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82 lines
2.8 KiB
Python
82 lines
2.8 KiB
Python
import os
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import pip
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from langchain.chat_models import AzureChatOpenAI
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from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
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from langchain.prompts.prompt import PromptTemplate
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from langchain.schema import HumanMessage
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def extract_intent(chat_prompt: str):
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if (
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"AZURE_OPENAI_API_KEY" not in os.environ
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or "AZURE_OPENAI_API_BASE" not in os.environ
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):
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# load environment variables from .env file
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try:
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from dotenv import load_dotenv
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except ImportError:
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# This can be removed if user using custom image.
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pip.main(["install", "python-dotenv"])
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from dotenv import load_dotenv
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load_dotenv()
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# AZURE_OPENAI_ENDPOINT conflict with AZURE_OPENAI_API_BASE when use with langchain
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if "AZURE_OPENAI_ENDPOINT" in os.environ:
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os.environ.pop("AZURE_OPENAI_ENDPOINT")
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chat = AzureChatOpenAI(
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deployment_name=os.environ.get("CHAT_DEPLOYMENT_NAME", "gpt-35-turbo"),
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openai_api_key=os.environ["AZURE_OPENAI_API_KEY"],
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openai_api_base=os.environ["AZURE_OPENAI_API_BASE"],
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openai_api_type="azure",
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openai_api_version="2023-07-01-preview",
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temperature=0,
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)
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reply_message = chat([HumanMessage(content=chat_prompt)])
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return reply_message.content
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def generate_prompt(customer_info: str, history: list, user_prompt_template: str):
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chat_history_text = "\n".join(
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[message["role"] + ": " + message["content"] for message in history]
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)
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prompt_template = PromptTemplate.from_template(user_prompt_template)
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chat_prompt_template = ChatPromptTemplate.from_messages(
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[HumanMessagePromptTemplate(prompt=prompt_template)]
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)
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return chat_prompt_template.format_prompt(
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customer_info=customer_info, chat_history=chat_history_text
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).to_string()
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if __name__ == "__main__":
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import json
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with open("./data/denormalized-flat.jsonl", "r") as f:
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data = [json.loads(line) for line in f.readlines()]
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# only ten samples
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data = data[:10]
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# load template from file
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with open("user_intent_zero_shot.jinja2", "r") as f:
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user_prompt_template = f.read()
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# each test
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for item in data:
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chat_prompt = generate_prompt(
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item["customer_info"], item["history"], user_prompt_template
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)
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reply = extract_intent(chat_prompt)
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print("=====================================")
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# print("Customer info: ", item["customer_info"])
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# print("+++++++++++++++++++++++++++++++++++++")
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print("Chat history: ", item["history"])
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print("+++++++++++++++++++++++++++++++++++++")
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print(reply)
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print("+++++++++++++++++++++++++++++++++++++")
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print(f"Ground Truth: {item['intent']}")
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print("=====================================")
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