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ask-llm.py
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ask-llm.py
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#!/usr/bin/env python3
import asyncio
import os
import json
import urllib.request
import time
LLM_API_BASE_URL = os.environ.get("LLM_API_BASE_URL", "https://api.openai.com/v1")
LLM_API_KEY = os.environ.get("LLM_API_KEY") or os.environ.get("OPENAI_API_KEY")
LLM_CHAT_MODEL = os.environ.get("LLM_CHAT_MODEL")
LLM_STREAMING = os.environ.get("LLM_STREAMING", "yes") != "no"
LLM_DEBUG = os.environ.get("LLM_DEBUG")
async def chat(messages, handler=None):
url = f"{LLM_API_BASE_URL}/chat/completions"
auth_header = f"Bearer {LLM_API_KEY}" if LLM_API_KEY else None
headers = {
"Content-Type": "application/json",
"User-Agent": "python-requests/2.31.0",
}
if auth_header:
headers["Authorization"] = auth_header
model = LLM_CHAT_MODEL or "gpt-4o-mini"
stop = ["<|im_end|>", "<|end|>", "<|eot_id|>"]
max_tokens = 200
temperature = 0
stream = LLM_STREAMING and callable(handler)
body = {
"messages": messages,
"model": model,
"stop": stop,
"max_tokens": max_tokens,
"temperature": temperature,
"stream": stream,
}
json_body = json.dumps(body).encode("utf-8")
request = urllib.request.Request(
url, data=json_body, headers=headers, method="POST"
)
response = urllib.request.urlopen(request)
if not stream:
if response.status != 200:
raise Exception(f"HTTP error: {response.status} {response.reason}")
data = json.loads(response.read().decode("utf-8"))
choices = data["choices"]
first = choices[0]
message = first["message"]
content = message["content"]
full_answer = content.strip()
if handler:
handler(full_answer)
return full_answer
else:
def parse(line):
partial = None
prefix = line[:6]
if prefix == "data: ":
payload = line[6:]
try:
choices = json.loads(payload)["choices"]
choice = choices[0]
delta = choice.get("delta", {})
partial = delta.get("content", "")
except Exception as e:
pass
return partial
finished = False
buffer = []
answer = ""
while not finished:
raw_bytes = response.read(8)
if not raw_bytes:
break
buffer.append(raw_bytes)
lines = b"".join(buffer).decode("utf-8").splitlines(True)
full_answer = ""
for line in lines:
if len(line) > 0:
if line[0] == ":":
continue
if line == "data: [DONE]":
finished = True
break
elif line:
partial = parse(line.strip())
if partial is not None:
if len(full_answer) == 0:
full_answer = partial.strip()
else:
full_answer += partial
if handler:
handler(full_answer.replace(answer, ""))
answer = full_answer
return answer
SYSTEM_PROMPT = "Answer the question politely and concisely."
async def main():
print(f"Using LLM at {LLM_API_BASE_URL}.")
print("Press Ctrl+D to exit.")
print()
messages = [{"role": "system", "content": SYSTEM_PROMPT}]
while True:
try:
question = input(">> ")
except EOFError:
break
messages.append({"role": "user", "content": question})
start = time.time()
stream = lambda partial: print(partial, end="", flush=True)
answer = await chat(messages, stream)
messages.append({"role": "assistant", "content": answer})
print()
elapsed = time.time() - start
if LLM_DEBUG:
print(f"[{round(elapsed * 1000)} ms]")
print()
asyncio.run(main())