How can i change the actual output to be in another languages in Langchain (like German or France) with a local files and simlary search?

Question

I have been trying to find some documentation about chaning the actual languages (like France or German) of the LMM output by langchain framework when i use a local file as a knowlegde for my LMM.

Here is the full code:

from PyPDF2 import PdfReader
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import ElasticVectorSearch, Pinecone, Weaviate, FAISS
from langchain.llms import OpenAI

from langchain import OpenAI, ConversationChain, LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory


# Get your API keys from openai, you will need to create an account. 
# Here is the link to get the keys: https://platform.openai.com/account/billing/overview
import os
os.environ["OPENAI_API_KEY"] = "i have enter my own API-key here"


# location of the pdf file/files. 
reader = PdfReader(r'C:\Users\admin\Downloads\2023_GPT4All_Technical_Report.pdf')


# read data from the file and put them into a variable called raw_text
raw_text = ''
for i, page in enumerate(reader.pages):
    text = page.extract_text()
    if text:
        raw_text += text
        


# We need to split the text that we read into smaller chunks so that during information retreival we don't hit the token size limits. 
text_splitter = CharacterTextSplitter(        
    separator = "\n",
    chunk_size = 1000,
    chunk_overlap  = 200,
    length_function = len,
)
texts = text_splitter.split_text(raw_text)

# Download embeddings from OpenAI
embeddings = OpenAIEmbeddings()

docsearch = FAISS.from_texts(texts, embeddings)

from langchain.chains.question_answering import load_qa_chain
from langchain.llms import OpenAI

chain = load_qa_chain(OpenAI(), chain_type="stuff")


query = input("ask a question \n")
docs = docsearch.similarity_search(query)
print(chain.run(input_documents=docs, question=query))

I have tried to change the code by using a agent from Langchain, but i could not get it to work

New codei have tried:

from langchain.chat_models import ChatOpenAI
from langchain import PromptTemplate, LLMChain
from langchain.prompts.chat import (
    ChatPromptTemplate,
    SystemMessagePromptTemplate,
    AIMessagePromptTemplate,
    HumanMessagePromptTemplate,
)
from langchain.schema import (
    AIMessage,
    HumanMessage,
    SystemMessage
)

template="You are a helpful assistant that translates {input_language} to {output_language}."
system_message_prompt = SystemMessagePromptTemplate.from_template(template)
human_template="{text}"
human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)

chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])

chat = ChatOpenAI(temperature=0)

# get a chat completion from the formatted messages
chat(chat_prompt.format_prompt(input_language="English", output_language="French", text="I love programming.").to_messages())


chain = LLMChain(llm=chat, prompt=chat_prompt)