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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("/<text>",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) |