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app.py

@@ -20,152 +20,57 @@ KNOWHOW = ("MCL: Sylgard 184 PDMS 10:1 ratio 48hr cure green laser PIV 70bpm 5L/
     "MHV: 27mm SJM Regent bileaflet also trileaflet monoleaflet pediatric. "
     "Equipment: Heska HT5 hematology analyzer time-resolved PIV Tygon tubing Arduino Uno.")
 
-CSS = """
-body, .gradio-container {
-    background: #f7f7f8 !important;
-    font-family: -apple-system, BlinkMacSystemFont, Segoe UI, sans-serif !important;
-    margin: 0 !important; padding: 0 !important;
-}
-.tab-nav {
-    background: #ffffff !important;
-    border-bottom: 1px solid #e5e7eb !important;
-    padding: 0 16px !important;
-    display: flex !important;
-    flex-wrap: wrap !important;
-    gap: 0 !important;
-}
-.tab-nav button {
-    background: transparent !important;
-    color: #6b7280 !important;
-    border: none !important;
-    border-bottom: 2px solid transparent !important;
-    padding: 12px 14px !important;
-    font-weight: 500 !important;
-    font-size: 0.82em !important;
-    white-space: nowrap !important;
-    border-radius: 0 !important;
+CHAT_MODELS = {
+    "Llama 3.3 70B (Best)": "llama-3.3-70b-versatile",
+    "Llama 3.1 8B (Fast)": "llama-3.1-8b-instant",
+    "Mixtral 8x7B": "mixtral-8x7b-32768",
+    "Gemma 2 9B": "gemma2-9b-it",
 }
+
+CSS = """
+body, .gradio-container { background: #f7f7f8 !important; font-family: -apple-system, BlinkMacSystemFont, Segoe UI, sans-serif !important; }
+.tab-nav { background: #ffffff !important; border-bottom: 1px solid #e5e7eb !important; padding: 0 16px !important; display: flex !important; flex-wrap: wrap !important; }
+.tab-nav button { background: transparent !important; color: #6b7280 !important; border: none !important; border-bottom: 2px solid transparent !important; padding: 10px 12px !important; font-weight: 500 !important; font-size: 0.8em !important; white-space: nowrap !important; border-radius: 0 !important; }
 .tab-nav button:hover { color: #111827 !important; background: #f9fafb !important; }
 .tab-nav button.selected { color: #c1121f !important; border-bottom: 2px solid #c1121f !important; font-weight: 700 !important; background: transparent !important; }
 .message.user { background: #f3f4f6 !important; color: #1a202c !important; border-radius: 12px !important; }
-.message.bot { background: #ffffff !important; color: #1a202c !important; border-left: 3px solid #c1121f !important; border-radius: 0 12px 12px 12px !important; }
-textarea { background: #ffffff !important; color: #1a202c !important; border: 1px solid #d1d5db !important; border-radius: 12px !important; }
-textarea:focus { border-color: #c1121f !important; outline: none !important; }
+.message.bot { background: #ffffff !important; color: #1a202c !important; border-left: 3px solid #c1121f !important; }
+textarea { background: #ffffff !important; color: #1a202c !important; border: 1px solid #d1d5db !important; border-radius: 10px !important; }
 button.primary { background: #c1121f !important; color: white !important; border: none !important; border-radius: 8px !important; font-weight: 600 !important; }
-button.primary:hover { background: #a00e18 !important; }
 button.secondary { background: #f3f4f6 !important; color: #374151 !important; border: 1px solid #d1d5db !important; border-radius: 8px !important; }
 input[type=number] { background: #f9fafb !important; color: #1a202c !important; border: 1px solid #d1d5db !important; border-radius: 8px !important; }
 label span { color: #374151 !important; font-weight: 500 !important; font-size: 0.85em !important; }
-::-webkit-scrollbar { width: 5px; } ::-webkit-scrollbar-thumb { background: #d1d5db; border-radius: 3px; }
-"""
-
-HEADER_HTML = """
-<div style="
-    background: linear-gradient(135deg, #0a0f2e 0%, #1a0a0a 40%, #0a0f2e 100%);
-    padding: 0;
-    margin: 0;
-    border-bottom: 3px solid #c1121f;
-    position: relative;
-    overflow: hidden;
-">
-    <!-- ECG Background Line -->
-    <svg style="position:absolute;top:0;left:0;width:100%;height:100%;opacity:0.08;" viewBox="0 0 1200 120" preserveAspectRatio="none">
-        <polyline points="0,60 100,60 130,20 150,100 170,10 200,90 220,60 400,60 430,20 450,100 470,10 500,90 520,60 700,60 730,20 750,100 770,10 800,90 820,60 1000,60 1030,20 1050,100 1070,10 1100,90 1120,60 1200,60"
-            fill="none" stroke="#c1121f" stroke-width="3"/>
-    </svg>
-
-    <div style="
-        max-width: 1200px;
-        margin: 0 auto;
-        padding: 18px 24px;
-        display: flex;
-        align-items: center;
-        justify-content: space-between;
-        position: relative;
-        z-index: 1;
-    ">
-        <!-- LEFT: SJSU Spartan Logo SVG -->
-        <div style="display:flex;align-items:center;gap:16px;">
-            <svg width="60" height="60" viewBox="0 0 100 100" xmlns="http://www.w3.org/2000/svg">
-                <!-- Spartan helmet simplified -->
-                <circle cx="50" cy="35" r="28" fill="#0057a8" opacity="0.9"/>
-                <!-- Helmet crest -->
-                <ellipse cx="50" cy="14" rx="22" ry="10" fill="#0057a8"/>
-                <!-- Crest spikes -->
-                <polygon points="30,14 33,4 36,14" fill="#e8a020"/>
-                <polygon points="36,12 39,2 42,12" fill="#e8a020"/>
-                <polygon points="42,11 45,1 48,11" fill="#e8a020"/>
-                <polygon points="48,11 51,1 54,11" fill="#e8a020"/>
-                <polygon points="54,12 57,2 60,12" fill="#e8a020"/>
-                <polygon points="60,14 63,4 66,14" fill="#e8a020"/>
-                <!-- Helmet face -->
-                <rect x="36" y="30" width="28" height="22" rx="4" fill="#0057a8"/>
-                <rect x="40" y="35" width="8" height="12" rx="2" fill="#e8a020"/>
-                <!-- Chin guard -->
-                <rect x="34" y="50" width="32" height="8" rx="4" fill="#0057a8"/>
-                <!-- Helmet shine -->
-                <ellipse cx="42" cy="28" rx="5" ry="3" fill="white" opacity="0.25"/>
-            </svg>
-
-            <div>
-                <div style="color:#9ca3af;font-size:0.7em;font-weight:500;letter-spacing:2px;text-transform:uppercase;">San Jose State University</div>
-                <div style="color:#e8a020;font-size:0.85em;font-weight:700;letter-spacing:1px;">Biomedical Engineering</div>
-            </div>
-        </div>
-
-        <!-- CENTER: CardioLab AI Branding -->
-        <div style="text-align:center;flex:1;padding:0 20px;">
-            <!-- ECG + Heart icon inline -->
-            <div style="display:flex;align-items:center;justify-content:center;gap:12px;margin-bottom:4px;">
-                <svg width="120" height="32" viewBox="0 0 120 32">
-                    <polyline points="0,16 20,16 26,4 30,28 34,2 38,26 44,16 120,16"
-                        fill="none" stroke="#c1121f" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round"/>
-                    <!-- Heart dot on ECG -->
-                    <circle cx="34" cy="2" r="3" fill="#c1121f"/>
-                </svg>
-                <div style="font-size:2.2em;font-weight:900;letter-spacing:2px;">
-                    <span style="color:#ffffff;">Cardio</span><span style="color:#c1121f;">Lab</span><span style="color:#ffffff;"> AI</span>
-                </div>
-                <svg width="120" height="32" viewBox="0 0 120 32" style="transform:scaleX(-1);">
-                    <polyline points="0,16 20,16 26,4 30,28 34,2 38,26 44,16 120,16"
-                        fill="none" stroke="#c1121f" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round"/>
-                    <circle cx="34" cy="2" r="3" fill="#c1121f"/>
-                </svg>
-            </div>
-            <div style="color:#9ca3af;font-size:0.72em;letter-spacing:3px;text-transform:uppercase;">
-                AI Research Agent &nbsp;|&nbsp; Built on Biomni Stanford &nbsp;|&nbsp; Llama 3.3 70B
-            </div>
-        </div>
-
-        <!-- RIGHT: Heart + Stats -->
-        <div style="display:flex;align-items:center;gap:16px;">
-            <div style="text-align:right;">
-                <div style="color:#9ca3af;font-size:0.7em;letter-spacing:1px;text-transform:uppercase;">Research Pillars</div>
-                <div style="color:#ffffff;font-size:0.75em;margin-top:4px;">🫀 MHV &nbsp; 🔬 CKD &nbsp; 💻 FSI</div>
-                <div style="color:#9ca3af;font-size:0.65em;margin-top:2px;">MCL · PIV · TGT · uPAD · COMSOL</div>
-            </div>
-            <!-- Heart SVG -->
-            <svg width="50" height="50" viewBox="0 0 100 90" xmlns="http://www.w3.org/2000/svg">
-                <path d="M50 85 C50 85 5 55 5 30 C5 15 18 5 30 5 C38 5 45 9 50 15 C55 9 62 5 70 5 C82 5 95 15 95 30 C95 55 50 85 50 85Z"
-                    fill="#c1121f" opacity="0.9"/>
-                <path d="M50 75 C50 75 12 50 12 30 C12 18 22 12 30 12 C38 12 45 16 50 22"
-                    fill="none" stroke="rgba(255,255,255,0.3)" stroke-width="3"/>
-                <!-- ECG inside heart -->
-                <polyline points="25,45 32,45 35,35 38,55 41,30 44,50 50,45 75,45"
-                    fill="none" stroke="white" stroke-width="2.5" stroke-linecap="round" opacity="0.9"/>
-            </svg>
-        </div>
-    </div>
-
-    <!-- Bottom accent bar -->
-    <div style="
-        height: 3px;
-        background: linear-gradient(90deg, #0057a8, #c1121f, #e8a020, #c1121f, #0057a8);
-        margin: 0;
-    "></div>
-</div>
 """
 
+HEADER = """<div style="background:linear-gradient(135deg,#0a0f2e 0%,#1a0a0a 100%);padding:0;border-bottom:3px solid #c1121f;position:relative;overflow:hidden;">
+<svg style="position:absolute;top:0;left:0;width:100%;height:100%;opacity:0.07;" viewBox="0 0 1200 120" preserveAspectRatio="none">
+<polyline points="0,60 100,60 130,20 150,100 170,10 200,90 220,60 400,60 430,20 450,100 470,10 500,90 520,60 700,60 730,20 750,100 770,10 800,90 820,60 1000,60 1030,20 1050,100 1070,10 1100,90 1120,60 1200,60" fill="none" stroke="#c1121f" stroke-width="3"/>
+</svg>
+<div style="max-width:1200px;margin:0 auto;padding:16px 24px;display:flex;align-items:center;justify-content:space-between;position:relative;z-index:1;">
+<div style="display:flex;align-items:center;gap:14px;">
+<svg width="55" height="55" viewBox="0 0 100 100"><circle cx="50" cy="35" r="28" fill="#0057a8" opacity="0.9"/><ellipse cx="50" cy="14" rx="22" ry="10" fill="#0057a8"/>
+<polygon points="30,14 33,4 36,14" fill="#e8a020"/><polygon points="36,12 39,2 42,12" fill="#e8a020"/><polygon points="42,11 45,1 48,11" fill="#e8a020"/>
+<polygon points="48,11 51,1 54,11" fill="#e8a020"/><polygon points="54,12 57,2 60,12" fill="#e8a020"/><polygon points="60,14 63,4 66,14" fill="#e8a020"/>
+<rect x="36" y="30" width="28" height="22" rx="4" fill="#0057a8"/><rect x="40" y="35" width="8" height="12" rx="2" fill="#e8a020"/>
+<rect x="34" y="50" width="32" height="8" rx="4" fill="#0057a8"/></svg>
+<div><div style="color:#9ca3af;font-size:0.7em;font-weight:500;letter-spacing:2px;text-transform:uppercase;">San Jose State University</div>
+<div style="color:#e8a020;font-size:0.82em;font-weight:700;">Biomedical Engineering</div></div></div>
+<div style="text-align:center;flex:1;padding:0 20px;">
+<div style="display:flex;align-items:center;justify-content:center;gap:10px;margin-bottom:3px;">
+<svg width="100" height="28" viewBox="0 0 120 32"><polyline points="0,16 20,16 26,4 30,28 34,2 38,26 44,16 120,16" fill="none" stroke="#c1121f" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round"/></svg>
+<div style="font-size:2em;font-weight:900;letter-spacing:2px;"><span style="color:#ffffff;">Cardio</span><span style="color:#c1121f;">Lab</span><span style="color:#ffffff;"> AI</span></div>
+<svg width="100" height="28" viewBox="0 0 120 32" style="transform:scaleX(-1);"><polyline points="0,16 20,16 26,4 30,28 34,2 38,26 44,16 120,16" fill="none" stroke="#c1121f" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round"/></svg></div>
+<div style="color:#9ca3af;font-size:0.7em;letter-spacing:2px;text-transform:uppercase;">AI Research Agent | Biomni Stanford | Llama 3.3 70B</div></div>
+<div style="display:flex;align-items:center;gap:14px;">
+<div style="text-align:right;"><div style="color:#9ca3af;font-size:0.68em;letter-spacing:1px;text-transform:uppercase;">Research Pillars</div>
+<div style="color:#ffffff;font-size:0.72em;margin-top:3px;">MHV  CKD  FSI</div>
+<div style="color:#9ca3af;font-size:0.62em;margin-top:2px;">MCL · PIV · TGT · uPAD · COMSOL</div></div>
+<svg width="48" height="48" viewBox="0 0 100 90">
+<path d="M50 85 C50 85 5 55 5 30 C5 15 18 5 30 5 C38 5 45 9 50 15 C55 9 62 5 70 5 C82 5 95 15 95 30 C95 55 50 85 50 85Z" fill="#c1121f" opacity="0.9"/>
+<polyline points="25,45 32,45 35,35 38,55 41,30 44,50 50,45 75,45" fill="none" stroke="white" stroke-width="2.5" stroke-linecap="round" opacity="0.9"/></svg></div></div>
+<div style="height:3px;background:linear-gradient(90deg,#0057a8,#c1121f,#e8a020,#c1121f,#0057a8);"></div></div>"""
+
+# ── SESSION MANAGEMENT ─────────────────────────────────────────────
 def load_all_sessions():
     if not HF_TOKEN: return {}
     try:
@@ -176,9 +81,10 @@ def load_all_sessions():
 def save_all_sessions(sessions):
     if not HF_TOKEN: return False
     try:
-        api = HfApi(token=HF_TOKEN)
-        api.upload_file(path_or_fileobj=json.dumps(sessions, indent=2).encode(), path_in_repo="chat_history.json",
-            repo_id=HISTORY_REPO, repo_type="dataset", token=HF_TOKEN, commit_message="Update")
+        api2 = HfApi(token=HF_TOKEN)
+        api2.upload_file(path_or_fileobj=json.dumps(sessions, indent=2).encode(),
+            path_in_repo="chat_history.json", repo_id=HISTORY_REPO, repo_type="dataset",
+            token=HF_TOKEN, commit_message="Update")
         return True
     except: return False
 
@@ -213,119 +119,199 @@ def delete_session(name):
 
 def new_chat(): return [], "", "New chat started"
 
-def get_pubmed(query, n=5):
-    try:
-        forced = query + " AND (heart valve OR hemodynamics OR microfluidic OR thrombogen OR creatinine OR PIV OR CKD)"
-        r = requests.get("https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi",
-            params={"db":"pubmed","term":forced,"retmax":n,"retmode":"json","sort":"date","field":"tiab"},timeout=10)
-        ids = r.json()["esearchresult"]["idlist"]
-        if not ids: return ""
-        return chr(10).join(["https://pubmed.ncbi.nlm.nih.gov/"+i for i in ids])
-    except: return ""
-
-def expand_query(query):
+# ── SEARCH FUNCTIONS ───────────────────────────────────────────────
+def expand_query_ai(query, model_id="llama-3.3-70b-versatile"):
     if not GROQ_KEY: return query
     try:
         client = Groq(api_key=GROQ_KEY)
-        system_msg = ("You are a biomedical engineering PubMed search expert for SJSU CardioLab. "
-            "Convert the user query into optimized PubMed keywords. "
-            "Focus on: mechanical heart valves, hemodynamics, blood flow, PIV, thrombogenicity, FSI, CFD, microfluidics, CKD, creatinine. "
-            "Return ONLY the search terms, no explanation, no dashes, no punctuation.")
-        resp = client.chat.completions.create(
-            model="llama-3.3-70b-versatile",
-            messages=[
-                {"role":"system","content":system_msg},
-                {"role":"user","content":"Optimize for PubMed: "+query}
-            ],
-            max_tokens=60
-        )
-        expanded = resp.choices[0].message.content.strip()
-        return expanded if expanded else query
+        resp = client.chat.completions.create(model=model_id,
+            messages=[{"role":"system","content":"Biomedical PubMed search expert for SJSU CardioLab. Convert query to optimized MeSH terms and technical keywords. Focus on: mechanical heart valves, hemodynamics, blood flow, PIV, thrombogenicity, FSI, CFD, microfluidics, CKD, creatinine. Return ONLY search terms no explanation."},
+            {"role":"user","content":"Optimize for PubMed: "+query}],max_tokens=80)
+        return resp.choices[0].message.content.strip() or query
     except: return query
 
-def search_pubmed_smart(query, n=8):
+def fetch_pubmed(query, n=8):
     try:
-        expanded = expand_query(query)
-        biomedical_filter = " AND (heart valve OR hemodynamics OR microfluidic OR thrombogen OR creatinine OR PIV OR CFD OR fluid structure OR CKD)"
-        forced = expanded + biomedical_filter
+        biofilter = " AND (heart valve OR hemodynamics OR microfluidic OR thrombogen OR creatinine OR PIV OR CFD OR CKD OR fluid structure)"
         r = requests.get("https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi",
-            params={"db":"pubmed","term":forced,"retmax":n,"retmode":"json","sort":"date","field":"tiab"},timeout=10)
+            params={"db":"pubmed","term":query+biofilter,"retmax":n,"retmode":"json","sort":"date","field":"tiab"},timeout=12)
         ids = r.json()["esearchresult"]["idlist"]
-        if not ids:
-            return "No PubMed results found for this topic.", expanded
+        if not ids: return []
         r2 = requests.get("https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi",
-            params={"db":"pubmed","id":",".join(ids),"retmode":"xml","rettype":"abstract"},timeout=10)
-        lines = []
-        try:
-            import xml.etree.ElementTree as ET
-            root = ET.fromstring(r2.content)
-            for article in root.findall(".//PubmedArticle"):
-                try:
-                    title_el = article.find(".//ArticleTitle")
-                    title = title_el.text if title_el is not None else "No title"
-                    pmid_el = article.find(".//PMID")
-                    pmid = pmid_el.text if pmid_el is not None else ""
-                    year_el = article.find(".//PubDate/Year")
-                    year = year_el.text if year_el is not None else ""
-                    url = "https://pubmed.ncbi.nlm.nih.gov/"+pmid
-                    lines.append(str(title)[:90]+" ("+year+")"+chr(10)+"  "+url)
-                except: continue
-        except:
-            lines = ["https://pubmed.ncbi.nlm.nih.gov/"+i for i in ids]
-        return chr(10)+chr(10).join(lines), expanded
-    except Exception as e:
-        return "PubMed error: "+str(e), query
+            params={"db":"pubmed","id":",".join(ids),"retmode":"xml","rettype":"abstract"},timeout=12)
+        import xml.etree.ElementTree as ET
+        root = ET.fromstring(r2.content)
+        results = []
+        for article in root.findall(".//PubmedArticle"):
+            try:
+                title = article.find(".//ArticleTitle").text or "No title"
+                pmid = article.find(".//PMID").text or ""
+                year_el = article.find(".//PubDate/Year")
+                year = year_el.text if year_el is not None else ""
+                results.append({"source":"PubMed","title":str(title),"year":year,
+                    "url":"https://pubmed.ncbi.nlm.nih.gov/"+pmid,"citations":"N/A"})
+            except: continue
+        return results
+    except: return []
 
-def search_scholar_smart(query, n=8):
+def fetch_scholar(query, n=8):
     try:
-        expanded = expand_query(query)
         r = requests.get("https://api.semanticscholar.org/graph/v1/paper/search",
-            params={"query":expanded,"limit":n,"fields":"title,year,url,citationCount"},
-            timeout=15)
+            params={"query":query,"limit":n,"fields":"title,year,url,citationCount"},timeout=12)
         papers = r.json().get("data",[])
-        if not papers:
-            return "No Semantic Scholar results found."
-        out = []
+        results = []
         for p in papers:
-            title = p.get("title","")
-            year = str(p.get("year",""))
-            url = p.get("url","")
-            citations = str(p.get("citationCount",0))
-            if url:
-                out.append(str(title)[:90]+" ("+year+") | "+citations+" citations"+chr(10)+"  "+url)
-        return chr(10)+chr(10).join(out) if out else "No results."
-    except Exception as e:
-        return "Scholar error: "+str(e)
-
-def quick_search(query):
+            year = p.get("year",0) or 0
+            if int(year) < 2015: continue
+            results.append({"source":"Semantic Scholar","title":p.get("title",""),"year":str(year),
+                "url":p.get("url",""),"citations":str(p.get("citationCount",0))})
+        results.sort(key=lambda x:(x["year"],int(x["citations"]) if x["citations"].isdigit() else 0),reverse=True)
+        return results
+    except: return []
+
+def fetch_europe_pmc(query, n=6):
+    try:
+        r = requests.get("https://www.ebi.ac.uk/europepmc/webservices/rest/search",
+            params={"query":query,"format":"json","pageSize":n,"sort":"P_PDATE_D desc","resulttype":"core"},timeout=12)
+        articles = r.json().get("resultList",{}).get("result",[])
+        results = []
+        for a in articles:
+            year = str(a.get("pubYear",""))
+            if year and int(year) < 2015: continue
+            pmid = a.get("pmid","")
+            doi = a.get("doi","")
+            url = ("https://pubmed.ncbi.nlm.nih.gov/"+pmid if pmid else "https://doi.org/"+doi if doi else "")
+            if not url: continue
+            results.append({"source":"Europe PMC","title":a.get("title",""),"year":year,
+                "url":url,"citations":str(a.get("citedByCount",0))})
+        return results
+    except: return []
+
+def fetch_crossref(query, n=5):
+    try:
+        r = requests.get("https://api.crossref.org/works",
+            params={"query":query,"rows":n,"sort":"relevance","select":"title,DOI,published"},timeout=12)
+        items = r.json().get("message",{}).get("items",[])
+        results = []
+        for item in items:
+            title = item.get("title",[""])[0] if item.get("title") else ""
+            doi = item.get("DOI","")
+            pub = item.get("published",{}).get("date-parts",[[""]])[0]
+            year = str(pub[0]) if pub else ""
+            if year and int(year) < 2015: continue
+            if not doi: continue
+            results.append({"source":"CrossRef","title":title,"year":year,
+                "url":"https://doi.org/"+doi,"citations":"N/A"})
+        return results
+    except: return []
+
+def fetch_sjsu_scholarworks(query, n=6):
+    try:
+        # SJSU ScholarWorks Digital Commons search
+        r = requests.get("https://scholarworks.sjsu.edu/do/search/",
+            params={"q":query,"start":"0","context":"6781027","format":"json"},
+            timeout=12, headers={"User-Agent":"CardioLab-AI/1.0"})
+        results = []
+        if r.status_code == 200:
+            try:
+                data = r.json()
+                docs = data.get("response",{}).get("docs",[])
+                for doc in docs[:n]:
+                    title = doc.get("title","")
+                    year = str(doc.get("publication_date",""))[:4]
+                    url = doc.get("url","") or "https://scholarworks.sjsu.edu/"
+                    if title:
+                        results.append({"source":"SJSU ScholarWorks","title":str(title),"year":year,
+                            "url":url,"citations":"SJSU"})
+            except: pass
+        if not results:
+            # Fallback: provide direct SJSU search link
+            search_url = "https://scholarworks.sjsu.edu/do/search/?q="+requests.utils.quote(query)+"&context=6781027"
+            results.append({"source":"SJSU ScholarWorks",
+                "title":"Click to search SJSU ScholarWorks for: "+query,
+                "year":"","url":search_url,"citations":"SJSU"})
+        return results
+    except:
+        search_url = "https://scholarworks.sjsu.edu/do/search/?q="+requests.utils.quote(query)
+        return [{"source":"SJSU ScholarWorks","title":"Search SJSU ScholarWorks: "+query,
+            "year":"","url":search_url,"citations":"SJSU"}]
+
+def rank_with_ai(query, results, model_id="llama-3.3-70b-versatile"):
+    if not GROQ_KEY or not results: return results
+    try:
+        client = Groq(api_key=GROQ_KEY)
+        papers_text = chr(10).join([str(i+1)+". "+r["title"]+" ("+r["year"]+")" for i,r in enumerate(results[:15])])
+        resp = client.chat.completions.create(model=model_id,
+            messages=[{"role":"system","content":"Biomedical research expert. Rank papers by relevance to query. Return ONLY numbers comma separated. Example: 3,1,5,2,4"},
+            {"role":"user","content":"Query: "+query+chr(10)+"Papers:"+chr(10)+papers_text}],max_tokens=60)
+        order_text = resp.choices[0].message.content.strip()
+        order = [int(x.strip())-1 for x in order_text.split(",") if x.strip().isdigit()]
+        ranked = [results[i] for i in order if i < len(results)]
+        rest = [r for i,r in enumerate(results) if i not in order]
+        return ranked + rest
+    except: return results
+
+def quick_search(query, search_model="Llama 3.3 70B (Best)"):
     if not query.strip(): return "Please enter a research topic."
-    pubmed_results, expanded = search_pubmed_smart(query, n=8)
-    scholar_results = search_scholar_smart(query, n=6)
-    result = "YOUR QUERY: " + query + chr(10)
-    result += "AI EXPANDED: " + expanded + chr(10)
-    result += "="*45 + chr(10) + chr(10)
-    result += "PUBMED RESULTS (titles + verified links):" + chr(10)
-    result += pubmed_results + chr(10) + chr(10)
-    result += "="*45 + chr(10)
-    result += "SEMANTIC SCHOLAR RESULTS:" + chr(10)
-    result += scholar_results
-    return result
-
-def research_chat(message, history):
+    model_id = CHAT_MODELS.get(search_model, "llama-3.3-70b-versatile")
+    expanded = expand_query_ai(query, model_id)
+    r1 = fetch_pubmed(expanded, n=8)
+    r2 = fetch_scholar(expanded, n=8)
+    r3 = fetch_europe_pmc(expanded, n=6)
+    r4 = fetch_crossref(expanded, n=5)
+    r5 = fetch_sjsu_scholarworks(query, n=6)
+    all_results = r1 + r2 + r3 + r4 + r5
+    seen = set()
+    unique = []
+    for r in all_results:
+        key = r["title"][:50].lower().strip()
+        if key not in seen and r["url"]:
+            seen.add(key); unique.append(r)
+    ranked = rank_with_ai(query, unique, model_id)
+    out = "QUERY: "+query+chr(10)
+    out += "AI MODEL: "+search_model+chr(10)
+    out += "AI EXPANDED: "+expanded+chr(10)
+    out += "SOURCES: PubMed + Semantic Scholar + Europe PMC + CrossRef + SJSU ScholarWorks"+chr(10)
+    out += "TOTAL UNIQUE PAPERS: "+str(len(ranked))+chr(10)
+    out += "="*45+chr(10)+chr(10)
+    groups = {"PubMed":[],"Semantic Scholar":[],"Europe PMC":[],"CrossRef":[],"SJSU ScholarWorks":[]}
+    for r in ranked[:25]:
+        if r["source"] in groups: groups[r["source"]].append(r)
+    for source, papers in groups.items():
+        if not papers: continue
+        out += "--- "+source+" ("+str(len(papers))+" papers) ---"+chr(10)
+        for p in papers:
+            out += p["title"][:85]+" ("+p["year"]+")"
+            if p["citations"] not in ("N/A","SJSU",""): out += " | "+p["citations"]+" citations"
+            out += chr(10)+"  "+p["url"]+chr(10)+chr(10)
+    return out
+
+def get_pubmed(query, n=3):
+    try:
+        r = requests.get("https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi",
+            params={"db":"pubmed","term":query+" AND (heart valve OR hemodynamics OR microfluidic OR thrombogen OR creatinine OR CKD)","retmax":n,"retmode":"json","sort":"date","field":"tiab"},timeout=10)
+        ids = r.json()["esearchresult"]["idlist"]
+        if not ids: return ""
+        return chr(10).join(["https://pubmed.ncbi.nlm.nih.gov/"+i for i in ids])
+    except: return ""
+
+# ── CHAT ───────────────────────────────────────────────────────────
+def research_chat(message, history, chat_model="Llama 3.3 70B (Best)"):
     if not GROQ_KEY:
         history.append({"role":"user","content":message})
         history.append({"role":"assistant","content":"Error: Add GROQ_API_KEY to Space Settings."})
         return "", history
     try:
+        model_id = CHAT_MODELS.get(chat_model, "llama-3.3-70b-versatile")
         client = Groq(api_key=GROQ_KEY)
         msgs = [{"role":"system","content":"You are CardioLab AI for SJSU Biomedical Engineering. Expert in MHV MCL PIV TGT uPAD CKD FSI. Remember conversation. Never invent URLs. "+KNOWHOW}]
         for item in history:
             if isinstance(item, dict): msgs.append({"role":item["role"],"content":item["content"]})
         msgs.append({"role":"user","content":message})
-        resp = client.chat.completions.create(model="llama-3.3-70b-versatile",messages=msgs,max_tokens=700)
+        resp = client.chat.completions.create(model=model_id,messages=msgs,max_tokens=700)
         answer = resp.choices[0].message.content
         pubmed = get_pubmed(message, n=3)
-        if pubmed: answer += chr(10)+chr(10)+"📚 PubMed:"+chr(10)+pubmed
+        if pubmed: answer += chr(10)+chr(10)+"PubMed:"+chr(10)+pubmed
         history.append({"role":"user","content":message})
         history.append({"role":"assistant","content":answer})
         return "", history
@@ -347,13 +333,14 @@ def voice_chat(audio, history):
             if isinstance(item, dict): msgs.append({"role":item["role"],"content":item["content"]})
         msgs.append({"role":"user","content":tx.text})
         resp = client.chat.completions.create(model="llama-3.3-70b-versatile",messages=msgs,max_tokens=500)
-        history.append({"role":"user","content":"🎙️ "+tx.text})
+        history.append({"role":"user","content":"Voice: "+tx.text})
         history.append({"role":"assistant","content":resp.choices[0].message.content})
         return history
     except Exception as e:
         history.append({"role":"assistant","content":"Voice error: "+str(e)})
         return history
 
+# ── ANALYSIS TOOLS ─────────────────────────────────────────────────
 def analyze_upad_photo(image):
     if image is None: return None, "Upload a uPAD photo first."
     try:
@@ -370,7 +357,7 @@ def analyze_upad_photo(image):
         else: s,a="Stage 5 CKD","Emergency care."
         ri=img.copy()
         import PIL.ImageDraw as D; D.Draw(ri).rectangle([x1,y1,x2,y2],outline=(0,255,0),width=3)
-        return ri,("uPAD ANALYSIS"+chr(10)+"━"*22+chr(10)+"R:"+str(round(R,1))+" G:"+str(round(G,1))+" B:"+str(round(B,1))+chr(10)+"Creatinine: "+str(c)+" mg/dL"+chr(10)+"Stage: "+s+chr(10)+"Action: "+a)
+        return ri,("uPAD ANALYSIS"+chr(10)+"R:"+str(round(R,1))+" G:"+str(round(G,1))+" B:"+str(round(B,1))+chr(10)+"Creatinine: "+str(c)+" mg/dL"+chr(10)+"Stage: "+s+chr(10)+"Action: "+a)
     except Exception as e: return None,"Error: "+str(e)
 
 def mk_chart(fn,title,bg,fg,gc,ac,pb):
@@ -393,42 +380,38 @@ def analyze_piv_csv(file,theme="White"):
         pb="#f7fafc" if theme=="White" else "#132340"
         x=np.arange(len(df))
         vc=next((c for c in cols if any(k in c for k in ["vel","speed","v_mag"])),num_cols[0] if num_cols else None)
-        sc=next((c for c in cols if any(k in c for k in ["shear","stress","tau","wss"])),num_cols[1] if len(num_cols)>1 else None)
+        sc2=next((c for c in cols if any(k in c for k in ["shear","stress","tau","wss"])),num_cols[1] if len(num_cols)>1 else None)
         tc=next((c for c in cols if "time" in c or "frame" in c),None); xv=df[tc] if tc else x
         def pv(ax):
             if vc:
                 ax.plot(xv,df[vc],color="#c1121f",linewidth=2.5,marker="o",markersize=5)
                 ax.fill_between(xv,df[vc],alpha=0.15,color="#c1121f")
                 ax.axhline(y=2.0,color="#f59e0b",linestyle="--",linewidth=2,label="Risk: 2.0 m/s")
-                ax.set_ylabel("Velocity (m/s)",color=ac,fontsize=11); ax.set_xlabel(tc or "Sample",color=ac,fontsize=11)
-                ax.legend(fontsize=9,labelcolor=fg,facecolor=pb)
+                ax.set_ylabel("Velocity (m/s)",color=ac,fontsize=11); ax.legend(fontsize=9,labelcolor=fg,facecolor=pb)
         def ps(ax):
-            if sc:
+            if sc2:
                 xp=xv.values if tc else x
-                ax.plot(xp,df[sc],color="#0057a8",linewidth=2.5,marker="s",markersize=5)
-                ax.fill_between(xp,df[sc],alpha=0.15,color="#0057a8")
+                ax.plot(xp,df[sc2],color="#0057a8",linewidth=2.5,marker="s",markersize=5)
+                ax.fill_between(xp,df[sc2],alpha=0.15,color="#0057a8")
                 ax.axhline(y=5,color="#f59e0b",linestyle="--",linewidth=2,label="Caution: 5 Pa")
                 ax.axhline(y=10,color="#c1121f",linestyle="--",linewidth=2,label="High risk: 10 Pa")
-                ax.set_ylabel("Shear (Pa)",color=ac,fontsize=11); ax.set_xlabel(tc or "Sample",color=ac,fontsize=11)
-                ax.legend(fontsize=9,labelcolor=fg,facecolor=pb)
+                ax.set_ylabel("Shear (Pa)",color=ac,fontsize=11); ax.legend(fontsize=9,labelcolor=fg,facecolor=pb)
         def psc(ax):
-            if vc and sc:
-                s2=ax.scatter(df[vc],df[sc],c=x,cmap="RdYlGn_r",s=90,edgecolors=fg,linewidth=0.5,zorder=5)
-                cb=plt.colorbar(s2,ax=ax,label="Time"); cb.ax.yaxis.label.set_color(fg); cb.ax.tick_params(colors=ac)
-                ax.axvline(x=2.0,color="#f59e0b",linestyle="--",linewidth=2,label="Vel risk")
-                ax.axhline(y=10,color="#c1121f",linestyle="--",linewidth=2,label="Shear risk")
+            if vc and sc2:
+                s3=ax.scatter(df[vc],df[sc2],c=x,cmap="RdYlGn_r",s=90,edgecolors=fg,linewidth=0.5,zorder=5)
+                cb=plt.colorbar(s3,ax=ax,label="Time"); cb.ax.yaxis.label.set_color(fg); cb.ax.tick_params(colors=ac)
+                ax.axvline(x=2.0,color="#f59e0b",linestyle="--",linewidth=2); ax.axhline(y=10,color="#c1121f",linestyle="--",linewidth=2)
                 ax.set_xlabel("Velocity (m/s)",color=ac,fontsize=11); ax.set_ylabel("Shear (Pa)",color=ac,fontsize=11)
-                ax.legend(fontsize=9,labelcolor=fg,facecolor=pb)
         def psum(ax):
             ax.axis("off"); risk=[]
-            st="CLINICAL SUMMARY"+chr(10)+"━"*20+chr(10)+chr(10)
+            st="CLINICAL SUMMARY"+chr(10)+"="*20+chr(10)+chr(10)
             for col in num_cols[:3]:
                 mn=round(df[col].mean(),3); mx=round(df[col].max(),3)
                 st+=col[:14]+":"+chr(10)+"  Mean: "+str(mn)+chr(10)+"  Max:  "+str(mx)+chr(10)+chr(10)
                 if "vel" in col and mx>2.0: risk.append("HIGH VELOCITY")
                 if "shear" in col and mx>10: risk.append("HIGH SHEAR")
             bc="#c1121f" if risk else "#2ecc71"
-            st+="━"*20+chr(10)+("OVERALL: HIGH RISK" if risk else "OVERALL: LOW RISK")
+            st+="="*20+chr(10)+("OVERALL: HIGH RISK" if risk else "OVERALL: LOW RISK")
             ax.text(0.05,0.97,st,transform=ax.transAxes,color=fg,fontsize=10,va="top",fontfamily="monospace",
                 bbox=dict(boxstyle="round,pad=0.8",facecolor=pb,edgecolor=bc,linewidth=2.5))
         i1=mk_chart(pv,"Velocity Profile",bg,fg,gc,ac,pb)
@@ -442,7 +425,7 @@ def analyze_piv_csv(file,theme="White"):
                 resp=client.chat.completions.create(model="llama-3.3-70b-versatile",
                     messages=[{"role":"system","content":"PIV expert SJSU CardioLab. Analyze stats give clinical interpretation."},
                     {"role":"user","content":"PIV from 27mm SJM Regent MHV 70bpm:"+chr(10)+df.describe().to_string()[:500]}],max_tokens=250)
-                ai=chr(10)+"━"*20+chr(10)+"AI: "+resp.choices[0].message.content
+                ai=chr(10)+"AI: "+resp.choices[0].message.content
             except: pass
         return i1,i2,i3,i4,"PIV: "+str(len(df))+" rows | "+", ".join(df.columns.tolist())+ai
     except Exception as e: return None,None,None,None,"Error: "+str(e)
@@ -473,7 +456,7 @@ def analyze_tgt_csv(file,theme="White"):
                         for xi,yi in zip(xp,yp): ax.annotate(str(round(yi,1)),(xi,yi),textcoords="offset points",xytext=(0,10),ha="center",color=fg,fontsize=10,fontweight="bold")
                     ax.axhline(y=lim,color="#f59e0b",linestyle="--",linewidth=2.5,label=ll)
                     ax.legend(fontsize=10,labelcolor=fg,facecolor=pb)
-                    ax.set_ylabel(yl,color=ac,fontsize=11); ax.set_xlabel(tc or "Sample",color=ac,fontsize=11)
+                    ax.set_ylabel(yl,color=ac,fontsize=11)
                     mv=round(float(np.max(yp)),2); st="HIGH" if mv>lim else "NORMAL"
                     ax.set_title(title+chr(10)+"Max: "+str(mv)+"  Status: "+st,color=fg,fontweight="bold",fontsize=12)
             return mk_chart(fn,title,bg,fg,gc,ac,pb)
@@ -488,7 +471,7 @@ def analyze_tgt_csv(file,theme="White"):
                 resp=client.chat.completions.create(model="llama-3.3-70b-versatile",
                     messages=[{"role":"system","content":"Hematology expert SJSU CardioLab. Give thrombogenicity risk LOW MODERATE or HIGH."},
                     {"role":"user","content":"TGT from 27mm SJM Regent:"+chr(10)+df.describe().to_string()[:500]}],max_tokens=250)
-                ai=chr(10)+"━"*20+chr(10)+"AI: "+resp.choices[0].message.content
+                ai=chr(10)+"AI: "+resp.choices[0].message.content
             except: pass
         return i1,i2,i3,i4,"TGT: "+str(len(df))+" rows | "+", ".join(df.columns.tolist())+ai
     except Exception as e: return None,None,None,None,"Error: "+str(e)
@@ -520,72 +503,69 @@ def generate_image(prompt):
     except Exception as e: return None,"Error: "+str(e),""
 
 def piv_manual(v,s,h):
-    vr="HIGH — stenosis risk" if float(v)>2.0 else "NORMAL"
-    sr="HIGH — thrombosis risk" if float(s)>10 else "ELEVATED" if float(s)>5 else "NORMAL"
-    return "Velocity: "+str(v)+" m/s — "+vr+chr(10)+"Shear: "+str(s)+" Pa — "+sr+chr(10)+"HR: "+str(h)+" bpm"
+    vr="HIGH - stenosis" if float(v)>2.0 else "NORMAL"
+    sr="HIGH - thrombosis" if float(s)>10 else "ELEVATED" if float(s)>5 else "NORMAL"
+    return "Velocity: "+str(v)+" m/s - "+vr+chr(10)+"Shear: "+str(s)+" Pa - "+sr+chr(10)+"HR: "+str(h)+" bpm"
 
 def tgt_manual(t,p,h,pl,tm):
     risk=sum([float(t)>15,float(p)>2.0,float(h)>50,float(pl)<150])
-    return "TAT:"+str(t)+" PF1.2:"+str(p)+chr(10)+"Hemo:"+str(h)+" Plt:"+str(pl)+chr(10)+"Time:"+str(tm)+" min"+chr(10)+"RESULT: "+("HIGH RISK" if risk>=3 else "MODERATE" if risk>=2 else "LOW RISK")
-
-with gr.Blocks(title="CardioLab AI — SJSU", css=CSS) as demo:
-
-    gr.HTML(HEADER_HTML)
+    return "TAT:"+str(t)+" PF1.2:"+str(p)+chr(10)+"Hemo:"+str(h)+" Plt:"+str(pl)+chr(10)+"RESULT: "+("HIGH RISK" if risk>=3 else "MODERATE" if risk>=2 else "LOW RISK")
 
+# ── UI ─────────────────────────────────────────────────────────────
+with gr.Blocks(title="CardioLab AI - SJSU", css=CSS) as demo:
+    gr.HTML(HEADER)
     with gr.Tabs():
 
-        with gr.Tab("💬 Chat"):
+        with gr.Tab("Chat"):
             with gr.Row():
-                with gr.Column(scale=1, min_width=210):
-                    gr.HTML('''<div style="background:#202123;padding:10px;border-radius:8px;margin-bottom:6px;">
-                        <div style="color:#e8a020;font-weight:700;font-size:0.85em;letter-spacing:1px;">⚔️ SJSU CARDIOLAB</div>
-                        <div style="color:#9ca3af;font-size:0.7em;margin-top:2px;">Conversations</div>
-                    </div>''')
-                    new_chat_btn = gr.Button("✏️  New Chat", variant="secondary")
-                    gr.HTML('''<div style="color:#9ca3af;font-size:0.72em;padding:8px 2px 4px 2px;letter-spacing:1px;">SAVED SESSIONS</div>''')
-                    session_dropdown = gr.Dropdown(choices=get_session_list(), label="", interactive=True, container=False)
-                    load_btn = gr.Button("📂  Load Session", variant="primary")
-                    session_name_box = gr.Textbox(placeholder="Name this session...", label="", lines=1, container=False)
+                with gr.Column(scale=1, min_width=200):
+                    gr.HTML('''<div style="background:#202123;padding:10px;border-radius:8px;margin-bottom:6px;"><div style="color:#e8a020;font-weight:700;font-size:0.85em;">SJSU CARDIOLAB</div><div style="color:#9ca3af;font-size:0.7em;">Conversations</div></div>''')
+                    new_chat_btn = gr.Button("New Chat", variant="secondary")
+                    session_dropdown = gr.Dropdown(choices=get_session_list(), label="Saved Sessions", interactive=True)
+                    load_btn = gr.Button("Load Session", variant="primary")
+                    session_name_box = gr.Textbox(placeholder="Session name...", label="", lines=1, container=False)
                     with gr.Row():
-                        save_btn = gr.Button("💾 Save", variant="primary", scale=2)
-                        delete_btn = gr.Button("🗑️", variant="secondary", scale=1)
+                        save_btn = gr.Button("Save", variant="primary", scale=2)
+                        delete_btn = gr.Button("Del", variant="secondary", scale=1)
                     session_status = gr.Textbox(label="", lines=1, interactive=False, container=False)
-
                 with gr.Column(scale=4):
-                    chatbot = gr.Chatbot(label="", height=500, show_label=False, container=False)
+                    chatbot = gr.Chatbot(label="", height=480, show_label=False, container=False)
                     with gr.Row():
-                        msg_box = gr.Textbox(placeholder="Message CardioLab AI...", label="", lines=2, scale=5, container=False)
-                        with gr.Column(scale=1, min_width=80):
-                            send_btn = gr.Button("Send ↑", variant="primary")
+                        msg_box = gr.Textbox(placeholder="Message CardioLab AI...", label="", lines=2, scale=4, container=False)
+                        with gr.Column(scale=1, min_width=120):
+                            chat_model_dd = gr.Dropdown(choices=list(CHAT_MODELS.keys()), value="Llama 3.3 70B (Best)", label="Model")
+                            send_btn = gr.Button("Send", variant="primary")
                             clear_btn = gr.Button("Clear", variant="secondary")
-
-            send_btn.click(research_chat, inputs=[msg_box, chatbot], outputs=[msg_box, chatbot])
-            msg_box.submit(research_chat, inputs=[msg_box, chatbot], outputs=[msg_box, chatbot])
+            send_btn.click(research_chat, inputs=[msg_box, chatbot, chat_model_dd], outputs=[msg_box, chatbot])
+            msg_box.submit(research_chat, inputs=[msg_box, chatbot, chat_model_dd], outputs=[msg_box, chatbot])
             clear_btn.click(lambda: ([], ""), outputs=[chatbot, msg_box])
             new_chat_btn.click(new_chat, outputs=[chatbot, msg_box, session_status])
             save_btn.click(save_session, inputs=[chatbot, session_name_box], outputs=[session_status, session_dropdown])
             load_btn.click(load_session, inputs=session_dropdown, outputs=[chatbot, session_status])
             delete_btn.click(delete_session, inputs=session_dropdown, outputs=[session_status, session_dropdown])
 
-        with gr.Tab("🎙️ Voice"):
-            voice_chatbot = gr.Chatbot(label="", height=380, show_label=False)
-            audio_input = gr.Audio(sources=["microphone"], type="filepath", label="Record your question")
+        with gr.Tab("Voice"):
+            voice_chatbot = gr.Chatbot(label="", height=360, show_label=False)
+            audio_input = gr.Audio(sources=["microphone"], type="filepath", label="Record Question")
             with gr.Row():
                 voice_btn = gr.Button("Ask by Voice", variant="primary")
                 voice_clear = gr.Button("Clear", variant="secondary")
             voice_btn.click(voice_chat, inputs=[audio_input, voice_chatbot], outputs=voice_chatbot)
             voice_clear.click(lambda: [], outputs=voice_chatbot)
 
-        with gr.Tab("🔍 Papers"):
+        with gr.Tab("Papers"):
+            gr.Markdown("### Search 5 sources: PubMed + Semantic Scholar + Europe PMC + CrossRef + SJSU ScholarWorks")
             with gr.Row():
-                search_input = gr.Textbox(placeholder="e.g. mechanical heart valve thrombogenicity 2024", label="Research Topic", scale=4)
-                search_btn = gr.Button("Search", variant="primary", scale=1)
-            search_output = gr.Textbox(label="Verified Results — PubMed + Semantic Scholar", lines=18)
-            search_btn.click(quick_search, inputs=search_input, outputs=search_output)
-            search_input.submit(quick_search, inputs=search_input, outputs=search_output)
-
-        with gr.Tab("📊 PIV CSV"):
-            gr.Markdown("Upload PIV CSV → 4 separate charts + AI clinical analysis")
+                search_input = gr.Textbox(placeholder="e.g. unsteady flow bileaflet mechanical heart valve hemodynamics", label="Research Topic", scale=3)
+                search_model_dd = gr.Dropdown(choices=list(CHAT_MODELS.keys()), value="Llama 3.3 70B (Best)", label="AI Model", scale=1)
+                search_btn = gr.Button("Search All 5 Sources", variant="primary", scale=1)
+            search_output = gr.Textbox(label="AI Ranked Results", lines=25)
+            search_btn.click(quick_search, inputs=[search_input, search_model_dd], outputs=search_output)
+            search_input.submit(quick_search, inputs=[search_input, search_model_dd], outputs=search_output)
+            gr.Markdown("**Try:** `bileaflet heart valve thrombogenicity` | `uPAD microfluidic creatinine CKD` | `PIV hemodynamics prosthetic valve` | `SJSU CardioLab biomedical`")
+
+        with gr.Tab("PIV CSV"):
+            gr.Markdown("Upload PIV CSV - 4 separate charts + AI clinical analysis")
             with gr.Row():
                 piv_file = gr.File(label="Upload PIV CSV", file_types=[".csv"], scale=3)
                 piv_theme = gr.Radio(["White","Dark"], value="White", label="Theme", scale=1)
@@ -599,8 +579,8 @@ with gr.Blocks(title="CardioLab AI — SJSU", css=CSS) as demo:
                 piv_c4=gr.Image(label="Clinical Summary",type="pil")
             piv_btn.click(analyze_piv_csv, inputs=[piv_file,piv_theme], outputs=[piv_c1,piv_c2,piv_c3,piv_c4,piv_result])
 
-        with gr.Tab("🩸 TGT CSV"):
-            gr.Markdown("Upload TGT CSV → blood biomarker charts + thrombogenicity assessment")
+        with gr.Tab("TGT CSV"):
+            gr.Markdown("Upload TGT CSV - blood biomarker charts + thrombogenicity assessment")
             with gr.Row():
                 tgt_file = gr.File(label="Upload TGT CSV", file_types=[".csv"], scale=3)
                 tgt_theme = gr.Radio(["White","Dark"], value="White", label="Theme", scale=1)
@@ -612,7 +592,7 @@ with gr.Blocks(title="CardioLab AI — SJSU", css=CSS) as demo:
                 tgt_c3=gr.Image(label="Hemoglobin",type="pil"); tgt_c4=gr.Image(label="Platelets",type="pil")
             tgt_btn.click(analyze_tgt_csv, inputs=[tgt_file,tgt_theme], outputs=[tgt_c1,tgt_c2,tgt_c3,tgt_c4,tgt_result])
 
-        with gr.Tab("🧪 uPAD"):
+        with gr.Tab("uPAD"):
             with gr.Row():
                 with gr.Column():
                     photo_input = gr.Image(label="Upload uPAD Photo", type="numpy", height=260)
@@ -621,15 +601,14 @@ with gr.Blocks(title="CardioLab AI — SJSU", css=CSS) as demo:
                     photo_img = gr.Image(label="Detection Zone", type="pil", height=260)
                     photo_text = gr.Textbox(label="CKD Result", lines=8)
             analyze_btn.click(analyze_upad_photo, inputs=photo_input, outputs=[photo_img, photo_text])
-            gr.Markdown("**Manual RGB:**")
             with gr.Row():
                 r=gr.Number(label="R",value=210); g=gr.Number(label="G",value=140); b=gr.Number(label="B",value=80)
-                out3=gr.Textbox(label="Result",lines=3)
+                out3=gr.Textbox(label="Manual Result",lines=3)
             gr.Button("Analyze RGB",variant="secondary").click(
                 lambda r,g,b:"Creatinine: "+str(max(0,round(0.02*(r-b)-0.5,2)))+" mg/dL"+chr(10)+("Normal" if max(0,round(0.02*(r-b)-0.5,2))<1.2 else "Borderline" if max(0,round(0.02*(r-b)-0.5,2))<1.5 else "CKD"),
                 inputs=[r,g,b],outputs=out3)
 
-        with gr.Tab("🎨 AI Image"):
+        with gr.Tab("AI Image"):
             with gr.Row():
                 img_prompt = gr.Textbox(placeholder="e.g. 27mm bileaflet mechanical heart valve cross section", label="Describe the image", lines=2, scale=4)
                 with gr.Column(scale=1):
@@ -639,7 +618,7 @@ with gr.Blocks(title="CardioLab AI — SJSU", css=CSS) as demo:
             img_output = gr.Image(label="Generated Image", type="pil", height=400)
             img_btn.click(generate_image, inputs=img_prompt, outputs=[img_output,img_status,img_desc])
 
-        with gr.Tab("📐 PIV Manual"):
+        with gr.Tab("PIV Manual"):
             with gr.Row():
                 with gr.Column():
                     v=gr.Number(label="Max Velocity m/s",value=1.8,info="Normal: 0.5-2.0")
@@ -648,7 +627,7 @@ with gr.Blocks(title="CardioLab AI — SJSU", css=CSS) as demo:
                     piv_out=gr.Textbox(label="Result",lines=4)
                     gr.Button("Analyze PIV",variant="primary").click(piv_manual,inputs=[v,s,h],outputs=piv_out)
 
-        with gr.Tab("🔬 TGT Manual"):
+        with gr.Tab("TGT Manual"):
             with gr.Row():
                 with gr.Column():
                     t1=gr.Number(label="TAT ng/mL",value=18,info="Normal: <8")
@@ -659,15 +638,7 @@ with gr.Blocks(title="CardioLab AI — SJSU", css=CSS) as demo:
                     out2=gr.Textbox(label="Result",lines=6)
                     gr.Button("Analyze TGT",variant="primary").click(tgt_manual,inputs=[t1,t2,t3,t4,t5],outputs=out2)
 
-    gr.HTML("""
-    <div style="text-align:center;padding:12px;border-top:1px solid #e5e7eb;margin-top:8px;background:#f9fafb;">
-        <span style="color:#9ca3af;font-size:0.75em;">
-            ❤️ CardioLab AI &nbsp;|&nbsp; SJSU Biomedical Engineering &nbsp;|&nbsp;
-            Built on <a href="https://github.com/snap-stanford/Biomni" style="color:#c1121f;">Biomni Stanford</a> &nbsp;|&nbsp;
-            <a href="https://github.com/pranatechsol/Cardio-Lab-Ai" style="color:#0057a8;">GitHub</a> &nbsp;|&nbsp;
-            Apache 2.0 &nbsp;|&nbsp; $0 Cost
-        </span>
-    </div>
-    """)
+    gr.HTML("""<div style="text-align:center;padding:10px;border-top:1px solid #e5e7eb;background:#f9fafb;">
+    <span style="color:#9ca3af;font-size:0.75em;">CardioLab AI | SJSU Biomedical Engineering | Built on <a href="https://github.com/snap-stanford/Biomni" style="color:#c1121f;">Biomni Stanford</a> | <a href="https://github.com/pranatechsol/Cardio-Lab-Ai" style="color:#0057a8;">GitHub</a> | Apache 2.0 | $0 Cost</span></div>""")
 
 demo.launch()