Spaces:
Running
Running
Change response parsing
Browse files
app.py
CHANGED
@@ -52,7 +52,7 @@ def create_prompt_for_image_generation(user_prompt: str) -> str:
|
|
52 |
3. Color Palette: Include details about the dominant colors or overall color scheme.
|
53 |
4. Perspective and Camera Details: Mention the point of view (e.g., wide-angle, close-up), camera type, lens, aperture, and lighting conditions if applicable.
|
54 |
5. Additional Details: Highlight any specific objects, text, or unique features with clear emphasis (e.g., 'with green text' or 'emphasis on golden hour lighting').
|
55 |
-
6. Output Settings: Suggest aspect ratio, output format (e.g.,
|
56 |
Ensure that the generated prompt is logical, descriptive, and written in natural language to maximize compatibility with FLUX-Schnell capabilities.
|
57 |
Example Input:
|
58 |
An image of a serene forest with a small cabin.
|
@@ -64,7 +64,7 @@ def create_prompt_for_image_generation(user_prompt: str) -> str:
|
|
64 |
The color palette includes rich greens, warm browns for the cabin, and soft gray mist.
|
65 |
The perspective is slightly elevated as if viewed from a drone camera at sunrise,
|
66 |
capturing golden hour lighting for soft shadows and warm highlights.
|
67 |
-
The aspect ratio is 1:1, using seed 42 for reproducibility.
|
68 |
"""
|
69 |
model = HfApiModel(
|
70 |
max_tokens=384,
|
@@ -80,8 +80,8 @@ def create_prompt_for_image_generation(user_prompt: str) -> str:
|
|
80 |
# response = model(
|
81 |
# prompt=prompt, temperature=1., max_tokens=512)
|
82 |
response = model(messages, stop_sequences=["END"])
|
83 |
-
|
84 |
-
return response
|
85 |
|
86 |
except Exception as e:
|
87 |
print(f"Error during LLM call: {str(e)}")
|
|
|
52 |
3. Color Palette: Include details about the dominant colors or overall color scheme.
|
53 |
4. Perspective and Camera Details: Mention the point of view (e.g., wide-angle, close-up), camera type, lens, aperture, and lighting conditions if applicable.
|
54 |
5. Additional Details: Highlight any specific objects, text, or unique features with clear emphasis (e.g., 'with green text' or 'emphasis on golden hour lighting').
|
55 |
+
6. Output Settings: Suggest aspect ratio, output format (e.g., JPG), quality level, and seed for reproducibility.
|
56 |
Ensure that the generated prompt is logical, descriptive, and written in natural language to maximize compatibility with FLUX-Schnell capabilities.
|
57 |
Example Input:
|
58 |
An image of a serene forest with a small cabin.
|
|
|
64 |
The color palette includes rich greens, warm browns for the cabin, and soft gray mist.
|
65 |
The perspective is slightly elevated as if viewed from a drone camera at sunrise,
|
66 |
capturing golden hour lighting for soft shadows and warm highlights.
|
67 |
+
The aspect ratio is 1:1, output format JPG, high quality, using seed 42 for reproducibility.
|
68 |
"""
|
69 |
model = HfApiModel(
|
70 |
max_tokens=384,
|
|
|
80 |
# response = model(
|
81 |
# prompt=prompt, temperature=1., max_tokens=512)
|
82 |
response = model(messages, stop_sequences=["END"])
|
83 |
+
return response['choices'][0]['text']
|
84 |
+
# return response
|
85 |
|
86 |
except Exception as e:
|
87 |
print(f"Error during LLM call: {str(e)}")
|