CRITICAL FIX: Stop load_fred_client() from clobbering FRED_API_AVAILABLE flag set in load_config()

Final consolidation: replace load_config() with clean, consolidated version that properly sets both REAL_DATA_MODE and FRED_API_AVAILABLE

Fix FRED_API_AVAILABLE wiring: set to True when valid key is detected and restore production streamlit_app.py

Add diagnostic wrapper to verify Streamlit secrets availability

Implement Streamlit-native solution: remove dotenv dependency and use st.secrets directly

Fix execution order: set FRED_API_KEY environment variable BEFORE importing streamlit and frontend app

Wire up FRED_API_AVAILABLE to flip to True when valid key is detected in load_config()

Add comprehensive debug logging to track FRED API key loading and propagation

Fix FRED API key propagation - make key loading dynamic instead of static at module import time

Add error handling and debug logging for AWS client initialization to prevent UnboundLocalError

Fix s3_client initialization in main() function - move AWS client initialization outside conditional block

Remove pre-flight FRED API key check - rely on REAL_DATA_MODE after load_config()

Fix st.secrets assignment error - remove read-only assignment and only set os.environ

Fix FRED API key propagation - ensure key is available in both os.environ and st.secrets for the real app

Add diagnostic version of streamlit_app.py to isolate FRED API key issues in Streamlit Cloud

Remove FRED API key debug message from UI and fix Streamlit Cloud deployment

Rewrite streamlit_app.py as a clean, robust Streamlit Cloud entry point

Merge remote-tracking branch 'parallel/main' and resolve all conflicts

Add FRED API key validation at app startup and improve environment variable loading

Added Dev Container Folder

Update README.md

Fix streamlit_app.py to properly use imported main() function instead of always overriding with fallback

Resolve README.md merge conflict for ParallelLLC Hugging Face remote, keep all clone URLs

Resolve README.md merge conflict and list all remote clone URLs as per user instructions

Fix Streamlit Cloud deployment import issue - Added robust import handling with fallbacks - Added current directory to Python path - Added error handling for import failures - Improved debugging output for deployment troubleshooting

Merge remote changes and resolve conflicts - Fixed frequency error (ME -> M) - Updated analytics availability checks - Resolved merge conflicts keeping local improvements

Fix frequency error and analytics availability issues - Fixed Invalid frequency: ME error by changing freq='ME' to freq='M' - Updated analytics availability check to verify modules directly - Improved error handling for real FRED data processing - Enhanced configuration page to show accurate analytics status

Restore secrets.toml with only FRED API key after history cleanup

Remove all demo data and update project to use only real FRED API data

Optimize Streamlit app performance with lazy imports and loading indicators

Merge feature/advanced-analytics-20250711 into main - Complete FRED ML platform with Streamlit Cloud deployment

Fix Streamlit Cloud deployment issues and deprecated pandas warnings

Merge remote main branch

Merge pull request #3 from EAName/feature/advanced-analytics-20250711

Prepare for Streamlit Cloud deployment - Add deployment files, fix clustering chart error, update requirements

feat: Integrate advanced analytics and enterprise UI

Update README.md

Update README.md

merge: Resolve merge conflict with hf-parallel, keep updated README

merge: Resolve merge conflict, keep updated README

docs: Add comprehensive deployment summary

Update README.md

Update README.md

docs: Add CI/CD pipeline status tracking

feat: Complete project cleanup and professional structure

Update README.md

Update README.md

Enterprise: Clean up directory structure and add proper CI/CD, monitoring, and deployment configurations

Enterprise: Transform to production-grade architecture with FastAPI, Docker, K8s, monitoring, and comprehensive tooling

Restore CSV and PNG files with Git LFS tracking