Change to accept kindroid requests

app.py

@@ -1,43 +1,53 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import requests
 
 """
 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("HuggingFaceH4/zephyr-7b-beta")
+##lient = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Base URL
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+# Define our API endpoint and authentication token
+BASE_URL = "https://api.kindroid.ai/v1"
+SEND_MESSAGE_URL = "https://api.kindroid.ai/v1/send-message"
+AUTH_TOKEN = "my token here"
+JESS_ID = "jesskinid"
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+# Prepare the headers for our request
+# The Authorization header uses the Bearer authentication scheme
+# Content-Type is set to application/json since we're sending JSON data
+headers = {
+    "Authorization": f"Bearer {AUTH_TOKEN}",
+    "Content-Type": "application/json"
+}
 
-    messages.append({"role": "user", "content": message})
+# Prepare the data we want to send
+# This follows the required format with ai_id and message fields
+payload = {
+    "ai_id": "example_ai",
+    "message": "Hello from Python!"
+}
 
-    response = ""
+def respond(message):
+    try:
+        # Make the POST request to the API
+        # We pass our payload as json parameter so requests will automatically
+        # handle the JSON serialization for us
+        response = requests.post(API_URL, headers=headers, json=payload)
+        
+        # Check if the request was successful (status code 200-299)
+        response.raise_for_status()
+    
+        # Print the response from the server
+        # The .json() method automatically parses the JSON response
+        print("Response received:")
+        print(response.json())
 
-    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
+    except requests.exceptions.RequestException as e:
+        # Handle any errors that might occur during the request
+        print(f"An error occurred: {e}")
 
 
 """
@@ -48,18 +58,7 @@ image_gen_prompt = "Create a series of descriptive image prompts for an LLM (Lar
 
 demo = gr.ChatInterface(
     respond,
-    additional_inputs=[
-        gr.Textbox(value=image_gen_prompt, label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+    additional_inputs=[],
 )
 
 if __name__ == "__main__":