Delete app.py with huggingface_hub

app.py

@@ -1,44 +0,0 @@
-from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
-from langchain_core.prompts import ChatPromptTemplate
-from langchain.prompts import PromptTemplate
-from langchain_core.output_parsers import StrOutputParser
-from langchain.memory import ConversationSummaryMemory
-from langchain_huggingface import HuggingFacePipeline
-from langchain_core.runnables import RunnableSequence
-import gradio as gr
-
-# Load model
-model_id = "google/gemma-2b"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id)
-
-# Text generation pipeline
-generator = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    max_new_tokens=100,
-    do_sample=True,
-    temperature=0.7
-)
-
-
-
-# LangChain wrapper
-llm = HuggingFacePipeline(pipeline=generator)
-
-# Prompt template
-prompt = ChatPromptTemplate.from_messages([
-     ("system", "You are a helpful assistant. Explain the following code clearly:\n\n{code}")
-])
-
-# Runnable sequence instead of LLMChain
-chain = prompt | llm | StrOutputParser()
-
-
-# Gradio interface
-def generate_answer(input_code):
-    result = chain.invoke({"code":input_code })
-    return result
-
-gr.Interface(fn=generate_answer, inputs="text", outputs="text", title="Gemma 2B Code Explainer").launch()