Create app.py

app.py

@@ -0,0 +1,96 @@
+import os
+import streamlit as st
+from langchain.llms import HuggingFaceHub
+
+
+from models import return_models, return_text2text_generation_models, return_task_name, return_text_generation_models
+dummy_parent = "google"
+models_count = return_text2text_generation_models(dummy_parent, True) + return_text_generation_models(dummy_parent, True)
+st.warning("Warning: Some models may not work and some models may require GPU to run")
+st.text(f"As of now there are {models_count} model available")
+st.text("Made with Langchain, StreamLit, Hugging Face and 💖")
+st.header('🦜🔗 One stop for Open Source Models')
+
+API_KEY = st.sidebar.text_input(
+    'API Key',
+    type='password',
+    help="Type in your HuggingFace API key to use this app")
+
+task_name = st.sidebar.selectbox(
+    label = "Choose the task you want to perform",
+    options = return_task_name(),
+    help="Choose your open source LLM to get started"
+    )
+if task_name is None:
+    model_parent_visibility = True
+else:
+    model_parent_visibility = False
+    
+model_parent_options = return_models(task_name)
+model_parent = st.sidebar.selectbox(
+    label = "Choose your Source",
+    options = model_parent_options,
+    help="Choose your source of models",
+    disabled=model_parent_visibility
+    )
+
+if model_parent is None:
+    model_name_visibility = True
+else:
+    model_name_visibility = False
+if task_name == "text2text-generation":
+    options = return_text2text_generation_models(model_parent)
+else:
+    options = return_text_generation_models(model_parent)
+model_name = st.sidebar.selectbox(
+    label = "Choose your Models",
+    options = options,
+    help="Choose your open source LLM to get started",
+    disabled=model_name_visibility
+    )
+
+temperature = st.sidebar.slider(
+    label="Temperature",
+    min_value=0.1,
+    max_value=1.0,
+    step=0.1,
+    value=0.9,
+    help="Set the temperature to get accurate results"
+    )
+
+max_token_length = st.sidebar.slider(
+    label="Token Length",
+    min_value=32,
+    max_value=1024,
+    step=32,
+    value=1024,
+    help="Set the max tokens to get accurate results"
+    )
+
+
+os.environ['HUGGINGFACEHUB_API_TOKEN'] = API_KEY
+def generate_response(input_text):
+    
+    model_kwargs = {
+        "temperature": temperature,
+        "max_length": max_token_length
+    }
+    llm = HuggingFaceHub(
+        repo_id = model_name,
+        model_kwargs = model_kwargs
+    )
+
+    st.info(llm(input_text))
+
+
+with st.form('my_form'):
+    try:
+        text = st.text_area('Enter Your Prompt', 'What are the three key pieces of advice for learning how to code?')
+        submitted = st.form_submit_button('Submit')
+        if not API_KEY.startswith('hf_'):
+            st.warning('Please enter your API key!', icon='⚠')
+        if submitted and API_KEY.startswith('hf_'):
+            with st.spinner("Running...."):
+                generate_response(text)
+    except Exception as e:
+        st.error(e, icon="🚨")