mirror of
https://github.com/hwchase17/langchain.git
synced 2025-04-28 11:55:21 +00:00
522 lines
19 KiB
Python
522 lines
19 KiB
Python
"""Callback Handler that prints to std out."""
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import threading
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from enum import Enum, auto
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from typing import Any, Dict, List
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from langchain_core._api import warn_deprecated
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from langchain_core.callbacks import BaseCallbackHandler
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from langchain_core.messages import AIMessage
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from langchain_core.outputs import ChatGeneration, LLMResult
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MODEL_COST_PER_1K_TOKENS = {
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# GPT-4.1 input
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"gpt-4.1": 0.002,
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"gpt-4.1-2025-04-14": 0.002,
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"gpt-4.1-cached": 0.0005,
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"gpt-4.1-2025-04-14-cached": 0.0005,
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# GPT-4.1 output
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"gpt-4.1-completion": 0.008,
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"gpt-4.1-2025-04-14-completion": 0.008,
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# GPT-4.1-mini input
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"gpt-4.1-mini": 0.0004,
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"gpt-4.1-mini-2025-04-14": 0.0004,
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"gpt-4.1-mini-cached": 0.0001,
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"gpt-4.1-mini-2025-04-14-cached": 0.0001,
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# GPT-4.1-mini output
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"gpt-4.1-mini-completion": 0.0016,
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"gpt-4.1-mini-2025-04-14-completion": 0.0016,
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# GPT-4.1-nano input
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"gpt-4.1-nano": 0.0001,
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"gpt-4.1-nano-2025-04-14": 0.0001,
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"gpt-4.1-nano-cached": 0.000025,
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"gpt-4.1-nano-2025-04-14-cached": 0.000025,
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# GPT-4.1-nano output
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"gpt-4.1-nano-completion": 0.0004,
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"gpt-4.1-nano-2025-04-14-completion": 0.0004,
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# GPT-4.5-preview input
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"gpt-4.5-preview": 0.075,
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"gpt-4.5-preview-2025-02-27": 0.075,
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"gpt-4.5-preview-cached": 0.0375,
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"gpt-4.5-preview-2025-02-27-cached": 0.0375,
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# GPT-4.5-preview output
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"gpt-4.5-preview-completion": 0.15,
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"gpt-4.5-preview-2025-02-27-completion": 0.15,
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# OpenAI o1 input
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"o1": 0.015,
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"o1-2024-12-17": 0.015,
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"o1-cached": 0.0075,
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"o1-2024-12-17-cached": 0.0075,
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# OpenAI o1 output
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"o1-completion": 0.06,
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"o1-2024-12-17-completion": 0.06,
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# OpenAI o1-pro input
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"o1-pro": 0.15,
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"o1-pro-2025-03-19": 0.15,
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# OpenAI o1-pro output
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"o1-pro-completion": 0.6,
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"o1-pro-2025-03-19-completion": 0.6,
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# OpenAI o3 input
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"o3": 0.01,
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"o3-2025-04-16": 0.01,
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"o3-cached": 0.0025,
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"o3-2025-04-16-cached": 0.0025,
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# OpenAI o3 output
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"o3-completion": 0.04,
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"o3-2025-04-16-completion": 0.04,
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# OpenAI o4-mini input
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"o4-mini": 0.0011,
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"o4-mini-2025-04-16": 0.0011,
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"o4-mini-cached": 0.000275,
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"o4-mini-2025-04-16-cached": 0.000275,
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# OpenAI o4-mini output
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"o4-mini-completion": 0.0044,
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"o4-mini-2025-04-16-completion": 0.0044,
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# OpenAI o3-mini input
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"o3-mini": 0.0011,
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"o3-mini-2025-01-31": 0.0011,
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"o3-mini-cached": 0.00055,
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"o3-mini-2025-01-31-cached": 0.00055,
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# OpenAI o3-mini output
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"o3-mini-completion": 0.0044,
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"o3-mini-2025-01-31-completion": 0.0044,
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# OpenAI o1-mini input (updated pricing)
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"o1-mini": 0.0011,
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"o1-mini-cached": 0.00055,
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"o1-mini-2024-09-12": 0.0011,
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"o1-mini-2024-09-12-cached": 0.00055,
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# OpenAI o1-mini output (updated pricing)
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"o1-mini-completion": 0.0044,
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"o1-mini-2024-09-12-completion": 0.0044,
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# OpenAI o1-preview input
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"o1-preview": 0.015,
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"o1-preview-cached": 0.0075,
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"o1-preview-2024-09-12": 0.015,
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"o1-preview-2024-09-12-cached": 0.0075,
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# OpenAI o1-preview output
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"o1-preview-completion": 0.06,
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"o1-preview-2024-09-12-completion": 0.06,
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# GPT-4o input
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"gpt-4o": 0.0025,
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"gpt-4o-cached": 0.00125,
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"gpt-4o-2024-05-13": 0.005,
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"gpt-4o-2024-08-06": 0.0025,
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"gpt-4o-2024-08-06-cached": 0.00125,
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"gpt-4o-2024-11-20": 0.0025,
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"gpt-4o-2024-11-20-cached": 0.00125,
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# GPT-4o output
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"gpt-4o-completion": 0.01,
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"gpt-4o-2024-05-13-completion": 0.015,
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"gpt-4o-2024-08-06-completion": 0.01,
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"gpt-4o-2024-11-20-completion": 0.01,
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# GPT-4o-audio-preview input
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"gpt-4o-audio-preview": 0.0025,
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"gpt-4o-audio-preview-2024-12-17": 0.0025,
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"gpt-4o-audio-preview-2024-10-01": 0.0025,
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# GPT-4o-audio-preview output
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"gpt-4o-audio-preview-completion": 0.01,
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"gpt-4o-audio-preview-2024-12-17-completion": 0.01,
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"gpt-4o-audio-preview-2024-10-01-completion": 0.01,
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# GPT-4o-realtime-preview input
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"gpt-4o-realtime-preview": 0.005,
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"gpt-4o-realtime-preview-2024-12-17": 0.005,
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"gpt-4o-realtime-preview-2024-10-01": 0.005,
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"gpt-4o-realtime-preview-cached": 0.0025,
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"gpt-4o-realtime-preview-2024-12-17-cached": 0.0025,
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"gpt-4o-realtime-preview-2024-10-01-cached": 0.0025,
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# GPT-4o-realtime-preview output
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"gpt-4o-realtime-preview-completion": 0.02,
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"gpt-4o-realtime-preview-2024-12-17-completion": 0.02,
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"gpt-4o-realtime-preview-2024-10-01-completion": 0.02,
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# GPT-4o-mini input
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"gpt-4o-mini": 0.00015,
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"gpt-4o-mini-cached": 0.000075,
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"gpt-4o-mini-2024-07-18": 0.00015,
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"gpt-4o-mini-2024-07-18-cached": 0.000075,
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# GPT-4o-mini output
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"gpt-4o-mini-completion": 0.0006,
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"gpt-4o-mini-2024-07-18-completion": 0.0006,
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# GPT-4o-mini-audio-preview input
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"gpt-4o-mini-audio-preview": 0.00015,
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"gpt-4o-mini-audio-preview-2024-12-17": 0.00015,
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# GPT-4o-mini-audio-preview output
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"gpt-4o-mini-audio-preview-completion": 0.0006,
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"gpt-4o-mini-audio-preview-2024-12-17-completion": 0.0006,
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# GPT-4o-mini-realtime-preview input
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"gpt-4o-mini-realtime-preview": 0.0006,
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"gpt-4o-mini-realtime-preview-2024-12-17": 0.0006,
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"gpt-4o-mini-realtime-preview-cached": 0.0003,
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"gpt-4o-mini-realtime-preview-2024-12-17-cached": 0.0003,
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# GPT-4o-mini-realtime-preview output
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"gpt-4o-mini-realtime-preview-completion": 0.0024,
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"gpt-4o-mini-realtime-preview-2024-12-17-completion": 0.0024,
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# GPT-4o-mini-search-preview input
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"gpt-4o-mini-search-preview": 0.00015,
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"gpt-4o-mini-search-preview-2025-03-11": 0.00015,
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# GPT-4o-mini-search-preview output
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"gpt-4o-mini-search-preview-completion": 0.0006,
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"gpt-4o-mini-search-preview-2025-03-11-completion": 0.0006,
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# GPT-4o-search-preview input
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"gpt-4o-search-preview": 0.0025,
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"gpt-4o-search-preview-2025-03-11": 0.0025,
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# GPT-4o-search-preview output
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"gpt-4o-search-preview-completion": 0.01,
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"gpt-4o-search-preview-2025-03-11-completion": 0.01,
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# Computer-use-preview input
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"computer-use-preview": 0.003,
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"computer-use-preview-2025-03-11": 0.003,
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# Computer-use-preview output
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"computer-use-preview-completion": 0.012,
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"computer-use-preview-2025-03-11-completion": 0.012,
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# GPT-4 input
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"gpt-4": 0.03,
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"gpt-4-0314": 0.03,
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"gpt-4-0613": 0.03,
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"gpt-4-32k": 0.06,
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"gpt-4-32k-0314": 0.06,
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"gpt-4-32k-0613": 0.06,
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"gpt-4-vision-preview": 0.01,
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"gpt-4-1106-preview": 0.01,
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"gpt-4-0125-preview": 0.01,
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"gpt-4-turbo-preview": 0.01,
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"gpt-4-turbo": 0.01,
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"gpt-4-turbo-2024-04-09": 0.01,
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# GPT-4 output
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"gpt-4-completion": 0.06,
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"gpt-4-0314-completion": 0.06,
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"gpt-4-0613-completion": 0.06,
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"gpt-4-32k-completion": 0.12,
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"gpt-4-32k-0314-completion": 0.12,
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"gpt-4-32k-0613-completion": 0.12,
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"gpt-4-vision-preview-completion": 0.03,
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"gpt-4-1106-preview-completion": 0.03,
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"gpt-4-0125-preview-completion": 0.03,
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"gpt-4-turbo-preview-completion": 0.03,
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"gpt-4-turbo-completion": 0.03,
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"gpt-4-turbo-2024-04-09-completion": 0.03,
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# GPT-3.5 input
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# gpt-3.5-turbo points at gpt-3.5-turbo-0613 until Feb 16, 2024.
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# Switches to gpt-3.5-turbo-0125 after.
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"gpt-3.5-turbo": 0.0015,
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"gpt-3.5-turbo-0125": 0.0005,
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"gpt-3.5-turbo-0301": 0.0015,
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"gpt-3.5-turbo-0613": 0.0015,
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"gpt-3.5-turbo-1106": 0.001,
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"gpt-3.5-turbo-instruct": 0.0015,
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"gpt-3.5-turbo-16k": 0.003,
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"gpt-3.5-turbo-16k-0613": 0.003,
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# GPT-3.5 output
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# gpt-3.5-turbo points at gpt-3.5-turbo-0613 until Feb 16, 2024.
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# Switches to gpt-3.5-turbo-0125 after.
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"gpt-3.5-turbo-completion": 0.002,
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"gpt-3.5-turbo-0125-completion": 0.0015,
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"gpt-3.5-turbo-0301-completion": 0.002,
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"gpt-3.5-turbo-0613-completion": 0.002,
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"gpt-3.5-turbo-1106-completion": 0.002,
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"gpt-3.5-turbo-instruct-completion": 0.002,
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"gpt-3.5-turbo-16k-completion": 0.004,
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"gpt-3.5-turbo-16k-0613-completion": 0.004,
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# Azure GPT-35 input
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"gpt-35-turbo": 0.0015, # Azure OpenAI version of ChatGPT
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"gpt-35-turbo-0125": 0.0005,
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"gpt-35-turbo-0301": 0.002, # Azure OpenAI version of ChatGPT
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"gpt-35-turbo-0613": 0.0015,
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"gpt-35-turbo-instruct": 0.0015,
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"gpt-35-turbo-16k": 0.003,
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"gpt-35-turbo-16k-0613": 0.003,
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# Azure GPT-35 output
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"gpt-35-turbo-completion": 0.002, # Azure OpenAI version of ChatGPT
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"gpt-35-turbo-0125-completion": 0.0015,
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"gpt-35-turbo-0301-completion": 0.002, # Azure OpenAI version of ChatGPT
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"gpt-35-turbo-0613-completion": 0.002,
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"gpt-35-turbo-instruct-completion": 0.002,
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"gpt-35-turbo-16k-completion": 0.004,
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"gpt-35-turbo-16k-0613-completion": 0.004,
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# Others
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"text-ada-001": 0.0004,
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"ada": 0.0004,
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"text-babbage-001": 0.0005,
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"babbage": 0.0005,
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"text-curie-001": 0.002,
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"curie": 0.002,
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"text-davinci-003": 0.02,
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"text-davinci-002": 0.02,
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"code-davinci-002": 0.02,
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# Fine Tuned input
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"babbage-002-finetuned": 0.0016,
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"davinci-002-finetuned": 0.012,
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"gpt-3.5-turbo-0613-finetuned": 0.003,
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"gpt-3.5-turbo-1106-finetuned": 0.003,
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"gpt-3.5-turbo-0125-finetuned": 0.003,
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"gpt-4o-mini-2024-07-18-finetuned": 0.0003,
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"gpt-4o-mini-2024-07-18-finetuned-cached": 0.00015,
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# Fine Tuned output
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"babbage-002-finetuned-completion": 0.0016,
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"davinci-002-finetuned-completion": 0.012,
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"gpt-3.5-turbo-0613-finetuned-completion": 0.006,
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"gpt-3.5-turbo-1106-finetuned-completion": 0.006,
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"gpt-3.5-turbo-0125-finetuned-completion": 0.006,
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"gpt-4o-mini-2024-07-18-finetuned-completion": 0.0012,
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# Azure Fine Tuned input
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"babbage-002-azure-finetuned": 0.0004,
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"davinci-002-azure-finetuned": 0.002,
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"gpt-35-turbo-0613-azure-finetuned": 0.0015,
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# Azure Fine Tuned output
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"babbage-002-azure-finetuned-completion": 0.0004,
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"davinci-002-azure-finetuned-completion": 0.002,
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"gpt-35-turbo-0613-azure-finetuned-completion": 0.002,
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# Legacy fine-tuned models
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"ada-finetuned-legacy": 0.0016,
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"babbage-finetuned-legacy": 0.0024,
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"curie-finetuned-legacy": 0.012,
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"davinci-finetuned-legacy": 0.12,
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}
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class TokenType(Enum):
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"""Token type enum."""
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PROMPT = auto()
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PROMPT_CACHED = auto()
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COMPLETION = auto()
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def standardize_model_name(
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model_name: str,
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is_completion: bool = False,
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*,
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token_type: TokenType = TokenType.PROMPT,
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) -> str:
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"""
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Standardize the model name to a format that can be used in the OpenAI API.
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Args:
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model_name: Model name to standardize.
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is_completion: Whether the model is used for completion or not.
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Defaults to False. Deprecated in favor of ``token_type``.
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token_type: Token type. Defaults to ``TokenType.PROMPT``.
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Returns:
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Standardized model name.
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"""
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if is_completion:
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warn_deprecated(
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since="0.3.13",
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message=(
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"is_completion is deprecated. Use token_type instead. Example:\n\n"
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"from langchain_community.callbacks.openai_info import TokenType\n\n"
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"standardize_model_name('gpt-4o', token_type=TokenType.COMPLETION)\n"
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),
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removal="1.0",
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)
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token_type = TokenType.COMPLETION
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model_name = model_name.lower()
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if ".ft-" in model_name:
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model_name = model_name.split(".ft-")[0] + "-azure-finetuned"
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if ":ft-" in model_name:
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model_name = model_name.split(":")[0] + "-finetuned-legacy"
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if "ft:" in model_name:
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model_name = model_name.split(":")[1] + "-finetuned"
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if token_type == TokenType.COMPLETION and (
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model_name.startswith("gpt-4")
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or model_name.startswith("gpt-3.5")
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or model_name.startswith("gpt-35")
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or model_name.startswith("o1-")
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or model_name.startswith("o3-")
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or model_name.startswith("o4-")
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or ("finetuned" in model_name and "legacy" not in model_name)
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):
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return model_name + "-completion"
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if (
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token_type == TokenType.PROMPT_CACHED
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and (
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model_name.startswith("gpt-4o")
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or model_name.startswith("gpt-4.1")
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or model_name.startswith("o1")
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or model_name.startswith("o3")
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or model_name.startswith("o4")
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)
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and not (model_name.startswith("gpt-4o-2024-05-13"))
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):
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return model_name + "-cached"
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else:
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return model_name
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def get_openai_token_cost_for_model(
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model_name: str,
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num_tokens: int,
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is_completion: bool = False,
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*,
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token_type: TokenType = TokenType.PROMPT,
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) -> float:
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"""
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Get the cost in USD for a given model and number of tokens.
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Args:
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model_name: Name of the model
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num_tokens: Number of tokens.
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is_completion: Whether the model is used for completion or not.
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Defaults to False. Deprecated in favor of ``token_type``.
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token_type: Token type. Defaults to ``TokenType.PROMPT``.
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Returns:
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Cost in USD.
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"""
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if is_completion:
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warn_deprecated(
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since="0.3.13",
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message=(
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"is_completion is deprecated. Use token_type instead. Example:\n\n"
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"from langchain_community.callbacks.openai_info import TokenType\n\n"
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"get_openai_token_cost_for_model('gpt-4o', 10, token_type=TokenType.COMPLETION)\n" # noqa: E501
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),
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removal="1.0",
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)
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token_type = TokenType.COMPLETION
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model_name = standardize_model_name(model_name, token_type=token_type)
|
|
if model_name not in MODEL_COST_PER_1K_TOKENS:
|
|
raise ValueError(
|
|
f"Unknown model: {model_name}. Please provide a valid OpenAI model name."
|
|
"Known models are: " + ", ".join(MODEL_COST_PER_1K_TOKENS.keys())
|
|
)
|
|
return MODEL_COST_PER_1K_TOKENS[model_name] * (num_tokens / 1000)
|
|
|
|
|
|
class OpenAICallbackHandler(BaseCallbackHandler):
|
|
"""Callback Handler that tracks OpenAI info."""
|
|
|
|
total_tokens: int = 0
|
|
prompt_tokens: int = 0
|
|
prompt_tokens_cached: int = 0
|
|
completion_tokens: int = 0
|
|
reasoning_tokens: int = 0
|
|
successful_requests: int = 0
|
|
total_cost: float = 0.0
|
|
|
|
def __init__(self) -> None:
|
|
super().__init__()
|
|
self._lock = threading.Lock()
|
|
|
|
def __repr__(self) -> str:
|
|
return (
|
|
f"Tokens Used: {self.total_tokens}\n"
|
|
f"\tPrompt Tokens: {self.prompt_tokens}\n"
|
|
f"\t\tPrompt Tokens Cached: {self.prompt_tokens_cached}\n"
|
|
f"\tCompletion Tokens: {self.completion_tokens}\n"
|
|
f"\t\tReasoning Tokens: {self.reasoning_tokens}\n"
|
|
f"Successful Requests: {self.successful_requests}\n"
|
|
f"Total Cost (USD): ${self.total_cost}"
|
|
)
|
|
|
|
@property
|
|
def always_verbose(self) -> bool:
|
|
"""Whether to call verbose callbacks even if verbose is False."""
|
|
return True
|
|
|
|
def on_llm_start(
|
|
self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
|
|
) -> None:
|
|
"""Print out the prompts."""
|
|
pass
|
|
|
|
def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
|
|
"""Print out the token."""
|
|
pass
|
|
|
|
def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
|
|
"""Collect token usage."""
|
|
# Check for usage_metadata (langchain-core >= 0.2.2)
|
|
try:
|
|
generation = response.generations[0][0]
|
|
except IndexError:
|
|
generation = None
|
|
if isinstance(generation, ChatGeneration):
|
|
try:
|
|
message = generation.message
|
|
if isinstance(message, AIMessage):
|
|
usage_metadata = message.usage_metadata
|
|
response_metadata = message.response_metadata
|
|
else:
|
|
usage_metadata = None
|
|
response_metadata = None
|
|
except AttributeError:
|
|
usage_metadata = None
|
|
response_metadata = None
|
|
else:
|
|
usage_metadata = None
|
|
response_metadata = None
|
|
|
|
prompt_tokens_cached = 0
|
|
reasoning_tokens = 0
|
|
|
|
if usage_metadata:
|
|
token_usage = {"total_tokens": usage_metadata["total_tokens"]}
|
|
completion_tokens = usage_metadata["output_tokens"]
|
|
prompt_tokens = usage_metadata["input_tokens"]
|
|
if response_model_name := (response_metadata or {}).get("model_name"):
|
|
model_name = standardize_model_name(response_model_name)
|
|
elif response.llm_output is None:
|
|
model_name = ""
|
|
else:
|
|
model_name = standardize_model_name(
|
|
response.llm_output.get("model_name", "")
|
|
)
|
|
if "cache_read" in usage_metadata.get("input_token_details", {}):
|
|
prompt_tokens_cached = usage_metadata["input_token_details"][
|
|
"cache_read"
|
|
]
|
|
if "reasoning" in usage_metadata.get("output_token_details", {}):
|
|
reasoning_tokens = usage_metadata["output_token_details"]["reasoning"]
|
|
else:
|
|
if response.llm_output is None:
|
|
return None
|
|
|
|
if "token_usage" not in response.llm_output:
|
|
with self._lock:
|
|
self.successful_requests += 1
|
|
return None
|
|
|
|
# compute tokens and cost for this request
|
|
token_usage = response.llm_output["token_usage"]
|
|
completion_tokens = token_usage.get("completion_tokens", 0)
|
|
prompt_tokens = token_usage.get("prompt_tokens", 0)
|
|
model_name = standardize_model_name(
|
|
response.llm_output.get("model_name", "")
|
|
)
|
|
|
|
if model_name in MODEL_COST_PER_1K_TOKENS:
|
|
uncached_prompt_tokens = prompt_tokens - prompt_tokens_cached
|
|
uncached_prompt_cost = get_openai_token_cost_for_model(
|
|
model_name, uncached_prompt_tokens, token_type=TokenType.PROMPT
|
|
)
|
|
cached_prompt_cost = get_openai_token_cost_for_model(
|
|
model_name, prompt_tokens_cached, token_type=TokenType.PROMPT_CACHED
|
|
)
|
|
prompt_cost = uncached_prompt_cost + cached_prompt_cost
|
|
completion_cost = get_openai_token_cost_for_model(
|
|
model_name, completion_tokens, token_type=TokenType.COMPLETION
|
|
)
|
|
else:
|
|
completion_cost = 0
|
|
prompt_cost = 0
|
|
|
|
# update shared state behind lock
|
|
with self._lock:
|
|
self.total_cost += prompt_cost + completion_cost
|
|
self.total_tokens += token_usage.get("total_tokens", 0)
|
|
self.prompt_tokens += prompt_tokens
|
|
self.prompt_tokens_cached += prompt_tokens_cached
|
|
self.completion_tokens += completion_tokens
|
|
self.reasoning_tokens += reasoning_tokens
|
|
self.successful_requests += 1
|
|
|
|
def __copy__(self) -> "OpenAICallbackHandler":
|
|
"""Return a copy of the callback handler."""
|
|
return self
|
|
|
|
def __deepcopy__(self, memo: Any) -> "OpenAICallbackHandler":
|
|
"""Return a deep copy of the callback handler."""
|
|
return self
|