I'm trying to use claude-sonnet-4-20250514 with the following settings in call_llm.py
...
response = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=16000,
thinking={
"type": "enabled",
"budget_tokens": 10000
},
messages=[
{"role": "user", "content": prompt}
]
)
...
after a bit of "Identifying abstractions using LLM..."
I get a exception stack dump with the following error:
anthropic.BadRequestError: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'prompt is too long: 211230 tokens > 200000 maximum'}}
211,230 tokens seems like alot... I don't think I understand how the max_tokens in the settings are being used in the prompt composing.
Can anyone help me understand what parameters I need to tweak to get it to process a repo. I'm not working a huge repo (just under 500 files fetched)
This is how I'm running the pipeline.
python main.py --dir /tmp/test-repo --include "*.java" "*.kt" --exclude ".github/*" -s 50000
Thanks in advance.
I'm trying to use
claude-sonnet-4-20250514with the following settings incall_llm.pyafter a bit of "Identifying abstractions using LLM..."
I get a exception stack dump with the following error:
211,230 tokens seems like alot... I don't think I understand how the max_tokens in the settings are being used in the prompt composing.
Can anyone help me understand what parameters I need to tweak to get it to process a repo. I'm not working a huge repo (just under 500 files fetched)
This is how I'm running the pipeline.
Thanks in advance.