Update app.py

app.py

@@ -1,190 +1,200 @@
-import streamlit as st
-from pdfminer.high_level import extract_text
-import smtplib
-from email.message import EmailMessage
-from email_validator import validate_email, EmailNotValidError
-import spacy
-from collections import Counter
-import heapq
-from fpdf import FPDF
-import pandas as pd
-import matplotlib.pyplot as plt
-import requests
-
-# Load spaCy model
-nlp = spacy.load("en_core_web_sm")
-
-# Predefined risk-related words
-RISK_WORDS = [
-    "fraud", "penalty", "violation", "risk", "lawsuit", "breach",
-    "noncompliance", "litigation", "regulatory", "fine"
-]
-
-HEADERS = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"}
-SENDER_EMAIL = "shreedeepthi2005@gmail.com"
-SENDER_PASSWORD = "qntm oher jqfz oflt"
-
-def extract_text_from_pdf(uploaded_file):
-    return extract_text(uploaded_file)
-
-def extract_key_clauses(text):
-    doc = nlp(text)
-    sentences = list(doc.sents)
-    clauses = [str(sentence).strip() for sentence in sentences if len(sentence) > 10]
-    return clauses[:10]  # Return top 10 clauses for simplicity
-
-def summarize_text(text, num_sentences=5):
-    doc = nlp(text)
-    sentences = list(doc.sents)
-    word_frequencies = Counter([token.text.lower() for token in doc if token.is_alpha and not token.is_stop])
-    sentence_scores = {}
-    for sent in sentences:
-        sentence_score = 0
-        for word in sent:
-            if word.text.lower() in word_frequencies:
-                sentence_score += word_frequencies[word.text.lower()]
-        sentence_scores[sent] = sentence_score
-    summarized_sentences = heapq.nlargest(num_sentences, sentence_scores, key=sentence_scores.get)
-    summary = ' '.join([str(sentence) for sentence in summarized_sentences])
-    return summary
-
-def detect_risks(text):
-    doc = nlp(text.lower())
-    detected_risks = [token.text for token in doc if token.text in RISK_WORDS]
-    return list(set(detected_risks))
-
-def get_regulatory_updates():
-    # Fallback: Pre-defined updates
-    predefined_updates = [
-        {"title": "New Compliance Guidelines", "summary": "SEC released new guidelines for regulatory compliance."},
-        {"title": "Update on Financial Risks", "summary": "New policies to mitigate risks in the financial sector."},
-    ]
-    url = "https://www.sec.gov/newsroom/press-releases"
-    try:
-        response = requests.get(url, headers=HEADERS)
-        response.raise_for_status()
-        updates = []  # Placeholder for parsed updates (needs a proper parsing method)
-        # Process response.content with BeautifulSoup or similar parser if allowed
-        return updates if updates else predefined_updates
-    except requests.exceptions.RequestException:
-        return predefined_updates
-
-def generate_pdf(summary, clauses, risks, updates, pdf_path="Analysis_Results.pdf"):
-    pdf = FPDF()
-    pdf.set_auto_page_break(auto=True, margin=15)
-    pdf.add_page()
-    pdf.set_font("Arial", size=12)
-
-    pdf.cell(200, 10, txt="Legal Document Analysis Results", ln=True, align="C")
-
-    # Summary
-    pdf.ln(10)
-    pdf.cell(200, 10, txt="Summary", ln=True, align="L")
-    pdf.set_font("Arial", size=10)
-    pdf.multi_cell(0, 10, summary)
-
-    # Key Clauses
-    pdf.ln(10)
-    pdf.set_font("Arial", size=12)
-    pdf.cell(200, 10, txt="Key Clauses", ln=True, align="L")
-    pdf.set_font("Arial", size=10)
-    for clause in clauses:
-        pdf.multi_cell(0, 10, f"- {clause}")
-
-    # Risks
-    pdf.ln(10)
-    pdf.set_font("Arial", size=12)
-    pdf.cell(200, 10, txt="Detected Risks", ln=True, align="L")
-    pdf.set_font("Arial", size=10)
-    pdf.multi_cell(0, 10, ", ".join(risks))
-
-    # Regulatory Updates
-    pdf.ln(10)
-    pdf.set_font("Arial", size=12)
-    pdf.cell(200, 10, txt="Regulatory Updates", ln=True, align="L")
-    pdf.set_font("Arial", size=10)
-    if updates:
-        for update in updates:
-            pdf.multi_cell(0, 10, f"- {update.get('title', 'N/A')}: {update.get('summary', 'N/A')}")
-
-    pdf.output(pdf_path)
-
-def send_email(pdf_path, recipient_email):
-    msg = EmailMessage()
-    msg["Subject"] = "Legal Document Analysis Results"
-    msg["From"] = SENDER_EMAIL
-    msg["To"] = recipient_email
-
-    msg.set_content("Please find attached the analysis results PDF.")
-
-    with open(pdf_path, "rb") as file:
-        msg.add_attachment(file.read(), maintype="application", subtype="pdf", filename="Analysis_Results.pdf")
-
-    with smtplib.SMTP("smtp.gmail.com", 587) as server:
-        server.starttls()
-        server.login(SENDER_EMAIL, SENDER_PASSWORD)
-        server.send_message(msg)
-
-def main():
-    st.title("Interactive Legal Document Analysis Dashboard")
-
-    # Sidebar options
-    st.sidebar.title("Options")
-    features = st.sidebar.multiselect("Select Features", 
-                                       ["Data Visualization", "Summary", "Key Clauses", "Risk Detection", "Regulatory Updates"])
-
-    # File upload
-    uploaded_file = st.file_uploader("Upload a legal document (PDF)", type="pdf")
-    recipient_email = st.text_input("Enter your email to receive the analysis results (optional)")
-
-    if uploaded_file is not None:
-        try:
-            text = extract_text_from_pdf(uploaded_file)
-            st.success("Text extracted successfully!")
-        except Exception as e:
-            st.error(f"Error extracting text from PDF: {e}")
-            return
-
-        summary = ""
-        clauses, risks, updates = [], [], []
-
-        if "Summary" in features:
-            summary = summarize_text(text)
-            st.subheader("Summary")
-            st.write(summary)
-
-        if "Key Clauses" in features:
-            clauses = extract_key_clauses(text)
-            st.subheader("Key Clauses")
-            for i, clause in enumerate(clauses, 1):
-                st.write(f"{i}. {clause}")
-
-        if "Risk Detection" in features:
-            risks = detect_risks(text)
-            st.subheader("Detected Risks")
-            st.write(", ".join(risks) if risks else "No risks detected.")
-
-        if "Regulatory Updates" in features:
-            updates = get_regulatory_updates()
-            st.subheader("Regulatory Updates")
-            for update in updates:
-                st.write(f"- **{update.get('title')}**: {update.get('summary')}")
-
-        # Generate PDF
-        if st.button("Generate PDF Report"):
-            pdf_path = "Analysis_Results.pdf"
-            generate_pdf(summary, clauses, risks, updates, pdf_path)
-            with open(pdf_path, "rb") as file:
-                st.download_button("Download PDF Report", file, file_name="Analysis_Results.pdf", mime="application/pdf")
-
-            # Email PDF
-            if recipient_email:
-                try:
-                    validate_email(recipient_email)
-                    send_email(pdf_path, recipient_email)
-                    st.success(f"PDF sent to {recipient_email} successfully!")
-                except EmailNotValidError:
-                    st.error("Invalid email address. Please enter a valid one.")
-
-if __name__ == "__main__":
-    main()
+import streamlit as st
+from pdfminer.high_level import extract_text
+import smtplib
+from email.message import EmailMessage
+from email_validator import validate_email, EmailNotValidError
+import spacy
+from collections import Counter
+import heapq
+from fpdf import FPDF
+import pandas as pd
+import matplotlib.pyplot as plt
+import requests
+import subprocess
+import sys
+
+# Install spaCy and the en_core_web_sm model if they are not installed
+try:
+    import spacy
+    spacy.load("en_core_web_sm")
+except OSError:
+    subprocess.check_call([sys.executable, "-m", "pip", "install", "spacy"])
+    subprocess.check_call([sys.executable, "-m", "spacy", "download", "en_core_web_sm"])
+
+# Load spaCy model
+nlp = spacy.load("en_core_web_sm")
+
+# Predefined risk-related words
+RISK_WORDS = [
+    "fraud", "penalty", "violation", "risk", "lawsuit", "breach",
+    "noncompliance", "litigation", "regulatory", "fine"
+]
+
+HEADERS = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"}
+SENDER_EMAIL = "shreedeepthi2005@gmail.com"
+SENDER_PASSWORD = "qntm oher jqfz oflt"
+
+def extract_text_from_pdf(uploaded_file):
+    return extract_text(uploaded_file)
+
+def extract_key_clauses(text):
+    doc = nlp(text)
+    sentences = list(doc.sents)
+    clauses = [str(sentence).strip() for sentence in sentences if len(sentence) > 10]
+    return clauses[:10]  # Return top 10 clauses for simplicity
+
+def summarize_text(text, num_sentences=5):
+    doc = nlp(text)
+    sentences = list(doc.sents)
+    word_frequencies = Counter([token.text.lower() for token in doc if token.is_alpha and not token.is_stop])
+    sentence_scores = {}
+    for sent in sentences:
+        sentence_score = 0
+        for word in sent:
+            if word.text.lower() in word_frequencies:
+                sentence_score += word_frequencies[word.text.lower()]
+        sentence_scores[sent] = sentence_score
+    summarized_sentences = heapq.nlargest(num_sentences, sentence_scores, key=sentence_scores.get)
+    summary = ' '.join([str(sentence) for sentence in summarized_sentences])
+    return summary
+
+def detect_risks(text):
+    doc = nlp(text.lower())
+    detected_risks = [token.text for token in doc if token.text in RISK_WORDS]
+    return list(set(detected_risks))
+
+def get_regulatory_updates():
+    # Fallback: Pre-defined updates
+    predefined_updates = [
+        {"title": "New Compliance Guidelines", "summary": "SEC released new guidelines for regulatory compliance."},
+        {"title": "Update on Financial Risks", "summary": "New policies to mitigate risks in the financial sector."},
+    ]
+    url = "https://www.sec.gov/newsroom/press-releases"
+    try:
+        response = requests.get(url, headers=HEADERS)
+        response.raise_for_status()
+        updates = []  # Placeholder for parsed updates (needs a proper parsing method)
+        # Process response.content with BeautifulSoup or similar parser if allowed
+        return updates if updates else predefined_updates
+    except requests.exceptions.RequestException:
+        return predefined_updates
+
+def generate_pdf(summary, clauses, risks, updates, pdf_path="Analysis_Results.pdf"):
+    pdf = FPDF()
+    pdf.set_auto_page_break(auto=True, margin=15)
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+
+    pdf.cell(200, 10, txt="Legal Document Analysis Results", ln=True, align="C")
+
+    # Summary
+    pdf.ln(10)
+    pdf.cell(200, 10, txt="Summary", ln=True, align="L")
+    pdf.set_font("Arial", size=10)
+    pdf.multi_cell(0, 10, summary)
+
+    # Key Clauses
+    pdf.ln(10)
+    pdf.set_font("Arial", size=12)
+    pdf.cell(200, 10, txt="Key Clauses", ln=True, align="L")
+    pdf.set_font("Arial", size=10)
+    for clause in clauses:
+        pdf.multi_cell(0, 10, f"- {clause}")
+
+    # Risks
+    pdf.ln(10)
+    pdf.set_font("Arial", size=12)
+    pdf.cell(200, 10, txt="Detected Risks", ln=True, align="L")
+    pdf.set_font("Arial", size=10)
+    pdf.multi_cell(0, 10, ", ".join(risks))
+
+    # Regulatory Updates
+    pdf.ln(10)
+    pdf.set_font("Arial", size=12)
+    pdf.cell(200, 10, txt="Regulatory Updates", ln=True, align="L")
+    pdf.set_font("Arial", size=10)
+    if updates:
+        for update in updates:
+            pdf.multi_cell(0, 10, f"- {update.get('title', 'N/A')}: {update.get('summary', 'N/A')}")
+
+    pdf.output(pdf_path)
+
+def send_email(pdf_path, recipient_email):
+    msg = EmailMessage()
+    msg["Subject"] = "Legal Document Analysis Results"
+    msg["From"] = SENDER_EMAIL
+    msg["To"] = recipient_email
+
+    msg.set_content("Please find attached the analysis results PDF.")
+
+    with open(pdf_path, "rb") as file:
+        msg.add_attachment(file.read(), maintype="application", subtype="pdf", filename="Analysis_Results.pdf")
+
+    with smtplib.SMTP("smtp.gmail.com", 587) as server:
+        server.starttls()
+        server.login(SENDER_EMAIL, SENDER_PASSWORD)
+        server.send_message(msg)
+
+def main():
+    st.title("Interactive Legal Document Analysis Dashboard")
+
+    # Sidebar options
+    st.sidebar.title("Options")
+    features = st.sidebar.multiselect("Select Features", 
+                                       ["Data Visualization", "Summary", "Key Clauses", "Risk Detection", "Regulatory Updates"])
+
+    # File upload
+    uploaded_file = st.file_uploader("Upload a legal document (PDF)", type="pdf")
+    recipient_email = st.text_input("Enter your email to receive the analysis results (optional)")
+
+    if uploaded_file is not None:
+        try:
+            text = extract_text_from_pdf(uploaded_file)
+            st.success("Text extracted successfully!")
+        except Exception as e:
+            st.error(f"Error extracting text from PDF: {e}")
+            return
+
+        summary = ""
+        clauses, risks, updates = [], [], []
+
+        if "Summary" in features:
+            summary = summarize_text(text)
+            st.subheader("Summary")
+            st.write(summary)
+
+        if "Key Clauses" in features:
+            clauses = extract_key_clauses(text)
+            st.subheader("Key Clauses")
+            for i, clause in enumerate(clauses, 1):
+                st.write(f"{i}. {clause}")
+
+        if "Risk Detection" in features:
+            risks = detect_risks(text)
+            st.subheader("Detected Risks")
+            st.write(", ".join(risks) if risks else "No risks detected.")
+
+        if "Regulatory Updates" in features:
+            updates = get_regulatory_updates()
+            st.subheader("Regulatory Updates")
+            for update in updates:
+                st.write(f"- **{update.get('title')}**: {update.get('summary')}")
+
+        # Generate PDF
+        if st.button("Generate PDF Report"):
+            pdf_path = "Analysis_Results.pdf"
+            generate_pdf(summary, clauses, risks, updates, pdf_path)
+            with open(pdf_path, "rb") as file:
+                st.download_button("Download PDF Report", file, file_name="Analysis_Results.pdf", mime="application/pdf")
+
+            # Email PDF
+            if recipient_email:
+                try:
+                    validate_email(recipient_email)
+                    send_email(pdf_path, recipient_email)
+                    st.success(f"PDF sent to {recipient_email} successfully!")
+                except EmailNotValidError:
+                    st.error("Invalid email address. Please enter a valid one.")
+
+if __name__ == "__main__":
+    main()