Update app.py

app.py

@@ -1,21 +1,22 @@
 from huggingface_hub import InferenceClient
 import gradio as gr
-import pandas as pd
 
-# Inference client initialization
-client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
+client = InferenceClient(
+    "mistralai/Mixtral-8x7B-Instruct-v0.1"
+)
+
 
-# Function to format the prompt
 def format_prompt(message, history):
-    prompt = "<s>"
-    for user_prompt, bot_response in history:
-        prompt += f"[INST] {user_prompt} [/INST]"
-        prompt += f" {bot_response}</s> "
-    prompt += f"[INST] {message} [/INST]"
-    return prompt
+  prompt = "<s>"
+  for user_prompt, bot_response in history:
+    prompt += f"[INST] {user_prompt} [/INST]"
+    prompt += f" {bot_response}</s> "
+  prompt += f"[INST] {message} [/INST]"
+  return prompt
 
-# Function to generate text based on prompt and history
-def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
+def generate(
+    prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, files=None
+):
     temperature = float(temperature)
     if temperature < 1e-2:
         temperature = 1e-2
@@ -30,10 +31,12 @@ def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=256
         seed=42,
     )
 
-    # Format the prompt
     formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
 
-    # Generate text using InferenceClient
+    if files is not None:
+        for file in files:
+            formatted_prompt += f"\n\nFile content: {file.decode()}"
+
     stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
     output = ""
 
@@ -42,44 +45,63 @@ def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=256
         yield output
     return output
 
-# Additional input components for Gradio interface
+
 additional_inputs=[
-    gr.File(label="Upload CSV or Document", type="binary"),  # Max file size is 2 GB
-    gr.Slider(label="Temperature", value=0.9, minimum=0.0, maximum=1.0, step=0.05, interactive=True, info="Higher values produce more diverse outputs"),
-    gr.Slider(label="Max new tokens", value=256, minimum=0, maximum=5120, step=64, interactive=True, info="The maximum numbers of new tokens"),
-    gr.Slider(label="Top-p (nucleus sampling)", value=0.90, minimum=0.0, maximum=1, step=0.05, interactive=True, info="Higher values sample more low-probability tokens"),
-    gr.Slider(label="Repetition penalty", value=1.2, minimum=1.0, maximum=2.0, step=0.05, interactive=True, info="Penalize repeated tokens")
+    gr.Textbox(
+        label="System Prompt",
+        max_lines=1,
+        interactive=True,
+    ),
+    gr.Slider(
+        label="Temperature",
+        value=0.9,
+        minimum=0.0,
+        maximum=1.0,
+        step=0.05,
+        interactive=True,
+        info="Higher values produce more diverse outputs",
+    ),
+    gr.Slider(
+        label="Max new tokens",
+        value=256,
+        minimum=0,
+        maximum=5120,
+        step=64,
+        interactive=True,
+        info="The maximum numbers of new tokens",
+    ),
+    gr.Slider(
+        label="Top-p (nucleus sampling)",
+        value=0.90,
+        minimum=0.0,
+        maximum=1,
+        step=0.05,
+        interactive=True,
+        info="Higher values sample more low-probability tokens",
+    ),
+    gr.Slider(
+        label="Repetition penalty",
+        value=1.2,
+        minimum=1.0,
+        maximum=2.0,
+        step=0.05,
+        interactive=True,
+        info="Penalize repeated tokens",
+    ),
+    gr.File(
+        label="Upload PDF or Document",
+        file_count="multiple",
+        file_types=[".pdf", ".doc", ".docx", ".txt"],
+        interactive=True,
+    )
 ]
 
-# Function to read uploaded CSV or Document
-def read_file(file):
-    if file is None:
-        return None
-    elif file.name.endswith('.csv'):
-        return pd.read_csv(file)
-    elif file.name.endswith('.txt'):
-        with open(file.name, 'r') as f:
-            return f.read()
 
-# Gradio Chat Interface
+
 gr.ChatInterface(
     fn=generate,
-    inputs=[
-        gr.inputs.Textbox(label="Prompt"),
-        gr.inputs.Textbox(label="History", placeholder="User1: Hello\nBot: Hi there!\nUser1: How are you?"),
-        gr.inputs.Textbox(label="System Prompt"),
-        gr.inputs.File(label="Upload CSV or Document", type="binary"),  # Max file size is 2 GB
-    ],
-    outputs=gr.outputs.Textbox(label="Response"),
-    title="Synthetic-data-generation-aze",
+    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
     additional_inputs=additional_inputs,
-    examples=[
-        ["What is the capital of France?", "Paris", "Ask me anything"],
-        ["How are you?", "I'm good, thank you!", "User"],
-    ],
-    allow_flagging=False,
-    allow_upvoting=False,
-    allow_duplicate_of_same_input=False,
-    flagging_options=["Inappropriate", "Incorrect", "Offensive"],
-    thumbs=None,
-).launch()
+    title="Synthetic-data-generation-aze",
+    concurrency_limit=20,
+).launch(show_api=False)