Update app.py

app.py

@@ -10,6 +10,49 @@ warnings.filterwarnings("ignore")
 from langchain.document_loaders import TextLoader
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.vectorstores import Pinecone as PineconeVectorStore
+from langchain.llms import HuggingFaceHub
+from langchain import PromptTemplate
+from langchain.schema.runnable import RunnablePassthrough
+from langchain.schema.output_parser import StrOutputParser
+
+
+from pinecone import Pinecone, ServerlessSpec
+pc = Pinecone(api_key=keyfile.PINECONE_API_KEY)
+os.environ["PINECONE_API_KEY"] = keyfile.PINECONE_API_KEY
+
+
+cloud = os.environ.get("PINECONE_CLOUD") or "aws"
+region = os.environ.get("PINECONE_REGION") or "us-east-1"
+serv = ServerlessSpec(cloud = cloud, region = region)
+
+model_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+llm = HuggingFaceHub(
+    repo_id = model_id,
+    model_kwargs = {"temperature" : 0.8, "top_k" : 50},
+    huggingfacehub_api_token = userdata.get("HFToken")
+)
+
+index_name = "parasgupta"
+# We are check if the name of our index is not existing in pinecone directory
+if index_name not in pc.list_indexes().names():
+  # if not then we will create a index for us
+  pc.create_index(
+      name = index_name,
+      dimension = 768,
+      metric = "cosine",
+      spec = serv
+  )
+  while not pc.describe_index(index_name).status['ready']:
+    time.sleep(1)
+# IF the index is not there in the index list
+if index_name not in pc.list_indexes():
+  docsearch = PineconeVectorStore.from_documents(docs, embeddings, index_name = index_name)
+else:
+  docsearch = PineconeVectorStore.from_existing_index(index_name, embeddings, pinecone_index = pc.Index(index_name))
+
+    
+
 
 loader = TextLoader("/content/drive/MyDrive/Intelli_GenAI/RAG/Machine Learning Operations.txt")
 documents = loader.load()