Update app.py

app.py

@@ -160,17 +160,17 @@ You are a friendly medical chatbot designed to assist users by providing accurat
 QA_PROMPT = PromptTemplate(QA_PROMPT_TMPL)
 gpt_4o_mm = OpenAIMultiModal(model="gpt-4o-mini-2024-07-18")
 
-class MultimodalQueryEngine(CustomQueryEngine):
-    # def __init__(self, qa_prompt, retriever, multi_modal_llm, node_postprocessors=[]):
-    #     super().__init__(qa_prompt=qa_prompt, retriever=retriever, multi_modal_llm=multi_modal_llm, node_postprocessors=node_postprocessors)
-
-    # def custom_query(self, query_str):
-    #     nodes = self.retriever.retrieve(query_str)
-    #     image_nodes = [NodeWithScore(node=ImageNode(image_path=n.node.metadata["image_path"])) for n in nodes]
-    #     ctx_str = "\n\n".join([r.node.get_content().strip() for r in nodes])
-    #     fmt_prompt = self.qa_prompt.format(context_str=ctx_str, query_str=query_str, encoded_image_url=encoded_image_url)
-    #     llm_response = self.multi_modal_llm.complete(prompt=fmt_prompt, image_documents=[image_node.node for image_node in image_nodes])
-    #     return Response(response=str(llm_response), source_nodes=nodes, metadata={"text_nodes": text_nodes, "image_nodes": image_nodes})
+# class MultimodalQueryEngine(CustomQueryEngine):
+#     # def __init__(self, qa_prompt, retriever, multi_modal_llm, node_postprocessors=[]):
+#     #     super().__init__(qa_prompt=qa_prompt, retriever=retriever, multi_modal_llm=multi_modal_llm, node_postprocessors=node_postprocessors)
+
+#     # def custom_query(self, query_str):
+#     #     nodes = self.retriever.retrieve(query_str)
+#     #     image_nodes = [NodeWithScore(node=ImageNode(image_path=n.node.metadata["image_path"])) for n in nodes]
+#     #     ctx_str = "\n\n".join([r.node.get_content().strip() for r in nodes])
+#     #     fmt_prompt = self.qa_prompt.format(context_str=ctx_str, query_str=query_str, encoded_image_url=encoded_image_url)
+#     #     llm_response = self.multi_modal_llm.complete(prompt=fmt_prompt, image_documents=[image_node.node for image_node in image_nodes])
+#     #     return Response(response=str(llm_response), source_nodes=nodes, metadata={"text_nodes": text_nodes, "image_nodes": image_nodes})
 
 
 class MultimodalQueryEngine(CustomQueryEngine):