Update app.py

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-import json, os, time, uuid
+import json, os, time, uuid, traceback
 from smolagents import CodeAgent, tool
 from smolagents.models import LiteLLMModel
 try:
@@ -7,15 +7,68 @@ try:
 except Exception:
     HfApiModel = None
 
-# --------- Shared model factory ---------
-def get_model():
-    if os.getenv("OPENAI_API_KEY"):
-        return LiteLLMModel(model_id=os.getenv("OPENAI_MODEL","gpt-5"),
-                            api_key=os.getenv("OPENAI_API_KEY"))
-    elif HfApiModel is not None:
-        return HfApiModel(os.getenv("HF_MODEL","Qwen/Qwen2.5-7B-Instruct"))
-    else:
-        raise RuntimeError("No model available. Set OPENAI_API_KEY or install HF Inference support.")
+# --------- Shared model factory with fallback + verbose errors ---------
+def get_model(prefer_openai=True):
+    """
+    Picks an LLM for the agent. Prefers OpenAI via LiteLLM if OPENAI_API_KEY is set,
+    falls back to Hugging Face Inference (HF_MODEL) otherwise.
+    """
+    last_error = None
+    if prefer_openai and os.getenv("OPENAI_API_KEY"):
+        model_id = os.getenv("OPENAI_MODEL", "gpt-5")  # change if your account lacks access
+        try:
+            return LiteLLMModel(
+                model_id=model_id,
+                api_key=os.getenv("OPENAI_API_KEY"),
+                base_url=os.getenv("OPENAI_BASE_URL")
+            )
+        except Exception as e:
+            last_error = f"OpenAI model init failed for '{model_id}': {e}"
+            # Try a widely available fallback
+            try:
+                return LiteLLMModel(
+                    model_id="gpt-4o-mini",
+                    api_key=os.getenv("OPENAI_API_KEY"),
+                    base_url=os.getenv("OPENAI_BASE_URL")
+                )
+            except Exception as e2:
+                last_error += f" | Fallback gpt-4o-mini failed: {e2}"
+
+    if HfApiModel is not None:
+        try:
+            return HfApiModel(os.getenv("HF_MODEL", "Qwen/Qwen2.5-7B-Instruct"))
+        except Exception as e:
+            last_error = f"HF model init failed: {e}"
+
+    raise RuntimeError(last_error or "No model available. Set OPENAI_API_KEY or HF_MODEL in Space secrets.")
+
+def diag_openai_ping(prompt="Say 'pong' and nothing else."):
+    """Quick connectivity test to your OpenAI key/model."""
+    try:
+        model = get_model(prefer_openai=True)  # force OpenAI path if possible
+
+        @tool
+        def echo_tool(x: str) -> str:
+            """Echo the provided text.
+            Args:
+                x (str): Text to echo back.
+            Returns:
+                str: The same text.
+            """
+            return x
+
+        agent = CodeAgent(
+            tools=[echo_tool],
+            model=model,
+            system_prompt="Reply with the user message verbatim. No extra words.",
+            add_base_tools=False,
+            verbosity_level=1,
+            temperature=0.0,
+        )
+        out = agent.run(prompt)
+        return f"✅ OpenAI ping ok.\nModel: {getattr(model, 'model_id', 'unknown')}\nOutput: {out}"
+    except Exception as e:
+        return "❌ OpenAI ping failed:\n" + "".join(traceback.format_exception_only(type(e), e))
 
 # =======================================
 # Exercise 1: Hello Tools (add + multiply)
@@ -23,7 +76,6 @@ def get_model():
 @tool
 def add(a: float, b: float) -> float:
     """Add two numbers.
-    
     Args:
         a (float): First addend.
         b (float): Second addend.
@@ -35,7 +87,6 @@ def add(a: float, b: float) -> float:
 @tool
 def mul(a: float, b: float) -> float:
     """Multiply two numbers.
-    
     Args:
         a (float): First factor.
         b (float): Second factor.
@@ -45,44 +96,50 @@ def mul(a: float, b: float) -> float:
     return a * b
 
 def run_ex1():
-    system = (
-        "You are a careful math assistant. Use the available tools to compute the answer.\n"
-        "Finally, PRINT ONLY a JSON object like {\"result\": <number>}."
-    )
-    agent = CodeAgent(
-        tools=[add, mul],
-        model=get_model(),
-        system_prompt=system,
-        add_base_tools=False,
-        verbosity_level=1,
-        temperature=0.0,
-    )
-    goal = "Compute 2 * (3 + 4) and return {\"result\": 14}."
-    out = agent.run(goal)
-    return str(out)
+    try:
+        system = (
+            "You are a careful math assistant. Use the available tools to compute the answer.\n"
+            "Finally, PRINT ONLY a JSON object like {\"result\": <number>}."
+        )
+        agent = CodeAgent(
+            tools=[add, mul],
+            model=get_model(),
+            system_prompt=system,
+            add_base_tools=False,
+            verbosity_level=1,
+            temperature=0.0,
+        )
+        goal = "Compute 2 * (3 + 4) and return {\"result\": 14}."
+        out = agent.run(goal)
+        return str(out)
+    except Exception:
+        return "❌ Exercise 1 error:\n" + traceback.format_exc()
 
 # =======================================
 # Exercise 2: Guardrails + fixed plan
 # =======================================
 def run_ex2():
-    system = (
-        "Follow this fixed plan exactly:\n"
-        "1) Call add(a=3, b=4) and store the result in x.\n"
-        "2) Call mul(a=2, b=x) to compute y.\n"
-        "3) PRINT ONLY this JSON: {\"result\": y}\n"
-        "Never print explanations."
-    )
-    agent = CodeAgent(
-        tools=[add, mul],
-        model=get_model(),
-        system_prompt=system,
-        add_base_tools=False,
-        verbosity_level=1,
-        temperature=0.0,
-    )
-    goal = "Please give me the product of two and the sum of three and four — as JSON."
-    out = agent.run(goal)
-    return str(out)
+    try:
+        system = (
+            "Follow this fixed plan exactly:\n"
+            "1) Call add(a=3, b=4) and store the result in x.\n"
+            "2) Call mul(a=2, b=x) to compute y.\n"
+            "3) PRINT ONLY this JSON: {\"result\": y}\n"
+            "Never print explanations."
+        )
+        agent = CodeAgent(
+            tools=[add, mul],
+            model=get_model(),
+            system_prompt=system,
+            add_base_tools=False,
+            verbosity_level=1,
+            temperature=0.0,
+        )
+        goal = "Please give me the product of two and the sum of three and four — as JSON."
+        out = agent.run(goal)
+        return str(out)
+    except Exception:
+        return "❌ Exercise 2 error:\n" + traceback.format_exc()
 
 # =======================================
 # Exercise 3: Mini PR -> PO
@@ -90,22 +147,20 @@ def run_ex2():
 @tool
 def validate_pr(pr: dict) -> dict:
     """Validate basic PR fields and structure.
-    
     Args:
-        pr (dict): Purchase Requisition object with keys: pr_id, requester, cost_center, currency, items.
+        pr (dict): Purchase Requisition with keys: pr_id, requester, cost_center, currency, items.
     Returns:
-        dict: {{"ok": bool, "errors": list[str]}}
+        dict: {"ok": bool, "errors": list[str]}
     """
-    req = ["pr_id","requester","cost_center","currency","items"]
+    req = ["pr_id", "requester", "cost_center", "currency", "items"]
     errors = [f"Missing {k}" for k in req if k not in pr]
     if not isinstance(pr.get("items", []), list) or not pr["items"]:
         errors.append("Items must be a non-empty list")
-    return {"ok": len(errors)==0, "errors": errors}
+    return {"ok": len(errors) == 0, "errors": errors}
 
 @tool
 def create_po(pr: dict) -> dict:
     """Create a simple Purchase Order (PO) from a PR.
-    
     Args:
         pr (dict): Validated PR dict with items[{sku, quantity, unit_price}] and currency.
     Returns:
@@ -115,18 +170,18 @@ def create_po(pr: dict) -> dict:
     items_out = []
     for it in pr.get("items", []):
         line = float(it["quantity"]) * float(it["unit_price"])
-        items_out.append({"sku": it.get("sku","UNKNOWN"), "line_total": round(line,2)})
+        items_out.append({"sku": it.get("sku", "UNKNOWN"), "line_total": round(line, 2)})
         subtotal += line
     tax = round(subtotal * 0.08, 2)
     total = round(subtotal + tax, 2)
     return {
         "po_id": f"PO-{int(time.time())}-{uuid.uuid4().hex[:6].upper()}",
-        "currency": pr.get("currency","SGD"),
+        "currency": pr.get("currency", "SGD"),
         "items": items_out,
-        "subtotal": round(subtotal,2),
+        "subtotal": round(subtotal, 2),
         "tax": tax,
         "total": total,
-        "source_pr_id": pr.get("pr_id")
+        "source_pr_id": pr.get("pr_id"),
     }
 
 DEFAULT_PR = json.dumps({
@@ -135,8 +190,8 @@ DEFAULT_PR = json.dumps({
     "cost_center": "CC-SG-OPS",
     "currency": "SGD",
     "items": [
-        {"sku":"PAPER-A4-80G","quantity":20,"unit_price":6.8},
-        {"sku":"STAPLER-01","quantity":5,"unit_price":18.5}
+        {"sku": "PAPER-A4-80G", "quantity": 20, "unit_price": 6.8},
+        {"sku": "STAPLER-01", "quantity": 5, "unit_price": 18.5}
     ]
 }, indent=2)
 
@@ -145,35 +200,47 @@ def run_ex3(pr_text):
         pr = json.loads(pr_text)
     except Exception as e:
         return f"Invalid JSON: {e}"
-    system = (
-        "You are a procurement agent. Use the tools as follows:\n"
-        "1) validate_pr(pr). If ok==false, PRINT ONLY {\"error\": errors}.\n"
-        "2) If ok==true, call create_po(pr).\n"
-        "3) PRINT ONLY the resulting PO JSON. No extra text."
-    )
-    agent = CodeAgent(
-        tools=[validate_pr, create_po],
-        model=get_model(),
-        system_prompt=system,
-        add_base_tools=False,
-        verbosity_level=1,
-        temperature=0.0,
-    )
-    goal = "Convert this PR to a PO (strict JSON). PR is in additional_context['pr']."
-    out = agent.run(goal, additional_context={"pr": pr})
-    return str(out)
+    try:
+        system = (
+            "You are a procurement agent. Use the tools as follows:\n"
+            "1) validate_pr(pr). If ok==false, PRINT ONLY {\"error\": errors}.\n"
+            "2) If ok==true, call create_po(pr).\n"
+            "3) PRINT ONLY the resulting PO JSON. No extra text."
+        )
+        agent = CodeAgent(
+            tools=[validate_pr, create_po],
+            model=get_model(),
+            system_prompt=system,
+            add_base_tools=False,
+            verbosity_level=1,
+            temperature=0.0,
+        )
+        goal = "Convert this PR to a PO (strict JSON). PR is in additional_context['pr']."
+        out = agent.run(goal, additional_context={"pr": pr})
+        return str(out)
+    except Exception:
+        return "❌ Exercise 3 error:\n" + traceback.format_exc()
 
+# --------------------- Gradio UI ---------------------
 with gr.Blocks(title="Smolagents Beginner Lab (Online)") as demo:
     gr.Markdown("# Smolagents Beginner Lab (Online)")
-    gr.Markdown("Click the buttons to run the exercises in the cloud. Set `OPENAI_API_KEY` in Space secrets for best results.")
+    gr.Markdown("Set `OPENAI_API_KEY` in Space secrets for best results. Optional: `OPENAI_MODEL` (e.g., gpt-5 or gpt-4o-mini).")
+
+    with gr.Tab("Diagnostics"):
+        ping_btn = gr.Button("Run OpenAI ping test")
+        ping_out = gr.Textbox(label="Diagnostics Output", lines=8)
+        ping_btn.click(lambda: diag_openai_ping(), inputs=None, outputs=ping_out)
+
     with gr.Tab("1) Hello Tools"):
         btn1 = gr.Button("Run Exercise 1")
         out1 = gr.Textbox(label="Output", lines=6)
         btn1.click(lambda: run_ex1(), inputs=None, outputs=out1)
+
     with gr.Tab("2) Guardrails (deterministic)"):
         btn2 = gr.Button("Run Exercise 2")
         out2 = gr.Textbox(label="Output", lines=6)
         btn2.click(lambda: run_ex2(), inputs=None, outputs=out2)
+
     with gr.Tab("3) Mini PR → PO"):
         pr_input = gr.Textbox(label="PR JSON", value=DEFAULT_PR, lines=16)
         btn3 = gr.Button("Run Exercise 3")