Update app.py

app.py

@@ -1,9 +1,8 @@
 import gradio as gr
-import os, requests
-from groq import Groq
+import os
+import requests
 
-GROQ_KEY = os.environ.get("GROQ_API_KEY","")
-client = Groq(api_key=GROQ_KEY)
+GROQ_KEY = os.environ.get("GROQ_API_KEY", "")
 
 KNOWHOW = """
 SJSU CardioLab Know-How:
@@ -14,21 +13,28 @@ 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
-13 Projects: MCL/PIV, TGT, FSI simulation, uPAD CKD diagnostics
 """
 
 def search_pubmed(query, n=3):
     try:
-        r = requests.get("https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi",
-            params={"db":"pubmed","term":query,"retmax":n,"retmode":"json","sort":"date"}, timeout=10)
+        r = requests.get(
+            "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi",
+            params={"db":"pubmed","term":query,"retmax":n,"retmode":"json","sort":"date"},
+            timeout=10
+        )
         ids = r.json()["esearchresult"]["idlist"]
-        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)
+        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
+        )
         import xmltodict
         data = xmltodict.parse(r2.content)
         articles = data.get("PubmedArticleSet",{}).get("PubmedArticle",[])
-        if isinstance(articles, dict): articles = [articles]
+        if isinstance(articles, dict):
+            articles = [articles]
         real_links = []
         context = ""
         for a in articles[:n]:
@@ -36,20 +42,27 @@ def search_pubmed(query, n=3):
                 c = a["MedlineCitation"]
                 title = str(c["Article"]["ArticleTitle"])
                 abstract = c["Article"].get("Abstract",{}).get("AbstractText","")
-                if isinstance(abstract, list): abstract = " ".join([str(x) for x in abstract])
-                if isinstance(abstract, dict): abstract = str(abstract.get("#text",""))
+                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"])
-                real_url = "https://pubmed.ncbi.nlm.nih.gov/" + pmid
-                real_links.append("- " + title[:100] + "\n  " + real_url)
+                url = "https://pubmed.ncbi.nlm.nih.gov/" + pmid
+                real_links.append("- " + title[:100] + "\n  " + url)
                 context += "[PubMed:" + pmid + "] " + title + ". " + str(abstract)[:300] + "\n"
-            except: continue
+            except:
+                continue
         return real_links, context
-    except: return [], ""
+    except:
+        return [], ""
 
 def search_scholar(query, n=3):
     try:
-        r = requests.get("https://api.semanticscholar.org/graph/v1/paper/search",
-            params={"query":query,"limit":n,"fields":"title,abstract,year,url"}, timeout=10)
+        r = requests.get(
+            "https://api.semanticscholar.org/graph/v1/paper/search",
+            params={"query":query,"limit":n,"fields":"title,abstract,year,url"},
+            timeout=10
+        )
         papers = r.json().get("data",[])
         real_links = []
         context = ""
@@ -62,37 +75,30 @@ def search_scholar(query, n=3):
                 real_links.append("- " + title[:100] + " (" + year + ")\n  " + url)
                 context += "[Scholar " + year + "] " + title + ". " + abstract + "\n"
         return real_links, context
-    except: return [], ""
+    except:
+        return [], ""
 
 def ask_with_memory(message, history):
     if not GROQ_KEY:
         return "Error: GROQ_API_KEY not set in Space secrets."
 
-    # Build messages with full history for memory
+    try:
+        from groq import Groq
+        client = Groq(api_key=GROQ_KEY)
+    except Exception as e:
+        return "Error loading Groq: " + str(e)
+
     messages = [
         {
             "role": "system",
-            "content": """You are CardioLab AI built on Biomni from Stanford SNAP Lab.
-Expert in SJSU Biomedical Engineering research.
-You remember everything said in this conversation.
-NEVER invent paper titles or URLs.
-ONLY cite papers from the search results provided.
-
-CARDIOLAB KNOW-HOW:
-""" + KNOWHOW
+            "content": "You are CardioLab AI built on Biomni from Stanford SNAP Lab. Expert in SJSU Biomedical Engineering. NEVER invent paper titles or URLs. Only cite papers from search results.\n\nCARDIOLAB KNOW-HOW:\n" + KNOWHOW
         }
     ]
 
-    # Add chat history — new Gradio format uses dicts
     for msg in history:
         if isinstance(msg, dict):
             messages.append({"role": msg["role"], "content": msg["content"]})
-        else:
-            # fallback for tuple format
-            messages.append({"role": "user", "content": str(msg[0])})
-            messages.append({"role": "assistant", "content": str(msg[1])})
 
-    # Search papers
     cardio_query = message + " mechanical heart valve OR microfluidic OR CKD creatinine OR PIV OR thrombogenicity"
     pubmed_links, pubmed_context = search_pubmed(cardio_query, n=3)
     scholar_links, scholar_context = search_scholar(message + " biomedical", n=3)
@@ -100,16 +106,18 @@ CARDIOLAB KNOW-HOW:
 
     messages.append({
         "role": "user",
-        "content": message + "\n\nReal papers (ONLY use these):\n" + sources[:3000]
+        "content": message + "\n\nReal papers found (ONLY use these):\n" + sources[:3000]
     })
 
-    response = client.chat.completions.create(
-        model="llama-3.3-70b-versatile",
-        messages=messages,
-        max_tokens=800
-    )
-
-    answer = response.choices[0].message.content
+    try:
+        response = client.chat.completions.create(
+            model="llama-3.3-70b-versatile",
+            messages=messages,
+            max_tokens=800
+        )
+        answer = response.choices[0].message.content
+    except Exception as e:
+        return "Error from Groq: " + str(e)
 
     links = ""
     if pubmed_links:
@@ -120,19 +128,25 @@ CARDIOLAB KNOW-HOW:
     return answer + links
 
 def piv_tool(velocity, shear, hr):
-    v = "HIGH - stenosis risk" if float(velocity)>2.0 else "NORMAL"
-    s = "HIGH - thrombosis risk" if float(shear)>10 else "ELEVATED - monitor" if float(shear)>5 else "NORMAL"
-    return "Velocity: "+str(velocity)+" m/s - "+v+"\nShear: "+str(shear)+" Pa - "+s+"\nHeart Rate: "+str(hr)+" bpm"
+    v = "HIGH - stenosis risk" if float(velocity) > 2.0 else "NORMAL"
+    s = "HIGH - thrombosis risk" if float(shear) > 10 else "ELEVATED - monitor" if float(shear) > 5 else "NORMAL"
+    return "Velocity: " + str(velocity) + " m/s - " + v + "\nShear: " + str(shear) + " Pa - " + s + "\nHeart Rate: " + str(hr) + " bpm"
 
 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)+" PF1.2:"+str(pf12)+" Hemo:"+str(hemo)+" Platelets:"+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\nStage: "+stage+"\nConfirm with: Heska Element HT5"
+    return "Creatinine: " + str(creatinine) + " mg/dL\nStage: " + stage + "\nConfirm with: Heska Element HT5"
+
+def respond(message, history):
+    bot_message = ask_with_memory(message, history)
+    history.append({"role": "user", "content": message})
+    history.append({"role": "assistant", "content": bot_message})
+    return "", history
 
 with gr.Blocks(title="CardioLab AI - SJSU") as demo:
     gr.Markdown("# CardioLab AI Agent")
@@ -140,27 +154,12 @@ with gr.Blocks(title="CardioLab AI - SJSU") as demo:
     gr.Markdown("GitHub: github.com/pranatechsol/Cardio-Lab-Ai")
 
     with gr.Tab("Research Chat"):
-        gr.Markdown("### Chat with memory — remembers your full conversation like ChatGPT")
-        chatbot = gr.Chatbot(
-            label="CardioLab AI",
-            height=500,
-            type="messages"
-        )
-        msg = gr.Textbox(
-            label="Your message",
-            placeholder="Ask anything about CardioLab research...",
-            lines=2
-        )
+        gr.Markdown("### Chat with memory — like ChatGPT but for CardioLab research")
+        chatbot = gr.Chatbot(label="CardioLab AI", height=500, type="messages")
+        msg = gr.Textbox(label="Your message", placeholder="Ask anything about CardioLab research...", lines=2)
         with gr.Row():
             send = gr.Button("Send", variant="primary")
             clear = gr.Button("Clear Chat")
-
-        def respond(message, history):
-            bot_message = ask_with_memory(message, history)
-            history.append({"role": "user", "content": message})
-            history.append({"role": "assistant", "content": bot_message})
-            return "", history
-
         send.click(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])
         msg.submit(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])
         clear.click(lambda: [], None, chatbot)
@@ -191,4 +190,4 @@ with gr.Blocks(title="CardioLab AI - SJSU") as demo:
         out3 = gr.Textbox(label="Result", lines=4)
         gr.Button("Analyze uPAD").click(upad_tool, inputs=[r,g,b], outputs=out3)
 
-demo.launch()
+demo.launch()