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ncoop57
commited on
Commit
•
321a2ed
1
Parent(s):
6842806
Add some janky syntax highlighting via rich
Browse files- app.py +27 -27
- requirements.txt +1 -0
app.py
CHANGED
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@@ -1,5 +1,7 @@
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import gradio as gr
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# model_name = "flax-community/gpt-code-clippy-1.3B-apps-alldata"
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@@ -8,34 +10,32 @@ model = AutoModelForCausalLM.from_pretrained(model_name)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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tokenizer.pad_token = tokenizer.eos_token
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def format_input(question, starter_code=""):
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answer_type =
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return f"\nQUESTION:\n{question}\n{starter_code}\n{answer_type}\nANSWER:\n"
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def format_outputs(text):
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formatted_text =
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</body>
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'''
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return formatted_text
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def generate_solution(question, starter_code="", temperature=1., num_beams=1):
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prompt = format_input(question, starter_code)
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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start = len(input_ids[0])
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output = model.generate(
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input_ids,
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max_length=start+200,
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do_sample=True,
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top_p=0.95,
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pad_token_id=tokenizer.pad_token_id,
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@@ -46,8 +46,10 @@ def generate_solution(question, starter_code="", temperature=1., num_beams=1):
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repetition_penalty=None,
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num_return_sequences=None,
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)
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return format_outputs(
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_EXAMPLES = [
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@@ -83,24 +85,22 @@ otherwise | 'Hello guest'
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def greet(name, owner):
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""",
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0.8,
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]
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]
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inputs = [
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gr.inputs.Textbox(placeholder="Define a problem here...", lines=7),
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gr.inputs.Textbox(placeholder="Provide optional starter code...", lines=3),
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gr.inputs.Slider(0.5, 1.5, 0.1, default=0.8, label="Temperature"),
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gr.inputs.Slider(1,4,1,default=1, label="Beam size")
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]
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outputs = [
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gr.outputs.HTML(label="Solution")
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]
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gr.Interface(
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generate_solution,
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inputs=inputs,
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outputs=outputs,
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title="Code Clippy: Problem Solver",
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examples=_EXAMPLES,
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import gradio as gr
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from rich.console import Console
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from rich.syntax import Syntax
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# model_name = "flax-community/gpt-code-clippy-1.3B-apps-alldata"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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tokenizer.pad_token = tokenizer.eos_token
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console = Console(record=True)
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def format_input(question, starter_code=""):
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answer_type = (
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"\nUse Call-Based format\n" if starter_code else "\nUse Standard Input format\n"
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)
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return f"\nQUESTION:\n{question}\n{starter_code}\n{answer_type}\nANSWER:\n"
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def format_outputs(text):
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formatted_text = Syntax(
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text, "python", line_numbers=True, indent_guides=True, word_wrap=True
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)
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console.print(formatted_text)
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return console.export_html(inline_styles=True)
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def generate_solution(question, starter_code="", temperature=1.0, num_beams=1):
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prompt = format_input(question, starter_code)
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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start = len(input_ids[0])
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output = model.generate(
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input_ids,
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max_length=start + 200,
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do_sample=True,
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top_p=0.95,
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pad_token_id=tokenizer.pad_token_id,
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repetition_penalty=None,
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num_return_sequences=None,
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)
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return format_outputs(
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tokenizer.decode(output[0][start:], skip_special_tokens=True).strip()
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)
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_EXAMPLES = [
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def greet(name, owner):
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""",
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0.8,
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],
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]
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inputs = [
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gr.inputs.Textbox(placeholder="Define a problem here...", lines=7),
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gr.inputs.Textbox(placeholder="Provide optional starter code...", lines=3),
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gr.inputs.Slider(0.5, 1.5, 0.1, default=0.8, label="Temperature"),
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gr.inputs.Slider(1, 4, 1, default=1, label="Beam size"),
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]
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outputs = [gr.outputs.HTML(label="Solution")]
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gr.Interface(
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generate_solution,
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inputs=inputs,
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outputs=outputs,
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title="Code Clippy: Problem Solver",
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examples=_EXAMPLES,
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requirements.txt
CHANGED
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@@ -1,2 +1,3 @@
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torch
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transformers
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torch
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transformers
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+
rich
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