77 lines
2.9 KiB
Python

import logging
from .client import OpenAIClient
from .models import OpenAIAssistant as OpenAIAssistantModel
logger = logging.getLogger(__name__)
class OpenAIAssistant:
"""
OpenAI Assistant for handling AI interactions.
"""
def __init__(self, name):
"""
Initialize the assistant by loading its configuration from the database.
"""
try:
self.config = OpenAIAssistantModel.objects.get(name=name)
self.client = OpenAIClient(self.config.api_key).get_client()
except OpenAIAssistantModel.DoesNotExist:
raise ValueError(f"Assistant '{name}' not found in the database.")
def chat_completion(self, user_message):
"""
Call OpenAI's chat completion API.
"""
try:
response = self.client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{
"role": "system",
"content": self.config.description, # Use description as the system prompt
},
{"role": "user", "content": user_message},
],
)
return response.choices[0].message.content
except Exception as e:
logger.error(f"Error in chat completion: {e}")
return f"Error in chat completion: {e}"
def agent_workflow(self, user_message):
"""
Call OpenAI's advanced agent workflow API.
"""
try:
if not self.config.assistant_id:
raise ValueError(f"Assistant '{self.config.name}' does not have an associated assistant ID.")
assistant = self.client.beta.assistants.retrieve(self.config.assistant_id)
thread = self.client.beta.threads.create()
# Create a message in the thread
self.client.beta.threads.messages.create(thread_id=thread.id, role="user", content=user_message)
# Run the assistant workflow
run = self.client.beta.threads.runs.create(thread_id=thread.id, assistant_id=assistant.id)
# Poll for the result
while run.status in ["queued", "in_progress"]:
run = self.client.beta.threads.runs.retrieve(thread_id=thread.id, run_id=run.id)
if run.status == "completed":
messages = self.client.beta.threads.messages.list(thread_id=thread.id)
return messages.data[0].content[0].text.value
return "Unexpected error: Workflow did not complete."
except Exception as e:
logger.error(f"Error in agent workflow: {e}")
return f"Error in agent workflow: {e}"
def handle_message(self, user_message):
"""
Automatically select the correct method based on assistant type.
"""
if self.config.is_special_assistant():
return self.agent_workflow(user_message)
return self.chat_completion(user_message)