Update app.py

app.py

@@ -1,43 +1,69 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import os
 
+CHAT_URL = os.getenv("CHAT_URL")
+TOKEN = os.getenv("TOKEN")
+PROJECT_ID = os.getenv("PROJECT_ID")
 
 def respond(
     message,
     history: list[dict[str, str]],
     system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    hf_token: gr.OAuthToken,
+    # max_tokens,
+    # temperature,
+    # top_p,
+    # hf_token: gr.OAuthToken,
 ):
     """
     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(token=hf_token.token, model="openai/gpt-oss-20b")
+    # client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")
 
-    messages = [{"role": "system", "content": system_message}]
+    # messages = [{"role": "system", "content": system_message}]
 
-    messages.extend(history)
+    # messages.extend(history)
 
-    messages.append({"role": "user", "content": message})
+    # messages.append({"role": "user", "content": message})
 
-    response = ""
+    # response = ""
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
+    # for message in client.chat_completion(
+    #     messages,
+    #     max_tokens=max_tokens,
+    #     stream=True,
+    #     temperature=temperature,
+    #     top_p=top_p,
+    # ):
+    #     choices = message.choices
+    #     token = ""
+    #     if len(choices) and choices[0].delta.content:
+    #         token = choices[0].delta.content
 
-        response += token
-        yield response
+    #     response += token
+    #     yield response
+
+    req = requests.post(
+        "project_id": PROJECT_ID,
+        "session_id":system_message,
+        "user_input":message,
+        "update_variables": { // update_variables wajib kalau tidak pakai #ai
+            "alfamidi":"",
+            "alfagift":"",
+            "karir":"",
+            "layanan":"",
+            "program":"",
+            "voucher":"",
+            "results":"",
+            "identitas":"",
+            "kerjasama":""
+        },
+        "output_variables": ["results"]
+    )
+
+    out = req.json()["data"]["results"]
+
+    return out
 
 
 """
@@ -47,16 +73,16 @@ chatbot = gr.ChatInterface(
     respond,
     type="messages",
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", 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)",
-        ),
+        gr.Textbox(value="TEST_123", label="session_id"),
+        # 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)",
+        # ),
     ],
 )