Update app.py

app.py

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+import streamlit as st
+import getpass
+import ibm_watsonx_ai
+from ibm_watsonx_ai.foundation_models import Model
+
+def get_credentials():
+    # Simulating the input of API key 'abc123456'
+    apikey = 'O0g17oATnv3hpejzM9svvjaNQc7LX7xV2qH5418saEXD'
+    return {
+        "url": "https://us-south.ml.cloud.ibm.com",
+        "apikey": apikey
+    }
+
+
+# Parameters and model initialization
+model_id = "codellama/codellama-34b-instruct-hf"
+parameters = {
+    "decoding_method": "greedy",
+    "max_new_tokens": 1000,
+    "min_new_tokens": 1,
+    "stop_sequences": ["<end of code>"],
+    "repetition_penalty": 1
+}
+
+# Streamlit app begins
+st.title('Code Generation with IBM WATSONX AI')
+
+# Input prompt text area
+prompt_input = st.text_area('Enter your prompt (instructions):', height=250)
+
+# Button to generate code
+if st.button('Generate Code'):
+    st.text("Generating code...")
+
+    # Initialize the model with credentials
+    credentials = get_credentials()
+    model = Model(
+        model_id=model_id,
+        params=parameters,
+        credentials=credentials,
+        project_id="78275590-aa27-4c1e-a426-f39640aa0003",
+    )
+
+    # Generate response based on the prompt
+    generated_response = model.generate_text(prompt=prompt_input, guardrails=False)
+
+    # Display the generated response
+    st.subheader('Generated Code:')
+    st.code(generated_response)
+
+# Instructions or info section
+st.markdown('''
+### Instructions:
+- Enter the instructions for code generation in the text area.
+- Click on **Generate Code** to generate Python code based on the instructions.
+''')