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app.py

@@ -3,19 +3,18 @@ import os, requests, glob
 from groq import Groq
 
 GROQ_KEY = os.environ.get("GROQ_API_KEY","")
+GITHUB_TOKEN = os.environ.get("GITHUB_TOKEN","")
 client = Groq(api_key=GROQ_KEY)
 
 KNOWHOW = """
 SJSU CardioLab Know-How:
-MCL: Mock Circulatory Loop using Sylgard 184 PDMS at 10:1 ratio cured 48hrs, green laser PIV, 70bpm 5L/min physiological flow
-TGT: Thrombogenicity Tester with Arduino Uno + Stepper Motor, 150mL blood, sample at 0/20/40/60min, measure TAT PF1.2 hemolysis platelets
-uPAD: Microfluidic Paper Device, Jaffe reaction creatinine + picric acid = orange-red color, normal creatinine 0.6-1.2 mg/dL, CKD above 1.5 mg/dL
-FSI: COMSOL Multiphysics ALE mesh, blood density 1060 kg/m3, viscosity 0.0035 Pa.s, St Jude Medical geometry reference
-MHV: 27mm SJM Regent bileaflet mechanical heart valve, also trileaflet, monoleaflet, pediatric designs studied
-CKD Stages: Stage 1 below 1.5, Stage 2 1.5-3.0, Stage 3-4 3.0-6.0, Stage 5 above 6.0 mg/dL creatinine
-Equipment: Heska Element HT5 hematology analyzer, time-resolved PIV, Tygon tubing
-Acoustic detection: microphone on valve housing detects clot formation via frequency shift
-Projects: 13 total, 3 pillars - MHV hemodynamics, CKD diagnostics, FSI simulations
+MCL: Sylgard 184 PDMS 10:1 ratio 48hr cure, green laser PIV, 70bpm 5L/min flow
+TGT: Arduino Uno + Stepper Motor, 150mL blood, sample 0/20/40/60min, TAT PF1.2 hemolysis platelets
+uPAD: Jaffe reaction creatinine + picric acid = orange-red, normal 0.6-1.2 mg/dL, CKD above 1.5
+FSI: COMSOL ALE mesh, blood 1060 kg/m3, 0.0035 Pa.s, St Jude geometry
+MHV: 27mm SJM Regent, bileaflet trileaflet monoleaflet pediatric
+CKD Stages: 1 below 1.5, 2 1.5-3.0, 3-4 3.0-6.0, 5 above 6.0 mg/dL
+Equipment: Heska HT5, time-resolved PIV, Tygon tubing, Arduino
 """
 
 def search_pubmed(query, n=3):
@@ -39,7 +38,7 @@ def search_pubmed(query, n=3):
                 if isinstance(abstract, list): abstract = " ".join([str(x) for x in abstract])
                 if isinstance(abstract, dict): abstract = str(abstract.get("#text",""))
                 pmid = str(c["PMID"]["#text"] if isinstance(c["PMID"],dict) else c["PMID"])
-                out.append("[PubMed: " + title[:80] + "]\n" + str(abstract)[:300] + "\nURL: https://pubmed.ncbi.nlm.nih.gov/" + pmid)
+                out.append("[PubMed: "+title[:80]+"]\n"+str(abstract)[:300]+"\nURL: https://pubmed.ncbi.nlm.nih.gov/"+pmid)
             except: continue
         return "\n\n".join(out)
     except: return ""
@@ -51,22 +50,50 @@ def search_scholar(query, n=3):
         papers = r.json().get("data",[])
         out = []
         for p in papers:
-            out.append("[Scholar " + str(p.get("year","")) + ": " + p.get("title","")[:80] + "]\n" + (p.get("abstract") or "")[:300] + "\nURL: " + p.get("url",""))
+            out.append("[Scholar "+str(p.get("year",""))+": "+p.get("title","")[:80]+"]\n"+(p.get("abstract") or "")[:300]+"\nURL: "+p.get("url",""))
         return "\n\n".join(out)
     except: return ""
 
+def search_web_realtime(query):
+    if not GITHUB_TOKEN:
+        return ""
+    try:
+        headers = {
+            "Authorization": "Bearer " + GITHUB_TOKEN,
+            "Content-Type": "application/json"
+        }
+        payload = {
+            "messages": [{"role": "user", "content": query}],
+            "model": "gpt-4o",
+            "tools": [{"type": "bing_search"}]
+        }
+        r = requests.post(
+            "https://api.githubcopilot.com/chat/completions",
+            headers=headers,
+            json=payload,
+            timeout=15
+        )
+        if r.status_code == 200:
+            data = r.json()
+            content = data["choices"][0]["message"]["content"]
+            return "[Real-time Web Search]\n" + str(content)[:600]
+        return ""
+    except Exception as e:
+        return ""
+
 def ask_agent(question):
     if not GROQ_KEY:
-        return "Error: GROQ_API_KEY not set in Space secrets."
+        return "Error: GROQ_API_KEY not set."
     cardio_query = question + " AND (mechanical heart valve OR microfluidic OR CKD creatinine OR PIV hemodynamics OR thrombogenicity)"
     pubmed = search_pubmed(cardio_query, n=3)
     scholar = search_scholar(question + " biomedical", n=3)
-    sources = pubmed + "\n\n" + scholar
+    web = search_web_realtime("Latest research on: " + question + " biomedical engineering 2024 2025")
+    all_sources = pubmed + "\n\n" + scholar + "\n\n" + web
     response = client.chat.completions.create(
         model="llama-3.3-70b-versatile",
         messages=[
-            {"role":"system","content":"You are CardioLab AI built on Biomni from Stanford SNAP Lab. Expert in SJSU Biomedical Engineering. Always cite sources.\n\nCARDIOLAB KNOW-HOW:\n" + KNOWHOW},
-            {"role":"user","content":"Research question: " + question + "\n\nOnline sources found:\n" + sources[:3000]}
+            {"role":"system","content":"You are CardioLab AI built on Biomni from Stanford SNAP Lab. Expert in SJSU Biomedical Engineering. Always cite sources with URLs when available.\n\nCARDIOLAB KNOW-HOW:\n" + KNOWHOW},
+            {"role":"user","content":"Research question: " + question + "\n\nSources found:\n" + all_sources[:4000]}
         ],
         max_tokens=800
     )
@@ -80,21 +107,21 @@ def piv_tool(velocity, shear, hr):
 def tgt_tool(tat, pf12, hemo, platelets, time):
     risk = sum([float(tat)>15, float(pf12)>2.0, float(hemo)>50, float(platelets)<150])
     overall = "HIGH THROMBOGENIC RISK" if risk>=3 else "MODERATE RISK" if risk>=2 else "LOW RISK"
-    return "TAT: "+str(tat)+"\nPF1.2: "+str(pf12)+"\nHemoglobin: "+str(hemo)+"\nPlatelets: "+str(platelets)+"\nTime: "+str(time)+" min\nResult: "+overall
+    return "TAT:"+str(tat)+" PF1.2:"+str(pf12)+" Hemo:"+str(hemo)+" Platelets:"+str(platelets)+"\nTime: "+str(time)+" min\nResult: "+overall
 
 def upad_tool(r, g, b):
     creatinine = max(0, round(0.02*(float(r)-float(b))-0.5, 2))
     stage = "Normal" if creatinine<1.2 else "Borderline" if creatinine<1.5 else "Stage 2 CKD" if creatinine<3.0 else "Stage 3-4 CKD" if creatinine<6.0 else "Stage 5 CKD"
-    return "Creatinine: "+str(creatinine)+" mg/dL\nCKD Stage: "+stage+"\nConfirm with: Heska Element HT5"
+    return "Creatinine: "+str(creatinine)+" mg/dL\nStage: "+stage+"\nConfirm with: Heska Element HT5"
 
 with gr.Blocks(title="CardioLab AI - SJSU") as demo:
     gr.Markdown("# CardioLab AI Agent")
-    gr.Markdown("### SJSU Biomedical Engineering | Built on Biomni (Stanford) | Llama 70B + PubMed + Semantic Scholar")
-    gr.Markdown("**Open Source** | GitHub: github.com/pranatechsol/Cardio-Lab-Ai")
+    gr.Markdown("### SJSU Biomedical Engineering | Biomni + Llama 70B + PubMed + Web Search")
+    gr.Markdown("GitHub: github.com/pranatechsol/Cardio-Lab-Ai")
     with gr.Tab("Research Assistant"):
-        gr.Markdown("### Ask anything — searches CardioLab papers + PubMed + Semantic Scholar")
-        q = gr.Textbox(label="Research question", placeholder="e.g. What are latest methods for MHV thrombogenicity detection?")
-        a = gr.Textbox(label="Answer with citations", lines=10)
+        gr.Markdown("### Searches CardioLab papers + PubMed + Semantic Scholar + Real-time Web")
+        q = gr.Textbox(label="Research question", placeholder="e.g. Latest methods for MHV thrombogenicity detection 2025")
+        a = gr.Textbox(label="Answer with citations", lines=12)
         gr.Button("Search & Answer").click(ask_agent, inputs=q, outputs=a)
     with gr.Tab("PIV Analysis"):
         gr.Markdown("### Analyze PIV flow data from Mock Circulatory Loop")