Update app.py

change to inference

app.py

@@ -5,7 +5,19 @@ from huggingface_hub import InferenceClient
 For more information on huggingface_hub Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
 """
 # client = InferenceClient("unsloth/Llama-3.2-1B-Instruct")
-client = InferenceClient(model="https://aq0teqpujnx3bv68.us-east-1.aws.endpoints.huggingface.cloud/")
+#client = InferenceClient(model="https://aq0teqpujnx3bv68.us-east-1.aws.endpoints.huggingface.cloud/")
+import requests
+
+API_URL = "https://aq0teqpujnx3bv68.us-east-1.aws.endpoints.huggingface.cloud"
+headers = {
+	"Accept" : "application/json",
+	"Content-Type": "application/json" 
+}
+
+def query(payload):
+	response = requests.post(API_URL, headers=headers, json=payload)
+	return response.json()
+
 
 def respond(
     message,
@@ -24,30 +36,15 @@ def respond(
     max_tokens = 512
     temperature = 0.7
     top_p = 0.95
+  
+    output = query({
+    	"inputs":system_message + "\n\n" + message,
+    	"parameters": {
+    		"max_new_tokens": 150
+    	}
+    })
+    return output
     
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
 
 
 """