change model to Mistral 7B

app.py

@@ -91,7 +91,7 @@ class RAGChatbot:
     """Chatbot with RAG capabilities."""
     
     # Default and fallback models (try in order until one is supported by your Inference API providers)
-    DEFAULT_CHAT_MODEL = "Qwen/Qwen2.5-Coder-7B-Instruct"
+    DEFAULT_CHAT_MODEL = "mistralai/Mistral-7B-Instruct-v0.3"
     FALLBACK_CHAT_MODELS = [
         "ServiceNow-AI/Apriel-1.6-15b-Thinker:together",
         "microsoft/phi-2",
@@ -237,7 +237,6 @@ Do not reveal your internal reasoning. Provide only the final answer.
 Structure your answer in the following format:
 Summary — A brief, high‑level answer.
 Supporting Details — Explain using information only from the provided context. When citing, use the Source label shown for that context (e.g. the document title or name in parentheses after [Context N]).
-Context References — List each reference with the exact Source shown for that context (e.g. "CAN/CGSB-32.312-2018" or the document title). Include section name or page when that information appears in the context text. Format: document/source, section or location if available, and a short quote or paraphrase. Do not use only "Context 1" or "Context 5" as the reference; always include the document title/source.
 
 Context:
 {context}
@@ -267,19 +266,21 @@ Answer:"""
                                     f"[Context {i}]",
                                     f"({source_label})",
                                 )
-                            # Append a References section so users see what each source is
-                            ref_lines = [
-                                "",
-                                "---",
-                                "**References**",
-                            ]
-                            for i, source_label in context_index_to_source.items():
-                                url = context_index_to_url.get(i)
-                                if url:
-                                    ref_lines.append(f"{i}. [{source_label}]({url})")
-                                else:
-                                    ref_lines.append(f"{i}. {source_label}")
-                            response_text = response_text.rstrip() + "\n\n" + "\n".join(ref_lines)
+                            # Only append references when the model actually answered
+                            no_answer_phrase = "The provided context does not contain enough information to answer this question."
+                            if no_answer_phrase not in response_text:
+                                ref_lines = [
+                                    "",
+                                    "---",
+                                    "**References**",
+                                ]
+                                for i, source_label in context_index_to_source.items():
+                                    url = context_index_to_url.get(i)
+                                    if url:
+                                        ref_lines.append(f"{i}. [{source_label}]({url})")
+                                    else:
+                                        ref_lines.append(f"{i}. {source_label}")
+                                response_text = response_text.rstrip() + "\n\n" + "\n".join(ref_lines)
                             return response_text
                         raise ValueError("Empty response from model")
                     except Exception as api_error: