Merge pull request #26 from opendatahub-io/sync-with-upstream @ v0.4.15

sync with upstream @ v0.4.15

caikit_nlp/modules/text_embedding/embedding.py

@@ -15,7 +15,7 @@
 # Standard
 from collections.abc import Sized
 from enum import Enum, auto
-from typing import Callable, Dict, List, NamedTuple, Optional, TypeVar, Union
+from typing import Any, Callable, Dict, List, NamedTuple, Optional, TypeVar, Union
 import importlib
 import os
 import time
@@ -178,6 +178,20 @@ def load(cls, model_path: str, *args, **kwargs) -> "EmbeddingModule":
 
         return cls(model)
 
+    @property
+    def public_model_info(cls) -> Dict[str, Any]:  # pylint: disable=no-self-argument
+        """Helper property to return public metadata about a specific Model. This
+        function is separate from `metdata` as that contains the entire ModelConfig
+        which might not want to be shared/exposed.
+
+        Returns:
+            Dict[str, str]: A dictionary of this models's public metadata
+        """
+        return {
+            "max_seq_length": cls.model.max_seq_length,
+            "sentence_embedding_dimension": cls.model.get_sentence_embedding_dimension(),
+        }
+
     @classmethod
     def _get_ipex(cls, ipex_flag):
         """Get IPEX optimization library if enabled and available, else return False

caikit_nlp/modules/text_generation/peft_tgis_remote.py

@@ -14,7 +14,9 @@
 """This file contains a distributed backend implementation for leveraging the PEFT-trained
 prompt vectors in TGIS generation requests.
 """
+
 # Standard
+from functools import cached_property
 from typing import Iterable, List, Optional, Tuple, Union
 import os
 
@@ -32,6 +34,7 @@
     TokenizationResults,
 )
 from caikit.interfaces.nlp.tasks import TextGenerationTask, TokenizationTask
+from caikit.interfaces.runtime.data_model import RuntimeServerContextType
 from caikit_tgis_backend import TGISBackend
 import alog
 
@@ -68,15 +71,14 @@ def __init__(
         prompt_artifacts: Optional[List[str]] = None,
     ) -> None:
         super().__init__()
-        # Configure the internal client
-        # NOTE: This is made optional for the cases where we do not need to execute `.run` function
-        # for example, bootstrapping a model to caikit format and saving.
-        self._client = None
+
         self._tgis_backend = tgis_backend
         if enable_backend:
+            error.type_check(
+                "<NLP33971947E>", TGISBackend, tgis_backend=self._tgis_backend
+            )
             # get_client will also launch a local TGIS process and get the model
             # loaded when using the local TGIS backend
-            self._client = tgis_backend.get_client(base_model_name)
 
             # Tell the backend to load all of the available prompt files
             if prompt_artifacts:
@@ -107,6 +109,14 @@ def __del__(self):
             if tgis_backend and prompt_cache_id and model_id:
                 tgis_backend.unload_prompt_artifacts(model_id, prompt_cache_id)
 
+    @cached_property
+    def _client(self):
+        # Configure the internal client
+        # NOTE: This is made optional for the cases where we do not need to execute `.run` function
+        # for example, bootstrapping a model to caikit format and saving.
+        if self._tgis_backend:
+            return self._tgis_backend.get_client(self.base_model_name)
+
     @classmethod
     def load(cls, model_path: str, load_backend: BackendBase) -> "PeftPromptTuningTGIS":
         """Load a TGIS Peft Prompt Tuning distributed module. Note that we do not
@@ -182,7 +192,7 @@ def save(self, model_path: str):
             )
 
     # pylint: disable=duplicate-code
-    @TextGenerationTask.taskmethod()
+    @TextGenerationTask.taskmethod(context_arg="context")
     def run(
         self,
         text: str,
@@ -206,6 +216,7 @@ def run(
         generated_tokens: bool = True,
         token_logprobs: bool = True,
         token_ranks: bool = True,
+        context: Optional[RuntimeServerContextType] = None,
     ) -> GeneratedTextResult:
         f"""Run inference against the model running in TGIS.
 
@@ -221,6 +232,8 @@ def run(
             self.enable_backend,
             "Backend must be configured and loaded with this module before executing `run` call.",
         )
+        self._register_model_connection_with_context(context)
+
         verbalized_text = render_verbalizer(self.verbalizer, {"input": text})
         return self.tgis_generation_client.unary_generate(
             text=verbalized_text,
@@ -244,7 +257,7 @@ def run(
             stop_sequences=stop_sequences,
         )
 
-    @TextGenerationTask.taskmethod(output_streaming=True)
+    @TextGenerationTask.taskmethod(output_streaming=True, context_arg="context")
     def run_stream_out(
         self,
         text: str,
@@ -268,6 +281,7 @@ def run_stream_out(
         generated_tokens: bool = True,
         token_logprobs: bool = True,
         token_ranks: bool = True,
+        context: Optional[RuntimeServerContextType] = None,
     ) -> Iterable[GeneratedTextStreamResult]:
         f"""Run output stream inferencing against the model running in TGIS
 
@@ -283,6 +297,9 @@ def run_stream_out(
             "Backend must be configured and loaded with this module \
             before executing `run_stream_out` call.",
         )
+
+        self._register_model_connection_with_context(context)
+
         verbalized_text = render_verbalizer(self.verbalizer, {"input": text})
         return self.tgis_generation_client.stream_generate(
             text=verbalized_text,
@@ -306,10 +323,11 @@ def run_stream_out(
             stop_sequences=stop_sequences,
         )
 
-    @TokenizationTask.taskmethod()
+    @TokenizationTask.taskmethod(context_arg="context")
     def run_tokenizer(
         self,
         text: str,
+        context: Optional[RuntimeServerContextType] = None,
     ) -> TokenizationResults:
         """Run tokenization task against the model running in TGIS.
 
@@ -320,6 +338,20 @@ def run_tokenizer(
             TokenizationResults
                 The token count
         """
+
+        self._register_model_connection_with_context(context)
+
         return self.tgis_generation_client.unary_tokenize(
             text=text,
         )
+
+    def _register_model_connection_with_context(
+        self, context: Optional[RuntimeServerContextType]
+    ):
+        """
+        Register a remote model connection with the configured TGISBackend if there is
+        a context override provided.
+        """
+        if self._tgis_backend:
+            self._tgis_backend.handle_runtime_context(self.base_model_name, context)
+            self._model_loaded = True

caikit_nlp/modules/text_generation/text_generation_tgis.py

@@ -14,6 +14,7 @@
 
 
 # Standard
+from functools import cached_property
 from typing import Iterable, List, Optional, Tuple, Union
 import os
 
@@ -30,6 +31,7 @@
     TokenizationResults,
 )
 from caikit.interfaces.nlp.tasks import TextGenerationTask, TokenizationTask
+from caikit.interfaces.runtime.data_model import RuntimeServerContextType
 from caikit_tgis_backend import TGISBackend
 import alog
 
@@ -86,28 +88,33 @@ def __init__(
         # Set _model_loaded as False by default. This will only get set to True if
         # we enable the tgis_backend and we are able to fetch the client successfully.
         self._model_loaded = False
-        # Configure the internal client
-        # NOTE: This is made optional for the cases where we do not need to execute `.run` function
-        # for example, bootstrapping a model to caikit format and saving.
-        self._client = None
         if tgis_backend:
-            self._client = tgis_backend.get_client(model_name)
-            # mark that the model is loaded so that we can unload it later
-            self._model_loaded = True
             self.tgis_backend = tgis_backend
 
+        self._tgis_backend = tgis_backend
         self._bos_token = bos_token
         self._sep_token = sep_token
         self._eos_token = eos_token
         self._pad_token = pad_token
-        self.tgis_generation_client = TGISGenerationClient(
-            self.model_name, self._eos_token, self._client, self.PRODUCER_ID
-        )
 
     def __del__(self):
         # nothing to unload if we didn't finish loading
-        if self._model_loaded and self.tgis_backend:
-            self.tgis_backend.unload_model(self.model_name)
+        if self._model_loaded and self._tgis_backend:
+            self._tgis_backend.unload_model(self.model_name)
+
+    @cached_property
+    def _client(self):
+        # Lazily configure/create the internal tgis backend client
+        if self._tgis_backend:
+            return self._tgis_backend.get_client(self.model_name)
+
+    @cached_property
+    def tgis_generation_client(self):
+        # Lazily create the generation client
+        # This in turn calls self._client which also lazily gets the tgis backend client
+        return TGISGenerationClient(
+            self.model_name, self._eos_token, self._client, self.PRODUCER_ID
+        )
 
     @classmethod
     def bootstrap(cls, model_path: str, load_backend: Union[BackendBase, None] = None):
@@ -207,7 +214,7 @@ def save(self, model_path: str):
             )
 
     # pylint: disable=duplicate-code
-    @TextGenerationTask.taskmethod()
+    @TextGenerationTask.taskmethod(context_arg="context")
     def run(
         self,
         text: str,
@@ -231,6 +238,7 @@ def run(
         generated_tokens: bool = True,
         token_logprobs: bool = True,
         token_ranks: bool = True,
+        context: Optional[RuntimeServerContextType] = None,
     ) -> GeneratedTextResult:
         f"""Run inference against the model running in TGIS.
 
@@ -240,6 +248,8 @@ def run(
             GeneratedTextResult
                 Generated text result produced by TGIS.
         """
+        self._register_model_connection_with_context(context)
+
         if self._model_loaded:
             return self.tgis_generation_client.unary_generate(
                 text=text,
@@ -263,7 +273,7 @@ def run(
                 stop_sequences=stop_sequences,
             )
 
-    @TextGenerationTask.taskmethod(output_streaming=True)
+    @TextGenerationTask.taskmethod(output_streaming=True, context_arg="context")
     def run_stream_out(
         self,
         text: str,
@@ -287,6 +297,7 @@ def run_stream_out(
         generated_tokens: bool = True,
         token_logprobs: bool = True,
         token_ranks: bool = True,
+        context: Optional[RuntimeServerContextType] = None,
     ) -> Iterable[GeneratedTextStreamResult]:
         f"""Run output stream inferencing for text generation module.
 
@@ -295,6 +306,7 @@ def run_stream_out(
         Returns:
             Iterable[GeneratedTextStreamResult]
         """
+        self._register_model_connection_with_context(context)
 
         if self._model_loaded:
             return self.tgis_generation_client.stream_generate(
@@ -319,10 +331,11 @@ def run_stream_out(
                 stop_sequences=stop_sequences,
             )
 
-    @TokenizationTask.taskmethod()
+    @TokenizationTask.taskmethod(context_arg="context")
     def run_tokenizer(
         self,
         text: str,
+        context: Optional[RuntimeServerContextType] = None,
     ) -> TokenizationResults:
         """Run tokenization task against the model running in TGIS.
 
@@ -333,7 +346,20 @@ def run_tokenizer(
             TokenizationResults
                 The token count
         """
+        self._register_model_connection_with_context(context)
+
         if self._model_loaded:
             return self.tgis_generation_client.unary_tokenize(
                 text=text,
             )
+
+    def _register_model_connection_with_context(
+        self, context: Optional[RuntimeServerContextType]
+    ):
+        """
+        Register a remote model connection with the configured TGISBackend if there is
+        a context override provided.
+        """
+        if self._tgis_backend:
+            self._tgis_backend.handle_runtime_context(self.model_name, context)
+            self._model_loaded = True

caikit_nlp/toolkit/text_generation/tgis_utils.py

@@ -11,8 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""This file is for helper functions related to TGIS.
-"""
+"""This file is for helper functions related to TGIS."""
+
 # Standard
 from typing import Iterable
 
@@ -33,6 +33,7 @@
     TokenizationResults,
     TokenStreamDetails,
 )
+from caikit_tgis_backend import TGISBackend
 from caikit_tgis_backend.protobufs import generation_pb2
 import alog
 
@@ -84,6 +85,11 @@
     grpc.StatusCode.UNAUTHENTICATED: CaikitCoreStatusCode.UNAUTHORIZED,
 }
 
+# HTTP Header / gRPC Metadata key used to identify a route override
+# (forwarded for API compatibility)
+ROUTE_INFO_HEADER_KEY = TGISBackend.ROUTE_INFO_HEADER_KEY
+get_route_info = TGISBackend.get_route_info
+
 
 def raise_caikit_core_exception(rpc_error: grpc.RpcError):
     """Helper to wrap logic of converting from grpc.RpcError ->
@@ -329,6 +335,21 @@ def __init__(
 
         self.tgis_req_timeout = get_config().tgis_request_timeout
 
+        if (
+            not self.tgis_req_timeout
+            or not isinstance(self.tgis_req_timeout, int)
+            or self.tgis_req_timeout <= 0
+        ):
+            log.debug("<RUN57106697I>", "TGIS timeout not set")
+            self.tgis_req_timeout = None
+
+        else:
+            log.debug(
+                "<RUN57106696T>",
+                "Setting TGIS timeout value to  %d",
+                self.tgis_req_timeout,
+            )
+
     def unary_generate(
         self,
         text,

pyproject.toml

@@ -14,8 +14,8 @@ classifiers=[
     "License :: OSI Approved :: Apache Software License"
 ]
 dependencies = [
-    "caikit[runtime-grpc,runtime-http]>=0.26.17,<0.27.0",
-    "caikit-tgis-backend>=0.1.27,<0.2.0",
+    "caikit[runtime-grpc,runtime-http]>=0.26.34,<0.27.0",
+    "caikit-tgis-backend>=0.1.34,<0.2.0",
     # TODO: loosen dependencies
     "grpcio>=1.62.2", # explicitly pin grpc dependencies to a recent version to avoid pip backtracking
     "grpcio-reflection>=1.62.2",