Create images for blogs - Stability AI

..env

@@ -0,0 +1,6 @@
+STABILITY_API_KEY=sk-Jdu0BrFe4tta19PDpU1AlpVAtE3eJlmGZiAYx61bNUZkAl4d
+STABILITY_API_KEY=sk-Jdu0BrFe4tta19PDpU1AlpVAtE3eJlmGZiAYx61bNUZkAl4d
+STABILITY_API_KEY=asada
+STABILITY_API_KEY=sk-Jdu0BrFe4tta19PDpU1AlpVAtE3eJlmGZiAYx61bNUZkAl4d
+STABILITY_API_KEY=sdsa
+STABILITY_API_KEY=sk-Jdu0BrFe4tta19PDpU1AlpVAtE3eJlmGZiAYx61bNUZkAl4d

alwrity.py

@@ -69,6 +69,7 @@ def start_interactive_mode():
         ("Competitor Analysis", "Competitor Analysis"),
         ("Create Blog Images", "Create Blog Images"),
         ("AI Social Media(TBD)", "AI Social Media(TBD)"),
+        ("AI Code Writer(TBD)", "AI Code Writer(TBD)"),
         ("Quit", "Quit")
     ]
     mode = radiolist_dialog(title="Choose an option:", values=choices).run()
@@ -98,6 +99,9 @@ def start_interactive_mode():
             #Linked-in posts
             """)
             raise typer.Exit()
+        elif mode == 'AI Code Writer(TBD)':
+            print("Coming soon, TBD")
+            raise typer.Exit()
         elif mode == 'Quit':
             typer.echo("Exiting, Getting Lost!")
             raise typer.Exit()
@@ -189,7 +193,7 @@ def check_llm_environs():
         # Update .env file
         os.environ["GPT_PROVIDER"] = gpt_provider
         with open(".env", "a") as env_file:
-            env_file.write(f"GPT_PROVIDER=gpt_provider\n")
+            env_file.write(f"GPT_PROVIDER={gpt_provider}\n")
             print(f"✅ API Key added to .env file.")
 
     if gpt_provider.lower() == "google":
@@ -241,7 +245,8 @@ if __name__ == "__main__":
     os.system("clear" if os.name == "posix" else "cls")
     check_search_apis()
     check_llm_environs()
-    os.environ["SEARCH_SAVE_FILE"] = os.path.join(os.getcwd(), "workspace",
+    os.environ["SEARCH_SAVE_FILE"] = os.path.join(os.getcwd(), "lib", "workspace") + "_" + datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
-            "web_research_report" + "_" + datetime.now().strftime("%Y-%m-%d_%H-%M-%S"))
+    os.environ["IMG_SAVE_DIR"] = os.path.join(os.getcwd(), "lib", "workspace")
+
     load_dotenv(Path('.env'))
     app()

lib/gpt_providers/text_to_image_generation/gen_stabl_diff_img.py

@@ -1,41 +1,56 @@
-from PIL import Image
-import requests
-
 # Ensure you sign up for an account to obtain an API key:
 # https://platform.stability.ai/
 # Your API key can be found here after account creation:
 # https://platform.stability.ai/account/keys
 
+import base64
+import os
+import requests
+from PIL import Image
+from io import BytesIO
+
+from .save_image import save_generated_image
+
 
 def generate_stable_diffusion_image(prompt):
-    """
+    engine_id = "stable-diffusion-xl-1024-v1-0"
-    Generate images using Stable Diffusion API based on a given prompt.
+    api_host = os.getenv('API_HOST', 'https://api.stability.ai')
+    api_key = os.getenv("STABILITY_API_KEY")
     
-    Args:
+    if api_key is None:
-        prompt (str): The prompt to generate the image.
+        raise Exception("Missing Stability API key.")
-        image_dir (str): The directory where the image will be saved.
-
-    Raises:
-        Warning: If the adult content classifier is triggered.
-        Exception: For any issues during image generation or saving.
-    """
-    api_key = os.getenv('STABILITY_API_KEY')
     
     response = requests.post(
-        f"https://api.stability.ai/v2beta/stable-image/generate/sd3",
+        f"{api_host}/v1/generation/{engine_id}/text-to-image",
         headers={
-            "authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json",
-            "accept": "image/*"
+            "Accept": "application/json",
+            "Authorization": f"Bearer {api_key}"
         },
-        files={"none": ''},
+        json={
-        data={
+            "text_prompts": [
-            "prompt": prompt,
+                {
-            "output_format": "webp",
+                    "text": prompt
+                }
+            ],
+            "cfg_scale": 7,
+            "height": 1024,
+            "width": 1024,
+            "samples": 1,
+            "steps": 30,
         },
     )
     
-    if response.status_code == 200:
+    if response.status_code != 200:
-        with open("./dog-wearing-glasses.jpeg", 'wb') as file:
+        raise Exception("Non-200 response: " + str(response.text))
-            file.write(response.content)
+    
-    else:
+    data = response.json()
-        raise Exception(str(response.json()))
+    save_generated_image(data)
+
+    for i, image in enumerate(data["artifacts"]):
+        # Decode base64 image data
+        img_data = base64.b64decode(image["base64"])
+        # Open image using PIL
+        img = Image.open(BytesIO(img_data))
+        # Display the image
+        img.show()  

lib/gpt_providers/text_to_image_generation/main_generate_image_from_prompt.py

@@ -23,9 +23,10 @@ logger.add(sys.stdout,
 #from .gen_dali2_images
 from .gen_dali3_images import generate_dalle3_images
 from .gen_stabl_diff_img import generate_stable_diffusion_image
+from ..text_generation.main_text_generation import llm_text_gen
 
 
-def generate_image(user_prompt, image_engine="dalle3"):
+def generate_image(user_prompt, image_engine):
     """
     The generation API endpoint creates an image based on a text prompt.
 
@@ -41,15 +42,17 @@ def generate_image(user_prompt, image_engine="dalle3"):
     Must be one of "url" or "b64_json". Defaults to "url".
     --> user (str): A unique identifier representing your end-user, which will help OpenAI to monitor and detect abuse.
     """
-    img_prompt = generate_img_prompt(user_prompt) 
+    try:
-    # call the OpenAI API to generate image from prompt.
+        img_prompt = generate_img_prompt(user_prompt)
-    logger.info(f"Calling image.generate with prompt: {img_prompt}")
+        if 'Dalle3' in image_engine:
-
+            logger.info(f"Calling Dalle3 text-to-image with prompt: {img_prompt}")
-    if 'Dalle3' in image_engine:
+            image_stored_at = generate_dalle3_images(img_prompt)
-        image_stored_at = generate_dalle3_images(img_prompt)
+        elif 'Stability-Stable-Diffusion' in image_engine:
-    elif 'Stable Diffusion' in image_engine:
+            logger.info(f"Calling Stable diffusion text-to-image with prompt: \n{img_prompt}")
-        image_stored_at = generate_stable_diffusion_image(img_prompt)
+            print("\n\n")
-
+            image_stored_at = generate_stable_diffusion_image(img_prompt)
+    except Exception as err:
+        logger.error(f"Failed to generate Image: {err}")
     return image_stored_at
 
 
@@ -57,17 +60,16 @@ def generate_img_prompt(user_prompt):
     """
     Given prompt, this functions generated a prompt for image generation.
     """
-    # I want you to act as an artist advisor providing advice on various art styles such tips on utilizing 
+    prompt = f"""
-    # light & shadow effects effectively in painting, shading techniques while sculpting etc.
+        As an expert prompt engineer and artist, I will provide you with 'text' for creating image.
-    # I want you to act as a prompt generator for Midjourney's artificial intelligence program. 
+        I want you to act as a prompt generator for AI text to image models(no more than 150 words).
-    # Your job is to provide detailed and creative descriptions that will inspire unique and interesting images from the AI. 
+        \n
-    # Here is your first prompt: ""
+        Choose from various art styles, utilize light & shadow effects etc.
-    logger.info(f"Generate image prompt for : {user_prompt}")
+        Make sure to avoid common image generation mistakes.
-    prompt = f"""As an educationist and expert infographic artist, your tasked to create prompts that will be used for image generation.
+        Reply with only one answer, no descrition and in plaintext.
-            Craft prompt for Openai Dall-e image generation program. Clearly describe the given text to represent it as image.
+        Make sure your prompt is detailed and creative descriptions that will inspire unique and interesting images from the AI. 
-            Make sure to avoid common image generation mistakes. 
+        
-            Advice for creating prompt for image from the given text(no more than 150 words).
+        \n\ntext:{user_prompt} """
-            Reply with only one answer and no descrition. Generate image prompt for the below text.
+
-            Text: {user_prompt}"""
+    response = llm_text_gen(prompt)
-    response = (prompt)
     return response

lib/gpt_providers/text_to_image_generation/save_image.py

@@ -1,35 +1,28 @@
+import base64
 import datetime
 import os
 import requests
 from PIL import Image
 import logging
 
-def save_generated_image(img_generation_response, image_dir):
+def save_generated_image(img_generation_response):
     """
     Save generated images for blog, ensuring unique names for SEO.
     """
     logging.basicConfig(level=logging.INFO)
     logger = logging.getLogger(__name__)
 
-    generated_image_name = f"generated_image_{datetime.datetime.now():%Y-%m-%d-%H-%M-%S}.png"
+    generated_image_name = f"generated_image_{datetime.datetime.now():%Y-%m-%d-%H-%M-%S}.webp"
-    generated_image_filepath = os.path.join(image_dir, generated_image_name)
+    generated_image_filepath = os.path.join(os.getenv('IMG_SAVE_DIR'), generated_image_name)
-    generated_image_url = img_generation_response.data[0].url
 
-    logger.info(f"Fetch the image from url: {generated_image_url}")
     try:
-        response = requests.get(generated_image_url, stream=True)
+        for i, image in enumerate(img_generation_response["artifacts"]):
-        response.raise_for_status()
+            with open(generated_image_filepath, "wb") as f:
-        with open(generated_image_filepath, "wb", encoding="utf-8") as image_file:
+                f.write(base64.b64decode(image["base64"]))
-            image_file.write(response.content)
     except requests.exceptions.RequestException as e:
         logger.error(f"Failed to get generated image content: {e}")
         return None
 
     logger.info(f"Saved image at path: {generated_image_filepath}")
 
-    if os.environ.get('DISPLAY', ''):  # Check if display is supported
-        img = Image.open(generated_image_filepath)
-        img.show()
-
     return generated_image_filepath
-

lib/utils/alwrity_utils.py

@@ -8,6 +8,8 @@ from prompt_toolkit import prompt
 from prompt_toolkit.completion import WordCompleter
 from prompt_toolkit.validation import Validator, ValidationError
 from prompt_toolkit.shortcuts import radiolist_dialog
+import typer
+from rich import print
 
 from lib.ai_web_researcher.gpt_online_researcher import gpt_web_researcher
 from lib.ai_web_researcher.metaphor_basic_neural_web_search import metaphor_find_similar
@@ -15,7 +17,7 @@ from lib.ai_writers.keywords_to_blog import write_blog_from_keywords
 from lib.ai_writers.speech_to_blog.main_audio_to_blog import generate_audio_blog
 from lib.gpt_providers.text_generation.ai_story_writer import ai_story_generator
 from lib.gpt_providers.text_generation.ai_essay_writer import ai_essay_generator
-from lib.gpt_providers.text_to_image_generation.generate_image_from_prompt import generate_image
+from lib.gpt_providers.text_to_image_generation.main_generate_image_from_prompt import generate_image
 
 
 def blog_from_audio():
@@ -270,7 +272,21 @@ def image_generator():
     print("Choose between:: Stable-Diffusion, Dalle2, Dalle3")
     img_model = prompt('Choose the image model to use for generation: ', completer=img_models, validator=ModelTypeValidator())
 
-    print(f"{img_prompt}----{img_model}")
+    if 'Stability-Stable-Diffusion' in img_model:
+        api_key = 'STABILITY_API_KEY'
+    elif 'Dalle3' in img_model:
+        api_key = 'OPENAI_API_KEY'
+
+    if os.getenv(api_key) is None:
+        print(f"\n\n[bold green] 🙋 Get {api_key} Here:https://platform.stability.ai/docs/getting-started 🙋 -- \n")
+        user_input = typer.prompt(f"💩 -**Please Enter(copy/paste) {api_key} Key** - Here🙋:")
+        os.environ[api_key] = user_input
+        try:
+            with open(".env", "a") as env_file:
+                env_file.write(f"{api_key}={user_input}\n")
+                print(f"✅ API Key added to .env file.")
+        except Exception as err:
+            print(f"Error: {err}")
     try:
         generate_image(img_prompt, img_model)
     except Exception as err: