cookiemonster69 commited on
Commit
26a1c7b
1 Parent(s): 998b252

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +6 -15
app.py CHANGED
@@ -1,34 +1,25 @@
1
- #Hello! It seems like you want to import the Streamlit library in Python. Streamlit is a powerful open-source framework used for building web applications with interactive data visualizations and machine learning models. To import Streamlit, you'll need to ensure that you have it installed in your Python environment.
2
- #Once you have Streamlit installed, you can import it into your Python script using the import statement,
3
 
4
  import streamlit as st
5
 
6
- #As Langchain team has been working aggresively on improving the tool, we can see a lot of changes happening every weeek,
7
- #As a part of it, the below import has been depreciated
8
- #from langchain.llms import OpenAI
9
 
10
- #New import from langchain, which replaces the above
11
  from langchain_openai import OpenAI
12
 
13
- #When deployed on huggingface spaces, this values has to be passed using Variables & Secrets setting, as shown in the video :)
14
- #import os
15
- #os.environ["OPENAI_API_KEY"] = "sk-werwerwerrtertertwkFJwtwetwteWSig4ZY9AT"
16
 
17
- #Function to return the response
 
18
  def load_answer(question):
19
- # "text-davinci-003" model is depreciated, so using the latest one https://platform.openai.com/docs/deprecations
20
  llm = OpenAI(model_name="gpt-3.5-turbo-instruct",temperature=0)
21
 
22
- #Last week langchain has recommended to use invoke function for the below please :)
23
  answer=llm.invoke(question)
24
  return answer
25
 
26
 
27
- #App UI starts here
28
  st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
29
  st.header("LangChain Demo")
30
 
31
- #Gets the user input
32
  def get_text():
33
  input_text = st.text_input("You: ", key="input")
34
  return input_text
@@ -39,7 +30,7 @@ response = load_answer(user_input)
39
 
40
  submit = st.button('Generate')
41
 
42
- #If generate button is clicked
43
  if submit:
44
 
45
  st.subheader("Answer:")
 
 
 
1
 
2
  import streamlit as st
3
 
 
 
 
4
 
 
5
  from langchain_openai import OpenAI
6
 
 
 
 
7
 
8
+
9
+
10
  def load_answer(question):
11
+
12
  llm = OpenAI(model_name="gpt-3.5-turbo-instruct",temperature=0)
13
 
14
+
15
  answer=llm.invoke(question)
16
  return answer
17
 
18
 
 
19
  st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
20
  st.header("LangChain Demo")
21
 
22
+
23
  def get_text():
24
  input_text = st.text_input("You: ", key="input")
25
  return input_text
 
30
 
31
  submit = st.button('Generate')
32
 
33
+
34
  if submit:
35
 
36
  st.subheader("Answer:")