Merge pull request #9 from lpm0073/next

style: lint and reorganize imports

Author: lpm0073

models/ssm.py

@@ -7,28 +7,27 @@
      https://python.langchain.com/docs/integrations/retrievers/pinecone_hybrid_search
 """
 
+# document loading
 import glob
 import os
 import textwrap
-from typing import List  # ClassVar
+from typing import List
 
 # pinecone integration
 import pinecone
 from langchain.cache import InMemoryCache
-
-# prompting and chat
 from langchain.chat_models import ChatOpenAI
-
-# document loading
 from langchain.document_loaders import PyPDFLoader
 
 # embedding
 from langchain.embeddings import OpenAIEmbeddings
-
-# vector database
 from langchain.globals import set_llm_cache
+
+# prompting and chat
 from langchain.llms.openai import OpenAI
 from langchain.prompts import PromptTemplate
+
+# hybrid search capability
 from langchain.retrievers import PineconeHybridSearchRetriever
 from langchain.schema import HumanMessage, SystemMessage
 from langchain.text_splitter import Document
@@ -39,9 +38,6 @@
 from models.const import Credentials
 
 
-# from pydantic import BaseModel, ConfigDict, Field
-
-
 ###############################################################################
 # initializations
 ###############################################################################
@@ -107,11 +103,6 @@ def prompt_with_template(self, prompt: PromptTemplate, concept: str, model: str
         retval = llm(prompt.format(concept=concept))
         return retval
 
-    def split_text(self, text: str) -> List[Document]:
-        """Split text. Leaving this here for now, since it exposes the return type."""
-        retval = self.text_splitter.create_documents([text])
-        return retval
-
     def fit_tf_idf_values(self, corpus: List[str]):
         """Fit TF-IDF values.
         1. Fit the BM25 encoder on the corpus