more agent and mcp friendly

app.py

@@ -1,6 +1,7 @@
 import os
 import sys
 import subprocess
+
 import torch
 
 
@@ -12,7 +13,6 @@ def clone_if_missing(path, repo, branch=None):
     if branch:
         cmd += ["-b", branch]
     cmd += [repo, path]
-
     subprocess.run(cmd, check=True)
 
 
@@ -21,7 +21,6 @@ clone_if_missing(
     "https://github.com/pharmapsychotic/BLIP.git",
     branch="lib",
 )
-
 clone_if_missing(
     "clip-interrogator",
     "https://github.com/pharmapsychotic/clip-interrogator.git",
@@ -31,9 +30,7 @@ clone_if_missing(
 sys.path.append("src/blip")
 sys.path.append("clip-interrogator")
 
-
 print("Download preprocessed cache files...")
-
 CACHE_URLS = [
     "https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_artists.pkl",
     "https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_flavors.pkl",
@@ -41,13 +38,10 @@ CACHE_URLS = [
     "https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_movements.pkl",
     "https://huggingface.co/pharma/ci-preprocess/resolve/main/ViT-H-14_laion2b_s32b_b79k_trendings.pkl",
 ]
-
 os.makedirs("cache", exist_ok=True)
-
 for url in CACHE_URLS:
     subprocess.run(["wget", "-nc", url, "-P", "cache"], check=False)
 
-
 import gradio as gr
 from clip_interrogator import Config, Interrogator
 
@@ -62,47 +56,50 @@ config.blip_num_beams = 64
 ci = Interrogator(config)
 
 
-def inference(image, mode, best_max_flavors):
-    if image is None:
-        return "Please upload an image."
+def generate_image_prompt(input_image, interrogation_mode: str, best_mode_max_flavors):
+    """
+    Generate a Stable Diffusion 2.0 prompt description from an input image.
+
+    Use this tool when you need to interrogate an image with CLIP Interrogator 2.1 and produce a text prompt.
 
-    image = image.convert("RGB")
+    Args:
+        input_image: PIL image to describe.
+        interrogation_mode (str): Interrogation mode to use: best, classic, or fast.
+        best_mode_max_flavors: Maximum number of flavors used only when interrogation_mode is best.
 
-    if mode == "best":
-        result = ci.interrogate(image, max_flavors=int(best_max_flavors))
-    elif mode == "classic":
-        result = ci.interrogate_classic(image)
+    Returns:
+        str: Generated prompt description, or an upload prompt when no image is provided.
+    """
+    if input_image is None:
+        return "Please upload an image."
+
+    input_image = input_image.convert("RGB")
+    if interrogation_mode == "best":
+        result = ci.interrogate(input_image, max_flavors=int(best_mode_max_flavors))
+    elif interrogation_mode == "classic":
+        result = ci.interrogate_classic(input_image)
     else:
-        result = ci.interrogate_fast(image)
+        result = ci.interrogate_fast(input_image)
 
-    print(f"mode {mode}: {result}")
+    print(f"mode {interrogation_mode}: {result}")
     return result
 
 
 title = """
-<div style="text-align: center; max-width: 500px; margin: 0 auto;">
-    <h1 style="font-weight: 600;">CLIP Interrogator 2.1</h1>
-    <p style="font-size: 94%; font-weight: 100; line-height: 1.5em;">
-        Want to figure out what a good prompt might be to create new images like an existing one?
-        <br />The CLIP Interrogator is here to get you answers!
-        <br />This version is specialized for Stable Diffusion 2.0 using the ViT-H-14 OpenCLIP model.
-    </p>
-</div>
+# CLIP Interrogator 2.1
+
+Want to figure out what a good prompt might be to create new images like an existing one?
+The CLIP Interrogator is here to get you answers!
+This version is specialized for Stable Diffusion 2.0 using the ViT-H-14 OpenCLIP model.
+
 """
 
 article = """
-<div style="text-align: center; max-width: 500px; margin: 0 auto; font-size: 94%;">
-    <p>
-        Server busy? You can also run on
-        <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/open-clip/clip_interrogator.ipynb">Google Colab</a>
-    </p>
-    <p>
-        Follow Pharma on twitter
-        <a href="https://twitter.com/pharmapsychotic">@pharmapsychotic</a>
-        and check out more tools at
-        <a href="https://pharmapsychotic.com/tools.html">Ai generative art tools list</a>
-    </p>
-</div>
+
+Server busy? You can also run on [Google Colab](https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/open-clip/clip_interrogator.ipynb)
+
+Follow Pharma on twitter [@pharmapsychotic](https://twitter.com/pharmapsychotic) and check out more tools at [Ai generative art tools list](https://pharmapsychotic.com/tools.html)
+
 """
 
 css = """
@@ -111,27 +108,23 @@ css = """
     margin-left: auto;
     margin-right: auto;
 }
-
 a {
     text-decoration-line: underline;
     font-weight: 600;
 }
 """
 
-
-with gr.Blocks(css=css) as demo:
+with gr.Blocks() as demo:
     with gr.Column(elem_id="col-container"):
         gr.HTML(title)
 
         input_image = gr.Image(type="pil", elem_id="input-img")
-
         with gr.Row():
             mode_input = gr.Radio(
                 ["best", "classic", "fast"],
                 label="Select mode",
                 value="best",
             )
-
             flavor_input = gr.Slider(
                 minimum=2,
                 maximum=24,
@@ -141,7 +134,6 @@ with gr.Blocks(css=css) as demo:
             )
 
         submit_btn = gr.Button("Submit")
-
         output_text = gr.Textbox(
             label="Description Output",
             elem_id="output-txt",
@@ -151,10 +143,9 @@ with gr.Blocks(css=css) as demo:
             ["27E894C4-9375-48A1-A95D-CB2425416B4B.png", "best", 4],
             ["DB362F56-BA98-4CA1-A999-A25AA94B723B.png", "fast", 4],
         ]
-
         gr.Examples(
             examples=examples,
-            fn=inference,
+            fn=generate_image_prompt,
             inputs=[input_image, mode_input, flavor_input],
             outputs=[output_text],
             cache_examples=False,
@@ -163,16 +154,16 @@ with gr.Blocks(css=css) as demo:
 
         gr.HTML(article)
 
-    submit_btn.click(
-        fn=inference,
-        inputs=[input_image, mode_input, flavor_input],
-        outputs=output_text,
-        api_name="clipi2",
-    )
-
+        submit_btn.click(
+            fn=generate_image_prompt,
+            inputs=[input_image, mode_input, flavor_input],
+            outputs=output_text,
+            api_name="clipi2",
+        )
 
 demo.queue(max_size=32).launch(
     footer_links=["api"],
     ssr_mode=False,
     mcp_server=True,
+    css=css,
 )