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fix: Fix embedding model listing and usage for watsonx
Signed-off-by: Bill Murdock <bmurdock@redhat.com>
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parent
999c28e809
commit
ecafe40a84
2 changed files with 36 additions and 26 deletions
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@ -56,15 +56,40 @@ class WatsonXInferenceAdapter(LiteLLMOpenAIMixin):
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async def list_models(self) -> list[Model] | None:
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models = []
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for model_spec in self._get_model_specs():
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models.append(
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Model(
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identifier=model_spec["model_id"],
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provider_resource_id=f"{self.__provider_id__}/{model_spec['model_id']}",
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provider_id=self.__provider_id__,
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metadata={},
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model_type=ModelType.llm,
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functions = [f['id'] for f in model_spec.get("functions", [])]
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# Format: {"embedding_dimension": 1536, "context_length": 8192}
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# Example of an embedding model:
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# {'model_id': 'ibm/granite-embedding-278m-multilingual',
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# 'label': 'granite-embedding-278m-multilingual',
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# 'model_limits': {'max_sequence_length': 512, 'embedding_dimension': 768},
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# ...
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if "embedding" in functions:
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embedding_dimension = model_spec["model_limits"]["embedding_dimension"]
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context_length = model_spec["model_limits"]["max_sequence_length"]
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embedding_metadata = {
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"embedding_dimension": embedding_dimension,
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"context_length": context_length,
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}
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models.append(
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Model(
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identifier=model_spec["model_id"],
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provider_resource_id=f"{self.__provider_id__}/{model_spec['model_id']}",
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provider_id=self.__provider_id__,
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metadata=embedding_metadata,
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model_type=ModelType.embedding,
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)
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)
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if "text_chat" in functions:
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models.append(
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Model(
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identifier=model_spec["model_id"],
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provider_resource_id=f"{self.__provider_id__}/{model_spec['model_id']}",
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provider_id=self.__provider_id__,
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metadata={},
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model_type=ModelType.llm,
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)
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)
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)
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return models
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# LiteLLM provides methods to list models for many providers, but not for watsonx.ai.
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@ -91,18 +116,3 @@ class WatsonXInferenceAdapter(LiteLLMOpenAIMixin):
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if "resources" not in response_data:
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raise ValueError("Resources not found in response")
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return response_data["resources"]
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# TO DO: Delete the test main method.
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if __name__ == "__main__":
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config = WatsonXConfig(url="https://us-south.ml.cloud.ibm.com", api_key="xxx", project_id="xxx", timeout=60)
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adapter = WatsonXInferenceAdapter(config)
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model_specs = adapter._get_model_specs()
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models = asyncio.run(adapter.list_models())
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for model in models:
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print(model.identifier)
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print(model.provider_resource_id)
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print(model.provider_id)
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print(model.metadata)
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print(model.model_type)
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print("--------------------------------")
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