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| from langchain.prompts import PromptTemplate, SystemMessagePromptTemplate, ChatPromptTemplate, \ | |
| HumanMessagePromptTemplate | |
| from langchain.llms import OpenAI | |
| from langchain.chat_models import ChatOpenAI, AzureChatOpenAI | |
| from langchain.cache import InMemoryCache | |
| import langchain | |
| langchain.llm_cache = InMemoryCache() | |
| import pandas as pd | |
| import os | |
| from langchain.chains import LLMChain | |
| from langchain.output_parsers import PydanticOutputParser | |
| from pydantic import BaseModel, Field | |
| os.environ["OPENAI_API_KEY"] = "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" | |
| class JSONPath_Generator: | |
| def __init__(self, json_input, target_value, json_condition): | |
| self.json_input = json_input | |
| self.target_value = target_value | |
| self.json_condition = json_condition | |
| # os.environ["OPENAI_API_KEY"] = "4b81012d55fb416c9e398f6149c3071e" | |
| # self.model = ChatOpenAI() | |
| # os.environ["OPENAI_API_TYPE"] = "azure" | |
| # os.environ["OPENAI_API_VERSION"] = "2023-03-15-preview" | |
| # self.model = AzureChatOpenAI( | |
| # # openaikey=openaikey, | |
| # # openai_api_version="2023-03-15-preview", | |
| # # azure_deployment="text-davinci-003", | |
| # # temperature=0, | |
| # deployment_name="gpt-4", | |
| # model_name="gpt-4", | |
| # ) | |
| self.model = OpenAI( | |
| temperature=0, | |
| # openai_api_key=self.api_key, | |
| model_name="gpt-3.5-turbo-instruct" | |
| ) | |
| def create_chat_prompt(self): | |
| # System Template | |
| with open("system_template.txt", "r") as sys_temp: | |
| system_template = sys_temp.read().strip() | |
| system_prompt = SystemMessagePromptTemplate.from_template(system_template) | |
| # Humman Template | |
| with open("human_template.txt", "r") as hum_temp: | |
| human_template = hum_temp.read().strip() | |
| if self.json_condition != '': | |
| human_template += " provided the {json_condition}" | |
| human_prompt = HumanMessagePromptTemplate.from_template(human_template) | |
| # Chat Prompt | |
| self.chat_prompt = ChatPromptTemplate.from_messages([system_prompt, human_prompt]) | |
| def create_llm_chain(self): | |
| # self.read_extract_api_details() | |
| self.create_chat_prompt() | |
| chain = LLMChain(llm=self.model, prompt=self.chat_prompt) | |
| self.response = chain.run(Target_value=self.target_value,json_condition = self.json_condition, | |
| JSON_Input=self.json_input) | |
| return self.response |