updata

app.py

@@ -3,7 +3,7 @@ import json
 import gradio as gr
 from datetime import datetime
 
-invoke_url = "https://es9ke27g82.execute-api.us-west-2.amazonaws.com/prod"
+invoke_url = "https://02u4taf9pf.execute-api.us-west-2.amazonaws.com/prod"
 api = invoke_url + '/langchain_processor_qa?query='
 
 # chinese_index = "smart_search_qa_test_0614_wuyue_2"
@@ -63,7 +63,7 @@ Please automatically generate as many questions as possible based on this manual
 """
 
 
-def get_answer(question,session_id,language,prompt,index,top_k,temperature):
+def get_answer(question,session_id,language,prompt,search_engine,index,top_k,temperature):
     
     if len(question) > 0:
         url = api + question
@@ -104,19 +104,28 @@ def get_answer(question,session_id,language,prompt,index,top_k,temperature):
     if len(prompt) > 0:
         url += ('&prompt='+prompt)
 
-        
-    if len(index) > 0:
-        url += ('&index='+index)
-    else:
-        if language.find("chinese") >= 0 and len(chinese_index) >0:
-            url += ('&index='+chinese_index)
-        elif language == "english" and len(english_index) >0:
-            url += ('&index='+english_index)
-    
+    if search_engine == "OpenSearch":
+        url += ('&search_engine=opensearch')
+        if len(index) > 0:
+            url += ('&index='+index)
+        else:
+            if language.find("chinese") >= 0 and len(chinese_index) >0:
+                url += ('&index='+chinese_index)
+            elif language == "english" and len(english_index) >0:
+                url += ('&index='+english_index)
+    elif search_engine == "Kendra":
+        url += ('&search_engine=kendra')
+        if len(index) > 0:
+            url += ('&kendra_index_id='+index)
+
     if int(top_k) > 0:
         url += ('&top_k='+str(top_k))
     
     url += ('&temperature='+str(temperature))
+    url += ('&cal_qa_relate_score=true')
+    url += ('&cal_answer_relate_scores=true')
+    url += ('&cal_list_overlap_score=true')
+
     print("url:",url)
 
     now1 = datetime.now()#begin time
@@ -144,31 +153,35 @@ def get_answer(question,session_id,language,prompt,index,top_k,temperature):
         _id = "num:" + str(item['id'])
         source = "source:" + item['source']
         score = "score:" + str(item['score'])
-        sentence = "sentence" + item['sentence']
+        sentence = "sentence:" + item['sentence']
         paragraph = "paragraph:" + item['paragraph']
         source_str += (_id + "      " + source + "      " + score + '\n')
-        source_str += sentence + '\n'
+        # source_str += sentence + '\n'
         source_str += paragraph + '\n\n'
     
     confidence = ""
-    query_doc_scores = ''
+    query_doc_scores = []
     if 'query_doc_scores' in result.keys():
-        query_doc_scores =  result['query_doc_scores']
-        confidence += ("query_doc_scores:" + str(query_doc_scores) + '\n')
+        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')
 
-    qa_relate_score = ''
+    qa_relate_score = 0
     if 'qa_relate_score' in result.keys():
         qa_relate_score =  result['qa_relate_score']
+    if float(qa_relate_score) > 0:
         confidence += ("qa_relate_score:" + str(qa_relate_score) + '\n')
 
-    answer_relate_scores = ''
+    answer_relate_scores = []
     if 'answer_relate_scores' in result.keys():
-        answer_relate_scores =  result['answer_relate_scores']
-        confidence += ("answer_relate_scores:" + str(answer_relate_scores) + '\n')
+        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')
 
-    list_overlap_score = ''
+    list_overlap_score = 0
     if 'list_overlap_score' in result.keys():
         list_overlap_score =  result['list_overlap_score']
+    if float(list_overlap_score) > 0:
         confidence += ("list_overlap_score:" + str(list_overlap_score) + '\n')
 
 
@@ -230,6 +243,7 @@ with demo:
                     qa_language_radio = gr.Radio(["chinese-glm","chinese-glm2", "english"],value="chinese-glm",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")
                     qa_index_textbox = gr.Textbox(label="Index")
                     qa_top_k_slider = gr.Slider(label="Top_k of source text to LLM",value=1, minimum=1, maximum=4, step=1)
                     
@@ -253,7 +267,7 @@ with demo:
                     text_output = gr.Textbox()
             
        
-    qa_button.click(get_answer, inputs=[query_textbox,session_id_textbox,qa_language_radio,qa_prompt_textbox,qa_index_textbox,qa_top_k_slider,temperature_slider], outputs=qa_output)
+    qa_button.click(get_answer, inputs=[query_textbox,session_id_textbox,qa_language_radio,qa_prompt_textbox,qa_search_engine_radio,qa_index_textbox,qa_top_k_slider,temperature_slider], outputs=qa_output)
     summarize_button.click(get_summarize, inputs=[text_input,sm_language_radio,sm_prompt_textbox], outputs=text_output)
 
 demo.launch()