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:gem: [Feature] Enable stream output of chat completions
Browse files- tests/openai.py +38 -12
tests/openai.py
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@@ -1,4 +1,6 @@
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import copy
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import uuid
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from pathlib import Path
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@@ -46,17 +48,16 @@ class OpenaiAPI:
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"http": http_proxy,
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"https": http_proxy,
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}
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else:
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self.requests_proxies = None
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def log_request(self, url, method="GET"):
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if ENVER["http_proxy"]:
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logger.note(f"> Using Proxy:", end=" ")
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logger.mesg(f"{ENVER['http_proxy']}")
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logger.note(f"> {method}:", end=" ")
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logger.mesg(f"{url}", end=" ")
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def log_response(self, res: requests.Response, stream=False):
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status_code = res.status_code
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status_code_str = f"[{status_code}]"
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@@ -64,12 +65,35 @@ class OpenaiAPI:
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logger_func = logger.success
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else:
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logger_func = logger.warn
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logger_func(status_code_str)
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if
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-
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-
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def get_models(self):
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self.log_request(self.api_models)
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@@ -111,7 +135,7 @@ class OpenaiAPI:
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"metadata": {},
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}
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],
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"parent_message_id":
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"model": "text-davinci-002-render-sha",
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"timezone_offset_min": -480,
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"suggestions": [],
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@@ -124,22 +148,24 @@ class OpenaiAPI:
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"websocket_request_id": str(uuid.uuid4()),
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}
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self.log_request(self.api_conversation, method="POST")
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self.api_conversation,
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headers=requests_headers,
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json=post_data,
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proxies=self.requests_proxies,
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timeout=10,
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impersonate="chrome120",
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)
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self.log_response(res, stream=True)
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if __name__ == "__main__":
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api = OpenaiAPI()
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# api.get_models()
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api.auth()
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prompt = "
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api.chat_completions(prompt)
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# python -m tests.openai
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import copy
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import json
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import re
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import uuid
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from pathlib import Path
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"http": http_proxy,
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"https": http_proxy,
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}
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logger.note(f"> Using Proxy:", end=" ")
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logger.mesg(f"{ENVER['http_proxy']}")
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else:
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self.requests_proxies = None
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def log_request(self, url, method="GET"):
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logger.note(f"> {method}:", end=" ")
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logger.mesg(f"{url}", end=" ")
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def log_response(self, res: requests.Response, stream=False, verbose=False):
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status_code = res.status_code
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status_code_str = f"[{status_code}]"
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logger_func = logger.success
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else:
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logger_func = logger.warn
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logger_func(status_code_str)
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if verbose:
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if stream:
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if not hasattr(self, "content_offset"):
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self.content_offset = 0
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for line in res.iter_lines():
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line = line.decode("utf-8")
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line = re.sub(r"^data:\s*", "", line)
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if re.match(r"^\[DONE\]", line):
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logger.success("\n[Finished]")
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break
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line = line.strip()
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if line:
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try:
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data = json.loads(line, strict=False)
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role = data["message"]["author"]["role"]
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if role != "assistant":
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continue
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content = data["message"]["content"]["parts"][0]
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delta_content = content[self.content_offset :]
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self.content_offset = len(content)
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logger_func(delta_content, end="")
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except Exception as e:
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logger.warn(e)
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else:
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logger_func(res.json())
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def get_models(self):
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self.log_request(self.api_models)
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"metadata": {},
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}
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],
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"parent_message_id": "",
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"model": "text-davinci-002-render-sha",
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"timezone_offset_min": -480,
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"suggestions": [],
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"websocket_request_id": str(uuid.uuid4()),
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}
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self.log_request(self.api_conversation, method="POST")
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s = requests.Session()
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res = s.post(
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self.api_conversation,
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headers=requests_headers,
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json=post_data,
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proxies=self.requests_proxies,
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timeout=10,
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impersonate="chrome120",
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stream=True,
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)
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self.log_response(res, stream=True, verbose=True)
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if __name__ == "__main__":
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api = OpenaiAPI()
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# api.get_models()
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api.auth()
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prompt = "你的名字?"
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api.chat_completions(prompt)
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# python -m tests.openai
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