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101 lines
3.8 KiB
Python
101 lines
3.8 KiB
Python
"""
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Module for generating the answer node
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"""
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from langchain_core.output_parsers import JsonOutputParser
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from langchain.prompts import PromptTemplate
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from .base_node import BaseNode
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class GenerateAnswerNode(BaseNode):
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"""
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A node that generates an answer using a language model (LLM) based on the user's input
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and the content extracted from a webpage. It constructs a prompt from the user's input
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and the scraped content, feeds it to the LLM, and parses the LLM's response to produce
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an answer.
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Attributes:
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llm (ChatOpenAI): An instance of a language model client, configured for generating answers.
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node_name (str): The unique identifier name for the node, defaulting
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to "GenerateAnswerNode".
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node_type (str): The type of the node, set to "node" indicating a
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standard operational node.
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Args:
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llm: An instance of the language model client (e.g., ChatOpenAI) used
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for generating answers.
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node_name (str, optional): The unique identifier name for the node.
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Defaults to "GenerateAnswerNode".
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Methods:
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execute(state): Processes the input and document from the state to generate an answer,
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updating the state with the generated answer under the 'answer' key.
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"""
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def __init__(self, llm, node_name: str = "GenerateAnswerNode"):
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"""
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Initializes the GenerateAnswerNode with a language model client and a node name.
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"""
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super().__init__(node_name, "node")
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self.llm = llm
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def execute(self, state: dict) -> dict:
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"""
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Generates an answer by constructing a prompt from the user's input and the scraped
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content, querying the language model, and parsing its response.
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The method updates the state with the generated answer under the 'answer' key.
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Args:
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state (dict): The current state of the graph, expected to contain 'user_input',
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and optionally 'parsed_document' or 'relevant_chunks' within 'keys'.
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Returns:
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dict: The updated state with the 'answer' key containing the generated answer.
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Raises:
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KeyError: If 'user_input' or 'document' is not found in the state, indicating
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that the necessary information for generating an answer is missing.
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"""
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print("---GENERATE ANSWER---")
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try:
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user_input = state["keys"]["user_input"]
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document = state["keys"]["document"]
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except KeyError as e:
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print(f"Error: {e} not found in state.")
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raise
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parsed_document = state["keys"].get("parsed_document", None)
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relevant_chunks = state["keys"].get("relevant_chunks", None)
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if relevant_chunks:
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context = relevant_chunks
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elif parsed_document:
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context = parsed_document
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else:
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context = document
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output_parser = JsonOutputParser()
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format_instructions = output_parser.get_format_instructions()
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template = """You are a website scraper and you have just scraped the
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following content from a website.
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You are now asked to answer a question about the content you have scraped.\n {format_instructions} \n The content is as follows: {context}
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Question: {question}
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"""
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schema_prompt = PromptTemplate(
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template=template,
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input_variables=["context", "question"],
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partial_variables={"format_instructions": format_instructions},
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)
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# Chain
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schema_chain = schema_prompt | self.llm | output_parser
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answer = schema_chain.invoke(
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{"context": context, "question": user_input})
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# Update the state with the generated answer
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state["keys"].update({"answer": answer})
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return state
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