Spaces:
Sleeping
Sleeping
Rename 2_rag_skeleton.py to app.py
Browse files
2_rag_skeleton.py → app.py
RENAMED
@@ -7,6 +7,8 @@ from langchain.chains import ConversationalRetrievalChain
|
|
7 |
from langchain_community.chat_message_histories import ChatMessageHistory
|
8 |
from langchain.memory import ConversationBufferMemory
|
9 |
from langchain_core.prompts import PromptTemplate
|
|
|
|
|
10 |
|
11 |
# Access the OpenAI API key from the environment
|
12 |
open_ai_key = os.getenv("OPENAI_API_KEY")
|
@@ -25,7 +27,8 @@ Helpful answer:
|
|
25 |
|
26 |
prompt = PromptTemplate(template=template, input_variables=["context", "question"])
|
27 |
|
28 |
-
|
|
|
29 |
# Load and process the PDF
|
30 |
loader = PyPDFLoader(pdf_file.name)
|
31 |
pdf_data = loader.load()
|
|
|
7 |
from langchain_community.chat_message_histories import ChatMessageHistory
|
8 |
from langchain.memory import ConversationBufferMemory
|
9 |
from langchain_core.prompts import PromptTemplate
|
10 |
+
import streamlit as st
|
11 |
+
|
12 |
|
13 |
# Access the OpenAI API key from the environment
|
14 |
open_ai_key = os.getenv("OPENAI_API_KEY")
|
|
|
27 |
|
28 |
prompt = PromptTemplate(template=template, input_variables=["context", "question"])
|
29 |
|
30 |
+
# upload PDF
|
31 |
+
pdf_file = st.file_uploader("Upload your pdf")
|
32 |
# Load and process the PDF
|
33 |
loader = PyPDFLoader(pdf_file.name)
|
34 |
pdf_data = loader.load()
|