diff --git a/docs/docs/examples/llm/predibase.ipynb b/docs/docs/examples/llm/predibase.ipynb
index 26e3cad282bbf0195f27a38ae6968666c2ba555b..9725c27beb1591525b5e2afa404f3aeaaed9c84d 100644
--- a/docs/docs/examples/llm/predibase.ipynb
+++ b/docs/docs/examples/llm/predibase.ipynb
@@ -79,6 +79,7 @@
"# Predibase-hosted fine-tuned adapter example\n",
"llm = PredibaseLLM(\n",
" model_name=\"mistral-7b\",\n",
+ " predibase_sdk_version=None, # optional parameter (defaults to the latest Predibase SDK version if omitted)\n",
" adapter_id=\"e2e_nlg\", # adapter_id is optional\n",
" adapter_version=1, # optional parameter (applies to Predibase only)\n",
" temperature=0.3,\n",
@@ -87,7 +88,7 @@
"# The `model_name` parameter is the Predibase \"serverless\" base_model ID\n",
"# (see https://docs.predibase.com/user-guide/inference/models for the catalog).\n",
"# You can also optionally specify a fine-tuned adapter that's hosted on Predibase or HuggingFace\n",
- "# In the case of Predibase-hosted adapters, you can also specify the adapter_version (assumed latest if omitted)"
+ "# In the case of Predibase-hosted adapters, you must also specify the adapter_version"
]
},
{
@@ -100,6 +101,7 @@
"# HuggingFace-hosted fine-tuned adapter example\n",
"llm = PredibaseLLM(\n",
" model_name=\"mistral-7b\",\n",
+ " predibase_sdk_version=None, # optional parameter (defaults to the latest Predibase SDK version if omitted)\n",
" adapter_id=\"predibase/e2e_nlg\", # adapter_id is optional\n",
" temperature=0.3,\n",
" max_new_tokens=512,\n",
@@ -197,6 +199,7 @@
"# Predibase-hosted fine-tuned adapter\n",
"llm = PredibaseLLM(\n",
" model_name=\"mistral-7b\",\n",
+ " predibase_sdk_version=None, # optional parameter (defaults to the latest Predibase SDK version if omitted)\n",
" adapter_id=\"e2e_nlg\", # adapter_id is optional\n",
" temperature=0.3,\n",
" context_window=1024,\n",
@@ -213,6 +216,7 @@
"# HuggingFace-hosted fine-tuned adapter\n",
"llm = PredibaseLLM(\n",
" model_name=\"mistral-7b\",\n",
+ " predibase_sdk_version=None, # optional parameter (defaults to the latest Predibase SDK version if omitted)\n",
" adapter_id=\"predibase/e2e_nlg\", # adapter_id is optional\n",
" temperature=0.3,\n",
" context_window=1024,\n",
diff --git a/llama-index-integrations/llms/llama-index-llms-predibase/llama_index/llms/predibase/base.py b/llama-index-integrations/llms/llama-index-llms-predibase/llama_index/llms/predibase/base.py
index cfa1dd717e7a39f3f24515972658da0979b8c9e6..8e28e7e5fdd2b86dd0af4ab257de0020a083deef 100644
--- a/llama-index-integrations/llms/llama-index-llms-predibase/llama_index/llms/predibase/base.py
+++ b/llama-index-integrations/llms/llama-index-llms-predibase/llama_index/llms/predibase/base.py
@@ -33,7 +33,7 @@ class PredibaseLLM(CustomLLM):
of a fine-tuned LLM adapter, whose base model is the `model` parameter; the
fine-tuned adapter must be compatible with its base model; otherwise, an
error is raised. If the fine-tuned adapter is hosted at Predibase,
- `adapter_version` can be specified (omitting it gives the latest version).
+ `adapter_version` must be specified.
Examples:
`pip install llama-index-llms-predibase`
@@ -47,6 +47,7 @@ class PredibaseLLM(CustomLLM):
llm = PredibaseLLM(
model_name="mistral-7b",
+ predibase_sdk_version=None, # optional parameter (defaults to the latest Predibase SDK version if omitted)
adapter_id="my-adapter-id", # optional parameter
adapter_version=3, # optional parameter (applies to Predibase only)
temperature=0.3,
@@ -59,6 +60,10 @@ class PredibaseLLM(CustomLLM):
model_name: str = Field(description="The Predibase base model to use.")
predibase_api_key: str = Field(description="The Predibase API key to use.")
+ predibase_sdk_version: str = Field(
+ default=None,
+ description="The optional version (string) of the Predibase SDK (defaults to the latest if not specified).",
+ )
adapter_id: str = Field(
default=None,
description="The optional Predibase ID or HuggingFace ID of a fine-tuned adapter to use.",
@@ -90,6 +95,7 @@ class PredibaseLLM(CustomLLM):
self,
model_name: str,
predibase_api_key: Optional[str] = None,
+ predibase_sdk_version: Optional[str] = None,
adapter_id: Optional[str] = None,
adapter_version: Optional[int] = None,
max_new_tokens: int = DEFAULT_NUM_OUTPUTS,
@@ -111,9 +117,10 @@ class PredibaseLLM(CustomLLM):
super().__init__(
model_name=model_name,
+ predibase_api_key=predibase_api_key,
+ predibase_sdk_version=predibase_sdk_version,
adapter_id=adapter_id,
adapter_version=adapter_version,
- predibase_api_key=predibase_api_key,
max_new_tokens=max_new_tokens,
temperature=temperature,
context_window=context_window,
@@ -125,26 +132,28 @@ class PredibaseLLM(CustomLLM):
output_parser=output_parser,
)
- self._client = self.initialize_client(predibase_api_key)
+ self._client: Union["PredibaseClient", "Predibase"] = self.initialize_client()
- @staticmethod
- def initialize_client(predibase_api_key: str) -> Any:
+ def initialize_client(
+ self,
+ ) -> Union["PredibaseClient", "Predibase"]:
try:
- from predibase import PredibaseClient
- from predibase.pql import get_session
- from predibase.pql.api import Session
-
- session: Session = get_session(
- token=predibase_api_key,
- gateway="https://api.app.predibase.com/v1",
- serving_endpoint="serving.app.predibase.com",
- )
- return PredibaseClient(session=session)
- except ImportError as e:
- raise ImportError(
- "Could not import Predibase Python package. "
- "Please install it with `pip install predibase`."
- ) from e
+ if self._is_deprecated_sdk_version():
+ from predibase import PredibaseClient
+ from predibase.pql import get_session
+ from predibase.pql.api import Session
+
+ session: Session = get_session(
+ token=self.predibase_api_key,
+ gateway="https://api.app.predibase.com/v1",
+ serving_endpoint="serving.app.predibase.com",
+ )
+ return PredibaseClient(session=session)
+
+ from predibase import Predibase
+
+ os.environ["PREDIBASE_GATEWAY"] = "https://api.app.predibase.com"
+ return Predibase(api_token=self.predibase_api_key)
except ValueError as e:
raise ValueError("Your API key is not correct. Please try again") from e
@@ -165,18 +174,6 @@ class PredibaseLLM(CustomLLM):
def complete(
self, prompt: str, formatted: bool = False, **kwargs: Any
) -> "CompletionResponse":
- from predibase.pql.api import ServerResponseError
- from predibase.resource.llm.interface import (
- HuggingFaceLLM,
- LLMDeployment,
- )
- from predibase.resource.llm.response import GeneratedResponse
- from predibase.resource.model import Model
-
- base_llm_deployment: LLMDeployment = self._client.LLM(
- uri=f"pb://deployments/{self.model_name}"
- )
-
options: Dict[str, Union[str, float]] = copy.deepcopy(kwargs)
options.update(
{
@@ -185,36 +182,133 @@ class PredibaseLLM(CustomLLM):
}
)
- result: GeneratedResponse
- if self.adapter_id:
- """
- Attempt to retrieve the fine-tuned adapter from a Predibase repository.
- If absent, then load the fine-tuned adapter from a HuggingFace repository.
- """
- adapter_model: Union[Model, HuggingFaceLLM]
- try:
- adapter_model = self._client.get_model(
- name=self.adapter_id,
- version=self.adapter_version,
- model_id=None,
- )
- except ServerResponseError:
- # Predibase does not recognize the adapter ID (query HuggingFace).
- adapter_model = self._client.LLM(uri=f"hf://{self.adapter_id}")
- result = base_llm_deployment.with_adapter(model=adapter_model).generate(
- prompt=prompt,
- options=options,
+ response_text: str
+
+ if self._is_deprecated_sdk_version():
+ from predibase.pql.api import ServerResponseError
+ from predibase.resource.llm.interface import (
+ HuggingFaceLLM,
+ LLMDeployment,
+ )
+ from predibase.resource.llm.response import GeneratedResponse
+ from predibase.resource.model import Model
+
+ base_llm_deployment: LLMDeployment = self._client.LLM(
+ uri=f"pb://deployments/{self.model_name}"
)
+
+ result: GeneratedResponse
+ if self.adapter_id:
+ """
+ Attempt to retrieve the fine-tuned adapter from a Predibase repository.
+ If absent, then load the fine-tuned adapter from a HuggingFace repository.
+ """
+ adapter_model: Union[Model, HuggingFaceLLM]
+ try:
+ adapter_model = self._client.get_model(
+ name=self.adapter_id,
+ version=self.adapter_version,
+ model_id=None,
+ )
+ except ServerResponseError:
+ # Predibase does not recognize the adapter ID (query HuggingFace).
+ adapter_model = self._client.LLM(uri=f"hf://{self.adapter_id}")
+ result = base_llm_deployment.with_adapter(model=adapter_model).generate(
+ prompt=prompt,
+ options=options,
+ )
+ else:
+ result = base_llm_deployment.generate(
+ prompt=prompt,
+ options=options,
+ )
+ response_text = result.response
else:
- result = base_llm_deployment.generate(
- prompt=prompt,
- options=options,
+ import requests
+ from lorax.client import Client as LoraxClient
+ from lorax.errors import GenerationError
+ from lorax.types import Response
+
+ lorax_client: LoraxClient = self._client.deployments.client(
+ deployment_ref=self.model_name
)
- return CompletionResponse(text=result.response)
+ response: Response
+ if self.adapter_id:
+ """
+ Attempt to retrieve the fine-tuned adapter from a Predibase repository.
+ If absent, then load the fine-tuned adapter from a HuggingFace repository.
+ """
+ if self.adapter_version:
+ # Since the adapter version is provided, query the Predibase repository.
+ pb_adapter_id: str = f"{self.adapter_id}/{self.adapter_version}"
+ try:
+ response = lorax_client.generate(
+ prompt=prompt,
+ adapter_id=pb_adapter_id,
+ **options,
+ )
+ except GenerationError as ge:
+ raise ValueError(
+ f'An adapter with the ID "{pb_adapter_id}" cannot be found in the Predibase repository of fine-tuned adapters.'
+ ) from ge
+ else:
+ # The adapter version is omitted, hence look for the adapter ID in the HuggingFace repository.
+ try:
+ response = lorax_client.generate(
+ prompt=prompt,
+ adapter_id=self.adapter_id,
+ adapter_source="hub",
+ **options,
+ )
+ except GenerationError as ge:
+ raise ValueError(
+ f"""Either an adapter with the ID "{self.adapter_id}" cannot be found in a HuggingFace repository, \
+or it is incompatible with the base model (please make sure that the adapter configuration is consistent).
+"""
+ ) from ge
+ else:
+ try:
+ response = lorax_client.generate(
+ prompt=prompt,
+ **options,
+ )
+ except requests.JSONDecodeError as jde:
+ raise ValueError(
+ f"""An LLM with the deployment ID "{self.model_name}" cannot be found at Predibase \
+(please refer to "https://docs.predibase.com/user-guide/inference/models" for the list of supported models).
+"""
+ ) from jde
+ response_text = response.generated_text
+
+ return CompletionResponse(text=response_text)
@llm_completion_callback()
def stream_complete(
self, prompt: str, formatted: bool = False, **kwargs: Any
) -> "CompletionResponseGen":
raise NotImplementedError
+
+ def _is_deprecated_sdk_version(self) -> bool:
+ try:
+ import semantic_version
+ from semantic_version.base import Version
+
+ from predibase.version import __version__ as current_version
+
+ sdk_semver_deprecated: Version = semantic_version.Version(
+ version_string="2024.4.8"
+ )
+ actual_current_version: str = self.predibase_sdk_version or current_version
+ sdk_semver_current: Version = semantic_version.Version(
+ version_string=actual_current_version
+ )
+ return not (
+ (sdk_semver_current > sdk_semver_deprecated)
+ or ("+dev" in actual_current_version)
+ )
+ except ImportError as e:
+ raise ImportError(
+ "Could not import Predibase Python package. "
+ "Please install it with `pip install semantic_version predibase`."
+ ) from e
diff --git a/llama-index-integrations/llms/llama-index-llms-predibase/pyproject.toml b/llama-index-integrations/llms/llama-index-llms-predibase/pyproject.toml
index 3cda9f5e11e11a273578ccb54c0811f8b23548ad..7855014ada3a0c32aa890994a443a95bd65a4b3d 100644
--- a/llama-index-integrations/llms/llama-index-llms-predibase/pyproject.toml
+++ b/llama-index-integrations/llms/llama-index-llms-predibase/pyproject.toml
@@ -27,7 +27,7 @@ exclude = ["**/BUILD"]
license = "MIT"
name = "llama-index-llms-predibase"
readme = "README.md"
-version = "0.1.4"
+version = "0.1.5"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"