Update app.py

app.py

@@ -1,51 +1,35 @@
-import os
-from langchain_community.llms import HuggingFaceEndpoint
-from langchain.chains import LLMChain
-from langchain_core.prompts import PromptTemplate
 import gradio as gr
-from langchain_community.chat_message_histories import ChatMessageHistory
-from langchain_core.chat_history import BaseChatMessageHistory
-from langchain_core.runnables.history import RunnableWithMessageHistory
-from langchain_core.messages import HumanMessage
-from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
-
-
-repo_id = "mistralai/Mistral-7B-Instruct-v0.3"  
-llm = HuggingFaceEndpoint(
-      repo_id=repo_id, max_length=128, temperature=0.2
+from huggingface_hub import InferenceClient
+
+client = InferenceClient(
+    "meta-llama/Meta-Llama-3-8B-Instruct",
+)
+
+def chat_mem(message,chat_history):
+
+  print(len(chat_history))
+  chat_history_role = [{"role": "system", "content": "You are a helpful assistant." },]
+  if chat_history != []:
+    for i in range(len(chat_history)):
+      chat_history_role.append({"role": "user", "content": chat_history[i][0]})
+      chat_history_role.append({"role": "assistant", "content": chat_history[i][1]})
+  chat_history_role.append({"role": "user", "content": message})
+  
+
+  chat_completion = client.chat_completion(
+  messages=chat_history_role,
+  # stream=True
   )
+  chat_history_role.append({"role": "assistant", "content": chat_completion.choices[0].message.content})
+  print(chat_history_role)
 
-store = {}
-
-def llm_chain(question, chat_history):  
-
-  def get_session_history(session_id: str) -> BaseChatMessageHistory:
-    if session_id not in store:
-        store[session_id] = ChatMessageHistory()
-    return store[session_id]
-
-
-
-  template = """Question: {question}
-
-  """
-
-  prompt = PromptTemplate.from_template(template)
-
-  chain = prompt | llm
-
-  with_message_history = RunnableWithMessageHistory(chain, get_session_history)
-  config = {"configurable": {"session_id": "abc1"}}
-  response = with_message_history.invoke(
-      [HumanMessage(content=question)],
-      config=config,
-  )
-  chat_history.append((question, response))
+  modified = map(lambda x: x["content"], chat_history_role)
+  a = list(modified)
+  chat_history=[(a[i*2+1], a[i*2+2]) for i in range(len(a)//2)]
 
   return "", chat_history
 
 
-
 with gr.Blocks() as demo:
   with gr.Row():
     with gr.Column():
@@ -53,10 +37,9 @@ with gr.Blocks() as demo:
       msg =  gr.Textbox(interactive=True, )
       with gr.Row():
         clear = gr.ClearButton([msg, chatbot], icon="https://img.icons8.com/?size=100&id=Xnx8cxDef16O&format=png&color=000000")
-        send_btn = gr.Button("Send", variant='primary', icon="https://img.icons8.com/?size=100&id=g8ltXTwIfJ1n&format=png&color=000000")        
-      msg.submit(fn=llm_chain, inputs=[msg, chatbot], outputs=[msg, chatbot])
-      send_btn.click(fn=llm_chain, inputs=[msg, chatbot], outputs=[msg, chatbot])
-      
+        send_btn = gr.Button("Send", variant='primary', icon="https://img.icons8.com/?size=100&id=g8ltXTwIfJ1n&format=png&color=000000")
+      msg.submit(fn=chat_mem, inputs=[msg, chatbot], outputs=[msg, chatbot])
+      send_btn.click(fn=chat_mem, inputs=[msg, chatbot], outputs=[msg, chatbot])
 
 
 if __name__ == "__main__":