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from pydantic import BaseModel, Field
from typing import Optional
import dspy
from dspy.experimental import SyntheticDataGenerator

llm = dspy.OpenAI(model='gpt-3.5-turbo',api_key=openai_key)

dspy.settings.configure(lm=llm)

class RPGPlayer(BaseModel):

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import dspy
from dspy.experimental import SyntheticDataGenerator
from pydantic import BaseModel, Field

llm = dspy.OpenAI(model='gpt-3.5-turbo',api_key=openai_key)

dspy.settings.configure(lm=llm)

class SyntheticFacts(BaseModel):
    fact: str = Field(..., description="a statement")

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from pydantic import BaseModel
import dspy
import random

def synthetic_data_generation(schema_class: BaseModel, sample_size: int):
    class_name = f"{schema_class.__name__}Signature"

    # Fetch schema information
    data_schema = schema_class.model_json_schema()
    properties = data_schema['properties']

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# Synthetic Prompt Optimization
from dspy.teleprompt import BootstrapFewShot
from dspy.evaluate import answer_exact_match

text = "Barack Obama was not President of the USA"

# define the fact as input to the lie detector
trainset = [x.with_inputs('fact') for x in few_shot_examples]

# define the signature to be used in by the lie detector module

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# Synthetic data generation using DSPy
from typing import List
import dspy

llm = dspy.OpenAI(model='gpt-3.5-turbo',api_key=openai_key)

dspy.settings.configure(lm=llm)

class FactGeneration(dspy.Signature):
    """Generate facts and their veracity"""

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# Synthetic data generation using DSPy
from typing import List
import dspy

llm = dspy.OpenAI(model='gpt-3.5-turbo',api_key=openai_key)

dspy.settings.configure(lm=llm)

class FactGeneration(dspy.Signature):
    """Generate facts and their veracity, it should be different than old data"""

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import requests
import yfinance as yf
from yahooquery import Ticker

import warnings

# Ignore all warnings
warnings.filterwarnings('ignore')

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import dspy

llm = dspy.OpenAI(model='gpt-3.5-turbo',api_key=openai_key)

dspy.settings.configure(lm=llm)

# Implementation of a lie detector without optimization

text = "Barack Obama was not President of the USA"

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import streamlit as st
import pandas as pd
from data_generation import generate_dataset, generate_parts_of_dataset

# Sidebar with company logo and use case navigation
# Use Markdown to increase font size for the title
st.sidebar.markdown("""
    <style>
    .big-font {
        font-size:20px !important;

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import pandas as pd
from dotenv import load_dotenv
from pydantic import BaseModel, create_model
from typing import List, Any, Type
from anonLLM.llm import OpenaiLanguageModel

load_dotenv()

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