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Sobit commited on Sep 30, 2024

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Create app.py

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+import os
+from google.colab import userdata
+import litellm
+from crewai import Agent, Task, Crew, Process
+from crewai_tools import SerperDevTool
+import pdfplumber
+from docx import Document
+import gradio as gr
+# Set up API keys
+litellm.api_key = userdata.get("GOOGLE_API_KEY")
+os.environ['SERPER_API_KEY'] = userdata.get('SERPER_API_KEY')
+# Define the LLM
+llm = "gemini/gemini-1.5-flash-exp-0827"  # Your LLM model
+# Initialize the tool for internet searching capabilities
+tool = SerperDevTool()
+# Create the CV Analysis Agent
+cv_analysis_agent = Agent(
+    role="CV Analyzer",
+    goal='Analyze the given CV and extract key skills and experiences and make improvements if needed for portfolio creation.',
+    verbose=True,
+    memory=True,
+    backstory=(
+        "As a CV Analyzer, you are skilled in identifying key information "
+        "from resumes to aid in building effective portfolios."
+        "You can add relevant skills and job responsibilities evaluating the whole cv."
+    ),
+    tools=[tool],
+    llm=llm,
+    allow_delegation=True
+)
+# Create the Portfolio Generation Agent
+portfolio_generation_agent = Agent(
+    role='Portfolio Generator',
+    goal='Generate a beautiful static HTML/CSS/JS landing portfolio webpage based on CV analysis.',
+    verbose=True,
+    memory=True,
+    backstory=(
+        "As a Portfolio Generator, you craft engaging web pages with effective functionalities and color combinations "
+        "to showcase individual talents and experiences with the best user experience."
+    ),
+    tools=[tool],
+    llm=llm,
+    allow_delegation=False
+)
+# Research task for CV analysis
+cv_analysis_task = Task(
+    description=(
+        "Analyze the provided {cv} and identify key skills, experiences, "
+        "and accomplishments. Highlight notable projects and educational background."
+    ),
+    expected_output='A summary of skills, experiences, and projects formatted for a portfolio.',
+    tools=[tool],
+    agent=cv_analysis_agent,
+)
+# Writing task for portfolio generation with enhanced UI requirements
+portfolio_task = Task(
+    description=(
+        "Generate a static HTML/CSS/JS landing portfolio with a name as header in top, navbar for different sections, beautiful and responsive design. "
+        "Ensure that the layout is clean, with sections for skills, projects, experiences, certifications, publications, and contact details if present in the CV. "
+        "Include a footer that does not overlap with the content. "
+        "Use a modern color palette and incorporate CSS frameworks if necessary, "
+        "but provide everything embedded in the HTML file. "
+        "The output should be a complete HTML document starting from <html> to </html>, ready to deploy."
+    ),
+    expected_output='A complete HTML/CSS/JS code content only for a portfolio website in a single .html file',
+    tools=[tool],
+    agent=portfolio_generation_agent,
+    async_execution=False,
+    output_file='portfolio.html'  # Output as HTML file
+)
+# Function to read CV from PDF or DOCX file
+def read_cv_file(file_path):
+    ext = os.path.splitext(file_path)[1].lower()
+    cv_content = ""
+    if ext == '.pdf':
+        with pdfplumber.open(file_path) as pdf:
+            for page in pdf.pages:
+                cv_content += page.extract_text()
+    elif ext == '.docx':
+        doc = Document(file_path)
+        for para in doc.paragraphs:
+            cv_content += para.text + "\n"
+    else:
+        raise ValueError("Unsupported file format. Please use .pdf or .docx.")
+    return cv_content.strip()
+# Create a Crew for processing
+crew = Crew(
+    agents=[cv_analysis_agent, portfolio_generation_agent],
+    tasks=[cv_analysis_task, portfolio_task],
+    process=Process.sequential,
+)
+# Function to process CV and generate portfolio
+import re
+# Function to process CV and generate portfolio
+def process_cv(file):
+    try:
+        cv_file_content = read_cv_file(file.name)
+        result = crew.kickoff(inputs={'cv': cv_file_content})
+        # Print the entire result object to explore its contents (for debugging)
+        print(result)
+        # Convert the result to string
+        html_output = str(result)
+        # Use replace to remove '''html''' and ''' from the output
+        clean_html_output = html_output.replace("'''html'''", '').replace("'''", '').strip()
+        return clean_html_output  # Return the cleaned HTML
+    except Exception as e:
+        return f"Error: {e}"
+# Gradio UI using Blocks
+with gr.Blocks() as iface:
+    gr.Markdown("# CV-2-HTML AI Enhanced Portfolio Website Generation")
+    gr.Markdown("Upload your CV in PDF or DOCX format to analyze its content and generate a portfolio.")
+    # File input for uploading CV
+    cv_input = gr.File(label="Upload your CV (.pdf or .docx)")
+    # Output textbox for generated HTML
+    output_textbox = gr.Textbox(label="Generated HTML", lines=20, placeholder="Your generated HTML will appear here...", interactive=True)
+    # Process button
+    process_button = gr.Button("Generate Portfolio")
+    # Define the button actions
+    process_button.click(fn=process_cv, inputs=cv_input, outputs=output_textbox)
+# Launch the Gradio interface
+iface.launch()