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import streamlit as st |
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import requests |
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from fpdf import FPDF |
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import os |
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import time |
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from datetime import datetime |
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import groq |
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mistral_api_key = os.getenv("MISTRAL_API_KEY", "gz6lDXokxgR6cLY72oomALWcm7vhjRzQ") |
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groq_api_key = os.getenv("GROQ_API_KEY", "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") |
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groq_client = groq.Client(api_key=groq_api_key) |
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def call_mistral_api(prompt): |
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url = "https://api.mistral.ai/v1/chat/completions" |
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headers = { |
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"Authorization": f"Bearer {mistral_api_key}", |
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"Content-Type": "application/json" |
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} |
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payload = { |
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"model": "mistral-medium", |
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"messages": [ |
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{"role": "user", "content": prompt} |
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] |
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} |
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try: |
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response = requests.post(url, headers=headers, json=payload) |
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response.raise_for_status() |
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return response.json()['choices'][0]['message']['content'] |
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except requests.exceptions.HTTPError as err: |
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if response.status_code == 429: |
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st.warning("Rate limit exceeded. Please wait a few seconds and try again.") |
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time.sleep(5) |
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return call_mistral_api(prompt) |
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return f"HTTP Error: {err}" |
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except Exception as err: |
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return f"Error: {err}" |
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def call_groq_api(prompt): |
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try: |
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response = groq_client.chat.completions.create( |
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model="llama3-70b-8192", |
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messages=[ |
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{"role": "user", "content": prompt} |
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] |
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) |
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return response.choices[0].message.content |
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except Exception as err: |
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st.error(f"Error: {err}") |
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return f"Error: {err}" |
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def analyze_requirement(requirement): |
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type_prompt = f"Classify the following requirement as Functional or Non-Functional in one word:\n\n{requirement}\n\nType:" |
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req_type = call_mistral_api(type_prompt).strip() |
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domain_prompt = f"Classify the domain for the following requirement in one word (e.g., E-commerce, Education, etc.):\n\n{requirement}\n\nDomain:" |
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domain = call_mistral_api(domain_prompt).strip() |
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stakeholder_prompt = f"""Identify key major stakeholders for this requirement. Provide a comma-separated list of roles. |
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Examples: Users, Administrators, Developers, Security Team. Requirement:\n\n{requirement}\n\nStakeholders:""" |
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stakeholders = call_groq_api(stakeholder_prompt).strip() |
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defects_prompt = f"""List ONLY the major defects in the following requirement (e.g., Ambiguity, Incompleteness, etc.) in 1-2 words each:\n\n{requirement}\n\nDefects:""" |
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defects = call_groq_api(defects_prompt).strip() |
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rewritten_prompt = f"""Rewrite the following requirement in 1-2 sentences to address the defects:\n\n{requirement}\n\nRewritten:""" |
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rewritten = call_groq_api(rewritten_prompt).strip() |
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return { |
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"Requirement": requirement, |
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"Type": req_type, |
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"Domain": domain, |
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"Stakeholders": stakeholders, |
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"Defects": defects, |
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"Rewritten": rewritten |
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} |
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def generate_pdf_report(results): |
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pdf = FPDF() |
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pdf.add_page() |
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pdf.set_font("Arial", size=12) |
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pdf.set_font("Arial", 'B', 50) |
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pdf.set_text_color(230, 230, 230) |
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pdf.rotate(45) |
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pdf.text(60, 150, "AI Powered Requirement Analysis") |
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pdf.rotate(0) |
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pdf.set_font("Arial", 'B', 16) |
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pdf.set_text_color(0, 0, 0) |
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pdf.cell(200, 10, txt="AI Powered Requirement Analysis and Defect Detection", ln=True, align='C') |
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pdf.set_font("Arial", size=12) |
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pdf.cell(200, 10, txt=f"Report Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", ln=True, align='C') |
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pdf.ln(10) |
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pdf.set_font("Arial", size=12) |
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for i, result in enumerate(results, start=1): |
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if pdf.get_y() > 250: |
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pdf.add_page() |
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pdf.set_font("Arial", 'B', 16) |
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pdf.cell(200, 10, txt="AI Powered Requirement Analysis and Defect Detection", ln=True, align='C') |
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pdf.set_font("Arial", size=12) |
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pdf.cell(200, 10, txt=f"Report Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", ln=True, align='C') |
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pdf.ln(10) |
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pdf.set_font("Arial", 'B', 14) |
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pdf.multi_cell(200, 10, txt=f"Requirement R{i}: {result['Requirement']}", align='L') |
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pdf.set_font("Arial", size=12) |
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pdf.multi_cell(200, 10, txt=f"Type: {result['Type']}", align='L') |
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pdf.multi_cell(200, 10, txt=f"Domain: {result['Domain']}", align='L') |
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pdf.multi_cell(200, 10, txt=f"Stakeholders: {result['Stakeholders']}", align='L') |
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pdf.multi_cell(200, 10, txt=f"Defects: {result['Defects']}", align='L') |
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pdf.multi_cell(200, 10, txt=f"Rewritten: {result['Rewritten']}", align='L') |
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pdf.multi_cell(200, 10, txt="-" * 50, align='L') |
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pdf.ln(5) |
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pdf_output = "requirements_report.pdf" |
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pdf.output(pdf_output) |
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return pdf_output |
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st.markdown(""" |
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<style> |
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.main { |
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background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%); |
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} |
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.stApp { |
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max-width: 1200px; |
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margin: 0 auto; |
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padding: 2rem; |
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} |
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.header { |
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text-align: center; |
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padding: 2rem; |
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background: white; |
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border-radius: 15px; |
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); |
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margin-bottom: 2rem; |
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border: 1px solid #e0e0e0; |
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} |
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.requirement-card { |
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background: white; |
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padding: 1.5rem; |
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border-radius: 10px; |
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box-shadow: 0 2px 4px rgba(0, 0, 0, 0.05); |
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margin-bottom: 1.5rem; |
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transition: transform 0.2s; |
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color: #333333; |
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} |
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.requirement-card:hover { |
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transform: translateY(-3px); |
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} |
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.analysis-badge { |
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padding: 0.5rem 1rem; |
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border-radius: 20px; |
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font-weight: 500; |
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margin: 0.3rem; |
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} |
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.download-btn { |
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width: 100%; |
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padding: 1rem; |
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font-size: 1.1rem; |
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margin-top: 2rem; |
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} |
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.type-functional { background: #e8f5e9; color: #2e7d32; } |
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.type-non-functional { background: #fff3e0; color: #ef6c00; } |
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.defect-badge { background: #ffebee; color: #c62828; } |
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.improved-badge { background: #e3f2fd; color: #1565c0; } |
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</style> |
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""", unsafe_allow_html=True) |
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def main(): |
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with st.container(): |
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st.markdown('<div class="header">', unsafe_allow_html=True) |
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st.title("π AI-Based Requirement Defect Detection Using Large Language Models (LLMs)") |
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st.markdown(""" |
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<div style="margin: 1.5rem 0;"> |
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<div style="font-size: 1.2rem; color: #4a4a4a;">Automated Requirement Classification, Defect Detection & Optimization</div> |
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<div style="display: flex; justify-content: center; gap: 1rem; margin: 1rem 0;"> |
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<div style="padding: 0.5rem 1rem; background: #f0f2f6;color: black; border-radius: 20px;">Team: Sadia, Areeba, Rabbia, Tesmia</div> |
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<div style="padding: 0.5rem 1rem; background: #f0f2f6; color: black; border-radius: 20px;">Mistral + Groq API</div> |
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</div> |
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</div> |
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""", unsafe_allow_html=True) |
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st.markdown('</div>', unsafe_allow_html=True) |
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with st.container(): |
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st.subheader("π₯ Input Requirements") |
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input_text = st.text_area( |
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"Enter your software requirements (one per line or separated by periods):", |
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height=200, |
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placeholder="Example:\nThe system shall allow users to reset their password via email verification.\nThe interface must load within 2 seconds of user interaction...", |
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help="Enter each requirement on a new line or separate with periods." |
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) |
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if st.button("π Start Analysis", type="primary", use_container_width=True): |
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if not input_text.strip(): |
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st.warning("β οΈ Please enter requirements to analyze") |
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else: |
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with st.spinner("π Analyzing requirements..."): |
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requirements = [req.strip() for req in input_text.replace("\n", ".").split(".") if req.strip()] |
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results = [] |
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progress_bar = st.progress(0) |
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for i, req in enumerate(requirements): |
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results.append(analyze_requirement(req)) |
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progress_bar.progress((i+1)/len(requirements)) |
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st.success("β
Analysis Completed!") |
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time.sleep(0.5) |
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st.session_state.results = results |
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if 'results' in st.session_state: |
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st.subheader("π Analysis Results") |
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with st.container(): |
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for i, result in enumerate(st.session_state.results, 1): |
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with st.expander(f"Requirement #{i}: {result['Requirement'][:50]}...", expanded=True): |
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st.markdown(f""" |
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<div class="requirement-card"> |
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<div style="margin-bottom: 1.5rem;"> |
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<div class="analysis-badge { 'type-functional' if 'functional' in result['Type'].lower() else 'type-non-functional' }"> |
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π <b>Type:</b> {result['Type']} |
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</div> |
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<div class="analysis-badge" style="background: #e8eaf6; color: #303f9f;"> |
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π·οΈ <b>Domain:</b> {result['Domain']} |
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</div> |
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<div class="analysis-badge" style="background: #e0f2f1; color: #00796b;"> |
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π₯ <b>Stakeholders:</b> {result['Stakeholders']} |
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</div> |
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<div class="analysis-badge" style="background: #b39ddb; color: purple;"> |
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π <b>Identified Defects:</b><br> Explanation: {result['Defects']} |
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</div> |
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<div class="analysis-badge" style="background: #8c9eff; color: blue;"> |
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β¨ <b>Improved Version:</b><br> Explanation: {result['Rewritten']} |
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</div> |
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</div> |
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</div> |
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""", unsafe_allow_html=True) |
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st.subheader("π€ Generate Report") |
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with st.container(): |
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col1, col2 = st.columns([3, 2]) |
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with col1: |
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st.info("π‘ Click below to generate a comprehensive PDF report with all analysis details") |
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with col2: |
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if st.button("π Generate PDF Report", type="secondary", use_container_width=True): |
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with st.spinner("Generating PDF..."): |
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pdf_report = generate_pdf_report(st.session_state.results) |
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with open(pdf_report, "rb") as f: |
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st.download_button( |
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label="β¬οΈ Download Full Report", |
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data=f, |
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file_name="Requirement_Analysis_Report.pdf", |
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mime="application/pdf", |
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use_container_width=True, |
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type="primary" |
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) |
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st.markdown("---") |
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st.markdown(""" |
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<div style="text-align: center; color: #666; margin-top: 3rem;"> |
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<p>AI-Powered Requirement Analysis System</p> |
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<p>π Powered by Mistral AI & Groq β’ π οΈ Developed by Team Four</p> |
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</div> |
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""", unsafe_allow_html=True) |
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if __name__ == "__main__": |
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main() |