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from pydantic import BaseModel
from anonLLM.llm import OpenaiLanguageModel
from dotenv import load_dotenv

load_dotenv()

llm = OpenaiLanguageModel(anonymize=False, temperature=1)


class Person(BaseModel):

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from langchain_openai import ChatOpenAI
from langchain_core.pydantic_v1 import BaseModel, Field
from dotenv import load_dotenv


load_dotenv()


class NextMove(BaseModel):
    move: str = Field(..., description="Best next move to win the chess game. It should be in Standard Algebraic Notation")

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import dspy
from dspy.functional import TypedPredictor
from pydantic import BaseModel, Field
from typing import List
from dotenv import load_dotenv


class Task(BaseModel):
    "Class for keeping track of a task"
    name: str = Field(..., description="name of the task")

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import requests
from bs4 import BeautifulSoup
from dotenv import load_dotenv
import os

load_dotenv()

BASE_URL = 'https://news.ycombinator.com'
USERNAME = os.getenv("USERNAME")
PASSWORD = os.getenv("PASSWORD")

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import streamlit as st
from st_chat_message import message
from dotenv import load_dotenv
import fitz

load_dotenv()

from raptor.raptor import RetrievalAugmentation # noqa

RA = RetrievalAugmentation()

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response = openai.ChatCompletion.create(
    model=fine_tuned_model_id, messages=test_messages, temperature=0.5
)
print(response["choices"][0]["message"]["content"])

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training_response = openai.File.create(
    file=open(training_file_name, "rb"), purpose="fine-tune"
)
training_file_id = training_response["id"]

validation_response = openai.File.create(
    file=open(validation_file_name, "rb"), purpose="fine-tune"
)
validation_file_id = validation_response["id"]

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import json

# Load JSON data from mypoems.json
with open('mypoems.json', 'r') as json_file:
    json_data = json.load(json_file)

# Conversion from JSON to JSONL
with open('mypoems.jsonl', 'w') as f:
    for entry in json_data:
        json_str = json.dumps(entry)

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# The goal of this program is to transform the poems.txt file into a well structured json file
from dotenv import load_dotenv
import json
import re
from anonLLM.llm import OpenaiLanguageModel

load_dotenv()

SEP = '---'

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import chess
import chess.engine
import os
import dspy
from pydantic import BaseModel, Field
from dspy.functional import TypedPredictor
from dotenv import load_dotenv


load_dotenv()