Text Generation
Transformers
PyTorch
codegen
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import gradio as gr
from transformers import pipeline
# 🔥 Program Synthesis Modell
synthesizer = pipeline("text-generation", model="microsoft/CodeGPT-small-py")
# 🔹 Gravatar
GRAVATAR_URL = "https://www.gravatar.com/avatar/7e6d02f7b39c0f35f7eae2f404a7d0b1?s=200"
GRAVATAR_LINK = "https://gravatar.com/skymeilin"
# 🔹 Finger Funktionen
def code_analysis(prompt):
return synthesizer(f"# Analysiere den Code:\n{prompt}\n# Analyse:", max_length=300)[0]['generated_text']
def code_optimization(prompt):
return synthesizer(f"# Optimiere den folgenden Code:\n{prompt}\n# Optimierter Code:", max_length=300)[0]['generated_text']
def code_comment(prompt):
return synthesizer(f"# Kommentiere den Code:\n{prompt}\n# Kommentar:", max_length=300)[0]['generated_text']
def code_multilang(prompt):
return synthesizer(f"# Übersetze oder generiere in gewünschter Sprache:\n{prompt}\n# Code:", max_length=300)[0]['generated_text']
def code_debug(prompt):
return synthesizer(f"# Finde Bugs und Vorschläge:\n{prompt}\n# Debug:", max_length=300)[0]['generated_text']
def code_test(prompt):
return synthesizer(f"# Generiere Testfälle für:\n{prompt}\n# Tests:", max_length=300)[0]['generated_text']
def code_refactor(prompt):
return synthesizer(f"# Refactore den Code nach Best Practices:\n{prompt}\n# Refactored Code:", max_length=300)[0]['generated_text']
def code_doc(prompt):
return synthesizer(f"# Dokumentiere den Code:\n{prompt}\n# Dokumentation:", max_length=300)[0]['generated_text']
def code_boilerplate(prompt):
return synthesizer(f"# Generiere Boilerplate / Deployment Code:\n{prompt}\n# Code:", max_length=300)[0]['generated_text']
def code_custom(prompt):
return synthesizer(f"# Eigene Conversational Anfrage:\n{prompt}\n# Antwort:", max_length=300)[0]['generated_text']
# Mapping Finger-Buttons
fingers = {
"Analyse": code_analysis,
"Optimierung": code_optimization,
"Kommentierung": code_comment,
"Mehrsprachig": code_multilang,
"Debugging": code_debug,
"Testfälle": code_test,
"Refactoring": code_refactor,
"Dokumentation": code_doc,
"Boilerplate": code_boilerplate,
"Conversational": code_custom
}
# Gradio UI
with gr.Blocks() as app:
# Header
with gr.Row():
gr.Image(GRAVATAR_URL, shape=(100,100), tooltips="Sky Meilin", interactive=True)
gr.Markdown(f"## 🔥 Anycoder 30de8a5b – Conversational Program Synthesis\n**Sky Meilin** – [Gravatar Profil]({GRAVATAR_LINK})")
# Input
prompt_input = gr.Textbox(label="Beschreibung oder Code eingeben", placeholder="Z.B. 'Sortiere eine Liste...'", lines=8)
# Finger Buttons
output_code = gr.Textbox(label="Ergebnis", lines=10)
with gr.Row():
for name, func in fingers.items():
gr.Button(name).click(func, inputs=prompt_input, outputs=output_code)
if __name__ == "__main__":
app.launch()