Update src/streamlit_app.py

src/streamlit_app.py

@@ -831,31 +831,59 @@ with tabs[4]:
 
 
                     # --- Call HF Llama-3-70B-Instruct API for summary ---
-                    import requests
-                    HF_TOKEN = os.getenv("HF_TOKEN")
+                    # --- Call HF Llama-3-70B-Instruct API for summary (robust + debug-safe) ---
+                    import requests, json, textwrap
+                    
+                    HF_TOKEN = os.getenv("HF_TOKEN")  # Works on Hugging Face Spaces
                     if not HF_TOKEN:
-                        st.error("HF_TOKEN not found in secrets or environment.")
+                        st.error("HF_TOKEN not detected. Check the Secrets tab in your Space settings.")
                     else:
-                        st.success("HF_TOKEN detected successfully.")
-                        API_URL = "https://api-inference.huggingface.co/models/meta-llama/Llama-3-70B-Instruct"
+                        API_URL = "https://api-inference.huggingface.co/models/meta-llama/Llama-3-8B-Instruct"
                         headers = {"Authorization": f"Bearer {HF_TOKEN}"}
-                        prompt = f"""
-                        You are an expert metallurgical process advisor.
-                        Based on these recommendations:
-                        {recommendations}
-                        Target: {target}
-                        Use case: {use_case}
-                        Summarize in three concise, professional lines what the operator should do this shift.
-                        """
-                        payload = {"inputs": prompt, "parameters": {"max_new_tokens": 150, "temperature": 0.6}}
-                        with st.spinner("Generating operator note (Llama-3-70B)…"):
+                    
+                        prompt = textwrap.dedent(f"""
+                            You are an expert metallurgical process advisor.
+                            Based on these SHAP-derived recommendations:
+                            {recommendations}
+                            Target: {target}
+                            Use case: {use_case}
+                            Summarize in three concise, professional lines what the operator should do this shift.
+                        """)
+                    
+                        payload = {
+                            "inputs": prompt,
+                            "parameters": {"max_new_tokens": 150, "temperature": 0.6}
+                        }
+                    
+                        with st.spinner("Generating operator note (Llama-3-8B)…"):
                             resp = requests.post(API_URL, headers=headers, json=payload, timeout=90)
-                            text = resp.json()[0].get("generated_text","").strip()
-                            st.info(text)
-                else:
-                    st.info("No suitable base model found.")
-            except Exception as e:
-                st.warning(f"Operator advisory skipped: {e}")
+                    
+                            # --- Debug section (safe, no secrets printed) ---
+                            try:
+                                data = resp.json()
+                                st.caption("Raw HF response:")
+                                st.json(data)
+                            except Exception as ex:
+                                st.warning(f"HF raw response parse error: {ex}")
+                                st.text(resp.text)
+                                data = None
+                    
+                            # --- Extract generated text robustly ---
+                            text = ""
+                            if isinstance(data, list) and len(data) > 0 and "generated_text" in data[0]:
+                                text = data[0]["generated_text"].strip()
+                            elif isinstance(data, dict) and "generated_text" in data:
+                                text = data["generated_text"].strip()
+                            elif isinstance(data, str):
+                                text = data.strip()
+                    
+                            if text:
+                                st.success("✅ Operator Advisory Generated:")
+                                st.info(text)
+                            else:
+                                st.warning("Operator advisory skipped: no text returned from model.")
+
+
 
 # ----- Business Impact tab
 with tabs[5]: