ui

README.md

@@ -10,3 +10,4 @@ pinned: false
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+https://huggingface.co/spaces/deepakaitcs/learnai

app.py

@@ -1,26 +1,42 @@
 ## Difference between Open AI and hugging face
 
+import streamlit as st
+
+
 from dotenv import load_dotenv
 load_dotenv()
 from langchain_openai import OpenAI
 llm = OpenAI()
-result= llm.invoke("What is capital of India")
-print(result)
 
-## Use Huggingface to load google Model using langchain
+def load_Answer(inputtext):
+    result= llm(inputtext)
+    return result
+
+st.set_page_config(
+    page_title="My Chat GPT",
+     page_icon="🧊",
+     layout="wide",
+     initial_sidebar_state="expanded",
+     menu_items={
+         'Get Help': 'https://www.extremelycoolapp.com/help',
+         'Report a bug': "https://www.extremelycoolapp.com/bug",
+         'About': "# This is a header. This is an *extremely* cool app!"
+     }
+ )
+
+st.header('This is a header')
+
+def get_text():
+    i= st.text_input("You: ", key="input")
+    return i
+
+user_input = get_text()
 
-from langchain import HuggingFaceHub
-llm2 = HuggingFaceHub(
-    repo_id="google/flan-t5-large",
-    model_kwargs={"temperature":0, "max_length":180}
-)
+response = load_Answer(user_input)
 
-results2= llm2("what is the capital of Sri lanka")
-print(results2)
+submit = st.button("Submit")
 
-## Use Google GenAI chat models using langChain
+if submit:
+    st.subheader("Answer:")
+    st.write(response)
 
-from langchain_google_genai import ChatGoogleGenerativeAI
-chat = ChatGoogleGenerativeAI(model="gemini-pro")
-results3 = chat.invoke("What is the capital of Pakistan")
-print(results3.content)

requirements.txt

@@ -1,4 +1,5 @@
 langchain
 openai
 langchain_openai
-langchain_google_genai
+langchain_google_genai
+streamlit