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| import streamlit as st | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| st.title("🤖 LLM Evaluation") | |
| pages = [ | |
| st.Page("GenerateModelTraces.py", title="Generate Traces"), | |
| st.Page("LLMasjudge.py", title="LLM as a Judge"), | |
| st.Page("evaluationwithexistingdata.py", title="Evaluate with existing data"), | |
| st.Page("experiments.py", title="Run Experiment"), | |
| ] | |
| pg = st.navigation(pages) | |
| pg.run() | |
| # action = st.radio("What would you like to do?", ["Generate Traces for Model", "Evaluate Model"]) | |
| # models = helpers.fetch_models() | |
| # if models: | |
| # if action == "Generate Traces for Model": | |
| # st.subheader("Select a Model") | |
| # if "selected_model" not in st.session_state: | |
| # st.session_state.selected_model = models[0] | |
| # st.selectbox( | |
| # "Choose a model to use:", | |
| # models, key = 'selected_model', | |
| # index=models.index(st.session_state.selected_model) if st.session_state.selected_model in models else 0 | |
| # ) | |
| # if st.session_state.selected_model: | |
| # st.subheader("Enter a Prompt") | |
| # if "prompt" not in st.session_state: | |
| # st.session_state.prompt = "" | |
| # st.session_state.prompt = st.text_area("Enter your prompt:", value=st.session_state.prompt) | |
| # if st.button("Generate Content", on_click=callback): | |
| # if st.session_state.prompt: | |
| # st.subheader("Model Output") | |
| # st.session_state.generated_content = helpers.generate_content(st.session_state.selected_model, st.session_state.prompt) | |
| # st.write(st.session_state.generated_content) | |
| # st.session_state.spans_df = phoenix_helpers.get_spans_df() | |
| # # print(spans_df) | |
| # st.dataframe(st.session_state.spans_df) | |
| # else: | |
| # st.write("Enter something to generate content.") | |
| # elif action == "Evaluate Model": | |
| # st.session_state.spans_df = phoenix_helpers.get_spans_df() | |
| # st.subheader("Evaluate LLM") | |
| # if "evaluation_result" not in st.session_state: | |
| # st.session_state.evaluation_result = None | |
| # if (st.button("Evaluate", on_click=callback2) or st.session_state.eval_btn_clicked): | |
| # if "eval_model" not in st.session_state: | |
| # st.session_state.eval_model = models[0] | |
| # st.selectbox( | |
| # "Choose a model to use for evaluation:", | |
| # models, key = 'eval_model', | |
| # index=models.index(st.session_state.eval_model) if st.session_state.eval_model in models else 0, | |
| # ) | |
| # if st.session_state.eval_model: | |
| # st.session_state.evaluation_result = phoenix_helpers.evaluate_model(st.session_state.spans_df, st.session_state.eval_model) | |
| # st.write(st.session_state.evaluation_result) | |