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#
# SPDX-FileCopyrightText: Hadad <[email protected]>
# SPDX-License-Identifier: Apache-2.0
#
import json # Import JSON module for encoding and decoding JSON data
from src.tools.image import ImageGeneration # Import ImageGeneration class to handle image creation
# Asynchronous handler for image generation command
async def image_integration(
input, # User input containing the /image command and instruction
new_history, # Conversation history in message format
session_id, # Session ID for conversation context
selected_model, # Selected AI model for generation
jarvis, # AI backend function for generating responses
mode, # Mode for AI response generation
temperature, # Temperature parameter for AI
top_k, # Top-k parameter for AI
min_p, # Min-p parameter for AI
top_p, # Top-p parameter for AI
repetition_penalty # Repetition penalty for AI
):
# Extract the image generation instruction after the '/image' command prefix and strip whitespace
generate_image_instruction = input[6:].strip() # Get instruction after /image
# If no instruction text is provided after the command, yield empty and exit early
if not generate_image_instruction: # Check if instruction is empty
yield [] # Yield empty list for missing instruction
return # Exit function
try: # Try block for image generation
# Asynchronously create image content based on the instruction using ImageGeneration class
image = await ImageGeneration.create_image(generate_image_instruction) # Generate image
# Serialize the image data and instruction into a JSON formatted string for processing
image_generation_content = json.dumps({
"image": image, # Image content or URL
"generate_image_instruction": generate_image_instruction # Instruction for image generation
})
# Construct the conversation history including the image generation result and formatting instructions
image_generation_result = (
new_history
+ [
{
"role": "system",
"content": (
"Image generation result:\n\n" + image_generation_content + "\n\n\n"
"Show the generated image using the following markdown syntax format, where '{image_link}' is the URL of the image:\n\n"
"\n\n"
"Please replace '{image_link}' with the actual image URL provided in the context.\n\n"
"Then, describe the generated image based on the above information.\n\n\n"
"Use the same language as the previous user input or user request.\n"
"For example, if the previous user input or user request is in Indonesian, explain in Indonesian.\n"
"If it is in English, explain in English. This also applies to other languages.\n\n\n"
)
}
]
)
# Use async generator to get descriptive text about the generated image from AI
async for image_description in jarvis(
session_id=session_id, # Session ID
model=selected_model, # Selected model
history=image_generation_result, # Updated history with image result
user_message=input, # User input
mode=mode, # Mode for AI response
temperature=temperature, # temperature parameter
top_k=top_k, # top_k parameter
min_p=min_p, # min_p parameter
top_p=top_p, # top_p parameter
repetition_penalty=repetition_penalty # repetition_penalty parameter
):
yield [{"role": "tool", "content": image_description}] # Yield image description in tool role
return # Exit after handling image
except Exception: # Exception handling for image generation failure
# If image generation fails, let AI generate a contextual error message
generation_failed = (
new_history
+ [
{
"role": "system",
"content": (
"Image generation failed for the user's request. The user tried to generate an image with the instruction: '"
+ generate_image_instruction + "'\n\n\n"
"Please explain to the user that image generation failed and suggest they wait 15 seconds before trying again.\n"
"Be helpful and empathetic in your response.\n\n\n"
"Use the same language as the previous user input or user request.\n"
"For example, if the previous user input or user request is in Indonesian, explain in Indonesian.\n"
"If it is in English, explain in English. This also applies to other languages.\n\n\n"
)
}
]
)
# Use AI to generate a contextual error message
async for error_response in jarvis(
session_id=session_id, # Session ID
model=selected_model, # Selected model
history=generation_failed, # History with error context
user_message=input, # User input
mode="/no_think", # Use non-reasoning mode for error handling
temperature=0.7, # Fixed temperature for more consistent error messages
top_k=20, # Limit token sampling
min_p=0, # Minimum probability threshold
top_p=0.8, # Nucleus sampling threshold
repetition_penalty=1 # No repetition penalty
):
yield [{"role": "tool", "content": error_response}] # Yield error response in tool role
return # Exit after error handling |