Files
tabbyAPI/common/gen_logging.py
2026-03-27 21:47:24 +01:00

106 lines
3.1 KiB
Python

"""
Functions for logging generation events.
"""
from common.logger import xlogger
from typing import Optional
from common.tabby_config import config
def broadcast_status():
"""Broadcasts the current logging status"""
enabled = []
if config.logging.log_prompt:
enabled.append("prompts")
if config.logging.log_generation_params:
enabled.append("generation params")
if len(enabled) > 0:
xlogger.info("Generation logging is enabled for: " + ", ".join(enabled))
else:
xlogger.info("Generation logging is disabled")
def log_generation_params(**kwargs):
"""Logs generation parameters to console."""
if config.logging.log_generation_params:
xlogger.info("Generation options:", kwargs, details=f"{kwargs}\n")
def log_prompt(prompt: str, request_id: str, negative_prompt: Optional[str] = None):
"""Logs the prompt to console."""
if config.logging.log_prompt:
xlogger.info(
f"Raw prompt (ID: {request_id}):",
{"prompt": prompt},
details=f"\n{prompt if prompt else 'Empty'}\n",
)
if negative_prompt:
xlogger.info(
"Negative Prompt:",
{"negative_prompt": negative_prompt},
details=f"\n{negative_prompt}\n",
)
def log_response(request_id: str, response: str):
"""Logs the response to console."""
if config.logging.log_prompt:
xlogger.info(
f"Response (ID: {request_id}):",
{"response": response},
details=f"\n{response if response else 'Empty'}\n",
)
def log_metrics(
request_id: str,
metrics: dict,
context_len: Optional[int],
max_seq_len: int,
):
initial_response = (
f"Metrics (ID: {request_id}): {metrics.get('gen_tokens')} "
f"tokens generated in {metrics.get('total_time')} seconds"
)
itemization = []
extra_parts = []
itemization.append(f"Queue: {metrics.get('queue_time')} s")
cached_tokens = metrics.get("cached_tokens")
prompt_tokens = metrics.get("prompt_tokens")
itemization.append(
f"Process: {cached_tokens} cached tokens and "
f"{prompt_tokens - cached_tokens} new tokens at "
f"{metrics.get('prompt_tokens_per_sec')} T/s"
)
itemization.append(f"Generate: {metrics.get('gen_tokens_per_sec')} T/s")
# Add context (original token count)
if context_len:
itemization.append(f"Context: {context_len} tokens")
if context_len > max_seq_len:
extra_parts.append("<-- Not accurate (truncated)")
# Print output
xlogger.info(
initial_response,
{
"new_tokens": prompt_tokens - cached_tokens,
"cached_tokens": cached_tokens,
"prompt_tokens": prompt_tokens,
"prompt_tokens_per_second": metrics.get("prompt_tokens_per_sec"),
"gen_tokens_per_second": metrics.get("gen_tokens_per_sec"),
"context_len": context_len,
"max_seq_len": max_seq_len,
},
details="(" + ", ".join(itemization) + ") " + " ".join(extra_parts),
)