updata

app.py

@@ -82,12 +82,12 @@ def get_answer(question,session_id,language,prompt,search_engine,index,top_k,tem
         url += '&language=english'
         url += ('&embedding_endpoint_name=pytorch-inference-all-minilm-l6-v2')
         url += ('&llm_embedding_name=pytorch-inference-vicuna-g5-2x')
-    elif language == "chinese-glm":
+    elif language == "chinese-llm-v1":
         url += '&language=chinese'
         url += ('&embedding_endpoint_name=huggingface-inference-text2vec-base-chinese-v1')
         url += ('&llm_embedding_name=pytorch-inference-chatglm-v1')
      
-    elif language == "chinese-glm2":
+    elif language == "chinese-llm-v2":
         url += '&language=chinese'
         url += ('&embedding_endpoint_name=huggingface-inference-text2vec-base-chinese-v1')
         url += ('&llm_embedding_name=pytorch-inference-chatglm2-g5-2x')   
@@ -164,7 +164,7 @@ def get_answer(question,session_id,language,prompt,search_engine,index,top_k,tem
     if 'query_doc_scores' in result.keys():
         query_doc_scores =  list(result['query_doc_scores'])
     if len(query_doc_scores) > 0:
-        confidence += ("query_doc_scores:" + str(float(query_doc_scores[0])) + '\n')
+        confidence += ("query_doc_scores:" + str(query_doc_scores) + '\n')
 
     qa_relate_score = 0
     if 'qa_relate_score' in result.keys():
@@ -176,7 +176,7 @@ def get_answer(question,session_id,language,prompt,search_engine,index,top_k,tem
     if 'answer_relate_scores' in result.keys():
         answer_relate_scores =  list(result['answer_relate_scores'])
     if len(answer_relate_scores) > 0:
-        confidence += ("answer_relate_scores:" + str(float(answer_relate_scores[0])) + '\n')
+        confidence += ("answer_relate_scores:" + str(answer_relate_scores) + '\n')
 
     list_overlap_score = 0
     if 'list_overlap_score' in result.keys():
@@ -240,7 +240,7 @@ with demo:
                     session_id_textbox = gr.Textbox(label="Session ID")
                     qa_button = gr.Button("Summit")
 
-                    qa_language_radio = gr.Radio(["chinese-glm","chinese-glm2", "english"],value="chinese-glm",label="Language")
+                    qa_language_radio = gr.Radio(["chinese-llm-v1","chinese-llm-v2", "english"],value="chinese-llm-v1",label="Language")
                     # qa_llm_radio = gr.Radio(["p3-8x", "g4dn-8x"],value="p3-8x",label="Chinese llm instance")
                     qa_prompt_textbox = gr.Textbox(label="Prompt( must include {context} and {question} )",placeholder=chinese_prompt,lines=2)
                     qa_search_engine_radio = gr.Radio(["OpenSearch","Kendra"],value="OpenSearch",label="Search engine")