Image Generation Chat App using Amazon Nova Canvas

 or higher and create a development directory.

Install the following packages with

 ```pip install -r requirements.txt```

.



```requirements.txt
boto3==1.38.6
streamlit==1.45.0

import base64
import json
import os
import random
import boto3
import streamlit as st

REGION = "us-east-1"
IMG_MODEL_ID = "amazon.nova-canvas-v1:0"
TXT_MODEL_ID = "anthropic.claude-3-haiku-20240307-v1:0"

@st.cache_resource
def get_bedrock_client():
    return boto3.client(service_name="bedrock-runtime", region_name=REGION)

def generate_image(native_message, image_size, image_num, system_prompt, ng_text):
    """Generate images"""
    message = system_prompt + native_message
    print(f'textToImageParams: {message}')

    seed = random.randint(0, 858993460)
    native_request = {
        "taskType": "TEXT_IMAGE",
        "textToImageParams": {
            "text": message,
            "negativeText": ng_text
        },
        "imageGenerationConfig": {
            "seed": seed,
            "quality": "standard",
            "height": image_size,
            "width": image_size,
            "cfgScale": 10,
            "numberOfImages": image_num,
        },
    }
    request = json.dumps(native_request)

    bedrock_client = get_bedrock_client()
    response = bedrock_client.invoke_model(modelId=IMG_MODEL_ID, body=request)
    model_response = json.loads(response["body"].read())

    image_path_list = []
    for base64_image_data in model_response["images"]:

        # Save image to local folder
        i, output_dir = 1, "output"
        if not os.path.exists(output_dir):
            os.makedirs(output_dir)
        while os.path.exists(os.path.join(output_dir, f"nova_canvas_{i}.png")):
            i += 1

        image_data = base64.b64decode(base64_image_data)        
        image_path = os.path.join(output_dir, f"nova_canvas_{i}.png")
        with open(image_path, "wb") as file:
            file.write(image_data)

        print(f"The generated image has been saved to {image_path}")
        image_path_list.append(image_path)

    return image_path_list


def textract_from_input(message):
    """Translate Japanese instructions in chat to English and extract key words.
    This process uses foundational models like Haiku or Sonnet for text processing, not Nova Canvas.
    """
    bedrock_client = get_bedrock_client()
    system_prompt = "Translate Other language to English and extract key English words from the translated sentence. "\
    "Extract less than 10 meaningful English words, separated by commas. "\
    "Do not include prepositions or articles. "\
    "<examleInput>かわいい猫と女の子が楽しく遊んでいる</examleInput>"\ # example of Japanese
    "<examleOutput>cute cat, girl, play, joyful</examleOutput>"

    message = {
        "role": "user",
        "content": [{"text": message}]
    }
    messages = [message]
    system_prompts = [{"text" : system_prompt}]

    inference_config = {"temperature": 0.5}
    additional_model_fields = {"top_k": 200}

    response = bedrock_client.converse(
        modelId=TXT_MODEL_ID,
        messages=messages,
        system=system_prompts,
        inferenceConfig=inference_config,
        additionalModelRequestFields=additional_model_fields
    )
    words = response["output"]["message"]["content"][0]["text"]
    return words


def display_history(messages):
    """Display chat history"""
    for message in messages:
        display_img_content(message)


def display_img_content(message):
    """Display message and images
    Handles multiple images generated by Nova
    """
    contents = message["content"]
    print(f'message contents: {contents}')
    with st.chat_message(message["role"]):
        for content in contents:
            if content.get('text', None) != None:
                st.write(content["text"])
            else:
                st.image(content["image"])


def sidebar():
    """Display sidebar"""
    with st.sidebar:
        st.sidebar.title("Image Settings")

        # Image size
        image_size = st.sidebar.slider(
            "Image Size",
            min_value=320,
            max_value=960,
            step=64,
            value=320
        )

        # Number of images
        image_number = st.sidebar.slider(
            "Number of Images",
            min_value=1,
            max_value=5,
            step=1,
            value=1
        )

        # System prompt
        system_prompt = st.sidebar.text_area(
            "System Prompt",
            value="minimalist icon, simple, flat design, dual-line design, 1.5px stroke weight line, "\
            "solid background, monochromatic, 2D, ",
            height=200
        )

        # Negative prompt
        negative_text = st.sidebar.text_area(
            "Negative Prompt",
            value="3D, color, photo, multiple images",
            height=100
        )

        return image_size, image_number, system_prompt, negative_text


def main():
    """Main process"""
    st.title("Simple Icon Generator by Nova Canvas")
    img_size, img_num, system_prompt, negative_text = sidebar()

    if "messages" not in st.session_state:
        st.session_state.messages = []

    display_history(st.session_state.messages)

    if prompt := st.chat_input("What's up?"):
        input_msg = {"role": "user", "content": [{"text": prompt}]}
        display_img_content(input_msg)
        st.session_state.messages.append(input_msg)
        print(f'st.session_state.messages: {st.session_state.messages}')

        # Expand input content
        print(f'input_msg: {input_msg}')
        textract_resp = textract_from_input(input_msg["content"][0]["text"])
        print(f'texttract: {textract_resp}')

        # Generate images
        resp_img_path_list = generate_image(
            textract_resp, img_size, img_num, system_prompt, negative_text
        )

        resp_img_contents = []
        for resp_img_path in resp_img_path_list:
            resp_img_contents.append({"text": f"Image created! filepath: {resp_img_path}"})
            resp_img_contents.append({"image": resp_img_path})
        resp_msg = {
            "role": "assistant",
            "content": resp_img_contents
        }
        display_img_content(resp_msg)
        st.session_state.messages.append(resp_msg)


if __name__ == "__main__":
    main()

streamlit run nova_canvas_chat.py --server.port 8080