Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import torch
+import csv
+import re
+import warnings
+
+warnings.filterwarnings("ignore")
+
+# Define a prompt template for Magicoder with placeholders for instruction and response.
+MAGICODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
+@@ Instruction
+{instruction}
+@@ Response
+"""
+
+# Create a text generation pipeline using the Magicoder model, text-generation task, bfloat16 torch data type and auto device mapping.
+generator = pipeline(
+    model="ise-uiuc/Magicoder-S-DS-6.7B",
+    task="text-generation",
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+# Function to generate response
+def generate_response(instruction):
+    prompt = MAGICODER_PROMPT.format(instruction=instruction)
+    result = generator(prompt, max_length=2048, num_return_sequences=1, temperature=0.0)
+    response = result[0]["generated_text"]
+    response_start_index = response.find("@@ Response") + len("@@ Response")
+    response = response[response_start_index:].strip()
+    return response
+
+# Function to append data to a CSV file
+def save_to_csv(data, filename):
+    with open(filename, 'a', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        writer.writerow(data)
+
+# Function to process user feedback
+def process_output(correct_output, feedback=None, correct_code=None):
+    if correct_output.lower() == 'yes':
+        save_to_csv(["Correct", feedback], 'output_ratings.csv')
+    else:
+        save_to_csv(["Incorrect", feedback, correct_code], 'output_ratings.csv')
+
+# Gradio interface
+input_text = gr.inputs.Textbox(lines=5, label="Enter your instruction here:")
+output_text = gr.outputs.Textbox(label="Generated response:")
+
+def generate_and_process(instruction, correct_output):
+    generated_response = generate_response(instruction)
+    if correct_output.lower() == "no":
+        feedback = gr.Interface(
+            lambda x: x,
+            gr.inputs.Textbox(lines=5, label="Please enter the correct code:"),
+            "text"
+        ).launch()
+        correct_code = feedback
+        process_output(correct_output, feedback, correct_code)
+    else:
+        feedback = ""
+        process_output(correct_output, feedback)
+    return generated_response
+
+title = "Magicoder Assistant"
+description = "An intelligent coding assistant that generates responses based on user instructions."
+examples = [["Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."]]
+
+gr.Interface(
+    generate_and_process,
+    inputs=[input_text, "radio"],
+    outputs=output_text,
+    title=title,
+    description=description,
+    examples=examples
+).launch()