import streamlit as st import requests from fpdf import FPDF import os import time from datetime import datetime import groq # API keys (replace with your keys or use environment variables) mistral_api_key = os.getenv("MISTRAL_API_KEY", "gz6lDXokxgR6cLY72oomALWcm7vhjRzQ") groq_api_key = os.getenv("GROQ_API_KEY", "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") # Initialize Groq client groq_client = groq.Client(api_key=groq_api_key) # Function to call Mistral API def call_mistral_api(prompt): url = "https://api.mistral.ai/v1/chat/completions" headers = { "Authorization": f"Bearer {mistral_api_key}", "Content-Type": "application/json" } payload = { "model": "mistral-medium", "messages": [ {"role": "user", "content": prompt} ] } try: response = requests.post(url, headers=headers, json=payload) response.raise_for_status() return response.json()['choices'][0]['message']['content'] except requests.exceptions.HTTPError as err: if response.status_code == 429: st.warning("Rate limit exceeded. Please wait a few seconds and try again.") time.sleep(5) return call_mistral_api(prompt) return f"HTTP Error: {err}" except Exception as err: return f"Error: {err}" # Function to call Groq API def call_groq_api(prompt): try: response = groq_client.chat.completions.create( model="llama-3.3-70b-versatile", messages=[ {"role": "user", "content": prompt} ] ) return response.choices[0].message.content except Exception as err: st.error(f"Error: {err}") return f"Error: {err}" # Function to analyze requirement def analyze_requirement(requirement): type_prompt = f"Classify the following requirement as Functional or Non-Functional in one word:\n\n{requirement}\n\nType:" req_type = call_mistral_api(type_prompt).strip() domain_prompt = f"Classify the domain for the following requirement in one word (e.g., E-commerce, Education, etc.):\n\n{requirement}\n\nDomain:" domain = call_mistral_api(domain_prompt).strip() 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:""" defects = call_groq_api(defects_prompt).strip() rewritten_prompt = f"""Rewrite the following requirement in 1-2 sentences to address the defects:\n\n{requirement}\n\nRewritten:""" rewritten = call_groq_api(rewritten_prompt).strip() return { "Requirement": requirement, "Type": req_type, "Domain": domain, "Defects": defects, "Rewritten": rewritten } # Function to generate PDF report def generate_pdf_report(results): pdf = FPDF() pdf.add_page() pdf.set_font("Arial", size=12) pdf.set_font("Arial", 'B', 50) pdf.set_text_color(230, 230, 230) pdf.rotate(45) pdf.text(60, 150, "AI Powered Requirement Analysis") pdf.rotate(0) pdf.set_font("Arial", 'B', 16) pdf.set_text_color(0, 0, 0) pdf.cell(200, 10, txt="AI Powered Requirement Analysis and Defect Detection", ln=True, align='C') pdf.set_font("Arial", size=12) pdf.cell(200, 10, txt=f"Report Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", ln=True, align='C') pdf.ln(10) pdf.set_font("Arial", size=12) for i, result in enumerate(results, start=1): if pdf.get_y() > 250: pdf.add_page() pdf.set_font("Arial", 'B', 16) pdf.cell(200, 10, txt="AI Powered Requirement Analysis and Defect Detection", ln=True, align='C') pdf.set_font("Arial", size=12) pdf.cell(200, 10, txt=f"Report Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}", ln=True, align='C') pdf.ln(10) pdf.set_font("Arial", 'B', 14) pdf.multi_cell(200, 10, txt=f"Requirement R{i}: {result['Requirement']}", align='L') pdf.set_font("Arial", size=12) pdf.multi_cell(200, 10, txt=f"Type: {result['Type']}", align='L') pdf.multi_cell(200, 10, txt=f"Domain: {result['Domain']}", align='L') pdf.multi_cell(200, 10, txt=f"Defects: {result['Defects']}", align='L') pdf.multi_cell(200, 10, txt=f"Rewritten: {result['Rewritten']}", align='L') pdf.multi_cell(200, 10, txt="-" * 50, align='L') pdf.ln(5) pdf_output = "requirements_report.pdf" pdf.output(pdf_output) return pdf_output # Streamlit UI def main(): st.markdown(""" """, unsafe_allow_html=True) st.markdown("""

🧠 AI Requirement Analyzer

Smart Analysis & Quality Enhancement System

👥 Team Members

Sadia

""", unsafe_allow_html=True) st.markdown("""

📥 Input Requirements

Enter multiple requirements separated by new lines or periods

""", unsafe_allow_html=True) input_text = st.text_area("", height=200, key="input_area", help="Example:\n1. The system must handle 1000 users\n2. User interface should be responsive") if st.button("🚀 Start Analysis", key="analyze_btn", use_container_width=True): if not input_text.strip(): st.warning("⚠️ Please enter requirements to analyze") else: requirements = [req.strip() for req in input_text.replace("\n", ".").split(".") if req.strip()] results = [] progress_bar = st.progress(0) with st.spinner("🔍 Analyzing requirements..."): for i, req in enumerate(requirements): results.append(analyze_requirement(req)) progress_bar.progress((i+1)/len(requirements)) time.sleep(0.1) st.success("✅ Analysis completed!") st.markdown("---") for i, result in enumerate(results, 1): st.markdown(f"""

🔖 Requirement R{i}

{result['Requirement']}

📝 {result['Type']} 🌍 {result['Domain']} ⚠️ {result['Defects']}

✏️ Optimized Version:

{result['Rewritten']}

""", unsafe_allow_html=True) st.markdown("---") st.markdown("### 📄 Generate Report") pdf_report = generate_pdf_report(results) with open(pdf_report, "rb") as f: st.download_button( label="📥 Download PDF Report", data=f, file_name="requirements_analysis.pdf", mime="application/pdf", use_container_width=True, key="download_btn" ) st.markdown("
", unsafe_allow_html=True) if __name__ == "__main__": main()