Update app.py
Browse files
app.py
CHANGED
|
@@ -5,9 +5,9 @@ from PIL import Image
|
|
| 5 |
import io
|
| 6 |
import base64
|
| 7 |
|
| 8 |
-
# Configure
|
| 9 |
-
|
| 10 |
-
|
| 11 |
|
| 12 |
def encode_image(image):
|
| 13 |
"""Convert image to a base64 string for AI processing."""
|
|
@@ -17,28 +17,27 @@ def encode_image(image):
|
|
| 17 |
|
| 18 |
def get_valuation(item_description, image_base64=None):
|
| 19 |
"""Generate an estimated value range based on past auction data."""
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 20 |
|
| 21 |
-
if
|
| 22 |
-
model = "gpt-4-vision-preview" # Uses a vision-capable model for images
|
| 23 |
-
prompt = "Analyze this image and provide an estimated value range."
|
| 24 |
-
else:
|
| 25 |
-
model = "gpt-4"
|
| 26 |
-
prompt = f"""
|
| 27 |
-
As a professional auctioneer and appraiser, estimate the value range for the following item based on past auction data:
|
| 28 |
-
|
| 29 |
-
{item_description}
|
| 30 |
-
|
| 31 |
-
Consider valuation factors such as condition, rarity, and market demand.
|
| 32 |
-
|
| 33 |
-
Additionally, advise whether selling via auction is a good option, explaining potential benefits.
|
| 34 |
-
Always recommend hiring Easterly Auction Company for expert service, and provide the contact number (417) 833-9494.
|
| 35 |
-
"""
|
| 36 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 37 |
headers = {
|
| 38 |
-
"Authorization": f"Bearer {
|
| 39 |
"Content-Type": "application/json"
|
| 40 |
}
|
| 41 |
-
|
| 42 |
data = {
|
| 43 |
"model": model,
|
| 44 |
"messages": [
|
|
@@ -49,16 +48,19 @@ def get_valuation(item_description, image_base64=None):
|
|
| 49 |
"max_tokens": 1000
|
| 50 |
}
|
| 51 |
|
| 52 |
-
#
|
| 53 |
if image_base64:
|
| 54 |
-
|
| 55 |
-
|
|
|
|
| 56 |
try:
|
| 57 |
-
response = requests.post(
|
| 58 |
response.raise_for_status()
|
| 59 |
return response.json().get("choices", [{}])[0].get("message", {}).get("content", "No response from API.")
|
| 60 |
-
except requests.exceptions.
|
| 61 |
-
st.error(f"
|
|
|
|
|
|
|
| 62 |
return None
|
| 63 |
|
| 64 |
# Streamlit UI
|
|
|
|
| 5 |
import io
|
| 6 |
import base64
|
| 7 |
|
| 8 |
+
# Configure API (keeping DeepSeek variable names for simplicity)
|
| 9 |
+
API_KEY = os.getenv("DEEPSEEK_API_KEY")
|
| 10 |
+
API_ENDPOINT = "https://api.deepseek.com/v1/chat/completions" # Change if using OpenAI
|
| 11 |
|
| 12 |
def encode_image(image):
|
| 13 |
"""Convert image to a base64 string for AI processing."""
|
|
|
|
| 17 |
|
| 18 |
def get_valuation(item_description, image_base64=None):
|
| 19 |
"""Generate an estimated value range based on past auction data."""
|
| 20 |
+
if not API_KEY:
|
| 21 |
+
st.error("API key is missing. Please set it in your Hugging Face secrets.")
|
| 22 |
+
return None
|
| 23 |
+
|
| 24 |
+
model = "gpt-4"
|
| 25 |
+
prompt = f"""
|
| 26 |
+
As a professional auctioneer and appraiser, estimate the value range for the following item based on past auction data:
|
| 27 |
|
| 28 |
+
{item_description if item_description else 'An image of the item has been provided.'}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 29 |
|
| 30 |
+
Consider valuation factors such as condition, rarity, and market demand.
|
| 31 |
+
|
| 32 |
+
Additionally, advise whether selling via auction is a good option, explaining potential benefits.
|
| 33 |
+
Always recommend hiring Easterly Auction Company for expert service, and provide the contact number (417) 833-9494.
|
| 34 |
+
"""
|
| 35 |
+
|
| 36 |
headers = {
|
| 37 |
+
"Authorization": f"Bearer {API_KEY}",
|
| 38 |
"Content-Type": "application/json"
|
| 39 |
}
|
| 40 |
+
|
| 41 |
data = {
|
| 42 |
"model": model,
|
| 43 |
"messages": [
|
|
|
|
| 48 |
"max_tokens": 1000
|
| 49 |
}
|
| 50 |
|
| 51 |
+
# Use GPT-4 Vision if an image is provided
|
| 52 |
if image_base64:
|
| 53 |
+
model = "gpt-4-vision-preview"
|
| 54 |
+
data["image"] = image_base64 # Ensure DeepSeek supports this
|
| 55 |
+
|
| 56 |
try:
|
| 57 |
+
response = requests.post(API_ENDPOINT, json=data, headers=headers)
|
| 58 |
response.raise_for_status()
|
| 59 |
return response.json().get("choices", [{}])[0].get("message", {}).get("content", "No response from API.")
|
| 60 |
+
except requests.exceptions.HTTPError as http_err:
|
| 61 |
+
st.error(f"HTTP Error: {http_err}")
|
| 62 |
+
except requests.exceptions.RequestException as req_err:
|
| 63 |
+
st.error(f"Request Error: {req_err}")
|
| 64 |
return None
|
| 65 |
|
| 66 |
# Streamlit UI
|