updating calls to

app/backend/approaches/chatreadretrieveread.py

@@ -194,9 +194,20 @@ async def run(self, history: Sequence[dict[str, str]], overrides: dict[str, Any]
                     # max_tokens=32, # setting it too low may cause malformed JSON
                     max_tokens=100,
                 n=1)
-            if not chat_completion or not chat_completion.choices[0].message.content:
-                raise ValueError("No choices returned in chat completion response")
-
+                # Initialize a list to collect filter reasons
+            filter_reasons = []
+
+            # Check for content filtering
+            if chat_completion.choices[0].finish_reason == 'content_filter':
+                for category, details in chat_completion.choices[0].content_filter_results.items():
+                    if details['filtered']:
+                        filter_reasons.append(f"{category} ({details['severity']})")
+
+            # Raise an error if any filters are triggered
+            if filter_reasons:
+                error_message = "The generated content was filtered due to triggering Azure OpenAI's content filtering system. Reason(s): The response contains content flagged as " + ", ".join(filter_reasons)
+                raise ValueError(error_message)
+
         except Exception as e:
             log.error(f"Error generating optimized keyword search: {str(e)}")
             yield json.dumps({"error": f"Error generating optimized keyword search: {str(e)}"}) + "\n"
@@ -431,11 +442,22 @@ async def run(self, history: Sequence[dict[str, str]], overrides: dict[str, Any]
                               "thought_chain": thought_chain,
                               "work_citation_lookup": citation_lookup,
                               "web_citation_lookup": {}}) + "\n"
-
+            
             # STEP 4: Format the response
             async for chunk in chat_completion:
                 # Check if there is at least one element and the first element has the key 'delta'
                 if len(chunk.choices) > 0:
+                    filter_reasons = []
+                    # Check for content filtering
+                    if chunk.choices[0].finish_reason == 'content_filter':
+                        for category, details in chunk.choices[0].content_filter_results.items():
+                            if details['filtered']:
+                                filter_reasons.append(f"{category} ({details['severity']})")
+
+                    # Raise an error if any filters are triggered
+                    if filter_reasons:
+                        error_message = "The generated content was filtered due to triggering Azure OpenAI's content filtering system. Reason(s): The response contains content flagged as " + ", ".join(filter_reasons)
+                        raise ValueError(error_message)
                     yield json.dumps({"content": chunk.choices[0].delta.content}) + "\n"
         except Exception as e:
             log.error(f"Error generating chat completion: {str(e)}")