Update app.py
Browse files
app.py
CHANGED
@@ -2,41 +2,48 @@ import streamlit as st
|
|
2 |
from huggingface_hub import InferenceClient
|
3 |
from config import HUGGINGFACE_API_KEY # Import your API key from a separate config file
|
4 |
from PIL import Image
|
|
|
5 |
from io import BytesIO
|
6 |
|
7 |
# Streamlit App Configuration
|
8 |
st.set_page_config(page_title="Llama-3.2 Demo App", page_icon="π€", layout="wide")
|
9 |
st.title("πΌοΈ Llama-3.2-90B-Vision-Instruct Demo App")
|
10 |
-
st.markdown("<p style='text-align: center; font-size: 18px; color: #555;'>
|
11 |
|
12 |
-
# User Inputs
|
13 |
-
|
14 |
user_prompt = st.text_input("Enter your prompt", value="Describe this image in a paragraph", placeholder="e.g., What is shown in the image?")
|
15 |
|
16 |
-
# Function to display the
|
17 |
-
def
|
18 |
try:
|
19 |
-
|
20 |
-
|
21 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
22 |
except Exception as e:
|
23 |
-
st.error(f"β Unable to
|
24 |
-
return None
|
25 |
|
26 |
# Process user input
|
27 |
if st.button("Get Description", key="get_description"):
|
28 |
-
if
|
29 |
try:
|
30 |
-
#
|
31 |
-
|
32 |
-
if img is None:
|
33 |
-
st.error("β Image processing failed.")
|
34 |
-
st.stop()
|
35 |
-
|
36 |
-
# Convert the image to bytes for model input
|
37 |
-
img_buffer = BytesIO()
|
38 |
-
img.save(img_buffer, format="PNG")
|
39 |
-
img_bytes = img_buffer.getvalue()
|
40 |
|
41 |
# Initialize the InferenceClient
|
42 |
client = InferenceClient(api_key=HUGGINGFACE_API_KEY)
|
@@ -47,7 +54,7 @@ if st.button("Get Description", key="get_description"):
|
|
47 |
"role": "user",
|
48 |
"content": [
|
49 |
{"type": "text", "text": user_prompt},
|
50 |
-
{"type": "
|
51 |
]
|
52 |
}
|
53 |
]
|
@@ -62,14 +69,16 @@ if st.button("Get Description", key="get_description"):
|
|
62 |
# Extract JSON response
|
63 |
model_response = completion.choices[0].message
|
64 |
|
65 |
-
# Display the result
|
66 |
st.subheader("π Model Response")
|
|
|
|
|
67 |
st.markdown(f"**Description**: {model_response.get('content', 'No description available')}")
|
68 |
|
69 |
except Exception as e:
|
70 |
st.error(f"β An error occurred: {e}")
|
71 |
else:
|
72 |
-
st.warning("β οΈ Please
|
73 |
|
74 |
# Clean UI Enhancements
|
75 |
st.markdown("""
|
@@ -93,10 +102,6 @@ st.markdown("""
|
|
93 |
border-radius: 10px;
|
94 |
}
|
95 |
|
96 |
-
.stFileUploader>div>div {
|
97 |
-
border-radius: 10px;
|
98 |
-
}
|
99 |
-
|
100 |
/* Center the image */
|
101 |
.stImage {
|
102 |
display: block;
|
@@ -104,4 +109,4 @@ st.markdown("""
|
|
104 |
margin-right: auto;
|
105 |
}
|
106 |
</style>
|
107 |
-
""", unsafe_allow_html=True)
|
|
|
2 |
from huggingface_hub import InferenceClient
|
3 |
from config import HUGGINGFACE_API_KEY # Import your API key from a separate config file
|
4 |
from PIL import Image
|
5 |
+
import requests
|
6 |
from io import BytesIO
|
7 |
|
8 |
# Streamlit App Configuration
|
9 |
st.set_page_config(page_title="Llama-3.2 Demo App", page_icon="π€", layout="wide")
|
10 |
st.title("πΌοΈ Llama-3.2-90B-Vision-Instruct Demo App")
|
11 |
+
st.markdown("<p style='text-align: center; font-size: 18px; color: #555;'>Enter an image URL and get a description</p>", unsafe_allow_html=True)
|
12 |
|
13 |
+
# User Inputs with placeholder
|
14 |
+
image_url = st.text_input("Enter Image URL", value="", placeholder="Paste image URL here...", max_chars=400)
|
15 |
user_prompt = st.text_input("Enter your prompt", value="Describe this image in a paragraph", placeholder="e.g., What is shown in the image?")
|
16 |
|
17 |
+
# Function to display the image from URL with height limit based on its actual size
|
18 |
+
def show_image_from_url(image_url, max_height=200):
|
19 |
try:
|
20 |
+
response = requests.get(image_url)
|
21 |
+
img = Image.open(BytesIO(response.content))
|
22 |
+
|
23 |
+
# Get the original image size
|
24 |
+
img_width, img_height = img.size
|
25 |
+
|
26 |
+
# Calculate the new height and width based on the max height while maintaining the aspect ratio
|
27 |
+
if img_height > max_height:
|
28 |
+
aspect_ratio = img_width / img_height
|
29 |
+
new_height = max_height
|
30 |
+
new_width = int(new_height * aspect_ratio)
|
31 |
+
img_resized = img.resize((new_width, new_height))
|
32 |
+
else:
|
33 |
+
img_resized = img # No resizing needed if the image is smaller than the max height
|
34 |
+
|
35 |
+
# Center the image and display it
|
36 |
+
st.image(img_resized, caption=f"Source: {image_url}", use_container_width=True)
|
37 |
+
|
38 |
except Exception as e:
|
39 |
+
st.error(f"β Unable to load image. Error: {e}")
|
|
|
40 |
|
41 |
# Process user input
|
42 |
if st.button("Get Description", key="get_description"):
|
43 |
+
if image_url and user_prompt:
|
44 |
try:
|
45 |
+
# Show the image with dynamic resizing based on the image size
|
46 |
+
show_image_from_url(image_url, max_height=600)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
47 |
|
48 |
# Initialize the InferenceClient
|
49 |
client = InferenceClient(api_key=HUGGINGFACE_API_KEY)
|
|
|
54 |
"role": "user",
|
55 |
"content": [
|
56 |
{"type": "text", "text": user_prompt},
|
57 |
+
{"type": "image_url", "image_url": {"url": image_url}}
|
58 |
]
|
59 |
}
|
60 |
]
|
|
|
69 |
# Extract JSON response
|
70 |
model_response = completion.choices[0].message
|
71 |
|
72 |
+
# Display the result in a clean and simple format
|
73 |
st.subheader("π Model Response")
|
74 |
+
|
75 |
+
# Display Content
|
76 |
st.markdown(f"**Description**: {model_response.get('content', 'No description available')}")
|
77 |
|
78 |
except Exception as e:
|
79 |
st.error(f"β An error occurred: {e}")
|
80 |
else:
|
81 |
+
st.warning("β οΈ Please enter an image URL and a prompt.")
|
82 |
|
83 |
# Clean UI Enhancements
|
84 |
st.markdown("""
|
|
|
102 |
border-radius: 10px;
|
103 |
}
|
104 |
|
|
|
|
|
|
|
|
|
105 |
/* Center the image */
|
106 |
.stImage {
|
107 |
display: block;
|
|
|
109 |
margin-right: auto;
|
110 |
}
|
111 |
</style>
|
112 |
+
""", unsafe_allow_html=True)
|