138 lines
5.1 KiB
Python
138 lines
5.1 KiB
Python
import logging
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from typing import Dict, Any, List, Union, Optional
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from modules.connectors.connectorAiOpenai import AiOpenai
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from modules.connectors.connectorAiAnthropic import AiAnthropic
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logger = logging.getLogger(__name__)
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class AiCalls:
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"""Interface for AI service interactions"""
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def __init__(self):
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self.openaiService = AiOpenai()
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self.anthropicService = AiAnthropic()
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async def callAiTextBasic(self, prompt: str, context: Optional[str] = None) -> str:
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"""
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Basic text processing using OpenAI.
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Args:
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prompt: The user prompt to process
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context: Optional system context/prompt
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Returns:
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The AI response as text
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"""
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# Prepare messages in OpenAI format
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messages = []
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# Add system message if context provided
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if context:
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messages.append({
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"role": "system",
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"content": context
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})
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# Add user message
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messages.append({
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"role": "user",
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"content": prompt
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})
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# Add language instruction for user-facing responses
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if hasattr(self, 'userLanguage') and self.userLanguage:
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ltext = f"Please respond in '{self.userLanguage}' language."
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if messages and messages[0]["role"] == "system":
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if "language" not in messages[0]["content"].lower():
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messages[0]["content"] = f"{ltext} {messages[0]['content']}"
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else:
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messages.insert(0, {
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"role": "system",
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"content": ltext
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})
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try:
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return await self.openaiService.callAiBasic(messages)
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except Exception as e:
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logger.error(f"Error in OpenAI call: {str(e)}")
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return f"Error: {str(e)}"
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async def callAiTextAdvanced(self, prompt: str, context: Optional[str] = None) -> str:
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"""
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Advanced text processing using Anthropic.
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Fallback to OpenAI if Anthropic is overloaded or rate-limited.
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"""
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# For Anthropic, we need to handle system content differently
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# Anthropic expects system content in a top-level parameter, not as a message role
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try:
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# Create messages without system role for Anthropic
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anthropic_messages = []
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if hasattr(self, 'userLanguage') and self.userLanguage:
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ltext = f"Please respond in '{self.userLanguage}' language."
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if context:
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# Combine context and language instruction
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full_context = f"{ltext}\n\n{context}"
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else:
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full_context = ltext
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else:
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full_context = context
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# Add user message
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anthropic_messages.append({
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"role": "user",
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"content": prompt
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})
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# Call Anthropic - let the connector handle system content conversion
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if full_context:
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# Send context as part of the user message for Anthropic
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enhanced_prompt = f"Context:\n{full_context}\n\nUser Request:\n{prompt}"
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response = await self.anthropicService.callAiBasic([
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{"role": "user", "content": enhanced_prompt}
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])
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else:
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response = await self.anthropicService.callAiBasic(anthropic_messages)
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return response["choices"][0]["message"]["content"]
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except Exception as e:
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err_str = str(e)
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logger.warning(f"[UI NOTICE] Advanced AI failed, falling back to Basic AI (OpenAI). Reason: {err_str}")
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# Fallback to OpenAI basic
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return await self.callAiTextBasic(prompt, context)
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async def callAiImageBasic(self, prompt: str, imageData: Union[str, bytes], mimeType: str = None) -> str:
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"""
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Basic image processing using OpenAI.
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Args:
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prompt: The prompt for image analysis
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imageData: The image data (file path or bytes)
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mimeType: Optional MIME type of the image
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Returns:
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The AI response as text
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"""
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try:
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return await self.openaiService.callAiImage(prompt, imageData, mimeType)
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except Exception as e:
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logger.error(f"Error in OpenAI image call: {str(e)}")
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return f"Error: {str(e)}"
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async def callAiImageAdvanced(self, prompt: str, imageData: Union[str, bytes], mimeType: str = None) -> str:
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"""
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Advanced image processing using Anthropic.
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Args:
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prompt: The prompt for image analysis
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imageData: The image data (file path or bytes)
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mimeType: Optional MIME type of the image
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Returns:
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The AI response as text
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"""
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try:
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return await self.anthropicService.callAiImage(prompt, imageData, mimeType)
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except Exception as e:
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logger.error(f"Error in Anthropic image call: {str(e)}")
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return f"Error: {str(e)}"
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