(docs) add cookbook on sagemaker streaming

cookbook/misc/sagmaker_streaming.py

@@ -0,0 +1,61 @@
+# Notes - on how to do sagemaker streaming using boto3
+import json
+import boto3
+
+import sys, os
+import traceback
+from dotenv import load_dotenv
+
+load_dotenv()
+import os, io
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import pytest
+import litellm
+
+import io
+import json
+
+
+class TokenIterator:
+    def __init__(self, stream):
+        self.byte_iterator = iter(stream)
+        self.buffer = io.BytesIO()
+        self.read_pos = 0
+
+    def __iter__(self):
+        return self
+
+    def __next__(self):
+        while True:
+            self.buffer.seek(self.read_pos)
+            line = self.buffer.readline()
+            if line and line[-1] == ord("\n"):
+                self.read_pos += len(line) + 1
+                full_line = line[:-1].decode("utf-8")
+                line_data = json.loads(full_line.lstrip("data:").rstrip("/n"))
+                return line_data["token"]["text"]
+            chunk = next(self.byte_iterator)
+            self.buffer.seek(0, io.SEEK_END)
+            self.buffer.write(chunk["PayloadPart"]["Bytes"])
+
+
+payload = {
+    "inputs": "How do I build a website?",
+    "parameters": {"max_new_tokens": 256},
+    "stream": True,
+}
+
+import boto3
+
+client = boto3.client("sagemaker-runtime", region_name="us-west-2")
+response = client.invoke_endpoint_with_response_stream(
+    EndpointName="berri-benchmarking-Llama-2-70b-chat-hf-4",
+    Body=json.dumps(payload),
+    ContentType="application/json",
+)
+
+# for token in TokenIterator(response["Body"]):
+#     print(token)