remove unused code

app.py

@@ -130,11 +130,7 @@ async def chat(query,history,audience,sources,reports,current_graphs):
     
     inputs = {"user_input": query,"audience": audience_prompt,"sources":sources}
     result = agent.astream_events(inputs,version = "v1") 
-    
-    # path_reformulation = "/logs/reformulation/final_output"
-    # path_keywords = "/logs/keywords/final_output"
-    # path_retriever = "/logs/find_documents/final_output"
-    # path_answer = "/logs/answer/streamed_output_str/-"
+
 
     docs = []
     docs_used = True
@@ -196,15 +192,6 @@ async def chat(query,history,audience,sources,reports,current_graphs):
                 elif event["name"] in ["retrieve_graphs", "retrieve_graphs_ai"] and event["event"] == "on_chain_end":
                     try:
                         recommended_content = event["data"]["output"]["recommended_content"]
-                        # graphs = [
-                        #     {
-                        #         "embedding": x.metadata["returned_content"],
-                        #         "metadata": {
-                        #             "source": x.metadata["source"],
-                        #             "category": x.metadata["category"]
-                        #             }
-                        #             } for x in recommended_content if x.metadata["source"] == "OWID"
-                        #             ]
                         
                         unique_graphs = []
                         seen_embeddings = set()
@@ -279,42 +266,6 @@ async def chat(query,history,audience,sources,reports,current_graphs):
         print(f"Error logging on Azure Blob Storage: {e}")
         raise gr.Error(f"ClimateQ&A Error: {str(e)[:100]} - The error has been noted, try another question and if the error remains, you can contact us :)")
 
-
-
-        
-    # image_dict = {}
-    # for i,doc in enumerate(docs):
-        
-    #     if doc.metadata["chunk_type"] == "image":
-    #         try:
-    #             key = f"Image {i+1}"
-    #             image_path = doc.metadata["image_path"].split("documents/")[1]
-    #             img = get_image_from_azure_blob_storage(image_path)
-
-    #             # Convert the image to a byte buffer
-    #             buffered = BytesIO()
-    #             img.save(buffered, format="PNG")
-    #             img_str = base64.b64encode(buffered.getvalue()).decode()
-
-    #             # Embedding the base64 string in Markdown
-    #             markdown_image = f"![Alt text](data:image/png;base64,{img_str})"
-    #             image_dict[key] = {"img":img,"md":markdown_image,"short_name": doc.metadata["short_name"],"figure_code":doc.metadata["figure_code"],"caption":doc.page_content,"key":key,"figure_code":doc.metadata["figure_code"], "img_str" : img_str}
-    #         except Exception as e:
-    #             print(f"Skipped adding image {i} because of {e}")
-
-    # if len(image_dict) > 0:
-
-    #     gallery = [x["img"] for x in list(image_dict.values())]
-    #     img = list(image_dict.values())[0]
-    #     img_md = img["md"]
-    #     img_caption = img["caption"]
-    #     img_code = img["figure_code"]
-    #     if img_code != "N/A":
-    #         img_name = f"{img['key']} - {img['figure_code']}"
-    #     else:
-    #         img_name = f"{img['key']}"
-
-    #     history.append(ChatMessage(role="assistant", content = f"\n\n{img_md}\n<p class='chatbot-caption'><b>{img_name}</b> - {img_caption}</p>"))
         
     docs_figures = [d for d in docs if d.metadata["chunk_type"] == "image"]
     for i, doc in enumerate(docs_figures):