[fix] Replace default generic model parser names with hardcoded defaults

Right now we get errors if trying to use aliasing in AIConfig for model parsers, so we need to use an actual model instead. For now just doing this so we can use these aliases like 'Image2Text' when we share demo to Gradio

cookbooks/Gradio/huggingface.aiconfig.json

@@ -4,17 +4,23 @@
   "metadata": {
     "parameters": {},
     "models": {
-      "TextGeneration": {
-        "model": "stevhliu/my_awesome_billsum_model",
-        "min_length": 10,
-        "max_length": 30
+      "AudioSpeechRecognition": {
+        "model": "openai/whisper-small"
       },
-      "ImageToText": {
+      "Image2Text": {
         "model": "Salesforce/blip-image-captioning-base"
       },
       "Text2Speech": {
         "model": "suno/bark"
       },
+      "Text2Image": {
+        "model": "runwayml/stable-diffusion-v1-5"
+      },
+      "TextGeneration": {
+        "model": "stevhliu/my_awesome_billsum_model",
+        "min_length": 10,
+        "max_length": 30
+      },
       "TextSummarization": {
         "model": "facebook/bart-large-cnn"
       },
@@ -24,16 +30,13 @@
     },
     "default_model": "TextGeneration",
     "model_parsers": {
+      "AudioSpeechRecognition": "HuggingFaceAutomaticSpeechRecognitionTransformer",
       "Image2Text": "HuggingFaceImage2TextTransformer",
-      "Salesforce/blip-image-captioning-base": "HuggingFaceImage2TextTransformer",
       "Text2Speech": "HuggingFaceText2SpeechTransformer",
-      "suno/bark": "HuggingFaceText2SpeechTransformer",
+      "Text2Image": "HuggingFaceText2ImageTransformer",
       "TextGeneration": "HuggingFaceTextGenerationTransformer",
-      // "stevhliu/my_awesome_billsum_model": "HuggingFaceTextGenerationTransformer",
       "TextSummarization": "HuggingFaceTextSummarizationTransformer",
-      "facebook/bart-large-cnn": "HuggingFaceTextSummarizationTransformer",
-      "TextTranslation": "HuggingFaceTextTranslationTransformer",
-      "translation_en_to_fr": "HuggingFaceTextTranslationTransformer"
+      "TextTranslation": "HuggingFaceTextTranslationTransformer"
     }
   },
   "description": "The Tale of the Quick Brown Fox",
@@ -52,22 +55,14 @@
         "parameters": {
           "city": "New York"
         }
-      },
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "execution_count": 0,
-          "data": "<pad> a sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden sudden",
-          "metadata": {}
-        }
-      ]
+      }
     },
     {
       "name": "translate_instruction",
       "input": "Tell the tale of {{topic}}",
       "metadata": {
         "model": {
-          "name": "TextGeneration",
+          "name": "TextTranslation",
           "settings": {
             "min_length": "",
             "max_new_tokens": 100
@@ -76,8 +71,7 @@
         "parameters": {
           "topic": "the quick brown fox"
         }
-      },
-      "outputs": []
+      }
     },
     {
       "name": "summarize_story",
@@ -88,17 +82,15 @@
           "settings": {}
         },
         "parameters": {}
-      },
-      "outputs": []
+      }
     },
     {
       "name": "generate_audio_title",
       "input": "The Quick Brown Fox was admired by all the animals in the forest.",
       "metadata": {
         "model": "Text2Speech",
         "parameters": {}
-      },
-      "outputs": []
+      }
     },
     {
       "name": "generate_caption",
@@ -113,8 +105,7 @@
       "metadata": {
         "model": "Image2Text",
         "parameters": {}
-      },
-      "outputs": []
+      }
     },
     {
       "name": "openai_gen_itinerary",
@@ -124,8 +115,7 @@
         "parameters": {
           "order_by": "geographic location"
         }
-      },
-      "outputs": []
+      }
     },
     {
       "name": "Audio Speech Recognition",
@@ -138,10 +128,9 @@
         ]
       },
       "metadata": {
-        "model": "openai/whisper-small",
+        "model": "AudioSpeechRecognition",
         "parameters": {}
-      },
-      "outputs": []
+      }
     }
   ],
   "$schema": "https://json.schemastore.org/aiconfig-1.0"

extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/automatic_speech_recognition.py

@@ -94,7 +94,12 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
 
         model_settings = self.get_model_settings(prompt, aiconfig)
         [pipeline_creation_data, _] = refine_pipeline_creation_params(model_settings)
-        model_name = aiconfig.get_model_name(prompt)
+
+        model_name: str = aiconfig.get_model_name(prompt)
+        # TODO: Clean this up after we allow people in the AIConfig UI to specify their
+        # own model name for HuggingFace tasks. This isn't great but it works for now
+        if (model_name == "TextTranslation"):
+            model_name = self._get_default_model_name()
 
         if isinstance(model_name, str) and model_name not in self.pipelines:
             device = self._get_device()
@@ -139,6 +144,9 @@ def get_output_text(
             if isinstance(output_data, str):
                 return output_data
         return ""
+
+    def _get_default_model_name(self) -> str:
+        return "openai/whisper-small"
 
 
 def validate_attachment_type_is_audio(attachment: Attachment):

extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_2_image.py

@@ -289,6 +289,11 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
         print(pipeline_building_disclaimer_message)
 
         model_name: str = aiconfig.get_model_name(prompt)
+        # TODO: Clean this up after we allow people in the AIConfig UI to specify their
+        # own model name for HuggingFace tasks. This isn't great but it works for now
+        if (model_name == "Text2Image"):
+            model_name = self._get_default_model_name()
+
         # TODO (rossdanlm): Figure out a way to save model and re-use checkpoint
         # Otherwise right now a lot of these models are taking 5 mins to load with 50
         # num_inference_steps (default value). See here for more details:
@@ -364,6 +369,9 @@ def _get_device(self) -> str:
             return "mps"
         return "cpu"
 
+    def _get_default_model_name(self) -> str:
+        return "runwayml/stable-diffusion-v1-5"
+
 def _refine_responses(
     response_images:  List[Image.Image],
     nsfw_content_detected: List[bool],

extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_2_speech.py

@@ -192,6 +192,11 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
         [pipeline_creation_data, _] = refine_pipeline_creation_params(model_settings)
 
         model_name: str = aiconfig.get_model_name(prompt)
+        # TODO: Clean this up after we allow people in the AIConfig UI to specify their
+        # own model name for HuggingFace tasks. This isn't great but it works for now
+        if (model_name == "Text2Speech"):
+            model_name = self._get_default_model_name()
+
         if isinstance(model_name, str) and model_name not in self.synthesizers:
             self.synthesizers[model_name] = pipeline("text-to-speech", model_name)
         synthesizer = self.synthesizers[model_name]
@@ -229,3 +234,6 @@ def get_output_text(
             elif isinstance(output.data, str):
                 return output.data
         return ""
+
+    def _get_default_model_name(self) -> str:
+        return "suno/bark"

extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_generation.py

@@ -240,10 +240,13 @@ async def run_inference(
         completion_data = await self.deserialize(prompt, aiconfig, options, parameters)
         completion_data["text_inputs"] = completion_data.pop("prompt", None)
 
-        model_name : str = aiconfig.get_model_name(prompt)
+        model_name: str = aiconfig.get_model_name(prompt)
+        # TODO: Clean this up after we allow people in the AIConfig UI to specify their
+        # own model name for HuggingFace tasks. This isn't great but it works for now
+        if (model_name == "TextGeneration"):
+            model_name = self._get_default_model_name()
+
         if isinstance(model_name, str) and model_name not in self.generators:
-            print(f"Rossdan Loading model {prompt.metadata.model}")
-            print(f"Rossdan Loading model {model_name}")
             self.generators[model_name] = pipeline('text-generation', model=model_name)
         generator = self.generators[model_name]
 
@@ -305,3 +308,6 @@ def get_output_text(
                 # calls so shouldn't get here, but just being safe
                 return json.dumps(output_data.value, indent=2)
         return ""
+
+    def _get_default_model_name(self) -> str:
+        return "stevhliu/my_awesome_billsum_model"

extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_summarization.py

@@ -239,6 +239,11 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
         inputs = completion_data.pop("prompt", None)
 
         model_name: str = aiconfig.get_model_name(prompt)
+        # TODO: Clean this up after we allow people in the AIConfig UI to specify their
+        # own model name for HuggingFace tasks. This isn't great but it works for now
+        if (model_name == "TextSummarization"):
+            model_name = self._get_default_model_name()
+
         if isinstance(model_name, str) and model_name not in self.summarizers:
             self.summarizers[model_name] = pipeline("summarization", model=model_name)
         summarizer = self.summarizers[model_name]
@@ -303,3 +308,6 @@ def get_output_text(
                 # calls so shouldn't get here, but just being safe
                 return json.dumps(output_data.value, indent=2)
         return ""
+
+    def _get_default_model_name(self) -> str:
+        return "facebook/bart-large-cnn"

extensions/HuggingFace/python/src/aiconfig_extension_hugging_face/local_inference/text_translation.py

@@ -239,6 +239,11 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
         inputs = completion_data.pop("prompt", None)
 
         model_name: str = aiconfig.get_model_name(prompt)
+        # TODO: Clean this up after we allow people in the AIConfig UI to specify their
+        # own model name for HuggingFace tasks. This isn't great but it works for now
+        if (model_name == "TextTranslation"):
+            model_name = self._get_default_model_name()
+
         if isinstance(model_name, str) and model_name not in self.translators:
             self.translators[model_name] = pipeline(model_name)
         translator = self.translators[model_name]
@@ -297,3 +302,6 @@ def get_output_text(
                 # calls so shouldn't get here, but just being safe
                 return json.dumps(output_data.value, indent=2)
         return ""
+
+    def _get_default_model_name(self) -> str:
+        return "translation_en_to_fr"