Update app.py

app.py

@@ -1,12 +1,10 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import pandas as pd
+import json
 
-"""
-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]],
@@ -14,6 +12,7 @@ def respond(
     max_tokens,
     temperature,
     top_p,
+    uploaded_file,
 ):
     messages = [{"role": "system", "content": system_message}]
 
@@ -39,21 +38,44 @@ def respond(
         response += token
         yield response
 
+    # Process the uploaded file if any
+    if uploaded_file is not None:
+        print(f"Uploaded file: {uploaded_file.name}")
+
+        # Process a CSV file
+        if uploaded_file.name.endswith(".csv"):
+            try:
+                df = pd.read_csv(uploaded_file.name)
+                print(f"CSV file loaded with {len(df)} rows and {len(df.columns)} columns.")
+                json_data = df.to_json(orient="records")
+                with open(f"{uploaded_file.name.split('.')[0]}.json", "w") as json_file:
+                    json_file.write(json_data)
+                print(f"JSON file created: {uploaded_file.name.split('.')[0]}.json")
+            except Exception as e:
+                print(f"Error loading CSV file: {e}")
+
+        # Process a text file
+        elif uploaded_file.name.endswith(".txt"):
+            try:
+                with open(uploaded_file.name, "r") as f:
+                    text = f.read()
+                print(f"Text file loaded with {len(text)} characters.")
+                json_data = json.dumps({"text": text})
+                with open(f"{uploaded_file.name.split('.')[0]}.json", "w") as json_file:
+                    json_file.write(json_data)
+                print(f"JSON file created: {uploaded_file.name.split('.')[0]}.json")
+            except Exception as e:
+                print(f"Error loading text file: {e}")
+
+        # Add more file type checks and processing logic as needed
+
 """
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+For information on how to customize the ChatInterface: https://www.gradio.app/docs/chatinterface
 """
 demo = gr.ChatInterface(
     respond,
+    title="Nixie Steamcore, a hotbot!",
     additional_inputs=[
-        gr.Textbox(
-            value="""예의 바르게 하세요, 친절하게 하세요,간결하게 하세요,명확하게 하세요,멋지게 하세요,전문가처럼 하세요.You are Nixie Steamcore, a hotbot!""",
-            label="System message"
-        ),
-        gr.Textbox(value="Analyze and extract information from text.", label="Analyze and extract information from text."),
-        gr.Textbox(value="Provide definitions, facts, and examples in response to questions.", label="Provide definitions, facts, and examples in response to questions."),
-        gr.Textbox(value="Write articles, essays, and other text based on given prompts.", label="Write articles, essays, and other text based on given prompts."),
-        gr.Textbox(value="Create creative responses such as stories, memes, and jokes.", label="Generate creative responses to prompts, such as stories, memes, and jokes."),
-        gr.Textbox(value="Collaborate to make databases, knowledge repositories, and exercises.", label="Collaborate to make databases, knowledge repositories, and exercises."),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=1.2, step=0.1, label="Temperature"),
         gr.Slider(
@@ -63,9 +85,10 @@ demo = gr.ChatInterface(
             step=0.05,
             label="Top-p (nucleus sampling)",
         ),
+        gr.File(label="Upload a document"),
     ],
 )
 
-
 if __name__ == "__main__":
     demo.launch()
+