Update app.py

app.py

@@ -15,24 +15,27 @@ ZEPHYR_API_URL = "https://api-inference.huggingface.co/models/HuggingFaceH4/zeph
 SD_API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
 
 def query_zephyr(linkedin_text):
-    # Headers for the HTTP request
     headers = {
         "Authorization": f"Bearer {ZEPHYR_API_TOKEN}",
         "Content-Type": "application/json",
     }
 
-    # Constructing the conversation
+    # Adapting the conversational format from the pipeline example
     prompt = "Prepare a prompt for Stable Diffusion for the following LinkedIn post:"
-    conversation = [
+    messages = [
         {"role": "system", "content": prompt},
         {"role": "user", "content": linkedin_text}
     ]
     
-    # Adjusting the payload structure based on the expected format
+    # Structuring the payload for a conversational input
     payload = {
-        "inputs": conversation,
+        "inputs": {
+            "past_user_inputs": [],
+            "generated_responses": [],
+            "text": linkedin_text,  # or possibly serialize the messages list if needed
+            "conversation": messages,  # This might need to be adjusted based on Zephyr's API requirements
+        }
     }
-
     # Sending the HTTP POST request
     response = requests.post(ZEPHYR_API_URL, headers=headers, json=payload)
     if response.status_code == 200: