Bases: OpenAILike
Databricks LLM.
Examples:
pip install llama-index-llms-databricks
from llama_index.llms.databricks import Databricks
# Set up the Databricks class with the required model, API key and serving endpoint
llm = Databricks(model="databricks-dbrx-instruct", api_key="your_api_key", api_base="https://[your-work-space].cloud.databricks.com/serving-endpoints")
# Call the complete method with a query
response = llm.complete("Explain the importance of open source LLMs")
print(response)
Source code in llama_index/llms/databricks/base.py
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57 | class Databricks(OpenAILike):
"""
Databricks LLM.
Examples:
`pip install llama-index-llms-databricks`
```python
from llama_index.llms.databricks import Databricks
# Set up the Databricks class with the required model, API key and serving endpoint
llm = Databricks(model="databricks-dbrx-instruct", api_key="your_api_key", api_base="https://[your-work-space].cloud.databricks.com/serving-endpoints")
# Call the complete method with a query
response = llm.complete("Explain the importance of open source LLMs")
print(response)
```
"""
def __init__(
self,
model: str,
api_key: Optional[str] = None,
api_base: Optional[str] = None,
is_chat_model: bool = True,
**kwargs: Any,
) -> None:
api_key = api_key or os.environ.get("DATABRICKS_TOKEN", None)
api_base = api_base or os.environ.get("DATABRICKS_SERVING_ENDPOINT", None)
super().__init__(
model=model,
api_key=api_key,
api_base=api_base,
is_chat_model=is_chat_model,
**kwargs,
)
@classmethod
def class_name(cls) -> str:
"""Get class name."""
return "Databricks"
def _get_model_kwargs(self, **kwargs: Any) -> Dict[str, Any]:
"""Get the kwargs that need to be provided to the model invocation."""
# Fix the input to work with the Databricks API
if "tool_choice" in kwargs and "tools" not in kwargs:
del kwargs["tool_choice"]
return super()._get_model_kwargs(**kwargs)
|
class_name
classmethod
Get class name.
Source code in llama_index/llms/databricks/base.py
| @classmethod
def class_name(cls) -> str:
"""Get class name."""
return "Databricks"
|