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Implement logging strategy (#444)

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* Logging strategy and convert all prints() to logging invocations
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cybermaggedon 2025-07-30 23:18:38 +01:00 • committed by GitHub
parent 3e0651222b
commit dd70aade11
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117 changed files with 1216 additions and 667 deletions
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14
trustgraph-flow/trustgraph/model/text_completion/claude/llm.py
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@ -6,10 +6,14 @@ Input is prompt, output is response.
import anthropic
import os
import logging
from .... exceptions import TooManyRequests
from .... base import LlmService, LlmResult
# Module logger
logger = logging.getLogger(__name__)
default_ident = "text-completion"
default_model = 'claude-3-5-sonnet-20240620'
@ -42,7 +46,7 @@ class Processor(LlmService):
self.temperature = temperature
self.max_output = max_output
print("Initialised", flush=True)
logger.info("Claude LLM service initialized")
async def generate_content(self, system, prompt):
@ -69,9 +73,9 @@ class Processor(LlmService):
resp = response.content[0].text
inputtokens = response.usage.input_tokens
outputtokens = response.usage.output_tokens
print(resp, flush=True)
print(f"Input Tokens: {inputtokens}", flush=True)
print(f"Output Tokens: {outputtokens}", flush=True)
logger.debug(f"LLM response: {resp}")
logger.info(f"Input Tokens: {inputtokens}")
logger.info(f"Output Tokens: {outputtokens}")
resp = LlmResult(
text = resp,
@ -91,7 +95,7 @@ class Processor(LlmService):
# Apart from rate limits, treat all exceptions as unrecoverable
print(f"Exception: {e}")
logger.error(f"Claude LLM exception ({type(e).__name__}): {e}", exc_info=True)
raise e
@staticmethod