Update app.py

app.py

@@ -1,27 +1,108 @@
+Hugging Face's logo
+Hugging Face
+Models
+Datasets
+Spaces
+Posts
+Docs
+Enterprise
+Pricing
+
+
+
+Spaces:
+
+DevQuasar
+/
+test
+
+
+like
+0
+App
+Files
+Community
+test
+/
+app.py
+
+csabakecskemeti's picture
+csabakecskemeti
+Duplicate from gradio-templates/chatbot
+644d5a5
+verified
+3 months ago
+raw
+
+Copy download link
+history
+blame
+contribute
+delete
+
+1.71 kB
 import gradio as gr
-from gradio_pdf import PDF
-from pdf2image import convert_from_path
-from transformers import pipeline
-from pathlib import Path
+from huggingface_hub import InferenceClient
 
-dir_ = Path(__file__).parent
+"""
+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")
 
-p = pipeline(
-    "document-question-answering",
-    model="impira/layoutlm-document-qa",
-)
 
-def qa(doc: str, question: str) -> str:
-    img = convert_from_path(doc)[0]
-    output = p(img, question)
-    return sorted(output, key=lambda x: x["score"], reverse=True)[0]['answer']
+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
 
-demo = gr.Interface(
-    qa,
-    [PDF(label="Document"), gr.Textbox()],
-    gr.Textbox(),
-    examples=[[str(dir_ / "invoice_2.pdf"), "What is the total gross worth?"]]
+        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)",
+        ),
+    ],
 )
 
-demo.launch()
+
+if __name__ == "__main__":
+    demo.launch()
+