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feat: log the count of consumed prompt and completion tokens consumed #22

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Aug 16, 2023
Merged

feat: log the count of consumed prompt and completion tokens consumed #22

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27 changes: 25 additions & 2 deletions textbook/dataset_gen/dataset_gen.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import threading
from concurrent.futures import ThreadPoolExecutor
import json
import os
Expand All @@ -14,9 +15,14 @@
from rich.progress import (
Progress,
TimeElapsedColumn,
TextColumn,
)
import hashlib

THREAD_LOCK = threading.Lock()
PROMPT_TOKENS_CNT = 0
COMPLETION_TOKENS_CNT = 0


class Exercise(BaseModel):
problem: str
Expand Down Expand Up @@ -78,12 +84,17 @@ def __init__(
self.model = model

def generate(self, prompt: str) -> Result:
global PROMPT_TOKENS_CNT
global COMPLETION_TOKENS_CNT
chat_completion = openai.ChatCompletion.create(
model=self.model,
messages=[{"role": "user", "content": prompt}],
max_tokens=250,
timeout=60,
)
with THREAD_LOCK:
PROMPT_TOKENS_CNT += chat_completion.usage.prompt_tokens
COMPLETION_TOKENS_CNT += chat_completion.usage.completion_tokens
result = Result(
prompt=prompt, output=chat_completion.choices[0].message.content
)
Expand Down Expand Up @@ -190,12 +201,24 @@ def mass_generation(
*Progress.get_default_columns(),
"•",
TimeElapsedColumn(),
TextColumn("completion: [bold green]{task.fields[completion_tokens]}"),
TextColumn("prompt: [bold green]{task.fields[prompt_tokens]}"),
) as progress:
with ThreadPoolExecutor(max_workers=pool_size) as executor:
progress_task = progress.add_task("[red]Generating...", total=len(prompts))
progress_task = progress.add_task(
"[red]Generating...",
total=len(prompts),
completion_tokens=0,
prompt_tokens=0,
)

def update_progress():
progress.update(progress_task, advance=1)
progress.update(
progress_task,
advance=1,
completion_tokens=COMPLETION_TOKENS_CNT,
prompt_tokens=PROMPT_TOKENS_CNT,
)

tasks = []

Expand Down
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