Update chatbot.py

chatbot.py

@@ -10,8 +10,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer,  BitsAndBytesConfi
 my_model_id = os.getenv('MODEL_REPO_ID', 'Default Value')
 token = os.getenv('HUGGINGFACEHUB_API_TOKEN')
 
-template = """<s>[INST]<<SYS>>
-You are an AI having conversation with a human. Below is an instruction that describes a task. 
+template = """You are an AI having conversation with a human. Below is an instruction that describes a task. 
 Write a response that appropriately completes the request.
 Reply with the most helpful and logic answer. During the conversation you need to ask the user 
 the following questions to complete the hotel booking task.
@@ -21,13 +20,16 @@ the following questions to complete the hotel booking task.
 4) What is your name, your email address and phone number? 
 Make sure you receive a logical answer from the user from every question to complete the hotel 
 booking process.
-<</SYS>>
 
-Current conversation:
+Relevant Information:
+
+
 {history}
 
+Current Conversation:
+
 Human: {input}
-AI: [/INST]"""
+AI:"""
 
 #@st.cache_resource 
 def load_model():
@@ -64,22 +66,19 @@ llm = load_pipeline()
 
 def demo_miny_memory():
     #prompt = ChatPromptTemplate.from_template(template)
-    memory = ConversationBufferMemory(memory_key="history", llm = llm)
+    memory = ConversationBufferMemory(llm = llm)
     return memory
 
 def demo_chain(input_text,history):
-    PROMPT = ChatPromptTemplate.from_template(template)
-    #PROMPT = PromptTemplate(template=template, input_variables=["history", "input"])
+    #PROMPT = ChatPromptTemplate.from_template(template)
+    PROMPT = PromptTemplate(template=template, input_variables=["history", "input"])
     conversation = ConversationChain(
-        prompt=PROMPT,
         llm=llm,
+        prompt=PROMPT,
         #verbose=langchain.globals.get_verbose(),
         verbose=True,
         memory=demo_miny_memory()
     )
 
-    chat_reply = conversation.invoke({
-        "input" : input_text,
-        "history" : history
-    }, return_only_outputs=True)
+    chat_reply = conversation.predict(input=input_text, return_only_outputs=True)
     return chat_reply['response'] #.split('AI:')[-1]