upload change toPalm

app.py

@@ -3,6 +3,7 @@ from streamlit_chat import message
 from langchain.chains import ConversationalRetrievalChain
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.llms import CTransformers
+from langchain.llms import GooglePalm
 from langchain.llms import Replicate
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.vectorstores import FAISS
@@ -10,6 +11,8 @@ from langchain.memory import ConversationBufferMemory
 from langchain.document_loaders import PyPDFLoader
 from langchain.document_loaders import TextLoader
 from langchain.document_loaders import Docx2txtLoader
+from langchain.document_loaders import CSVLoader
+from langchain.document_loaders import UnstructuredExcelLoader
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
 import os
 from dotenv import load_dotenv
@@ -63,11 +66,16 @@ def create_conversational_chain(vector_store):
                         #streaming=True, 
                         #callbacks=[StreamingStdOutCallbackHandler()],
                         #model_type="llama", config={'max_new_tokens': 500, 'temperature': 0.01})
-    llm = Replicate(
+    # llm = Replicate(
+    #     streaming = True,
+    #     model = "replicate/llama-2-70b-chat:58d078176e02c219e11eb4da5a02a7830a283b14cf8f94537af893ccff5ee781", 
+    #     callbacks=[StreamingStdOutCallbackHandler()],
+    #     input = {"temperature": 0.01, "max_length" :500,"top_p":1})
+    llm = GooglePlam(
         streaming = True,
-        model = "replicate/llama-2-70b-chat:58d078176e02c219e11eb4da5a02a7830a283b14cf8f94537af893ccff5ee781", 
+        model = "google/flan-t5-large", #" models/text-bison-001"
         callbacks=[StreamingStdOutCallbackHandler()],
-        input = {"temperature": 0.01, "max_length" :500,"top_p":1})
+        input = {"temperature": 0.07, "max_length" :1024,"top_p":0.95})
     memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
 
     chain = ConversationalRetrievalChain.from_llm(llm=llm, chain_type='stuff',
@@ -98,6 +106,10 @@ def main():
                 loader = PyPDFLoader(temp_file_path)
             elif file_extension == ".docx" or file_extension == ".doc":
                 loader = Docx2txtLoader(temp_file_path)
+            elif file_extension == ".xlsx" or file_extension == ".xls":
+                loader = UnstructuredExcelLoader(temp_file_path)
+            elif file_extension == ".csv":
+                loader = CSVLoader(temp_file_path)
             elif file_extension == ".txt":
                 loader = TextLoader(temp_file_path)
 

requirements.txt

@@ -11,4 +11,5 @@ huggingface-hub
 pypdf
 python-dotenv
 replicate
-docx2txt
+docx2txt
+google-generativeai