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from langchain_community.llms import Replicate | |
from langchain_core.prompts import ChatPromptTemplate | |
# LLM | |
replicate_id = "andreasjansson/llama-2-13b-chat-gguf:60ec5dda9ff9ee0b6f786c9d1157842e6ab3cc931139ad98fe99e08a35c5d4d4" # noqa: E501 | |
model = Replicate( | |
model=replicate_id, | |
model_kwargs={"temperature": 0.8, "max_length": 500, "top_p": 0.95}, | |
) | |
# Prompt with output schema specification | |
template = """You are an AI language model assistant. Your task is to generate 3 different versions of the given user / | |
question to retrieve relevant documents from a vector database. By generating multiple perspectives on the user / | |
question, your goal is to help the user overcome some of the limitations of distance-based similarity search. / | |
Respond with json that adheres to the following jsonschema: | |
{{ | |
"$schema": "http://json-schema.org/draft-07/schema#", | |
"type": "object", | |
"properties": {{ | |
"question_1": {{ | |
"type": "string", | |
"description": "First version of the user question." | |
}}, | |
"question_2": {{ | |
"type": "string", | |
"description": "Second version of the user question." | |
}}, | |
"question_3": {{ | |
"type": "string", | |
"description": "Third version of the user question." | |
}} | |
}}, | |
"required": ["question_1","question_2","question_3"], | |
"additionalProperties": false | |
}}""" # noqa: E501 | |
prompt = ChatPromptTemplate.from_messages( | |
[("system", template), ("human", "{question}")] | |
) | |
# Chain | |
chain = prompt | model | |