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from langchain.prompts import ( | |
SystemMessagePromptTemplate, | |
HumanMessagePromptTemplate, | |
ChatPromptTemplate, | |
MessagesPlaceholder | |
) | |
from langchain.chains import ConversationChain | |
class Chain: | |
def __init__(self, llm, history=None): | |
self.llm = llm | |
# self.chain = self.get_conversational_chain() | |
if history is not None: | |
self.history = history | |
def run_conversational_chain(self, prompt_template): | |
ans = self.llm.invoke(prompt_template).content | |
return ans | |
def get_chain_with_history(self): | |
system_msg_template = SystemMessagePromptTemplate.from_template(template="""Answer the question as truthfully as possible using the provided context, | |
and if the answer is not contained within the text below, say 'I don't know'""") | |
human_msg_template = HumanMessagePromptTemplate.from_template(template="{input}") | |
prompt_template = ChatPromptTemplate.from_messages([system_msg_template, MessagesPlaceholder(variable_name="history"), human_msg_template]) | |
conversation = ConversationChain(memory=self.history, prompt=prompt_template, llm=self.llm, verbose=True) | |
return conversation |