Merge 3794baa1098c83ea56077dddec9c969f3dc9ff14 into d7eb05b9361febead29a74e71ddffc2ebeff5302

examples/langchain-python-rag-privategpt/ingest.py

@@ -5,7 +5,7 @@ from typing import List
 from multiprocessing import Pool
 from tqdm import tqdm
 
-from langchain.document_loaders import (
+from langchain_community.document_loaders import (
     CSVLoader,
     EverNoteLoader,
     PyMuPDFLoader,
@@ -20,9 +20,9 @@ from langchain.document_loaders import (
 )
 
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.vectorstores import Chroma
-from langchain.embeddings import HuggingFaceEmbeddings
-from langchain.docstore.document import Document
+from langchain_community.vectorstores import Chroma
+from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain_community.docstore.document import Document
 from constants import CHROMA_SETTINGS
 
 

examples/langchain-python-rag-privategpt/privateGPT.py

@@ -1,9 +1,9 @@
 #!/usr/bin/env python3
 from langchain.chains import RetrievalQA
-from langchain.embeddings import HuggingFaceEmbeddings
+from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
-from langchain.vectorstores import Chroma
-from langchain.llms import Ollama
+from langchain_community.vectorstores import Chroma
+from langchain_community.llms import Ollama
 import chromadb
 import os
 import argparse
@@ -30,7 +30,7 @@ def main():
     # activate/deactivate the streaming StdOut callback for LLMs
     callbacks = [] if args.mute_stream else [StreamingStdOutCallbackHandler()]
 
-    llm = Ollama(model=model, callbacks=callbacks)
+    llm = Ollama(base_url='http://localhost:11434', model=model, callbacks=callbacks)
 
     qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents= not args.hide_source)
     # Interactive questions and answers