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| import asyncio | |
| import os | |
| from importlib import import_module | |
| import pandas as pd | |
| import rich | |
| import streamlit as st | |
| import weave | |
| from dotenv import load_dotenv | |
| from guardrails_genie.guardrails import GuardrailManager | |
| from guardrails_genie.llm import OpenAIModel | |
| from guardrails_genie.metrics import AccuracyMetric | |
| def initialize_session_state(): | |
| load_dotenv() | |
| if "weave_project_name" not in st.session_state: | |
| st.session_state.weave_project_name = "guardrails-genie" | |
| if "uploaded_file" not in st.session_state: | |
| st.session_state.uploaded_file = None | |
| if "dataset_name" not in st.session_state: | |
| st.session_state.dataset_name = None | |
| if "preview_in_app" not in st.session_state: | |
| st.session_state.preview_in_app = False | |
| if "is_dataset_published" not in st.session_state: | |
| st.session_state.is_dataset_published = False | |
| if "publish_dataset_button" not in st.session_state: | |
| st.session_state.publish_dataset_button = False | |
| if "dataset_ref" not in st.session_state: | |
| st.session_state.dataset_ref = None | |
| initialize_session_state() | |
| st.title(":material/monitoring: Evaluation") | |
| weave_project_name = st.sidebar.text_input( | |
| "Weave project name", value=st.session_state.weave_project_name | |
| ) | |
| st.session_state.weave_project_name = weave_project_name | |
| if st.session_state.weave_project_name != "": | |
| weave.init(project_name=st.session_state.weave_project_name) | |
| uploaded_file = st.sidebar.file_uploader( | |
| "Upload the evaluation dataset as a CSV file", type="csv" | |
| ) | |
| st.session_state.uploaded_file = uploaded_file | |
| if st.session_state.uploaded_file is not None: | |
| dataset_name = st.sidebar.text_input("Evaluation dataset name", value=None) | |
| st.session_state.dataset_name = dataset_name | |
| preview_in_app = st.sidebar.toggle("Preview in app", value=False) | |
| st.session_state.preview_in_app = preview_in_app | |
| publish_dataset_button = st.sidebar.button("Publish dataset") | |
| st.session_state.publish_dataset_button = publish_dataset_button | |
| if ( | |
| st.session_state.publish_dataset_button | |
| and ( | |
| st.session_state.dataset_name is not None | |
| and st.session_state.dataset_name != "" | |
| ) | |
| ): | |
| with st.expander("Evaluation Dataset Preview", expanded=True): | |
| dataframe = pd.read_csv(st.session_state.uploaded_file) | |
| data_list = dataframe.to_dict(orient="records") | |
| dataset = weave.Dataset(name=st.session_state.dataset_name, rows=data_list) | |
| st.session_state.dataset_ref = weave.publish(dataset) | |
| entity = st.session_state.dataset_ref.entity | |
| project = st.session_state.dataset_ref.project | |
| dataset_name = st.session_state.dataset_name | |
| digest = st.session_state.dataset_ref._digest | |
| dataset_url = f"https://wandb.ai/{entity}/{project}/weave/objects/{dataset_name}/versions/{digest}" | |
| st.markdown( | |
| f"Dataset published to [**Weave**]({dataset_url})" | |
| ) | |
| if preview_in_app: | |
| st.dataframe(dataframe.head(20)) | |
| if len(dataframe) > 20: | |
| st.markdown( | |
| f"⚠️ Dataset is too large to preview in app, please explore in the [**Weave UI**]({dataset_url})" | |
| ) | |
| st.session_state.is_dataset_published = True | |
| if st.session_state.is_dataset_published: | |
| st.write("Maza Ayega") | |