
|
||||||
|
|
||||||
|
# Store API keys in session state
|
||||||
|
if openai_api_key and firecrawl_api_key and exa_api_key:
|
||||||
|
st.session_state.openai_api_key = openai_api_key
|
||||||
|
st.session_state.firecrawl_api_key = firecrawl_api_key
|
||||||
|
st.session_state.exa_api_key = exa_api_key
|
||||||
|
else:
|
||||||
|
st.sidebar.warning("Please enter all API keys to proceed.")
|
||||||
|
|
||||||
|
# Main UI
|
||||||
|
st.title("AI Competitor Intelligence Agent")
|
||||||
|
st.info(
|
||||||
|
"""
|
||||||
|
This app helps businesses analyze their competitors by extracting structured data from competitor websites and generating insights using AI.
|
||||||
|
- Provide a **URL** or a **description** of your company.
|
||||||
|
- The app will fetch competitor URLs, extract relevant information, and generate a detailed analysis report.
|
||||||
|
"""
|
||||||
|
)
|
||||||
|
|
||||||
|
# Input fields for URL and description
|
||||||
|
url = st.text_input("Enter your company URL (optional):")
|
||||||
|
description = st.text_area("Enter a description of your company (if URL is not available):")
|
||||||
|
|
||||||
|
# Initialize API keys and tools
|
||||||
|
if "openai_api_key" in st.session_state and "firecrawl_api_key" in st.session_state and "exa_api_key" in st.session_state:
|
||||||
|
exa = Exa(api_key=st.session_state.exa_api_key)
|
||||||
|
|
||||||
|
firecrawl_tools = FirecrawlTools(
|
||||||
|
api_key=st.session_state.firecrawl_api_key,
|
||||||
|
scrape=False,
|
||||||
|
crawl=True,
|
||||||
|
limit=5
|
||||||
|
)
|
||||||
|
|
||||||
|
firecrawl_agent = Agent(
|
||||||
|
model=OpenAIChat(id="gpt-4", api_key=st.session_state.openai_api_key),
|
||||||
|
tools=[firecrawl_tools, DuckDuckGo()],
|
||||||
|
show_tool_calls=True,
|
||||||
|
markdown=True
|
||||||
|
)
|
||||||
|
|
||||||
|
analysis_agent = Agent(
|
||||||
|
model=OpenAIChat(id="gpt-4", api_key=st.session_state.openai_api_key),
|
||||||
|
show_tool_calls=True,
|
||||||
|
markdown=True
|
||||||
|
)
|
||||||
|
|
||||||
|
def get_competitor_urls(url=None, description=None):
|
||||||
|
if url:
|
||||||
|
result = exa.find_similar(
|
||||||
|
url=url,
|
||||||
|
num_results=2,
|
||||||
|
exclude_source_domain=True,
|
||||||
|
category="company"
|
||||||
|
)
|
||||||
|
elif description:
|
||||||
|
result = exa.search(
|
||||||
|
description,
|
||||||
|
type="neural",
|
||||||
|
category="company",
|
||||||
|
use_autoprompt=True,
|
||||||
|
num_results=2
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
raise ValueError("Please provide either a URL or a description.")
|
||||||
|
|
||||||
|
competitor_urls = [item.url for item in result.results]
|
||||||
|
return competitor_urls
|
||||||
|
|
||||||
|
def extract_competitor_info(competitor_url: str):
|
||||||
|
try:
|
||||||
|
crawl_response = firecrawl_agent.run(f"Crawl and summarize {competitor_url}")
|
||||||
|
crawled_data = crawl_response.content
|
||||||
|
|
||||||
|
structured_info = firecrawl_agent.run(
|
||||||
|
f"""Extract the following information from the crawled data:
|
||||||
|
- Product pricing and features: Extract exact pricing numbers from their pricing page.
|
||||||
|
- Technology stack information
|
||||||
|
- Marketing messaging/positioning
|
||||||
|
- Customer testimonials/case studies
|
||||||
|
- Latest news and developments (use DuckDuckGo to search for the latest news and developments)
|
||||||
|
|
||||||
|
Crawled Data:
|
||||||
|
{crawled_data}
|
||||||
|
"""
|
||||||
|
)
|
||||||
|
|
||||||
|
return {
|
||||||
|
"competitor": competitor_url,
|
||||||
|
"data": structured_info.content
|
||||||
|
}
|
||||||
|
except Exception as e:
|
||||||
|
return {
|
||||||
|
"competitor": competitor_url,
|
||||||
|
"error": str(e)
|
||||||
|
}
|
||||||
|
|
||||||
|
def generate_analysis_report(competitor_data: list):
|
||||||
|
combined_data = "\n\n".join([str(data) for data in competitor_data])
|
||||||
|
|
||||||
|
report = analysis_agent.run(
|
||||||
|
f"""Analyze the following competitor data and identify market opportunities to improve my own company:
|
||||||
|
{combined_data}
|
||||||
|
|
||||||
|
Tasks:
|
||||||
|
1. Identify market gaps and opportunities based on competitor offerings
|
||||||
|
2. Analyze competitor weaknesses that we can capitalize on
|
||||||
|
3. Recommend unique features or capabilities we should develop
|
||||||
|
4. Suggest pricing and positioning strategies to gain competitive advantage
|
||||||
|
5. Outline specific growth opportunities in underserved market segments
|
||||||
|
6. Provide actionable recommendations for product development and go-to-market strategy
|
||||||
|
|
||||||
|
Focus on finding opportunities where we can differentiate and do better than competitors.
|
||||||
|
Highlight any unmet customer needs or pain points we can address.
|
||||||
|
"""
|
||||||
|
)
|
||||||
|
return report.content
|
||||||
|
|
||||||
|
# Run analysis when the user clicks the button
|
||||||
|
if st.button("Analyze Competitors"):
|
||||||
|
if url or description:
|
||||||
|
with st.spinner("Fetching competitor URLs..."):
|
||||||
|
competitor_urls = get_competitor_urls(url=url, description=description)
|
||||||
|
st.write(f"Competitor URLs: {competitor_urls}")
|
||||||
|
|
||||||
|
competitor_data = []
|
||||||
|
for url in competitor_urls:
|
||||||
|
with st.spinner(f"Analyzing Competitor: {url}..."):
|
||||||
|
competitor_info = extract_competitor_info(url)
|
||||||
|
competitor_data.append(competitor_info)
|
||||||
|
|
||||||
|
with st.spinner("Generating analysis report..."):
|
||||||
|
analysis_report = generate_analysis_report(competitor_data)
|
||||||
|
|
||||||
|
st.success("Analysis complete!")
|
||||||
|
st.subheader("Competitor Analysis Report")
|
||||||
|
st.markdown(analysis_report)
|
||||||
|
else:
|
||||||
|
st.error("Please provide either a URL or a description.")
|
||||||
|
|
@ -1,41 +0,0 @@
|
||||||
from phi.agent import Agent
|
|
||||||
from phi.tools.firecrawl import FirecrawlTools
|
|
||||||
from phi.model.openai import OpenAIChat
|
|
||||||
|
|
||||||
firecrawl_tools = FirecrawlTools(
|
|
||||||
api_key="",
|
|
||||||
scrape=False,
|
|
||||||
crawl=True,
|
|
||||||
limit=5
|
|
||||||
)
|
|
||||||
|
|
||||||
agent = Agent(
|
|
||||||
model=OpenAIChat(id="gpt-4o-mini", api_key=""),
|
|
||||||
tools=[firecrawl_tools],
|
|
||||||
show_tool_calls=True,
|
|
||||||
markdown=True
|
|
||||||
)
|
|
||||||
|
|
||||||
def extract_competitor_info(competitor_url: str):
|
|
||||||
crawl_response = agent.run(f"Crawl and summarize {competitor_url}")
|
|
||||||
crawled_data = crawl_response.content
|
|
||||||
|
|
||||||
structured_info = agent.run(
|
|
||||||
f"""Extract the following information from the crawled data:
|
|
||||||
- Product pricing and features - exact pricing numbers from their pricing page
|
|
||||||
- Technology stack information
|
|
||||||
- Marketing messaging/positioning
|
|
||||||
- Customer testimonials/case studies
|
|
||||||
|
|
||||||
Crawled Data:
|
|
||||||
{crawled_data}
|
|
||||||
"""
|
|
||||||
)
|
|
||||||
|
|
||||||
return structured_info.content
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
competitor_url = "https://www.equal.in"
|
|
||||||
competitor_info = extract_competitor_info(competitor_url)
|
|
||||||
print(f"Competitor: {competitor_url}")
|
|
||||||
print(competitor_info)
|
|
||||||
|
|
@ -1,117 +0,0 @@
|
||||||
from exa_py import Exa
|
|
||||||
from phi.agent import Agent
|
|
||||||
from phi.tools.firecrawl import FirecrawlTools
|
|
||||||
from phi.model.openai import OpenAIChat
|
|
||||||
from phi.tools.duckduckgo import DuckDuckGo
|
|
||||||
|
|
||||||
exa = Exa(api_key="")
|
|
||||||
|
|
||||||
firecrawl_tools = FirecrawlTools(
|
|
||||||
api_key="fc-",
|
|
||||||
scrape=False,
|
|
||||||
crawl=True,
|
|
||||||
limit=5
|
|
||||||
)
|
|
||||||
|
|
||||||
firecrawl_agent = Agent(
|
|
||||||
model=OpenAIChat(id="gpt-4o-mini", api_key="sk-proj-"),
|
|
||||||
tools=[firecrawl_tools, DuckDuckGo() ],
|
|
||||||
show_tool_calls=True,
|
|
||||||
markdown=True
|
|
||||||
)
|
|
||||||
|
|
||||||
analysis_agent = Agent(
|
|
||||||
model=OpenAIChat(id="gpt-4o-mini", api_key="sk-proj-"),
|
|
||||||
show_tool_calls=True,
|
|
||||||
markdown=True
|
|
||||||
)
|
|
||||||
|
|
||||||
def get_competitor_urls(url=None, description=None):
|
|
||||||
|
|
||||||
if url:
|
|
||||||
result = exa.find_similar(
|
|
||||||
url=url,
|
|
||||||
num_results=2,
|
|
||||||
exclude_source_domain=True,
|
|
||||||
category="company"
|
|
||||||
)
|
|
||||||
elif description:
|
|
||||||
result = exa.search(
|
|
||||||
description,
|
|
||||||
type="neural",
|
|
||||||
category="company",
|
|
||||||
use_autoprompt=True,
|
|
||||||
num_results=2
|
|
||||||
)
|
|
||||||
else:
|
|
||||||
raise ValueError("Please provide either a URL or a description.")
|
|
||||||
|
|
||||||
competitor_urls = [item.url for item in result.results]
|
|
||||||
return competitor_urls
|
|
||||||
|
|
||||||
def extract_competitor_info(competitor_url: str):
|
|
||||||
try:
|
|
||||||
crawl_response = firecrawl_agent.run(f"Crawl and summarize {competitor_url}")
|
|
||||||
crawled_data = crawl_response.content
|
|
||||||
|
|
||||||
structured_info = firecrawl_agent.run(
|
|
||||||
f"""Extract the following information from the crawled data:
|
|
||||||
- Product pricing and features: Extract exact pricing numbers from their pricing page.
|
|
||||||
- Technology stack information
|
|
||||||
- Marketing messaging/positioning
|
|
||||||
- Customer testimonials/case studies
|
|
||||||
- Latest news and developements (use DuckDuckGo to search for the latest news and developements)
|
|
||||||
|
|
||||||
Crawled Data:
|
|
||||||
{crawled_data}
|
|
||||||
"""
|
|
||||||
)
|
|
||||||
|
|
||||||
return {
|
|
||||||
"competitor": competitor_url,
|
|
||||||
"data": structured_info.content
|
|
||||||
}
|
|
||||||
except Exception as e:
|
|
||||||
return {
|
|
||||||
"competitor": competitor_url,
|
|
||||||
"error": str(e)
|
|
||||||
}
|
|
||||||
|
|
||||||
def generate_analysis_report(competitor_data: list):
|
|
||||||
combined_data = "\n\n".join([str(data) for data in competitor_data])
|
|
||||||
|
|
||||||
report = analysis_agent.run(
|
|
||||||
f"""Analyze the following competitor data and identify market opportunities to improve my own company:
|
|
||||||
{combined_data}
|
|
||||||
|
|
||||||
Tasks:
|
|
||||||
1. Identify market gaps and opportunities based on competitor offerings
|
|
||||||
2. Analyze competitor weaknesses that we can capitalize on
|
|
||||||
3. Recommend unique features or capabilities we should develop
|
|
||||||
4. Suggest pricing and positioning strategies to gain competitive advantage
|
|
||||||
5. Outline specific growth opportunities in underserved market segments
|
|
||||||
6. Provide actionable recommendations for product development and go-to-market strategy
|
|
||||||
|
|
||||||
Focus on finding opportunities where we can differentiate and do better than competitors.
|
|
||||||
Highlight any unmet customer needs or pain points we can address.
|
|
||||||
"""
|
|
||||||
)
|
|
||||||
return report.content
|
|
||||||
|
|
||||||
def main():
|
|
||||||
competitor_urls = get_competitor_urls(url="https://www.harvey.ai")
|
|
||||||
print(f"Competitor URLs: {competitor_urls}")
|
|
||||||
|
|
||||||
competitor_data = []
|
|
||||||
for url in competitor_urls:
|
|
||||||
print(f"\nAnalyzing Competitor: {url}")
|
|
||||||
competitor_info = extract_competitor_info(url)
|
|
||||||
competitor_data.append(competitor_info)
|
|
||||||
|
|
||||||
analysis_report = generate_analysis_report(competitor_data)
|
|
||||||
|
|
||||||
print("\nCompetitor Analysis Report:")
|
|
||||||
print(analysis_report)
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
main()
|
|
||||||
Loading…
Reference in a new issue