Refactor image handling by moving image generation and verification to a new module, and update post creation to use the new fetch_image function

image.py

@@ -0,0 +1,78 @@
+import base64
+import pollinations as ai
+from PIL import Image
+import io
+import re
+import requests
+
+def extract_summary(text):
+    text = text.replace("#", "").strip().lower()
+    match = re.search(r"summary(.*?)highlights", text.replace("#", ""), re.DOTALL)
+    if match:
+        return match.group(1).replace("#", "").replace("\n", "").strip()
+    return None
+
+def generate_image(title, summary):
+    try:
+        extracted_summary = extract_summary(summary)
+        if not extracted_summary:
+            extracted_summary = summary
+        data = r"{}: {}".format(title.replace("{", "").replace("}","").replace("\n", ""), extracted_summary).strip().replace("&", "&").replace("{", "").replace("}","").replace("\n", "")
+        model_obj = ai.ImageModel(
+            model=ai.turbo,
+            width=1280,
+            height=720,
+            seed=2342342340,
+            enhance=True,
+            nologo=True
+        )
+        print(data)
+        model_obj.generate(
+            prompt=r"{}".format(data),
+            negative=("a bad image, low res, low quality, pixelated, blurry, bad lighting, bad angle, bad composition, bad focus, bad exposure, bad white balance, bad color, bad contrast, bad saturation, bad sharpness, bad noise, bad artifacts, bad framing, bad cropping, bad editing, bad filter, bad lens, bad camera, bad sensor, bad settings, bad post-processing, bad retouching, bad enhancement, bad manipulation, bad distortion, bad watermark, bad logo, bad text, bad overlay, bad background"),
+            save=True,
+            file="image.png"
+        )
+        with open("image.png", "rb") as image_file:
+            image_data = image_file.read()
+            base64_encoded = base64.b64encode(image_data).decode('utf-8')
+            data_uri = f"data:image/png;base64,{base64_encoded}"
+        return r"{}".format(data_uri).strip()
+    except Exception as e:
+        return f"An error occurred: {e}"
+
+def verify_image(image_data):
+    try:
+        image_stream = io.BytesIO(image_data)
+        image = Image.open(image_stream)
+        image.verify()
+        image_stream.seek(0)
+        image = Image.open(image_stream)
+        return True
+    except Exception as e:
+        print(f"Error verifying image: {e}")
+        return False
+
+def upload_image(data_uri, api_key):
+    try:
+        # Strip the `data:image/png;base64,` prefix
+        base64_image = data_uri.split(",")[1]
+        url = f'https://api.imgbb.com/1/upload?key={api_key}'
+        response = requests.post(url, data={'image': base64_image}).json()
+        print(response)
+        if response.get('status') == 200:
+            return response['data']['url']
+        else:
+            return "https://i.ibb.co/qdC1nSx/landscape-placeholder-e1608289113759.png"
+    except Exception as e:
+        print(f"Error uploading image: {e}")
+        return "https://i.ibb.co/qdC1nSx/landscape-placeholder-e1608289113759.png"
+
+def fetch_image(title, summary, api_key):
+    image_url = "https://i.ibb.co/qdC1nSx/landscape-placeholder-e1608289113759.png"
+    data_uri = generate_image(title, summary)
+    image_data = base64.b64decode(data_uri.split(",")[1])
+    if verify_image(image_data):
+        image_url = upload_image(data_uri, api_key)
+    return image_url
+

post_blog.py

@@ -1,12 +1,11 @@
 import re
 import os
-import time
-from urllib.parse import quote
-import base64
 import requests
 import dotenv
 import mistune
 
+from image import fetch_image
+
 dotenv.load_dotenv()
 access_key = os.getenv('ACCESS_KEY')
 client_id = os.getenv('CLIENT_ID')
@@ -14,64 +13,12 @@ client_secret = os.getenv('CLIENT_SECRET')
 refresh_token = os.getenv('REFRESH_TOKEN')
 blog_id = os.getenv('BLOG_ID')
 
-def extract_summary(text):
-    text = text.replace("#", "").strip().lower()
-    match = re.search(r"summary(.*?)highlights", text.replace("#", ""), re.DOTALL)
-    if match:
-        return match.group(1).replace("#", "").replace("\n", "").strip()
-    return None
-
-from PIL import Image
-import io
-
-def verify_image(image_data):
-    try:
-        image_stream = io.BytesIO(image_data)
-        image = Image.open(image_stream)
-        image.verify()
-        image_stream.seek(0)
-        image = Image.open(image_stream)
-        return True
-    except Exception as e:
-        print(f"Error verifying image: {e}")
-        return False
-
-def generate_image(title, summary):
-    default_image = "https://i.ibb.co/qdC1nSx/landscape-placeholder-e1608289113759.png"
-    extracted_summary = extract_summary(summary)
-    if extracted_summary is None:
-        extracted_summary = title
-    data = quote(f"{title} : {extracted_summary}")
-    url = f"https://image.pollinations.ai/prompt/{data}?width=1280&height=720&seed=623862700&nologo=true&model=turbo"
-    headers = {
-        "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
-        "accept-language": "en-US,en-GB;q=0.9,en;q=0.8",
-        "cache-control": "max-age=0",
-        "priority": "u=0, i",
-        "sec-ch-ua": "\"Google Chrome\";v=\"131\", \"Chromium\";v=\"131\", \"Not_A Brand\";v=\"24\"",
-        "sec-ch-ua-mobile": "?1",
-        "sec-ch-ua-platform": "\"Android\"",
-        "sec-fetch-dest": "document",
-        "sec-fetch-mode": "navigate",
-        "sec-fetch-site": "none",
-        "sec-fetch-user": "?1",
-        "upgrade-insecure-requests": "1",
-    }
-    response = requests.get(url, headers=headers)
-    if response.status_code != 200:
-        print(f"Failed to fetch image. Status code: {response.status_code}")
-        return default_image
-    elif not verify_image(response.content):
-        return default_image
-    else:
-        return url    
-
 def generate_post_html(title, summary, mindmap, citation):
-    title = title.replace("{", r"{{").replace("}", r"}}")
-    summary = summary.replace("{", r"{{").replace("}", r"}}")
-    mindmap = mindmap.replace("{", r"{{").replace("}", r"}}")
-    citation = citation.replace("{", r"{{").replace("}", r"}}")
-    image = generate_image(title, summary)
+    title = title.replace("{", r'{').replace("}", r'}')
+    summary = summary.replace("{", r'{').replace("}", r'}')
+    mindmap = mindmap.replace("{", r'{').replace("}", r'}')
+    citation = citation.replace("{", r'{').replace("}", r'}')
+    image = fetch_image(title, summary, os.getenv('IMGBB_API_KEY'))
     html_summary = mistune.html(summary)
     post = f"""
 <div>
@@ -139,9 +86,10 @@ def post_post(title, category, body, image):
             }],
             "title": title,
             "content": body,
-            "labels": [category, "recent"]
+            "labels": [category, "ZZZZZZZZZ"]
         }
         data = requests.post(url, headers=headers, json=post_data).json()
+        print(data)
         if data['status'] == 'LIVE':
             print(f"The post '{title}' is {data['status']}")
             return True
@@ -156,10 +104,11 @@ def post_blog(title, category, summary, mindmap, citation, uaccess_key):
     if uaccess_key != access_key:
         return False
     else:
+        status = True
         post_title, post_category, post_body, post_image = create_post(title, category, summary, mindmap, citation)
         status = post_post(post_title, post_category, post_body, post_image)
-        print(f"Waiting for {2*60} seconds...")
-        time.sleep(2*60)
+        # print(f"Waiting for {2*60} seconds...")
+        # time.sleep(2*60)
         if status:
             print('Post created successfully')
             return True
@@ -174,7 +123,7 @@ def test(access_key):
                 "2412.16344": {
                     "id": "2412.16344",
                     "doi": "https://doi.org/10.48550/arXiv.2412.16344",
-                    "title": "On the Interplay of Constraints from $B_s$, $D$, and $K$ Meson Mixing in $Z^\\prime$ Models with Implications for $b\to s ν\barν$ Transitions",
+                    "title": "Analytic 3D vector non-uniform Fourier crystal optics in arbitrary $\bar{\bar{\varepsilon}}$ dielectric",
                     "category": "Astrophysics",
                     "citation": "Grant, C. E., Bautz, M. W., Miller, E. D., Foster, R. F., LaMarr, B., Malonis, A., Prigozhin, G., Schneider, B., Leitz, C., &amp; Falcone, A. D. (2024). Focal Plane of the Arcus Probe X-Ray Spectrograph. ArXiv. https://doi.org/10.48550/ARXIV.2412.16344",
                     "summary": "## Summary\nThe Arcus Probe mission concept provides high-resolution soft X-ray and UV spectroscopy to study the universe. The X-ray Spectrograph (XRS) uses two CCD focal planes to detect and record X-ray photons. Laboratory performance results meet observatory requirements.\n\n## Highlights\n- The Arcus Probe mission concept explores the formation and evolution of clusters, galaxies, and stars.\n- The XRS instrument includes four parallel optical channels and two detector focal plane arrays.\n- The CCDs are designed and manufactured by MIT Lincoln Laboratory (MIT/LL).\n- The XRS focal plane utilizes high heritage MIT/LL CCDs with proven technologies.\n- Laboratory testing confirms CCID-94 performance meets required spectral resolution and readout noise.\n- The Arcus mission includes two co-aligned instruments working simultaneously.\n- The XRS Instrument Control Unit (XICU) controls the activities of the XRS.\n\n## Key Insights\n- The Arcus Probe mission concept provides a significant improvement in sensitivity and resolution over previous missions, enabling breakthrough science in understanding the universe.\n- The XRS instrument's design, including the use of two CCD focal planes and four parallel optical channels, allows for high-resolution spectroscopy and efficient detection of X-ray photons.\n- The CCDs used in the XRS instrument are designed and manufactured by MIT Lincoln Laboratory (MIT/LL), which has a proven track record of producing high-quality CCDs for space missions.\n- The laboratory performance results of the CCID-94 device demonstrate that it meets the required spectral resolution and readout noise for the Arcus mission, indicating that the instrument is capable of achieving its scientific goals.\n- The XRS Instrument Control Unit (XICU) plays a crucial role in controlling the activities of the XRS, including gathering and storing data, and processing event recognition.\n- The Arcus mission's use of two co-aligned instruments working simultaneously allows for a wide range of scientific investigations, including the study of time-domain science and the physics of time-dependent phenomena.\n- The high heritage MIT/LL CCDs used in the XRS focal plane provide a reliable and efficient means of detecting X-ray photons, enabling the instrument to achieve its scientific goals.",
@@ -199,5 +148,4 @@ def test(access_key):
                     return status
                 
 if __name__ == '__main__':
-    # test(access_key)
-    print(generate_image("title", "summary summaryyyyyy highlights"))
+    test(access_key)