[HF][streaming][1/n] Text Summarization

TSIA

Adding streaming functionality to text summarization model parser

## Test Plan
Rebase onto and test it with 11ace0a.

Follow the README from AIConfig Editor https://github.com/lastmile-ai/aiconfig/tree/main/python/src/aiconfig/editor#dev, then run these command
```bash
aiconfig_path=/Users/rossdancraig/Projects/aiconfig/cookbooks/Gradio/huggingface.aiconfig.json
parsers_path=/Users/rossdancraig/Projects/aiconfig/cookbooks/Gradio/hf_model_parsers.py
alias aiconfig="python3 -m 'aiconfig.scripts.aiconfig_cli'"
aiconfig edit --aiconfig-path=$aiconfig_path --server-port=8080 --server-mode=debug_servers --parsers-module-path=$parsers_path
```

Then in AIConfig Editor run the prompt (it will be streaming format by default)


https://github.com/lastmile-ai/aiconfig/assets/151060367/e91a1d8b-a3e9-459c-9eb1-2d8e5ec58e73

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

@@ -251,7 +251,7 @@ async def run_inference(
             not "stream" in completion_data or completion_data.get("stream") != False
         )
         if should_stream:
-            tokenizer : AutoTokenizer = AutoTokenizer.from_pretrained(model_name)
+            tokenizer: AutoTokenizer = AutoTokenizer.from_pretrained(model_name)
             streamer = TextIteratorStreamer(tokenizer)
             completion_data["streamer"] = streamer
 

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

@@ -128,13 +128,18 @@ def construct_stream_output(
             "metadata": {},
         }
     )
+
     accumulated_message = ""
     for new_text in streamer:
         if isinstance(new_text, str):
+            # For some reason these symbols aren't filtered out by the streamer
+            new_text = new_text.replace("</s>", "")
+            new_text = new_text.replace("<s>", "")
+
             accumulated_message += new_text
             options.stream_callback(new_text, accumulated_message, 0)
-
             output.data = accumulated_message
+
     return output
 
 
@@ -245,7 +250,9 @@ async def run_inference(self, prompt: Prompt, aiconfig: "AIConfigRuntime", optio
 
         # if stream enabled in runtime options and config, then stream. Otherwise don't stream.
         streamer = None
-        should_stream = (options.stream if options else False) and (not "stream" in completion_data or completion_data.get("stream") != False)
+        should_stream = (options.stream if options else False) and (
+            not "stream" in completion_data or completion_data.get("stream") != False
+        )
         if should_stream:
             tokenizer: AutoTokenizer = AutoTokenizer.from_pretrained(model_name)
             streamer = TextIteratorStreamer(tokenizer)