Update app.py

app.py

@@ -23,7 +23,7 @@ with open(css_file) as f:
     st.markdown("<style>{}</style>".format(f.read()), unsafe_allow_html=True)
     
 HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
-repo_id=os.getenv("repo_id")
+repo_id=os.getenv("LLM_RepoID")
 model_name=os.getenv("model_name")
 
 documents=[]
@@ -35,6 +35,19 @@ def generate_random_string(length):
 random_string = generate_random_string(20)
 directory_path=random_string
 
+print(f"定义处理多余的Context文本的函数")
+def remove_context(text):
+    # 检查 'Context:' 是否存在
+    if 'Context:' in text:
+        # 找到第一个 '\n\n' 的位置
+        end_of_context = text.find('\n\n')
+        # 删除 'Context:' 到第一个 '\n\n' 之间的部分
+        return text[end_of_context + 2:]  # '+2' 是为了跳过两个换行符
+    else:
+        # 如果 'Context:' 不存在，返回原始文本
+        return text
+print(f"处理多余的Context文本函数定义结束")      
+
 st.sidebar.markdown(
     """
     <style>
@@ -87,8 +100,8 @@ with st.sidebar:
 embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name=model_name))
 
 llm = HuggingFaceHub(repo_id=repo_id,
-                     model_kwargs={"min_length":1024,
-                                   "max_new_tokens":5632, "do_sample":True,
+                     model_kwargs={"min_length":512,
+                                   "max_new_tokens":1024, "do_sample":True,
                                    "temperature":0.1,
                                    "top_k":50,
                                    "top_p":0.95, "eos_token_id":49155}) 
@@ -110,9 +123,11 @@ if question !="" and not question.strip().isspace() and not question == "" and n
         loadedindex = load_index_from_storage(storage_context=storage_context, service_context=service_context)
         query_engine = loadedindex.as_query_engine() 
         initial_response = query_engine.query(question)
+        cleaned_initial_ai_response=st(initial_response)
+        final_ai_response = cleaned_initial_ai_response.split('<|end|>\n<|system|>\n<|end|>\n<|user|>')[0].strip().replace('\n\n', '\n').replace('<|end|>', '').replace('<|user|>', '').replace('<|system|>', '').replace('<|assistant|>', '')
         #temp_ai_response=str(initial_response)
         #final_ai_response=temp_ai_response.partition('<|end|>')[0]
-        st.write("AI Response:\n\n"+str(initial_response))
+        st.write("AI Response:\n\n"+final_ai_response)
     #else:
      #   print("Check the Checkbox to get AI Response.")
       #  sys.exit()