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README.md

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+---
+title: Chatbot
+emoji: 🐠
+colorFrom: green
+colorTo: red
+sdk: gradio
+sdk_version: 3.49.0
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import requests
+import os
+
+
+def respond(message, history, endpoint, token, temp, max_token=0):
+    if len(message.strip()) == 0:
+        return "ERROR the question should not be empty"
+
+    if len(token.strip()) > 0 and len(endpoint.strip()) > 0:
+        local_token = token
+        local_endpoint = endpoint
+        custom_message = "[*] "
+    else:
+        local_token = os.environ['API_TOKEN']
+        local_endpoint = os.environ['API_ENDPOINT']
+        custom_message = ""
+
+    # Add your API token to the headers
+    headers = {
+        'Content-Type': 'application/json',
+        'Authorization': f'Bearer {local_token}'
+    }
+    q = {"inputs": {"prompt": ["Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:\n" +
+                               message + "\n\n### Response:\n"], "max_tokens": [int(max_token)], "temperature": [int(temp)]}}
+    try:
+        response = requests.post(local_endpoint, json=q, headers=headers, timeout=100)
+        response_data = response.json(
+        )["predictions"][0]["candidates"][0]["text"]
+    except:
+        response_data = "ERROR status_code:" + \
+            str(response.status_code) + " response:" + response.text
+
+    return custom_message + response_data
+
+
+demo = gr.ChatInterface(
+    respond,
+    chatbot=gr.Chatbot(height=400),
+    textbox=gr.Textbox(placeholder="Ask me a question",
+                       container=False, scale=7),
+    title="Chat with a Databricks LLM serving endpoint",
+    description="This a MPT-7b model",
+    examples=[["Hello"], ["What is MLflow?"], ["What is Apache Spark?"]],
+    cache_examples=False,
+    theme="soft",
+    retry_btn=None,
+    undo_btn=None,
+    clear_btn="Clear",
+    additional_inputs=[
+        gr.Textbox(label="Custom Endpoint", type="text",
+                   placeholder="https://XXXXXX.cloud.databricks.com/serving-endpoints/XXXXX/invocations"),
+        gr.Textbox(label="Custom Token", type="password",
+                   placeholder="dapiXXXXXXXXXX"),
+        gr.Slider(0, 100, label="Temp", value=0),
+        gr.Slider(0, 100, label="Max token", value=75)
+    ],
+    additional_inputs_accordion_name="Settings"
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+
+