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Create main.py
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main.py
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import re
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import os
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import json
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import requests
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import google.generativeai as genai
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from reportlab.lib.pagesizes import letter
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from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, ListFlowable, ListItem
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from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
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from fastapi import FastAPI, HTTPException, Query
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from fastapi.responses import FileResponse
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# ----------------------------
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# Helper functions (provided code)
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# ----------------------------
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def convert_markdown(text):
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"""
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Convert simple markdown bold markers **text** to HTML <b> tags.
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"""
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return re.sub(r"\*\*(.*?)\*\*", r"<b>\1</b>", text)
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def parse_report_text(report_text):
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"""
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Parse the generated report text and return a list of ReportLab flowables
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with proper headings, subheadings, and bullet-point formatting.
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Conventions used:
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- A line that starts and ends with '**' is treated as a heading.
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- Lines starting with '*' are treated as bullet items.
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- All other nonempty lines are treated as normal paragraphs.
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"""
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styles = getSampleStyleSheet()
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# You can tweak these styles if needed.
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heading_style = styles["Heading1"]
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subheading_style = styles["Heading2"]
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normal_style = styles["BodyText"]
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bullet_style = styles["Bullet"]
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flowables = []
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bullet_items = [] # temporary list for bullet items
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# Split the report text into lines.
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lines = report_text.splitlines()
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for line in lines:
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line = line.strip()
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# If the line is empty, flush any bullet list and add a spacer.
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if not line:
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if bullet_items:
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flowables.append(ListFlowable(bullet_items, bulletType='bullet', leftIndent=20))
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bullet_items = []
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flowables.append(Spacer(1, 12))
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continue
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# Check if line is a bullet point (starts with '*')
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if line.startswith("*"):
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bullet_text = line.lstrip("*").strip()
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bullet_text = convert_markdown(bullet_text)
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bullet_paragraph = Paragraph(bullet_text, bullet_style)
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bullet_items.append(bullet_paragraph)
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# Check if the entire line is a heading (starts and ends with '**')
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elif line.startswith("**") and line.endswith("**"):
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if bullet_items:
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flowables.append(ListFlowable(bullet_items, bulletType='bullet', leftIndent=20))
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bullet_items = []
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# Remove the asterisks and convert markdown if needed.
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heading_text = convert_markdown(line.strip("*").strip())
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flowables.append(Paragraph(heading_text, heading_style))
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else:
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if bullet_items:
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flowables.append(ListFlowable(bullet_items, bulletType='bullet', leftIndent=20))
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bullet_items = []
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# Otherwise, treat as normal paragraph.
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normal_text = convert_markdown(line)
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flowables.append(Paragraph(normal_text, normal_style))
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# Flush any remaining bullet items.
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if bullet_items:
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flowables.append(ListFlowable(bullet_items, bulletType='bullet', leftIndent=20))
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return flowables
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def get_pagespeed_data(target_url, pagespeed_api_key):
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"""
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Fetch data from the PageSpeed Insights API for the given URL.
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"""
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endpoint = "https://www.googleapis.com/pagespeedonline/v5/runPagespeed"
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params = {
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"url": target_url,
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"key": pagespeed_api_key
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}
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response = requests.get(endpoint, params=params)
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if response.status_code == 200:
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return response.json()
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else:
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raise Exception(f"Error fetching PageSpeed data: {response.status_code} - {response.text}")
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def generate_report_with_gemini(pagespeed_data, gemini_api_key):
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"""
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Uses the Gemini model to generate a detailed report based on the PageSpeed Insights data.
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"""
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# Configure the Gemini API with the provided key
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genai.configure(api_key=gemini_api_key)
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# Select a Gemini model. For this example, we use 'gemini-2.0-flash'.
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model = genai.GenerativeModel("gemini-2.0-flash")
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# Prepare the prompt including the pretty-printed JSON.
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prompt = (
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"Please generate a detailed and well-structured report on the website performance based "
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"on the following PageSpeed Insights data. Organize the report with clear headings, "
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"subheadings, and bullet points for key metrics and recommendations:\n\n" +
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json.dumps(pagespeed_data, indent=2)
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)
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# Generate the content using Gemini.
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response = model.generate_content(prompt)
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if response and hasattr(response, "text"):
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return response.text
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else:
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return "No report could be generated."
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def save_report_to_pdf(report_text, pdf_filename="pagespeed_report.pdf"):
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"""
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Format the report text into headings, subheadings, and bullet points, then save it as a PDF.
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"""
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# Create a SimpleDocTemplate for the PDF
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doc = SimpleDocTemplate(pdf_filename, pagesize=letter,
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rightMargin=72, leftMargin=72,
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topMargin=72, bottomMargin=72)
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# Parse the report text into platypus flowables
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flowables = parse_report_text(report_text)
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# Build the PDF document.
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doc.build(flowables)
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print(f"Report saved as {pdf_filename}")
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# ----------------------------
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# FastAPI App and Endpoints
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# ----------------------------
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app = FastAPI()
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# Load API keys from environment variables.
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PAGESPEED_API_KEY = os.environ.get("PAGESPEED_API_KEY")
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GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
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PDF_FILENAME = "pagespeed_report.pdf"
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if not PAGESPEED_API_KEY or not GEMINI_API_KEY:
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raise Exception("Please set the PAGESPEED_API_KEY and GEMINI_API_KEY environment variables.")
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@app.get("/")
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def read_root():
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"""
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Root endpoint providing basic information.
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"""
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return {
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"message": "Welcome to the PageSpeed Insights Report Generator API. "
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"Use /generate_report?url=<target_url> (POST) to generate a report and /download_pdf (GET) to download the PDF."
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}
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@app.post("/generate_report")
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def generate_report(url: str = Query(..., description="The target URL for which to generate the report")):
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"""
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Generates the report by:
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1. Fetching PageSpeed Insights data for the given URL.
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2. Generating a report via the Gemini API.
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3. Saving the report as a PDF.
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Returns the generated report text.
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"""
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try:
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# Step 1: Fetch PageSpeed data for the provided URL.
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pagespeed_data = get_pagespeed_data(url, PAGESPEED_API_KEY)
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# Step 2: Generate report using the Gemini API.
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report_text = generate_report_with_gemini(pagespeed_data, GEMINI_API_KEY)
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# Step 3: Save the report as a PDF.
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save_report_to_pdf(report_text, pdf_filename=PDF_FILENAME)
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return {"report": report_text}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/download_pdf")
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def download_pdf():
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"""
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Returns the generated PDF file for download.
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Make sure you have already called /generate_report.
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"""
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if not os.path.exists(PDF_FILENAME):
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raise HTTPException(status_code=404, detail="PDF report not found. Please generate the report first.")
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return FileResponse(PDF_FILENAME, media_type="application/pdf", filename=PDF_FILENAME)
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# To run the app, use the command:
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# uvicorn main:app --reload
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