remove conversational from hf

Author: czaloom

.gitignore

@@ -19,7 +19,7 @@ bin
 *.swp
 *.swo
 *~
-.env
+.env*
 
 # Python dev
 .mypy_cache

runtimes/huggingface/mlserver_huggingface/codecs/__init__.py

@@ -3,7 +3,6 @@
 from .json import HuggingfaceSingleJSONCodec
 from .jsonlist import HuggingfaceListJSONCodec
 from .numpylist import NumpyListCodec
-from .conversation import HuggingfaceConversationCodec
 from .raw import RawCodec
 from .utils import EqualUtil
 from .chariot import ChariotImgModelOutputCodec
@@ -14,7 +13,6 @@
     "PILImageCodec",
     "HuggingfaceSingleJSONCodec",
     "HuggingfaceListJSONCodec",
-    "HuggingfaceConversationCodec",
     "ChariotImgModelOutputCodec",
     "NumpyListCodec",
     "RawCodec",

runtimes/huggingface/mlserver_huggingface/codecs/base.py

@@ -25,7 +25,6 @@
 from .image import PILImageCodec
 from .json import HuggingfaceSingleJSONCodec
 from .jsonlist import HuggingfaceListJSONCodec
-from .conversation import HuggingfaceConversationCodec
 from .numpylist import NumpyListCodec
 from .raw import RawCodec
 
@@ -207,7 +206,6 @@ class HuggingfaceRequestCodec(MultiInputRequestCodec):
         PILImageCodec,
         HuggingfaceSingleJSONCodec,
         HuggingfaceListJSONCodec,
-        HuggingfaceConversationCodec,
         NumpyListCodec,
         RawCodec,
     ]

runtimes/huggingface/mlserver_huggingface/codecs/conversation.py

@@ -4,7 +4,6 @@
 import base64
 import numpy as np
 from PIL import Image, ImageChops
-from transformers.pipelines import Conversation
 
 IMAGE_PREFIX = "data:image/"
 DEFAULT_IMAGE_FORMAT = "PNG"
@@ -29,13 +28,6 @@ def default(self, obj):
                 + ";base64,"
                 + base64.b64encode(buf.getvalue()).decode()
             )
-        elif isinstance(obj, Conversation):
-            return {
-                "uuid": str(obj.uuid),
-                "past_user_inputs": obj.past_user_inputs,
-                "generated_responses": obj.generated_responses,
-                "new_user_input": obj.new_user_input,
-            }
         else:
             return json.JSONEncoder.default(self, obj)
 
@@ -69,29 +61,12 @@ def do(cls, raw):
         else:
             return raw
 
-    @classmethod
-    def convert_conversation(cls, d: Dict[str, Any]):
-        if set(d.keys()) == conversation_keys:
-            return Conversation(
-                text=d["new_user_input"],
-                conversation_id=d["uuid"],
-                past_user_inputs=d["past_user_inputs"],
-                generated_responses=d["generated_responses"],
-            )
-        return None
-
     @classmethod
     def convert_dict(cls, d: Dict[str, Any]):
-        conversation = cls.convert_conversation(d)
-        if conversation is not None:
-            return conversation
         tmp = {}
         for k, v in d.items():
             if isinstance(v, dict):
-                if set(v.keys()) == conversation_keys:
-                    tmp[k] = Conversation(text=v["new_user_input"])
-                else:
-                    tmp[k] = cls.convert_dict(v)
+                tmp[k] = cls.convert_dict(v)
             elif isinstance(v, list):
                 tmp[k] = cls.convert_list(v)
             elif isinstance(v, str):

runtimes/huggingface/mlserver_huggingface/codecs/utils.py

@@ -200,12 +200,20 @@
     ),
     "text-generation": dict(
         inputs=[
+            # string input
             MetadataTensor(
                 name="array_inputs",
                 shape=[-1],
                 datatype="BYTES",
                 parameters=dict(content_type="str"),
             ),
+            # list of dict inputs
+            MetadataTensor(
+                name="array_inputs",
+                shape=[-1],
+                datatype="BYTES",
+                parameters=dict(content_type="hg_jsonlist"),
+            ),
         ],
         outputs=[],
     ),
@@ -258,17 +266,6 @@
         ],
         outputs=[],
     ),
-    "conversational": dict(
-        inputs=[
-            MetadataTensor(
-                name="array_inputs",
-                shape=[-1],
-                datatype="FP32",
-                parameters=dict(content_type="hg_conversation"),
-            ),
-        ],
-        outputs=[],
-    ),
     "image-classification": dict(
         inputs=[
             # file path inputs

runtimes/huggingface/mlserver_huggingface/metadata.py

@@ -1 +1 @@
-__version__ = "2.0.12"
+__version__ = "2.0.14"

runtimes/huggingface/mlserver_huggingface/version.py

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "mlserver-huggingface"
-version = "2.0.12"
+version = "2.0.14"
 description = "HuggingFace runtime for MLServer"
 authors = ["Seldon Technologies Ltd. <hello@seldon.io>"]
 license = "Apache-2.0"