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"""
OpenAI Provider Integration
Handles API calls to OpenAI for text and image generation
"""
import os
import time
import json
import logging
from typing import Dict, Any, Optional, List
# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("openai")
try:
import openai
from openai import OpenAI
HAS_OPENAI = True
except ImportError:
logger.warning("OpenAI package not installed. Install with: pip install openai")
HAS_OPENAI = False
class OpenAIProvider:
"""OpenAI API provider for model inference"""
def __init__(self, api_key: Optional[str] = None):
"""Initialize the OpenAI provider with API key"""
if not HAS_OPENAI:
logger.error("OpenAI package not installed. Install with: pip install openai")
return
self.api_key = api_key or os.getenv("OPENAI_API_KEY")
if not self.api_key:
logger.warning("No OpenAI API key provided. Set OPENAI_API_KEY env variable.")
# Initialize client
self.client = OpenAI(api_key=self.api_key)
def generate_text(self,
prompt: str,
model: str = "gpt-3.5-turbo",
max_tokens: int = 1000,
temperature: float = 0.7,
system_message: str = "You are a helpful assistant.",
**kwargs) -> Dict[str, Any]:
"""Generate text using OpenAI models"""
if not HAS_OPENAI or not self.api_key:
return {"success": False, "error": "OpenAI package not installed or API key not provided"}
start_time = time.time()
try:
messages = [
{"role": "system", "content": system_message},
{"role": "user", "content": prompt}
]
response = self.client.chat.completions.create(
model=model,
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
**kwargs
)
# Extract the generated text
generated_text = response.choices[0].message.content
return {
"success": True,
"text": generated_text,
"model": model,
"provider": "openai",
"response_time": time.time() - start_time,
"tokens": {
"prompt": response.usage.prompt_tokens,
"completion": response.usage.completion_tokens,
"total": response.usage.total_tokens
},
"raw_response": response.model_dump()
}
except Exception as e:
logger.error(f"Error generating text with OpenAI: {e}")
return {
"success": False,
"error": str(e),
"response_time": time.time() - start_time,
"model": model,
"provider": "openai"
}
def generate_image(self,
prompt: str,
model: str = "dall-e-3",
size: str = "1024x1024",
quality: str = "standard",
n: int = 1,
**kwargs) -> Dict[str, Any]:
"""Generate image using OpenAI DALL-E models"""
if not HAS_OPENAI or not self.api_key:
return {"success": False, "error": "OpenAI package not installed or API key not provided"}
start_time = time.time()
try:
response = self.client.images.generate(
model=model,
prompt=prompt,
size=size,
quality=quality,
n=n,
**kwargs
)
return {
"success": True,
"image_url": response.data[0].url, # URL of the generated image
"model": model,
"provider": "openai",
"response_time": time.time() - start_time,
"raw_response": response.model_dump()
}
except Exception as e:
logger.error(f"Error generating image with OpenAI: {e}")
return {
"success": False,
"error": str(e),
"response_time": time.time() - start_time,
"model": model,
"provider": "openai"
}
def get_available_models(self) -> List[Dict[str, Any]]:
"""Get available OpenAI models"""
if not HAS_OPENAI or not self.api_key:
return []
try:
response = self.client.models.list()
models = [
{
"id": model.id,
"name": model.id,
"created": model.created
}
for model in response.data
]
# Filter to only include completion and chat models
text_models = [
model for model in models
if any(prefix in model["id"] for prefix in ["gpt-", "text-"])
]
# Add DALL-E models (they don't show up in the list)
image_models = [
{"id": "dall-e-3", "name": "DALL-E 3"},
{"id": "dall-e-2", "name": "DALL-E 2"}
]
return {
"text_models": text_models,
"image_models": image_models
}
except Exception as e:
logger.error(f"Error fetching OpenAI models: {e}")
return []
# Example usage
if __name__ == "__main__":
# Test the provider
provider = OpenAIProvider()
result = provider.generate_text("Write a short poem about AI.")
print(json.dumps(result, indent=2)) |