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Method ov_token_counter

llmware/models.py:5627–5646  ·  view source on GitHub ↗

Called twice in inference generation loop to get the input_token_count and output_token_count. This step can be skipped by setting the OVConfig as follows: `from llmware.configs import OVConfig OVConfig().set_config("get_token_counts", False)` In our testin

(self, text)

Source from the content-addressed store, hash-verified

5625 return output_response
5626
5627 def ov_token_counter(self, text):
5628
5629 """ Called twice in inference generation loop to get the input_token_count and
5630 output_token_count. This step can be skipped by setting the OVConfig as follows:
5631
5632 `from llmware.configs import OVConfig
5633 OVConfig().set_config("get_token_counts", False)`
5634
5635 In our testing, the performance impact is negligible, but may be different in your
5636 environment and use case.
5637
5638 If this is set to False, then no token counts will be provided in the usage totals.
5639 """
5640
5641 if self.tokenizer:
5642 toks = len(self.tokenizer.encode(text))
5643 else:
5644 toks = 0
5645
5646 return toks
5647
5648 def prompt_engineer(self, query, context, inference_dict):
5649 """ Implemented by openvino_genai module """

Callers 1

streamMethod · 0.95

Calls 1

encodeMethod · 0.80

Tested by

no test coverage detected