T

README.md

@@ -3,9 +3,9 @@ title: Documentreader
 emoji: 💬
 colorFrom: yellow
 colorTo: purple
-sdk: docker
+sdk: gradio
 sdk_version: 5.0.1
-app_file: app.sh
+app_file: app.py
 pinned: false
 license: apache-2.0
 short_description: Document Reader

app.py

@@ -1,17 +1,76 @@
-import nbformat
-from nbconvert.preprocessors import ExecutePreprocessor
-import jupyter_client
+#!/usr/bin/env python
+# coding: utf-8
 
-print("Available kernels:", jupyter_client.kernelspec.find_kernel_specs())
+# In[1]:
 
-def run_notebook(path):
-    with open(path, "r", encoding="utf-8") as f:
-        nb = nbformat.read(f, as_version=4)
 
-    ep = ExecutePreprocessor(timeout=600, kernel_name="python3")
-    ep.preprocess(nb, {"metadata": {"path": "./"}})
+import gradio as gr
+from huggingface_hub import InferenceClient
 
-    with open("executed_" + path, "w", encoding="utf-8") as f:
-        nbformat.write(nb, f)
 
-run_notebook("app.ipynb")
+
+# In[ ]:
+
+
+"""
+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")
+
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    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
+
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    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)",
+        ),
+    ],
+)
+
+
+if __name__ == "__main__":
+    demo.launch()
+