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| import streamlit as st | |
| import requests | |
| import os | |
| import json | |
| import re | |
| from bs4 import BeautifulSoup | |
| from urllib.parse import urlparse | |
| st.set_page_config(page_title="AI Sentiment Analyzer", page_icon="🌐", layout="wide") | |
| st.markdown(""" | |
| <style> | |
| @import url('https://fonts.googleapis.com/css2?family=Sora:wght@300;400;500;600;700&family=JetBrains+Mono:wght@400;500&display=swap'); | |
| html, body, [class*="css"] { font-family: 'Sora', sans-serif; } | |
| .main { background: #0a0a0f; } | |
| .hero { | |
| background: linear-gradient(135deg, #0d0d1a 0%, #0a0a0f 100%); | |
| border: 1px solid #1e1e2e; border-top: 3px solid #a78bfa; | |
| border-radius: 14px; padding: 28px 32px; margin-bottom: 24px; | |
| } | |
| .hero h1 { font-size: 1.8rem; font-weight: 700; color: #f1f5f9; margin: 0 0 6px 0; } | |
| .hero p { color: #4b5563; font-size: 0.88rem; margin: 0; } | |
| .insight-card { | |
| background: #0d0d1a; border: 1px solid #1e1e2e; | |
| border-radius: 12px; padding: 20px 24px; margin: 10px 0; | |
| } | |
| /* Sentiment meter */ | |
| .sentiment-positive { color: #4ade80; } | |
| .sentiment-negative { color: #f87171; } | |
| .sentiment-neutral { color: #94a3b8; } | |
| .sentiment-mixed { color: #fbbf24; } | |
| .big-sentiment { | |
| font-size: 3rem; font-weight: 700; text-align: center; | |
| padding: 20px; letter-spacing: -0.02em; | |
| } | |
| .sentiment-score-label { | |
| text-align: center; font-size: 0.82rem; color: #4b5563; | |
| font-family: 'JetBrains Mono', monospace; | |
| } | |
| .entity-tag { | |
| display: inline-block; border-radius: 6px; | |
| padding: 4px 10px; font-size: 0.78rem; margin: 3px; | |
| font-family: 'JetBrains Mono', monospace; | |
| } | |
| .entity-person { background: rgba(167,139,250,0.12); color: #a78bfa; border: 1px solid rgba(167,139,250,0.25); } | |
| .entity-org { background: rgba(59,130,246,0.1); color: #60a5fa; border: 1px solid rgba(59,130,246,0.25); } | |
| .entity-location { background: rgba(34,197,94,0.1); color: #4ade80; border: 1px solid rgba(34,197,94,0.25); } | |
| .entity-topic { background: rgba(251,191,36,0.1); color: #fbbf24; border: 1px solid rgba(251,191,36,0.25); } | |
| .entity-product { background: rgba(248,113,113,0.1); color: #f87171; border: 1px solid rgba(248,113,113,0.25); } | |
| .theme-pill { | |
| display: inline-block; background: #1e1e2e; border: 1px solid #2d2d3e; | |
| border-radius: 20px; padding: 5px 14px; margin: 4px; | |
| font-size: 0.8rem; color: #94a3b8; | |
| } | |
| .section-label { | |
| font-size: 0.68rem; text-transform: uppercase; letter-spacing: 0.1em; | |
| color: #2d2d3e; font-weight: 600; margin: 18px 0 8px 0; | |
| } | |
| .stat-row { display: flex; gap: 10px; margin: 16px 0; } | |
| .stat-box { | |
| flex: 1; background: #0d0d1a; border: 1px solid #1e1e2e; | |
| border-radius: 10px; padding: 14px; text-align: center; | |
| } | |
| .stat-val { font-size: 1.3rem; font-weight: 700; color: #f1f5f9; } | |
| .stat-lbl { font-size: 0.68rem; color: #4b5563; margin-top: 2px; } | |
| .url-chip { | |
| background: #0d0d1a; border: 1px solid #1e1e2e; border-radius: 8px; | |
| padding: 10px 14px; font-family: 'JetBrains Mono', monospace; | |
| font-size: 0.78rem; color: #4b5563; word-break: break-all; | |
| margin-bottom: 16px; | |
| } | |
| section[data-testid="stSidebar"] { background: #060609; border-right: 1px solid #1e1e2e; } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| def fetch_url_text(url: str) -> tuple[str, str]: | |
| headers = {"User-Agent": "Mozilla/5.0 (compatible; InsightBot/1.0)"} | |
| r = requests.get(url, headers=headers, timeout=15) | |
| r.raise_for_status() | |
| soup = BeautifulSoup(r.text, "html.parser") | |
| title = soup.title.string.strip() if soup.title else urlparse(url).netloc | |
| for tag in soup(["script", "style", "nav", "footer", "header", "aside", "form"]): | |
| tag.decompose() | |
| text = soup.get_text(separator=" ", strip=True) | |
| text = re.sub(r'\s+', ' ', text).strip() | |
| return text[:4000], title | |
| def analyze_content(text: str, url: str, title: str, api_key: str) -> dict: | |
| prompt = f"""You are an expert content analyst. Analyze the following webpage content and extract deep insights. | |
| Source URL: {url} | |
| Page Title: {title} | |
| Content: | |
| {text} | |
| Respond ONLY with a valid JSON object in exactly this format: | |
| {{ | |
| "sentiment": "<one of: Positive | Negative | Neutral | Mixed>", | |
| "sentiment_score": <float between -1.0 (very negative) and 1.0 (very positive)>, | |
| "sentiment_explanation": "<1-2 sentences explaining the sentiment>", | |
| "one_line_summary": "<single sentence capturing the entire content>", | |
| "key_themes": ["<theme 1>", "<theme 2>", "<theme 3>", "<theme 4>", "<theme 5>"], | |
| "named_entities": {{ | |
| "persons": ["<name>"], | |
| "organizations": ["<org>"], | |
| "locations": ["<location>"], | |
| "products": ["<product>"] | |
| }}, | |
| "content_type": "<one of: News Article | Product Page | Review | Blog Post | Research | Social Media | Other>", | |
| "target_audience": "<who this content is written for>", | |
| "key_insights": ["<insight 1>", "<insight 2>", "<insight 3>"], | |
| "tone": "<one of: Informative | Promotional | Critical | Analytical | Emotional | Persuasive | Neutral>", | |
| "credibility_signals": ["<signal 1>", "<signal 2>"], | |
| "word_count_estimate": <integer> | |
| }}""" | |
| headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"} | |
| payload = { | |
| "model": "llama-3.3-70b-versatile", | |
| "messages": [{"role": "user", "content": prompt}], | |
| "max_tokens": 1000, | |
| "temperature": 0.1, | |
| } | |
| r = requests.post("https://api.groq.com/openai/v1/chat/completions", | |
| headers=headers, json=payload, timeout=30) | |
| r.raise_for_status() | |
| raw = r.json()["choices"][0]["message"]["content"] | |
| raw = re.sub(r"```json|```", "", raw).strip() | |
| return json.loads(raw) | |
| # ─── Sidebar ────────────────────────────────────────────────────────────────── | |
| with st.sidebar: | |
| st.markdown("## 🌐 Sentiment Analyzer") | |
| st.markdown("<div style='color:#2d2d3e;font-size:0.8rem'>AI-powered content intelligence</div>", unsafe_allow_html=True) | |
| st.markdown("---") | |
| env_key = os.environ.get("GROQ_API_KEY", "") | |
| api_key = env_key if env_key else st.text_input("🔑 Groq API Key", type="password", placeholder="gsk_...") | |
| if not env_key and not api_key: | |
| st.caption("Free key → [console.groq.com](https://console.groq.com)") | |
| st.markdown("---") | |
| st.markdown(""" | |
| <div style='font-size:0.78rem;color:#2d2d3e;line-height:2'> | |
| <b style='color:#4b5563'>Extracts</b><br> | |
| 🎭 Sentiment & Score<br> | |
| 🏷️ Key Themes<br> | |
| 👤 Named Entities<br> | |
| 💡 Key Insights<br> | |
| 🎯 Target Audience<br> | |
| 🗣️ Content Tone<br> | |
| 📰 Content Type | |
| </div>""", unsafe_allow_html=True) | |
| st.markdown("---") | |
| st.markdown(""" | |
| <div style='font-size:0.78rem;color:#2d2d3e;line-height:2'> | |
| <b style='color:#4b5563'>Try these URLs</b><br> | |
| • Any news article<br> | |
| • Amazon product page<br> | |
| • Wikipedia article<br> | |
| • Company blog post<br> | |
| • G2 / Trustpilot review | |
| </div>""", unsafe_allow_html=True) | |
| # ─── Main UI ────────────────────────────────────────────────────────────────── | |
| st.markdown(""" | |
| <div class='hero'> | |
| <h1>🌐 AI Webpage Sentiment & Insight Analyzer</h1> | |
| <p>Paste any URL — AI extracts sentiment, themes, entities, tone, and key insights in seconds</p> | |
| </div> | |
| """, unsafe_allow_html=True) | |
| if not api_key: | |
| st.warning("👈 Add your Groq API key in the sidebar.") | |
| st.stop() | |
| st.markdown("<div class='section-label'>Paste a URL to analyze</div>", unsafe_allow_html=True) | |
| col_input, col_btn = st.columns([5, 1]) | |
| with col_input: | |
| url_input = st.text_input("URL", placeholder="https://...", label_visibility="collapsed") | |
| with col_btn: | |
| analyze_btn = st.button("Analyze ➤", type="primary", use_container_width=True) | |
| # Example URLs | |
| st.markdown("<div class='section-label'>Quick examples</div>", unsafe_allow_html=True) | |
| examples = [ | |
| "https://en.wikipedia.org/wiki/Artificial_intelligence", | |
| "https://techcrunch.com", | |
| "https://www.bbc.com/news", | |
| ] | |
| cols = st.columns(len(examples)) | |
| clicked_url = None | |
| for i, ex in enumerate(examples): | |
| parsed = urlparse(ex) | |
| label = parsed.netloc | |
| if cols[i].button(f"🔗 {label}", key=f"ex_{i}", use_container_width=True): | |
| clicked_url = ex | |
| final_url = clicked_url or (url_input if analyze_btn else None) | |
| if final_url: | |
| with st.spinner(f"Fetching and analyzing {final_url}..."): | |
| try: | |
| content_text, page_title = fetch_url_text(final_url) | |
| result = analyze_content(content_text, final_url, page_title, api_key) | |
| sentiment = result.get("sentiment", "Neutral") | |
| score = result.get("sentiment_score", 0) | |
| sentiment_color = ( | |
| "#4ade80" if sentiment == "Positive" else | |
| "#f87171" if sentiment == "Negative" else | |
| "#fbbf24" if sentiment == "Mixed" else | |
| "#94a3b8" | |
| ) | |
| sentiment_emoji = ( | |
| "😊" if sentiment == "Positive" else | |
| "😟" if sentiment == "Negative" else | |
| "😐" if sentiment == "Neutral" else "🤔" | |
| ) | |
| score_pct = int((score + 1) / 2 * 100) | |
| st.markdown(f"<div class='url-chip'>🔗 {final_url}</div>", unsafe_allow_html=True) | |
| st.markdown(f"### 📄 {page_title}") | |
| # Top row | |
| col_sent, col_summary = st.columns([1, 2]) | |
| with col_sent: | |
| st.markdown(f""" | |
| <div class='insight-card' style='text-align:center'> | |
| <div style='font-size:0.72rem;text-transform:uppercase;letter-spacing:0.1em;color:#4b5563;margin-bottom:8px'>Sentiment</div> | |
| <div style='font-size:3.5rem'>{sentiment_emoji}</div> | |
| <div style='font-size:1.6rem;font-weight:700;color:{sentiment_color};margin:4px 0'>{sentiment}</div> | |
| <div style='font-family:JetBrains Mono,monospace;font-size:0.8rem;color:#4b5563'>score: {score:+.2f}</div> | |
| <div style='background:#1e1e2e;border-radius:4px;height:6px;margin:10px 0'> | |
| <div style='height:6px;border-radius:4px;width:{score_pct}%;background:{sentiment_color}'></div> | |
| </div> | |
| <div style='font-size:0.78rem;color:#4b5563;margin-top:8px'>{result.get("sentiment_explanation","")}</div> | |
| </div> | |
| """, unsafe_allow_html=True) | |
| with col_summary: | |
| entities = result.get("named_entities", {}) | |
| persons_html = "".join([f"<span class='entity-tag entity-person'>👤 {e}</span>" for e in entities.get("persons", [])[:4]]) | |
| orgs_html = "".join([f"<span class='entity-tag entity-org'>🏢 {e}</span>" for e in entities.get("organizations", [])[:4]]) | |
| locations_html = "".join([f"<span class='entity-tag entity-location'>📍 {e}</span>" for e in entities.get("locations", [])[:3]]) | |
| products_html = "".join([f"<span class='entity-tag entity-product'>📦 {e}</span>" for e in entities.get("products", [])[:3]]) | |
| entities_html = persons_html + orgs_html + locations_html + products_html or "<span style='color:#4b5563;font-size:0.82rem'>None detected</span>" | |
| st.markdown(f""" | |
| <div class='insight-card'> | |
| <div style='font-size:0.72rem;text-transform:uppercase;letter-spacing:0.1em;color:#4b5563;margin-bottom:10px'>One-Line Summary</div> | |
| <div style='font-size:1rem;color:#f1f5f9;font-weight:500;line-height:1.6;margin-bottom:16px'>"{result.get("one_line_summary","")}"</div> | |
| <div style='display:flex;gap:16px;margin-bottom:14px'> | |
| <div><span style='font-size:0.72rem;color:#4b5563'>Content Type</span><br><span style='color:#a78bfa;font-weight:600;font-size:0.88rem'>{result.get("content_type","")}</span></div> | |
| <div><span style='font-size:0.72rem;color:#4b5563'>Tone</span><br><span style='color:#60a5fa;font-weight:600;font-size:0.88rem'>{result.get("tone","")}</span></div> | |
| <div><span style='font-size:0.72rem;color:#4b5563'>Audience</span><br><span style='color:#4ade80;font-weight:600;font-size:0.88rem'>{result.get("target_audience","")}</span></div> | |
| </div> | |
| <div style='font-size:0.72rem;text-transform:uppercase;letter-spacing:0.1em;color:#4b5563;margin-bottom:8px'>Named Entities</div> | |
| {entities_html} | |
| </div> | |
| """, unsafe_allow_html=True) | |
| # Themes + Insights | |
| col_themes, col_insights = st.columns(2) | |
| with col_themes: | |
| themes_html = "".join([f"<div class='theme-pill'>#{t}</div>" for t in result.get("key_themes", [])]) | |
| st.markdown(f""" | |
| <div class='insight-card'> | |
| <div style='font-size:0.72rem;text-transform:uppercase;letter-spacing:0.1em;color:#4b5563;margin-bottom:12px'>🏷️ Key Themes</div> | |
| {themes_html} | |
| </div>""", unsafe_allow_html=True) | |
| with col_insights: | |
| insights_html = "".join([f"<div style='padding:8px 0;border-bottom:1px solid #1e1e2e;font-size:0.87rem;color:#94a3b8;line-height:1.6'>→ {ins}</div>" for ins in result.get("key_insights", [])]) | |
| st.markdown(f""" | |
| <div class='insight-card'> | |
| <div style='font-size:0.72rem;text-transform:uppercase;letter-spacing:0.1em;color:#4b5563;margin-bottom:12px'>💡 Key Insights</div> | |
| {insights_html} | |
| </div>""", unsafe_allow_html=True) | |
| # Credibility | |
| cred = result.get("credibility_signals", []) | |
| if cred: | |
| cred_html = "".join([f"<span style='background:rgba(74,222,128,0.08);border:1px solid rgba(74,222,128,0.2);border-radius:6px;padding:4px 12px;margin:3px;display:inline-block;font-size:0.8rem;color:#4ade80'>✓ {c}</span>" for c in cred]) | |
| st.markdown(f""" | |
| <div class='insight-card'> | |
| <div style='font-size:0.72rem;text-transform:uppercase;letter-spacing:0.1em;color:#4b5563;margin-bottom:10px'>🛡️ Credibility Signals</div> | |
| {cred_html} | |
| </div>""", unsafe_allow_html=True) | |
| except requests.exceptions.ConnectionError: | |
| st.error("❌ Could not reach that URL. Make sure it's publicly accessible.") | |
| except json.JSONDecodeError: | |
| st.error("❌ AI returned unexpected output. Try again.") | |
| except Exception as e: | |
| st.error(f"❌ Error: {str(e)}") | |