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| """Data analysis workflow form and runner.""" | |
| from pathlib import Path | |
| import streamlit as st | |
| from loguru import logger | |
| from utils import cleanup_uploaded_data, save_and_extract_upload | |
| from scider.core import constant | |
| from scider.workflows.data_workflow import DataWorkflow | |
| from scider.workflows.hypo_data_workflow import HypoDataWorkflow | |
| def run_data(path, q, workspace_path): | |
| """Run data workflow. Called from background thread.""" | |
| data_path = Path(path) if Path(path).exists() else path # may be HF repo name | |
| logger.info(f"Running data analysis on path: {data_path}") | |
| w = DataWorkflow( | |
| data_path=Path(path) if Path(path).exists() else Path(str(path)), | |
| workspace_path=workspace_path, | |
| recursion_limit=100, | |
| ) | |
| w.run() | |
| intermediate_state = getattr(w, "data_agent_intermediate_state", []) | |
| if w.final_status != "success": | |
| error_msg = w.error_message or "Data workflow failed" | |
| return f"Data workflow failed: {error_msg}", intermediate_state | |
| out = ["## Data Analysis Complete"] | |
| if w.data_summary: | |
| out.append(w.data_summary) | |
| return "\n\n".join(out), intermediate_state | |
| def run_hypo_data(feature_desc, num_rows, query, workspace_path): | |
| """Run hypothetical data workflow. Called from background thread.""" | |
| logger.info(f"Running hypothetical data generation: {feature_desc[:100]}...") | |
| w = HypoDataWorkflow( | |
| feature_desc=feature_desc, | |
| workspace_path=workspace_path, | |
| num_rows=num_rows, | |
| user_query=query, | |
| recursion_limit=100, | |
| ) | |
| w.run() | |
| if w.final_status != "success": | |
| error_msg = w.error_message or "Hypothetical data workflow failed" | |
| return f"Workflow failed: {error_msg}", [] | |
| out = ["## Hypothetical Data Analysis Complete"] | |
| if w.data_summary: | |
| out.append(w.data_summary) | |
| return "\n\n".join(out), [] | |
| def render_form(): | |
| """Render the data analysis form. Returns workflow_config dict or None.""" | |
| hf_enabled = constant.HF_DATASET_DOWNLOAD_ENABLED | |
| source_options = ["Upload local file"] | |
| if hf_enabled: | |
| source_options.append("HuggingFace dataset") | |
| source_options.append("Generate hypothetical data") | |
| data_source = st.radio( | |
| "Data Source", | |
| source_options, | |
| horizontal=True, | |
| key="data_source_radio", | |
| ) | |
| with st.form("data_form", clear_on_submit=True): | |
| st.markdown("### Data Analysis Workflow") | |
| if data_source == "Generate hypothetical data": | |
| feature_desc = st.text_area( | |
| "Describe the data you want to generate", | |
| placeholder=( | |
| "e.g. A dataset about house prices with features: " | |
| "square footage (1000-5000 sq ft), number of bedrooms (1-6), " | |
| "age of house (0-100 years), price ($100k-$1M)" | |
| ), | |
| height=150, | |
| help="Describe the features, their ranges, and the domain of the dataset.", | |
| ) | |
| num_rows = st.number_input( | |
| "Number of rows", | |
| min_value=10, | |
| max_value=100000, | |
| value=1000, | |
| step=100, | |
| ) | |
| query = st.text_input( | |
| "Analysis query", | |
| placeholder="What would you like to analyze about this data?", | |
| ) | |
| submitted = st.form_submit_button("Generate & Analyze") | |
| if submitted: | |
| if not feature_desc or not feature_desc.strip(): | |
| st.error("Please describe the data you want to generate.") | |
| return None | |
| return { | |
| "type": "data_hypo", | |
| "feature_desc": feature_desc.strip(), | |
| "num_rows": num_rows, | |
| "query": query | |
| or f"Analyze this synthetic dataset: {feature_desc.strip()[:200]}", | |
| } | |
| elif data_source == "HuggingFace dataset": | |
| hf_repo = st.text_input( | |
| "HuggingFace Dataset Repo", | |
| placeholder="e.g. scikit-learn/iris", | |
| help="Enter a HuggingFace dataset repository name. It will be downloaded automatically.", | |
| ) | |
| query = st.text_input("Query", placeholder="What would you like to analyze?") | |
| submitted = st.form_submit_button("Run Data Analysis") | |
| if submitted: | |
| if not hf_repo or not hf_repo.strip(): | |
| st.error("Please enter a HuggingFace dataset repository name.") | |
| return None | |
| if not query or not query.strip(): | |
| query = "Analyze this dataset — explore its structure, key patterns, and notable findings." | |
| return {"type": "data", "path": hf_repo.strip(), "query": query} | |
| else: | |
| st.caption("Upload a zip dataset or enter a path to existing data") | |
| uploaded_zip = st.file_uploader( | |
| "Upload ZIP dataset (optional)", | |
| type=["zip"], | |
| help="Upload a zip file containing your dataset. Extracted temporarily, deleted on reset.", | |
| ) | |
| if st.session_state.get("uploaded_data_path"): | |
| st.info(f"Using uploaded data: `{st.session_state.uploaded_data_path}`") | |
| query = st.text_input("Query", placeholder="What would you like to analyze?") | |
| submitted = st.form_submit_button("Run Data Analysis") | |
| if submitted: | |
| if not query or not query.strip(): | |
| query = "Analyze this dataset — explore its structure, key patterns, and notable findings." | |
| path_to_use = None | |
| if uploaded_zip: | |
| cleanup_uploaded_data() | |
| extracted = save_and_extract_upload(uploaded_zip) | |
| if extracted and extracted.exists(): | |
| extracted = extracted.resolve() | |
| st.session_state.uploaded_data_path = str(extracted) | |
| st.session_state.workspace_path = extracted.parent | |
| path_to_use = str(extracted) | |
| st.success(f"File uploaded and extracted to: {path_to_use}") | |
| else: | |
| st.error( | |
| f"Failed to process uploaded zip file. Extracted path: {extracted}" | |
| ) | |
| elif st.session_state.get("uploaded_data_path"): | |
| path = Path(st.session_state.uploaded_data_path).resolve() | |
| if path.exists(): | |
| path_to_use = str(path) | |
| st.session_state.workspace_path = path.parent | |
| else: | |
| st.warning(f"Previously uploaded path no longer exists: {path}") | |
| cleanup_uploaded_data() | |
| if path_to_use: | |
| verify_path = Path(path_to_use).resolve() | |
| if not verify_path.exists(): | |
| st.error(f"Path does not exist: {path_to_use}") | |
| else: | |
| return {"type": "data", "path": str(verify_path), "query": query} | |
| else: | |
| st.error("Please upload a zip file or enter a data path.") | |
| return None | |