HFLLMAPI2 / examples /chat_with_post.py
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:gem: [Feature] New examples: chat with openai and post
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import ast
import httpx
import json
import re
# If runnning this service with proxy, you might need to unset `http(s)_proxy`.
chat_api = "http://127.0.0.1:23333"
api_key = "sk-xxxxx"
requests_headers = {}
requests_payload = {
"model": "mixtral-8x7b",
"messages": [
{
"role": "user",
"content": "what is your model",
}
],
"stream": True,
}
with httpx.stream(
"POST",
chat_api + "/chat/completions",
headers=requests_headers,
json=requests_payload,
timeout=httpx.Timeout(connect=20, read=60, write=20, pool=None),
) as response:
# https://docs.aiohttp.org/en/stable/streams.html
# https://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb
response_content = ""
for line in response.iter_lines():
remove_patterns = [r"^\s*data:\s*", r"^\s*\[DONE\]\s*"]
for pattern in remove_patterns:
line = re.sub(pattern, "", line).strip()
if line:
try:
line_data = json.loads(line)
except Exception as e:
try:
line_data = ast.literal_eval(line)
except:
print(f"Error: {line}")
raise e
# print(f"line: {line_data}")
delta_data = line_data["choices"][0]["delta"]
finish_reason = line_data["choices"][0]["finish_reason"]
if "role" in delta_data:
role = delta_data["role"]
if "content" in delta_data:
delta_content = delta_data["content"]
response_content += delta_content
print(delta_content, end="", flush=True)
if finish_reason == "stop":
print()