temporarily remove inline references (needs to be cleaned up)

app.py

@@ -269,26 +269,10 @@ Answer:"""
                     try:
                         response_text = self._generate_with_chat(prompt, max_new_tokens=512)
                         if response_text:
-                            # Resolve [Context N] to actual source labels in the body
-                            # Expand bare/grouped "Context N, M" forms to individual [Context N] tags.
-                            # Use negative lookbehind (?<!\[) so already-bracketed [Context N] are not double-wrapped.
-                            def _expand_grouped_context(m):
-                                indices = [int(x.strip()) for x in re.split(r'[,\s]+', m.group(1)) if x.strip().isdigit()]
-                                return " ".join(f"[Context {idx}]" for idx in indices)
-                            response_text = re.sub(r'(?<!\[)\bContext\s+([\d][,\s\d]*)', _expand_grouped_context, response_text)
-                            # Now replace all [Context N] with source labels/links
-                            for i, source_label in context_index_to_source.items():
-                                url = context_index_to_url.get(i)
-                                replacement = f"[{source_label}]({url})" if url else source_label
-                                response_text = response_text.replace(f"[Context {i}]", replacement)
-                            # Deduplicate repeated inline markdown links — keep first as link, rest as plain text
-                            seen_inline = set()
-                            def _dedup_link(m):
-                                if m.group(0) in seen_inline:
-                                    return m.group(1)
-                                seen_inline.add(m.group(0))
-                                return m.group(0)
-                            response_text = re.sub(r'\[([^\]]+)\]\([^)]+\)', _dedup_link, response_text)
+                            # Strip all inline [Context N] references and bare "Context N" mentions from the body
+                            response_text = re.sub(r'\[Context\s+\d+\]', '', response_text)
+                            response_text = re.sub(r'(?<!\[)\bContext\s+[\d][,\s\d]*', '', response_text)
+                            response_text = re.sub(r'\s{2,}', ' ', response_text)
                             # Only append references when the model actually answered
                             no_answer_phrase = "The provided context does not contain enough information to answer this question."
                             no_answer_replacement = "The organic documents provided do not contain enough information to answer your question. For more information, try taking a look at the [Canadian Food Inspection Agency](https://inspection.canada.ca/en/food-labels/organic-products/), the [Certified Organic Growers of Canada](https://cog.ca/), or the [Canada Organic Trade Association](https://canada-organic.ca/en/organic)."