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"""
NOTE: This example is designed to produce mildly incorrect output -- 
see the definition of `IncomeData` and note that it fixes the earnings_per_share to 2.33.

To make this function normally, simply remove the `__init__` method or the 
`self.earnings_per_share = 2.33` line.
"""

import warnings
warnings.filterwarnings('ignore')

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import warnings
warnings.filterwarnings('ignore')

from rich import print

import outlines
from cleanlab_tlm import TLM
import os
from pydantic import BaseModel
from transformers import AutoTokenizer

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emotions:
- connection_to_content:
    relationship: CAUSES
    strength: 0.5
  emotionType: enthusiasm
  text: There is a sense of excitement and energy surrounding the launch of Comind,
    an open-source project aimed at developing a cognitive layer for ATProto. Mr.
    Dr. Cameron Pfiffer expresses a passionate invitation for contributors, showcasing
    enthusiasm for the project's potential in building a network of AI agents.
- connection_to_content:

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# Setup instructions:
# pip install 'outlines[transformers]'

import outlines 
from transformers import AutoTokenizer
import json

# MODEL_STRING = "HuggingFaceTB/SmolLM2-135M-Instruct" # Small model
# MODEL_STRING = "HuggingFaceTB/SmolLM2-1.7B-Instruct" # Larger but kind of boring
MODEL_STRING = "NousResearch/Hermes-3-Llama-3.1-8B"

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import outlines
import os
from pydantic import BaseModel, Field
from transformers import AutoTokenizer

model_str = 'Qwen/Qwen2.5-7B-Instruct-1M'
model = outlines.models.transformers(
    model_str,
    device='cuda'
)

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import time
from typing import Literal
import outlines
import re
import torch
from transformers import AutoTokenizer
from outlines.fsm.json_schema import convert_json_schema_to_str
from outlines_core.fsm.json_schema import build_regex_from_schema
from pydantic import BaseModel

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UnderstandingResponse(
    understanding=Understanding(
        chain_of_thought=[
            "The user profile belongs to akhilrao.bsky.social, with a display name of 'grand theft eigenvalue 🔆'. Their description indicates that they are an economist and that it's a personal account, including their pronouns
as 'he/him'.",
            "Their first post is about the Mobius YIMBY arc, a topic related to economics and possibly linked to geographical development or real estate markets, based on the acronym 'YIMBY' (Yes In My Back Yard), usually
associated with urban development. The term 'Mobius', referencing a strip with no boundaries, might metaphorically suggest infinite or unexplored opportunities or issues in the economic landscape.",
            "The second post comments on the affordability and proliferation of LEO (Low Earth Orbit) satellites, critiquing the notion that because they are inexpensive, it's acceptable to deploy them en masse without concern
for their potential environmental and spatial clut

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import outlines
from transformers import AutoTokenizer

model_string = 'deepseek-ai/DeepSeek-R1-Distill-Qwen-7B'
# model_string = 'deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B' # For small machines

model = outlines.models.transformers(
    model_string,
    device='cuda', # also 'cpu', 'mps','auto'
)

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import outlines
from pydantic import BaseModel
from transformers import AutoTokenizer
from rich import print

model_string = "HuggingFaceTB/SmolLM2-1.7B-Instruct"
model = outlines.models.transformers(model_string)
tokenizer = AutoTokenizer.from_pretrained(model_string)

class Highlights(BaseModel):

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"""
pip install outlines torch==2.4.0 transformers accelerate pillow rich

sudo apt-get install poppler-utils
"""

from enum import Enum
from PIL import Image
import outlines
import torch