added few shots examples.

agents.py

@@ -29,7 +29,7 @@ SmolagentsInstrumentor().instrument(tracer_provider=trace_provider)
 HUGGING_FACE_TOKEN = os.environ["HUGGING_FACE_TOKEN"]
 
 image_operator_model = InferenceClientModel(
-    model_id="Qwen/Qwen3-14B", provider="nebius", token=HUGGING_FACE_TOKEN, max_tokens=5000
+    model_id="Qwen/Qwen3-32B", provider="nebius", token=HUGGING_FACE_TOKEN, max_tokens=5000
 )
 
 picture_operator_prompt = """
@@ -56,6 +56,210 @@ picture_operator_prompt = """
     Once all enhancements are satisfactory, your task is complete.
     You must call to conversion function rgb_to_hsl and hsl_to_rgb only once for each.
     You will be fined every time you exceed 1 call for each function.
+    You must save the image only once.
+
+    The code must be structured as follows :
+    1. You load the image
+    2. You call the needed that take a rgb image as input
+    3. You convert the image into h, s, li canals
+    4. You adjust the saturation, luminance and hue of color channels
+    5. You convert back into r,g,b
+    6. You save the rgb image
+
+    Examples:
+    Prompt: Increase contrast by a lot and orange saturation by a bit.
+    Answer:
+    img = load_image(path=image_path)
+
+    # Apply strong contrast adjustment
+    img = adjust_contrast(
+        img=img,
+        factor=1.1  # 1.1 is considered a lot per tool documentation
+    )
+
+    # Convert to HSL for color-specific adjustments
+    h, s, li = rgb_to_hsl(img)
+
+    # Enhance orange saturation slightly
+    h, s, li = adjust_saturation_color(
+        h=h,
+        s=s,
+        li=li,
+        color='orange',
+        factor=0.2)
+    # Convert back to RGB
+
+    # Save the result
+    save_image(
+        h, s, li
+        output_directory=output_directory
+    )
+    critic(output_directory=output_path,
+            original_image_path=image_path,
+            user_prompt=user_query,
+            list_of_enhancements=enhancements)
+
+
+
+    Prompt 2: increase contrast by a lot, raise saturation medium,
+    add some vignetage, a very little of grain,
+    raise the exposition by a tiny bit,
+    raise the orange saturation by a bit, the blue yellow and green luminance by a lot
+
+    Answer:
+    img = load_image(path=image_path)
+
+    # Convert back to RGB and apply global adjustments
+    img = adjust_contrast(img, factor=1.5)  # Increase contrast a lot
+    img = adjust_saturation(img, factor=1.2)  # Medium saturation increase
+    img = adjust_exposure(img, ev=0.05)  # Tiny exposure increase
+    img = add_vignette(img, strength=0.5)  # Add some vignette
+    img = add_grain(img, amount=0.01)  # Add very little grain
+
+    h, s, li = rgb_to_hsl(img)
+    # Adjust orange saturation by a bit
+    h, s, li = adjust_saturation_color(h, s, li, color='orange', factor=1.1)
+
+    # Increase luminance for blue, yellow, and green by a lot (factor=2)
+    for color in ['blue', 'yellow', 'green']:
+        h, s, li = adjust_luminance_color(h, s, li, color=color, factor=2)
+
+    # Save the processed image
+    save_image(h, s, li, output_directory=output_directory)
+
+    # Final confirmation
+    critic(output_directory=output_path,
+            original_image_path=image_path,
+            user_prompt=user_query,
+            list_of_enhancements=enhancements)
+
+
+    Prompt 3:
+    Here’s my proposal to enhance the image with a vibrant,
+    Instagram-style aesthetic while preserving its serene energy:
+    **1.    Global Adjustments**
+    **Contrast**: Slightly increased to add depth to the balloons'
+    patterns without flattening the sky's gradient.
+    **Exposure**: Brightened moderately to amplify the sunlit atmosphere,
+    especially on the foreground balloon's geometric design.
+    **Saturation**: Boosted a lot to intensify the mosaic of colors
+    (red, orange, yellow, green, blue) on the balloons, making them feel more dynamic.
+    **Temperature**: Warmed up to enhance the golden-hour glow, complementing the balloons' warm gradients.
+    **Shadows/Highlights**: Shadows lifted slightly to reveal texture
+    in the balloon fabrics, while highlights are tamed
+    to avoid blowing out the sky's delicate clouds.
+    **2. Color-Specific Tweaks**
+    **Red**: Boosted saturation significantly for the background Red Bull
+    balloon to make the brand text pop, while slightly increasing
+    luminance to prevent it from feeling too heavy.
+    **Orange**: Enhanced hue slightly, shifting toward amber to deepen the
+    middle balloon's gradient, adding warmth without muddiness.
+    **Blue**: Adjusted hue to a richer cobalt tone in the foreground balloon's
+    pattern, making the geometric shapes stand out against warmer hues.
+    **Green**: Increased luminance moderately in the foreground balloon's
+    green sections to balance the vibrant reds and oranges.
+    **3. Subtle Textures**
+    **Vignette**: Applied barely, with a subtle darkening at the corners
+    to frame the balloons without distracting from the sky's serenity.
+    **Grain**: Omitted entirely—this scene’s tranquility works best with a clean, smooth finish.
+    **Result**: A luminous, hyper-saturated scene where the balloons’ colors
+    feel bolder and more immersive, the sky appears crisper,
+    and the overall mood is elevated to evoke joyful adventure.
+    The adjustments amplify the image’s natural vibrancy
+    without sacrificing its peaceful essence.
+
+
+    Answer:
+    img = load_image(path=image_path)
+
+    # Apply global adjustments in RGB space
+    img = adjust_exposure(
+        img=img,
+        ev=0.1  # Moderate brightening for golden-hour amplification
+    )
+
+    img = adjust_contrast(
+        img=img,
+        factor=1.05  # Slightly increased depth for balloon patterns
+    )
+
+    img = adjust_saturation(
+        img=img,
+        factor=1.5  # "Boosted a lot" to enhance vibrancy
+    )
+
+    img = adjust_temperature(
+        img=img,
+        delta=500  # Warm up by 500 mireds for golden-hour glow
+    )
+
+    img = adjust_shadows_highlights(
+        img=img,
+        shadow=1.1,  # Slight shadow lifting to reveal textures
+        highlight=0.9  # Tame highlights to preserve sky colors
+    )
+
+    img = add_vignette(
+        img=img,
+        strength=0.3  # Subtle corner darkening for framing effect
+    )
+
+    # Convert to HSL for color-specific adjustments
+    h, s, li = rgb_to_hsl(img)
+
+    # Red color tweaks: Boost saturation and luminance
+    h, s, li = adjust_saturation_color(
+        h=h,
+        s=s,
+        li=li,
+        color='red',
+        factor=1.3  # "Significantly" boosted saturation
+    )
+    h, s, li = adjust_luminance_color(
+        h=h,
+        s=s,
+        li=li,
+        color='red',
+        factor=1.1  # Slight luminance lift to avoid heaviness
+    )
+
+    # Orange hue shift toward amber
+    h, s, li = adjust_hue_color(
+        h=h,
+        s=s,
+        li=li,
+        color='orange',
+        delta=15  # 15° shift = slight hue adjustment
+    )
+
+    # Blue hue adjustment to cobalt
+    h, s, li = adjust_hue_color(
+        h=h,
+        s=s,
+        li=li,
+        color='blue',
+        delta=15  # Slight shift to richer tones
+    )
+
+    # Green luminance increase for balance
+    h, s, li = adjust_luminance_color(
+        h=h,
+        s=s,
+        li=li,
+        color='green',
+        factor=1.2  # Moderate luminance lift for balance
+    )
+
+    # Save final enhanced image
+    save_image(
+        h=h, s=s, li=li,
+        output_directory=output_path
+    )
+
+    critic(output_directory=output_path,
+            original_image_path=image_path,
+            user_prompt=user_query,
+            list_of_enhancements=enhancements)
     """
 
 picture_operator = CodeAgent(
@@ -75,7 +279,6 @@ picture_operator = CodeAgent(
         flt.load_image,
         jdg.critic,
         flt.rgb_to_hsl,
-        flt.hsl_to_rgb,
     ],
     model=image_operator_model,
     name="PictureOperator",

filters.py

@@ -211,7 +211,6 @@ def rgb_to_hsl(img: Image.Image) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
     return h, s, li
 
 
-@tool
 def hsl_to_rgb(h: np.ndarray, s: np.ndarray, li: np.ndarray) -> np.ndarray:
     """Vectorised HSL→RGB conversion.
 
@@ -412,19 +411,22 @@ def add_grain(img: Image.Image, amount: float = 0.05) -> Image.Image:
 
 
 @tool
-def save_image(img: Image.Image, output_directory: str) -> None:
-    """Save a PIL image as a JPEG file in the specified directory.
+def save_image(h: np.ndarray, s: np.ndarray, li: np.ndarray, output_directory: str) -> None:
+    """Save an HSL image as a JPEG file in the specified directory.
 
     The image will be saved with a filename of the form "trial_N.jpeg", where N is the
     current count of JPEG files in the directory.
 
     Args:
-        img (PIL.Image.Image): Image to save.
+        h (np.ndarray): Hue channel `[0, 1]`.
+        s (np.ndarray): Saturation channel `[0, 1]`.
+        li (np.ndarray): Lightness channel `[0, 1]`.
         output_directory (str): Path to the output directory.
 
     Returns:
         str: The full path to the saved image file.
     """
+    img = hsl_to_rgb(h, s, li)
     nb_iter = str(len([f for f in os.listdir(output_directory) if f.endswith(".jpeg")]))
     output_path = os.path.join(output_directory, f"trial_{nb_iter}.jpeg")
     img.save(output_path, format="JPEG", quality=95)