Reorganize project structure: move public files to public/ directory

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Russell Ballestrini 2025-10-24 13:23:42 -04:00
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#!/usr/bin/env python3
"""
uncloseai. - Async Python Client (httpx)
A Python async client for OpenAI-compatible APIs with streaming support
"""
import httpx
import json
import os
import asyncio
from typing import List, Dict, Optional, AsyncIterator
class uncloseai:
"""Async client for OpenAI-compatible API endpoints with streaming support"""
def __init__(
self,
model_endpoints: Optional[List[str]] = None,
tts_endpoints: Optional[List[str]] = None,
api_key: Optional[str] = None,
timeout: float = 30.0
):
self.timeout = timeout
self.api_key = api_key
self.models: List[Dict] = []
self.tts_endpoints: List[str] = []
self._initialized = False
self._model_endpoints = model_endpoints or self._discover_env_endpoints("MODEL_ENDPOINT")
self._tts_endpoints = tts_endpoints or self._discover_env_endpoints("TTS_ENDPOINT")
def _discover_env_endpoints(self, prefix: str) -> List[str]:
endpoints = []
for i in range(1, 10000):
endpoint = os.getenv(f"{prefix}_{i}")
if not endpoint:
break
endpoints.append(endpoint)
return endpoints
async def _ensure_initialized(self):
if self._initialized:
return
async with httpx.AsyncClient(timeout=self.timeout) as client:
for endpoint in self._model_endpoints:
await self._discover_models_from_endpoint(client, endpoint)
self.tts_endpoints = self._tts_endpoints
self._initialized = True
async def _discover_models_from_endpoint(self, client: httpx.AsyncClient, endpoint: str) -> None:
try:
headers = {}
if self.api_key:
headers["Authorization"] = f"Bearer {self.api_key}"
response = await client.get(f"{endpoint}/models", headers=headers)
if response.status_code == 200:
data = response.json()
for model in data.get("data", []):
self.models.append({
"id": model["id"],
"endpoint": endpoint,
"max_tokens": model.get("max_model_len", 8192)
})
except Exception as e:
print(f"Warning: Failed to discover models from {endpoint}: {e}")
async def list_models(self) -> List[Dict]:
await self._ensure_initialized()
return self.models.copy()
async def chat(
self,
messages: List[Dict[str, str]],
model: Optional[str] = None,
max_tokens: int = 100,
temperature: float = 0.7,
**kwargs
) -> Dict:
await self._ensure_initialized()
model_info = self._get_model_info(model)
headers = {"Content-Type": "application/json"}
if self.api_key:
headers["Authorization"] = f"Bearer {self.api_key}"
payload = {
"model": model_info["id"],
"messages": messages,
"max_tokens": max_tokens,
"temperature": temperature,
"stream": False,
**kwargs
}
async with httpx.AsyncClient(timeout=self.timeout) as client:
response = await client.post(
f"{model_info['endpoint']}/chat/completions",
headers=headers,
json=payload
)
response.raise_for_status()
return response.json()
async def chat_stream(
self,
messages: List[Dict[str, str]],
model: Optional[str] = None,
max_tokens: int = 500,
temperature: float = 0.7,
**kwargs
) -> AsyncIterator[Dict]:
await self._ensure_initialized()
model_info = self._get_model_info(model)
headers = {"Content-Type": "application/json"}
if self.api_key:
headers["Authorization"] = f"Bearer {self.api_key}"
payload = {
"model": model_info["id"],
"messages": messages,
"max_tokens": max_tokens,
"temperature": temperature,
"stream": True,
**kwargs
}
async with httpx.AsyncClient(timeout=self.timeout) as client:
async with client.stream(
"POST",
f"{model_info['endpoint']}/chat/completions",
headers=headers,
json=payload
) as response:
response.raise_for_status()
async for line in response.aiter_lines():
if not line:
continue
if line.startswith('data: '):
data = line[6:]
if data.strip() == '[DONE]':
break
try:
chunk = json.loads(data)
yield chunk
except json.JSONDecodeError:
continue
async def tts(
self,
text: str,
voice: str = "alloy",
model: str = "tts-1",
response_format: str = "mp3"
) -> bytes:
await self._ensure_initialized()
if not self.tts_endpoints:
raise ValueError("No TTS endpoints available")
endpoint = self.tts_endpoints[0]
headers = {"Content-Type": "application/json"}
if self.api_key:
headers["Authorization"] = f"Bearer {self.api_key}"
payload = {
"model": model,
"voice": voice,
"input": text,
"response_format": response_format
}
async with httpx.AsyncClient(timeout=self.timeout) as client:
response = await client.post(
f"{endpoint}/audio/speech",
headers=headers,
json=payload
)
response.raise_for_status()
return response.content
def _get_model_info(self, model: Optional[str] = None) -> Dict:
if not self.models:
raise ValueError("No models available. Check endpoint configuration.")
if model is None:
return self.models[0]
for m in self.models:
if m["id"] == model:
return m
raise ValueError(f"Model '{model}' not found in discovered models")
async def main():
print("=== uncloseai. Python Async Client (httpx) ===\n")
client = uncloseai()
models = await client.list_models()
if not models:
print("ERROR: No models discovered. Set environment variables:")
print(" MODEL_ENDPOINT_1, MODEL_ENDPOINT_2, etc.")
return
print(f"Discovered {len(models)} model(s)")
for model in models:
print(f" - {model['id']} (max_tokens: {model['max_tokens']})")
print()
# Non-streaming chat
print("=== Non-Streaming Chat ===")
response = await client.chat(
messages=[
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "Explain quantum computing in one sentence."}
],
max_tokens=100
)
print(f"Model: {response['model']}")
print(f"Response: {response['choices'][0]['message']['content']}\n")
# Streaming chat
print("=== Streaming Chat ===")
model_id = models[1]["id"] if len(models) > 1 else None
print(f"Model: {model_id or models[0]['id']}")
print("Response: ", end="", flush=True)
async for chunk in client.chat_stream(
messages=[
{"role": "system", "content": "You are a coding assistant."},
{"role": "user", "content": "Write a Python async function to fetch multiple URLs"}
],
model=model_id,
max_tokens=200
):
if chunk.get("choices") and len(chunk["choices"]) > 0:
delta = chunk["choices"][0].get("delta", {})
content = delta.get("content", "")
if content:
print(content, end="", flush=True)
print("\n")
# TTS
if client.tts_endpoints:
print("=== TTS Speech Generation ===")
audio_data = await client.tts(
text="Hello from uncloseai. Python async client! This demonstrates text to speech with streaming support.",
voice="alloy"
)
with open("speech.mp3", "wb") as f:
f.write(audio_data)
print(f"[OK] Speech file created: speech.mp3 ({len(audio_data)} bytes)\n")
print("=== Examples Complete ===")
if __name__ == "__main__":
asyncio.run(main())