Delete main.py

main.py

@@ -1,44 +0,0 @@
-from langchain.text_splitter import CharacterTextSplitter
-from langchain.docstore.document import Document
-from langchain.chains.summarize import load_summarize_chain
-from langchain import OpenAI, LLMChain, HuggingFaceHub
-import textwrap
-
-
-def summarize(doc):
-    text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=0,
-                                          separator="\n")  # Initilize an instance of CharacterTextSplitter
-    chunks = text_splitter.split_text(doc)
-    doc_store = [Document(page_content=text) for text in chunks]
-    llm_model = OpenAI(model_name="text-davinci-003", temperature=0)  # define your language model
-
-    summarization_chain2 = load_summarize_chain(llm=llm_model,
-                                                chain_type='map_reduce',
-                                                verbose=True  # define the chain type)
-                                                )
-    output_summary = summarization_chain2.run(doc_store)
-    wrapped_text = textwrap.fill(output_summary, width=100)
-
-    return wrapped_text
-
-if __name__ == "__main__":
-    # make a gradio interface
-    import gradio as gr
-
-    outputs = gr.outputs.Textbox()
-
-    app = gr.Interface(fn=summarize, inputs='text', outputs=outputs,description="This is a text summarization model").launch()
-
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