from flask import Flask, jsonify, render_template, request, send_file from langchain import OpenAI from langchain.docstore.document import Document from langchain.text_splitter import CharacterTextSplitter from langchain.chains.summarize import load_summarize_chain from langchain_g4f import G4FLLM from g4f import Provider, models app = Flask(__name__) @app.route("/") def index(): return jsonify({"output": ""}) @app.route("/",methods=["GET"]) def t5(text): # prompt_template = """Write a concise summary around 450 words of the following : # "{text}" # CONCISE SUMMARY:""" # prompt = PromptTemplate.from_template(prompt_template) # # Instantiate the LLM model # llm = G4FLLM( # model=models.gpt_35_turbo, # provider=Provider.FreeGpt, # ) # llm_chain = LLMChain(llm=llm, prompt=prompt) # # Define StuffDocumentsChain # stuff_chain = StuffDocumentsChain( # llm_chain=llm_chain, document_variable_name="text" # ) # docs = loader.load() output = stuff_chain.run(docs) output = text return jsonify({"output": output}) if __name__ == "__main__": app.run(host="0.0.0.0", port=7860)