Update src/streamlit_app.py

src/streamlit_app.py

@@ -690,38 +690,65 @@ with tabs[4]:
 
                 # --- Hugging Face advisory ---
                 import requests, json, textwrap
+                
                 HF_TOKEN = os.getenv("HF_TOKEN")
                 if not HF_TOKEN:
-                    st.error("HF_TOKEN not detected.")
+                    st.error("HF_TOKEN not detected in environment or secrets.toml.")
                 else:
-                    API_URL = "https://router.huggingface.co/hf-inference/models/meta-llama/Llama-3-8B-Instruct"
-                    headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+                    API_URL = "https://api-inference.huggingface.co/v1/chat/completions"
+                    headers = {
+                        "Authorization": f"Bearer {HF_TOKEN}",
+                        "Content-Type": "application/json"
+                    }
+                
+                    # Safer prompt handling
                     prompt = textwrap.dedent(f"""
-                        You are an expert metallurgical advisor.
+                        You are an expert metallurgical process advisor.
+                        Analyze these operator recommendations and rewrite them
+                        as a concise 3-line professional advisory note.
                         Recommendations: {recs}
-                        Target: {target}
+                        Target variable: {target}
                         Use case: {use_case}
-                        Summarize in three professional lines for the shift operator.
                     """)
-                    payload = {"inputs": prompt, "parameters": {"max_new_tokens": 120, "temperature": 0.6}}
-                    with st.spinner("Generating advisory (Llama-3-8B)…"):
-                        resp = requests.post(API_URL, headers=headers, json=payload, timeout=90)
+                
+                    payload = {
+                        "model": "meta-llama/Llama-3-8B-Instruct",
+                        "messages": [
+                            {"role": "system", "content": "You are an expert metallurgical advisor."},
+                            {"role": "user", "content": prompt}
+                        ],
+                        "max_tokens": 200,
+                        "temperature": 0.5
+                    }
+                
+                    with st.spinner("Generating operator advisory (Llama 3-8B)…"):
                         try:
-                            data = resp.json()
-                            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()
-                            if text:
-                                st.success("✅ Operator Advisory Generated:")
-                                st.info(text)
+                            resp = requests.post(API_URL, headers=headers, json=payload, timeout=90)
+                            if resp.status_code != 200:
+                                st.warning(f" HF API error {resp.status_code}: {resp.text}")
                             else:
-                                st.warning("Operator advisory skipped: no text returned.")
+                                raw_text = resp.text.strip()
+                                if not raw_text:
+                                    st.warning("Operator advisory skipped: empty HF response body.")
+                                else:
+                                    try:
+                                        data = resp.json()
+                                        # OpenAI-compatible schema
+                                        text = ""
+                                        if "choices" in data and len(data["choices"]) > 0:
+                                            text = data["choices"][0]["message"]["content"].strip()
+                                        elif isinstance(data, list) and "generated_text" in data[0]:
+                                            text = data[0]["generated_text"].strip()
+                                        if text:
+                                            st.success("Operator Advisory Generated:")
+                                            st.info(text)
+                                        else:
+                                            st.warning(f"Operator advisory skipped: could not parse text.\nRaw HF output:\n{raw_text}")
+                                    except Exception:
+                                        st.warning(f"Operator advisory skipped: invalid JSON. Raw response:\n{raw_text}")
                         except Exception as e:
                             st.warning(f"Operator advisory skipped: {e}")
-            except Exception as e:
-                st.warning(f"Operator advisory skipped: {e}")
+
 
 
 # ----- Business Impact tab