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