gradio app

app.py

@@ -1,7 +1,89 @@
 import gradio as gr
+from huggingface_hub import InferenceClient
 
-def greet(name):
-    return "Hello " + name + "!!"
+from query_data import query_data
+from create_database import split_text
+import os
+import shutil 
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+
+import logging
+
+logging.basicConfig(filename='myapp.log',format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %I:%M:%S %p')
+logger = logging.getLogger(__name__)
+
+"""
+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
+"""
+
+
+CHROMA_PATH = "chroma"
+DATA_PATH = "./data"
+
+
+accesstoken = os.environ['HF_TOKEN']
+checkpoint = "HuggingFaceH4/zephyr-7b-beta"
+client = InferenceClient(checkpoint,token = accesstoken)
+
+def upload_file(file):
+    if not os.path.exists(DATA_PATH):
+        os.mkdir(DATA_PATH)
+
+    shutil.copy(file,DATA_PATH)
+    gr.Info("File uploading")
+
+
+logger.info("### Inference client: "+checkpoint)
+
+
+
+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})
+
+    logger.info(messages)
+    response = query_data(message)
+    yield response
+
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+with gr.Blocks() as demo: 
+
+    upload_button = gr.UploadButton("Click the button to upload")
+    upload_button.upload(upload_file,upload_button)
+
+    gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot that helps searching knowledge into scientific articles.", 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()