From 671b9f481edc3d7ecf5c27d9ed9b2efd6714c237 Mon Sep 17 00:00:00 2001
From: T0xan <96002702+Touxan@users.noreply.github.com>
Date: Mon, 4 Dec 2023 14:23:12 +0100
Subject: [PATCH] Update gpt.py

---
 bunkoer/utils/gpt.py | 34 ----------------------------------
 1 file changed, 34 deletions(-)

diff --git a/bunkoer/utils/gpt.py b/bunkoer/utils/gpt.py
index ce9e273..a964770 100644
--- a/bunkoer/utils/gpt.py
+++ b/bunkoer/utils/gpt.py
@@ -2,14 +2,6 @@
 import json
 import os
 
-from langchain.llms.openai import OpenAI
-from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.document_loaders.csv_loader import CSVLoader
-from langchain.chains import RetrievalQA
-from langchain.vectorstores import FAISS
-from langchain.chat_models import ChatOpenAI
-
-
 def send_gpt_request(input_message, model, temperature, max_tokens):
     API_KEY = os.environ.get('OPENAI_API_KEY')
     API_ENDPOINT = "https://api.openai.com/v1/chat/completions"
@@ -41,29 +33,3 @@ def send_gpt_request(input_message, model, temperature, max_tokens):
     else:
         raise Exception(f"[ERROR] Gpt request : {response.status_code}: {response.text}")
     
-def embeding(temperature, model_name, user_input, base_file):
-    if os.path.isfile(base_file):
-        try:
-            loader = CSVLoader(file_path=base_file, encoding="utf-8")
-            data = loader.load()
-        except:
-            loader = CSVLoader(file_path=base_file, encoding="cp1252")
-            data = loader.load()
-
-        embeddings = OpenAIEmbeddings()
-        vectors = FAISS.from_documents(data, embeddings)
-        llm = ChatOpenAI(temperature=temperature, model_name=model_name)
-        qa = RetrievalQA.from_chain_type(llm=llm,
-                                         chain_type="stuff",
-                                         retriever=vectors.as_retriever(),
-                                         verbose=True)
-
-        def conversational_chat(query):
-            result = qa.run(query)
-            answer = result
-            return answer
-
-        response_text = conversational_chat(user_input)
-        return response_text
-    else:
-        return "Error the file is empty"