| import os | |
| import streamlit as st | |
| from clarifai.client.model import Model | |
| # Read API key from environment variable | |
| api_key = os.getenv("CodestralPat") | |
| # Function to get prediction from the model | |
| def get_model_prediction(prompt): | |
| model_url = "https://clarifai.com/mistralai/completion/models/codestral-22b-instruct" | |
| model = Model(url=model_url, pat=api_key) | |
| model_prediction = model.predict_by_bytes(prompt.encode(), input_type="text") | |
| return model_prediction.outputs[0].data.text.raw | |
| # Streamlit interface | |
| st.title("Codestral Goal Creator with Clarifai") | |
| st.write("Exam Data Analysis Example") | |
| prompt = st.text_area("Enter your prompt:", "Generate 10 specific, industry-relevant goals for exam data analysis using Python and Pandas. Each goal should include a brief name and a one-sentence description of the task or skill. Focus on practical applications in educational assessment, covering areas such as data processing, statistical analysis, visualization, and advanced techniques.", height=70) | |
| if st.button("Create Goals Using Codestral"): | |
| prediction = get_model_prediction(prompt) | |
| st.write("Model Prediction:") | |
| st.write(prediction) | |