Update app.py

app.py

@@ -1,42 +1,45 @@
-import os
-import streamlit as st
-from huggingface_hub import InferenceClient
-
-# Load the API token from an environment variable
-api_key = os.getenv("HF_TOKEN")
-
-# Instantiate the InferenceClient
-client = InferenceClient(api_key=api_key)
-
-# Streamlit app title
-st.title("Hugging Face Inference with Streamlit")
-
-# Create a text input area for user prompts
-with st.form("my_form"):
-    text = st.text_area("Enter text:", "Tell me a joke to make me laugh.")
-    submitted = st.form_submit_button("Submit")
-
-# Initialize the full_text variable
-full_text = ""
-
-if submitted:
-    messages = [
-        {"role": "user", "content": text}
-    ]
-    
-    # Create a new stream for each submission
-    stream = client.chat.completions.create(
-        model="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
-        messages=messages,
-        temperature=0.5,
-        max_tokens=100,
-        top_p=0.7,
-        stream=True
-    )
-
-    # Concatenate chunks to form the full response
-    for chunk in stream:
-        full_text += chunk.choices[0].delta.content
-
-    # Display the full response
-    st.info(full_text)
+"""
+@author: idoia lerchundi
+"""
+import os
+import streamlit as st
+from huggingface_hub import InferenceClient
+
+# Load the API token from an environment variable
+api_key = os.getenv("HF_TOKEN")
+
+# Instantiate the InferenceClient
+client = InferenceClient(api_key=api_key)
+
+# Streamlit app title
+st.title("Hugging Face Inference with Streamlit")
+
+# Create a text input area for user prompts
+with st.form("my_form"):
+    text = st.text_area("Enter text:", "Tell me a joke to make me laugh.")
+    submitted = st.form_submit_button("Submit")
+
+# Initialize the full_text variable
+full_text = ""
+
+if submitted:
+    messages = [
+        {"role": "user", "content": text}
+    ]
+    
+    # Create a new stream for each submission
+    stream = client.chat.completions.create(
+        model="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+        messages=messages,
+        temperature=0.5,
+        max_tokens=100,
+        top_p=0.7,
+        stream=True
+    )
+
+    # Concatenate chunks to form the full response
+    for chunk in stream:
+        full_text += chunk.choices[0].delta.content
+
+    # Display the full response
+    st.info(full_text)