Update app.py

app.py

@@ -120,7 +120,6 @@ def rag_chain(llm, prompt, db):
     return completion, rag_chain
 
 def wandb_trace(rag_option, prompt, completion, result, chain, err_msg, start_time_ms, end_time_ms):
-    print("###")
     wandb.init(project = "openai-llm-rag")
     trace = Trace(
         kind = "chain",
@@ -139,12 +138,12 @@ def wandb_trace(rag_option, prompt, completion, result, chain, err_msg, start_ti
         },
         model_dict = {"llm_client": (str(chain.llm.client) if (rag_option == RAG_OFF) else
                                      str(chain.combine_documents_chain.llm_chain.llm.client)) if (str(err_msg) == "") else "",
-                      "llm_model_name": (chain.llm.model_name if (rag_option == RAG_OFF) else
-                                         chain.combine_documents_chain.llm_chain.llm.model_name) if (str(err_msg) == "") else "",
+                      "llm_model_name": (str(chain.llm.model_name) if (rag_option == RAG_OFF) else
+                                         str(chain.combine_documents_chain.llm_chain.llm.model_name)) if (str(err_msg) == "") else "",
                       "llm_temperature": (chain.llm.temperature if (rag_option == RAG_OFF) else
                                           chain.combine_documents_chain.llm_chain.llm.temperature) if (str(err_msg) == "") else "",
-                      "chain_prompt": (chain.prompt if (rag_option == RAG_OFF) else 
-                                       chain.combine_documents_chain.llm_chain.prompt) if (str(err_msg) == "") else "",
+                      "chain_prompt": (str(chain.prompt) if (rag_option == RAG_OFF) else 
+                                       str(chain.combine_documents_chain.llm_chain.prompt)) if (str(err_msg) == "") else "",
                       "chain_retriever": ("" if (rag_option == RAG_OFF) else str(chain.retriever)) if (str(err_msg) == "") else "",
         },
         start_time_ms = start_time_ms,