commented gpt model

chatBot/common/chatgpt.py

@@ -1,43 +1,43 @@
-import os
-from chatBot.common.pdfToText import loadLatestPdf
-os.environ["OPENAI_API_KEY"] = "INSERTYOUROWNAPIKEYHERE"
-from langchain.document_loaders import PyPDFLoader
-from langchain.text_splitter import CharacterTextSplitter
-import pickle
-import faiss
-from langchain.vectorstores import FAISS
-from langchain.embeddings import OpenAIEmbeddings
-from langchain.chains import RetrievalQAWithSourcesChain
-from langchain.chains.question_answering import load_qa_chain
-from langchain import OpenAI
+# import os
+# from chatBot.common.pdfToText import loadLatestPdf
+# os.environ["OPENAI_API_KEY"] = "INSERTYOUROWNAPIKEYHERE"
+# from langchain.document_loaders import PyPDFLoader
+# from langchain.text_splitter import CharacterTextSplitter
+# import pickle
+# import faiss
+# from langchain.vectorstores import FAISS
+# from langchain.embeddings import OpenAIEmbeddings
+# from langchain.chains import RetrievalQAWithSourcesChain
+# from langchain.chains.question_answering import load_qa_chain
+# from langchain import OpenAI
 
-urls = [
-    'http://en.espn.co.uk/f1/motorsport/story/3836.html', 'https://www.mercedes-amg-hpp.com/formula-1-engine-facts/#' , 'https://www.redbullracing.com/int-en/five-things-about-yas-marina' , 'https://www.redbull.com/gb-en/history-of-formula-1'
-, 'https://www.formula1.com/en/information.abu-dhabi-yas-marina-circuit-yas-island.4YtOtpaWvaxWvDBTItP7s6.html']
+# urls = [
+#     'http://en.espn.co.uk/f1/motorsport/story/3836.html', 'https://www.mercedes-amg-hpp.com/formula-1-engine-facts/#' , 'https://www.redbullracing.com/int-en/five-things-about-yas-marina' , 'https://www.redbull.com/gb-en/history-of-formula-1'
+# , 'https://www.formula1.com/en/information.abu-dhabi-yas-marina-circuit-yas-island.4YtOtpaWvaxWvDBTItP7s6.html']
 
 
-data = loadLatestPdf()
+# data = loadLatestPdf()
 
 
-text_splitter = CharacterTextSplitter(separator='\n',
-                                      chunk_size=1000,
-                                      chunk_overlap=200)
+# text_splitter = CharacterTextSplitter(separator='\n',
+#                                       chunk_size=1000,
+#                                       chunk_overlap=200)
 
 
-docs = text_splitter.split_documents(data)
+# docs = text_splitter.split_documents(data)
 
 
-embeddings = OpenAIEmbeddings()
+# embeddings = OpenAIEmbeddings()
 
-vectorStore1_openAI = FAISS.from_documents(docs, embeddings)
+# vectorStore1_openAI = FAISS.from_documents(docs, embeddings)
 
-with open("faiss_store_openai.pkl", "wb") as f:
-    pickle.dump(vectorStore1_openAI, f)
+# with open("faiss_store_openai.pkl", "wb") as f:
+#     pickle.dump(vectorStore1_openAI, f)
 
-with open("faiss_store_openai.pkl", "rb") as f:
-    VectorStore = pickle.load(f)
+# with open("faiss_store_openai.pkl", "rb") as f:
+#     VectorStore = pickle.load(f)
 
 
-llm=OpenAI(temperature=0.8, verbose = True)
+# llm=OpenAI(temperature=0.8, verbose = True)
 
-gptModel = RetrievalQAWithSourcesChain.from_llm(llm=llm, retriever=VectorStore.as_retriever())
+# gptModel = RetrievalQAWithSourcesChain.from_llm(llm=llm, retriever=VectorStore.as_retriever())

chatBot/common/utils.py

@@ -1,4 +1,4 @@
-from chatBot.common.chatgpt import gptModel
+# from chatBot.common.chatgpt import gptModel
 from chatBot.common.llama import llamaModel
 
 
@@ -6,4 +6,4 @@ def getAnswerLlama(question):
     return llamaModel(question) 
 
 def getAnswerGpt(question):
-    return gptModel({'question' : question}, return_only_outputs = True)['answer']
+    return "answer"