diff --git a/python/llm/src/bigdl/llm/ggml/model/bloom/bloom.py b/python/llm/src/bigdl/llm/ggml/model/bloom/bloom.py
index ba903c1e..242962f2 100644
--- a/python/llm/src/bigdl/llm/ggml/model/bloom/bloom.py
+++ b/python/llm/src/bigdl/llm/ggml/model/bloom/bloom.py
@@ -47,6 +47,9 @@
 
 from .bloom_cpp import bloom_load, bloom_free, bloom_run
 from bigdl.llm.utils.common import invalidInputError
+from typing import List, Optional
+import time
+import uuid
 
 
 class Bloom:
@@ -81,6 +84,7 @@ class Bloom:
         Returns:
             A Bloom instance.
         """
+        self.model_path = model_path
         self.ctx = bloom_load(bytes(model_path, encoding='utf-8'), n_ctx, n_threads)
         invalidInputError(self.ctx is not None, f"Failed to load model from {model_path}")
         self.n_ctx = n_ctx
@@ -91,15 +95,39 @@ class Bloom:
         self.last_n_tokens_size = last_n_tokens_size
         self.verbose = verbose
 
-    def __call__(self, prompt: str, max_tokens: int, stream: bool = False):
+    def __call__(self, prompt: str, max_tokens: int, stream: bool = False,
+                 stop: Optional[List[str]] = []):
         if stream:
-            return self.stream(prompt, max_tokens)
+            return self.stream(prompt, max_tokens, stop)
         else:
-            return self._eval(prompt, max_tokens, False)
+            return self._eval(prompt, max_tokens, False, stop)
 
-    def _eval(self, prompt: str, max_tokens: int, match_str: bool):
+    def _eval(self, prompt: str, max_tokens: int, match_str: bool,
+              stop: Optional[List[str]] = []):
+        completion_id: str = f"cmpl-{str(uuid.uuid4())}"
+        created: int = int(time.time())
         if prompt.endswith("</s>") or max_tokens < 1:
-            return prompt
+            return {
+                "id": completion_id,
+                "object": "text_completion",
+                "created": created,
+                "model": self.model_path,
+                "choices": [
+                    {
+                        "text": prompt,
+                        "index": 0,
+                        "logprobs": None,
+                        "finish_reason": "length",
+                    }
+                ],
+                "usage":
+                {
+                    # TODO: need tokenize
+                    "prompt_tokens": None,
+                    "completion_tokens": None,
+                    "total_tokens": None,
+                }
+            }
         # use `buf` to store prompt and generated string,
         # assume the average length of words is less than 20 bytes
         buf = bytes((len(prompt) + max_tokens) * 20)
@@ -112,18 +140,85 @@ class Bloom:
                         prompt=bytes(prompt, encoding='utf-8'),
                         buf=buf)
         s = str(buf, encoding='utf-8').rstrip("\x00")
-        return s
 
-    def stream(self, prompt: str, max_tokens: int):
+        text = s.split(prompt)[1]
+        split_text = text
+        if stop != []:
+            for stop_word in stop:
+                split_text = split_text.split(stop_word)[0]
+        if split_text != text:
+            finish_reason = "stop"
+        else:
+            finish_reason = None
+        return {"id": completion_id,
+                "object": "text_completion",
+                "created": created,
+                "model": self.model_path,
+                "choices": [
+                    {
+                        "text": prompt + split_text,
+                        "index": 0,
+                        "logprobs": None,
+                        "finish_reason": finish_reason,
+                    }
+                ],
+                "usage":
+                {
+                    # TODO: need tokenize
+                    "prompt_tokens": None,
+                    "completion_tokens": None,
+                    "total_tokens": None,
+                }
+                }
+
+    def stream(self, prompt: str, max_tokens: int, stop: Optional[List[str]] = []):
+        completion_id: str = f"cmpl-{str(uuid.uuid4())}"
+        created: int = int(time.time())
         if prompt.endswith("</s>") or max_tokens < 1:
-            yield prompt
+            yield {
+                "id": completion_id,
+                "object": "text_completion",
+                "created": created,
+                "model": self.model_path,
+                "choices": [
+                    {
+                        "text": prompt,
+                        "index": 0,
+                        "logprobs": None,
+                        "finish_reason": "length",
+                    }
+                ],
+                "usage":
+                    {
+                        # TODO: need tokenize
+                        "prompt_tokens": None
+                }
+            }
         else:
             for i in range(max_tokens):
                 if prompt.endswith("</s>"):
                     break
                 else:
-                    prompt = self._eval(prompt, 1, i != 0)
-                    yield prompt
+                    prompt = self._eval(prompt, 1, i != 0, stop)['choices'][0]['text']
+                    yield {
+                        "id": completion_id,
+                        "object": "text_completion",
+                        "created": created,
+                        "model": self.model_path,
+                        "choices": [
+                            {
+                                "text": prompt,
+                                "index": 0,
+                                "logprobs": None,
+                                "finish_reason": None,
+                            }
+                        ],
+                        "usage":
+                            {
+                                # TODO: need tokenize
+                                "prompt_tokens": None
+                        }
+                    }
 
     def free(self):
         bloom_free(self.ctx)