Literary illustrator bot Done by CTRL_Pix-A-Thon

integrations/LiteraryIllustrator/README.md

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+# StableDiffusion
+📌 Overview
+
+ Stable Diffusion is a platform that lets you create realistic images from text prompts using latent text-to-image diffusion models. Our AI-powered platform empowers you to generate stunning, photo-realistic images based on any text input.
+Our system uses only one agent, the AI Model Agent, for handling image description requests and interfacing with the Hugging Face API.
+
+# Instructions to run the project:
+Step 1 Account Setup:Create an account on Hugging Face to obtain your API key.
+
+Step 2 Imgur Integration: Create an account on Imgur to obtain your client key.
+
+Step 3 Configuration:Replace the placeholders in the code with your API key and client key as instructed.
+
+Step 4 Generate Illustration:Use the provided function to input the desired literature, paragraph, or note for illustration.
+
+Step 5 Accessing the Image:Click on the link generated after the illustration process to access your image.
+
+
+# Use case Examples:
+1.Artistic Rendering: Creating artistic images from textual descriptions or prompts.
+
+2.Poem Visualization: Converting poems into visually appealing images.
+
+3.Content Creation: Generating images for social media posts, blogs, and articles.
+
+4.Educational Material: Creating visual aids for educational content.
+
+5.Storytelling: Enhancing storytelling by visualizing scenes or characters from stories.

integrations/LiteraryIllustrator/main.py

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+

integrations/LiteraryIllustrator/pyproject.toml

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+

integrations/LiteraryIllustrator/src/__init__.py

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+

integrations/LiteraryIllustrator/src/agent.py

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+import requests
+from pydantic import BaseModel, Field
+from ai_engine import UAgentResponse, UAgentResponseType
+from uagents import Agent, Context, Protocol, Model
+
+# Define the API keys and URLs
+BERT_API_URL = "https://api-inference.huggingface.co/models/google-bert/bert-base-uncased"
+BERT_HEADERS = {"Authorization": "Bearer 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"}
+
+STADIF_API_KEY = "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"
+
+# Define the models for prompt generation and image generation
+class PromptGenModel(Model):
+ paragraph: str = Field(description="Given a paragraph prompt describing a scene or concept, your task is to identify and extract useful and relevant information or tokens that can be utilized for image generation. Focus on key details such as objects, settings, actions, emotions, and any other elements that contribute to the visual representation of the described scene. Your output should provide a structured representation of the extracted information, facilitating the generation of coherent and visually compelling images. Please ensure that the extracted tokens accurately reflect the content and context of the paragraph prompt. Ignore all other irrelevant information")
+
+class ImgGenModel(Model):
+ symbol: str = Field(description="Enter prompt to generate high quality, realistic images with dynamic lighting that envoke strong emotions in a visually appealing and interesting way")
+
+# Function to query BERT model for relevant information extraction
+def query_bert(paragraph: str):
+ try:
+ response = requests.post(BERT_API_URL, headers=BERT_HEADERS, json={"inputs": paragraph})
+ response.raise_for_status() # Raise exception for HTTP errors
+ return response.json()
+ except requests.exceptions.RequestException as e:
+ raise RuntimeError(f"Error from Hugging Face API: {e}")
+
+# Function to query image generation model
+def query_img_gen(symbol: str):
+ API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
+ headers = {"Authorization": f"Bearer {STADIF_API_KEY}"}
+ try:
+ response = requests.post(API_URL, headers=headers, json={"inputs": symbol})
+ response.raise_for_status() # Raise exception for HTTP errors
+ return response.content
+ except requests.exceptions.RequestException as e:
+ raise RuntimeError(f"Error from Hugging Face API: {e}")
+
+# Function to upload image to Imgur
+def upload_image_to_imgur(image_bytes):
+ headers = {
+ "Authorization": "Client-ID ff9ffff4455eadf" # Replace "your-client-id" with your actual Imgur client ID
+ }
+ files = {
+ 'image': ('generated_image.jpg', image_bytes, 'image/jpeg')
+ }
+ try:
+ response = requests.post("https://api.imgur.com/3/image", headers=headers, files=files)
+ response.raise_for_status() # Raise exception for HTTP errors
+ return response.json()["data"]["link"]
+ except requests.exceptions.RequestException as e:
+ raise RuntimeError(f"Error uploading image to Imgur: {e}")
+
+# Define protocols for handling prompt generation and image generation
+PromptGen_protocol = Protocol("PromptGenProtocol")
+ImgGen_protocol = Protocol("ImgGenProtocol")
+
+# Function to handle prompt generation
+@PromptGen_protocol.on_message(model=PromptGenModel, replies={ImgGenModel})
+def handle_promptgen(ctx: Context, sender: str, msg: PromptGenModel):
+ ctx.logger.info(f"Received message from {sender}, session: {ctx.session}")
+ try:
+ relevant_info = query_bert(msg.paragraph)
+ ctx.logger.info(f"Relevant information extracted: {relevant_info}")
+ ctx.send(sender, ImgGenModel(symbol=relevant_info))
+ except Exception as ex:
+ ctx.logger.error(f"Error occurred during relevant information extraction: {ex}")
+ ctx.send(sender, UAgentResponse(message=str(ex), type=UAgentResponseType.ERROR))
+
+# Function to handle image generation
+@ImgGen_protocol.on_message(model=ImgGenModel, replies={UAgentResponse})
+def handle_imggen(ctx: Context, sender: str, msg: ImgGenModel):
+ ctx.logger.info(f"Received message from {sender}, session: {ctx.session}")
+ try:
+ image_bytes = query_img_gen(msg.symbol)
+ image_link = upload_image_to_imgur(image_bytes)
+ ctx.logger.info(f"Image link from Imgur: {image_link}")
+ ctx.send(sender, UAgentResponse(message=image_link, type=UAgentResponseType.FINAL))
+ except Exception as ex:
+ ctx.logger.error(f"Error occurred during image generation: {ex}")
+ ctx.send(sender, UAgentResponse(message=str(ex), type=UAgentResponseType.ERROR))
+
+# Initialize the agent
+agent = Agent()
+
+# Include ImgGen_protocol
+agent.include(ImgGen_protocol, publish_manifest=True)
+
+# Include PromptGen_protocol if ImgGen_protocol is successfully included
+if ImgGen_protocol in agent.protocols:
+ agent.include(PromptGen_protocol, publish_manifest=True)

integrations/LiteraryIllustrator/src/messages/__init__.py

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+

integrations/LiteraryIllustrator/src/utils

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+