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"""
OpenAI GPT Implementation
"""
import os
import openai
from typing import Dict, List, Any
from .llm_interface import LLMInterface
from utils.logger import log_info, log_error, log_warning, log_debug, LogTimer
DEFAULT_LLM_TIMEOUT = int(os.getenv("LLM_TIMEOUT_SECONDS", "60"))
MAX_RESPONSE_LENGTH = 4096 # Max response length
class OpenAILLM(LLMInterface):
"""OpenAI GPT integration with improved error handling"""
def __init__(self, api_key: str, model: str = "gpt-4", settings: Dict[str, Any] = None):
super().__init__(settings)
self.api_key = api_key
self.model = model
self.timeout = self.settings.get("timeout", DEFAULT_LLM_TIMEOUT)
openai.api_key = api_key
log_info(f"🔌 OpenAI LLM initialized", model=self.model, timeout=self.timeout)
async def generate(self, system_prompt: str, user_input: str, context: List[Dict]) -> str:
"""Generate response with consistent error handling"""
# Build messages
messages = []
if system_prompt:
messages.append({"role": "system", "content": system_prompt})
# Add context
for msg in context[-10:]: # Last 10 messages
role = "assistant" if msg.get("role") == "assistant" else "user"
messages.append({"role": role, "content": msg.get("content", "")})
# Add current input
messages.append({"role": "user", "content": user_input})
try:
with LogTimer(f"OpenAI {self.model} request"):
# Use async client
client = openai.AsyncOpenAI(
api_key=self.api_key,
timeout=self.timeout
)
response = await client.chat.completions.create(
model=self.model,
messages=messages,
max_tokens=self.settings.get("max_tokens", 2048),
temperature=self.settings.get("temperature", 0.7),
stream=False
)
# Extract content
content = response.choices[0].message.content
# Check length
if len(content) > MAX_RESPONSE_LENGTH:
log_warning(f"Response exceeded max length, truncating",
original_length=len(content),
max_length=MAX_RESPONSE_LENGTH)
content = content[:MAX_RESPONSE_LENGTH] + "..."
# Log token usage
if response.usage:
log_info(f"Token usage",
prompt_tokens=response.usage.prompt_tokens,
completion_tokens=response.usage.completion_tokens,
total_tokens=response.usage.total_tokens)
return content
except openai.RateLimitError as e:
log_warning("OpenAI rate limit", error=str(e))
raise
except openai.APITimeoutError as e:
log_error("OpenAI timeout", error=str(e))
raise
except openai.APIError as e:
log_error("OpenAI API error",
status_code=e.status_code if hasattr(e, 'status_code') else None,
error=str(e))
raise
except Exception as e:
log_error("OpenAI unexpected error", error=str(e))
raise
async def startup(self, project_config: Dict) -> bool:
"""OpenAI doesn't need startup"""
log_info("OpenAI startup called (no-op)")
return True
def get_provider_name(self) -> str:
return f"openai-{self.model}"
def get_model_info(self) -> Dict[str, Any]:
return {
"provider": "openai",
"model": self.model,
"max_tokens": self.settings.get("max_tokens", 2048),
"temperature": self.settings.get("temperature", 0.7)
} |