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What exact combination of Gemini models, config settings, and initialize.py functions are required to run the UI successfully in the current Docker build? Has anyone actually done it from a clean install?
Here is what I've tried (AI summarized)
User Context:
Experienced dev with Docker and AI tools
Attempted to run Agent Zero on Windows 11 via Docker with only Gemini APIs as I don't have Perplexity, Claude...
Goal: Run a local agent that uses Gemini via embedded key.
✅ What Worked:
Docker container built and ran
Embedded Gemini API key setup successfully (agent_zero_config.py)
System logs indicated several services launching (Whisper, MCP middleware, etc.)
Tunnel server and some subservices started
Logs confirmed MCP/Gemini middleware registration
❌ What Didn’t Work (Major Issues):
Container Reboots Due to Missing Attributes
run_ui.py references non-existent functions like:
initialize.initialize_chats()
initialize.initialize_mcp()
initialize.initialize_job_loop()
These cause hard crashes and a boot loop (exit status 1) in Supervisor.
Broken Module Calls
Repeated failures on models.get_huggingface_embedding suggest either:
The models.py structure has changed, or
Preload script expects outdated huggingface API logic
Poor Graceful Failure Handling
Any missing attribute in Python causes container-wide failure. There’s no fallback or recovery mechanism.
Attempts to access web GUI shows JSON parse errors or network backend unavailable.
Developer-Unfriendly Debugging
Docker container doesn’t include even basic tools (vi, nano, or paste support in terminal)
Manual editing becomes nightmarish without escape hatches
Patch cycle was slow due to restarting entire containers to remove broken lines
🛠 Suggestions for Developer:
Robust Function Checks
Use hasattr() or try/except in initialize.py to check for optional functions (e.g. initialize_job_loop) before calling them
This would prevent crashes from minor config mismatches
Graceful UI Startup
If run_ui fails, don’t crash the entire stack — log the error and continue showing basic UI
Default Model Safety
If get_huggingface_embedding fails, use a fallback or clearly document setup instructions for that dependency
Better Developer Console Support
Add paste-capable terminal, or mount /a0 to allow editing from host
Include nano or vi in container image by default
Configuration Validation Tool
Before boot, run a CLI command like python validate_config.py to check that all references (e.g., API keys, model functions) are defined
Documentation Improvements
Include:
Troubleshooting flowchart
List of optional vs required services
Example .env or agent_zero_config.py setup
Expected port/URL mappings
Final Thoughts:
Agent Zero shows a ton of promise, with just a little more polish, this could be a STELLAR local LLM agent platform.
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What exact combination of Gemini models, config settings, and initialize.py functions are required to run the UI successfully in the current Docker build? Has anyone actually done it from a clean install?
Here is what I've tried (AI summarized)
User Context:
Experienced dev with Docker and AI tools
Attempted to run Agent Zero on Windows 11 via Docker with only Gemini APIs as I don't have Perplexity, Claude...
Goal: Run a local agent that uses Gemini via embedded key.
✅ What Worked:
Docker container built and ran
Embedded Gemini API key setup successfully (agent_zero_config.py)
System logs indicated several services launching (Whisper, MCP middleware, etc.)
Tunnel server and some subservices started
Logs confirmed MCP/Gemini middleware registration
❌ What Didn’t Work (Major Issues):
Container Reboots Due to Missing Attributes
run_ui.py references non-existent functions like:
initialize.initialize_chats()
initialize.initialize_mcp()
initialize.initialize_job_loop()
These cause hard crashes and a boot loop (exit status 1) in Supervisor.
Broken Module Calls
Repeated failures on models.get_huggingface_embedding suggest either:
The models.py structure has changed, or
Preload script expects outdated huggingface API logic
Poor Graceful Failure Handling
Any missing attribute in Python causes container-wide failure. There’s no fallback or recovery mechanism.
Attempts to access web GUI shows JSON parse errors or network backend unavailable.
Developer-Unfriendly Debugging
Docker container doesn’t include even basic tools (vi, nano, or paste support in terminal)
Manual editing becomes nightmarish without escape hatches
Patch cycle was slow due to restarting entire containers to remove broken lines
🛠 Suggestions for Developer:
Robust Function Checks
Use hasattr() or try/except in initialize.py to check for optional functions (e.g. initialize_job_loop) before calling them
This would prevent crashes from minor config mismatches
Graceful UI Startup
If run_ui fails, don’t crash the entire stack — log the error and continue showing basic UI
Default Model Safety
If get_huggingface_embedding fails, use a fallback or clearly document setup instructions for that dependency
Better Developer Console Support
Add paste-capable terminal, or mount /a0 to allow editing from host
Include nano or vi in container image by default
Configuration Validation Tool
Before boot, run a CLI command like python validate_config.py to check that all references (e.g., API keys, model functions) are defined
Documentation Improvements
Include:
Troubleshooting flowchart
List of optional vs required services
Example .env or agent_zero_config.py setup
Expected port/URL mappings
Final Thoughts:
Agent Zero shows a ton of promise, with just a little more polish, this could be a STELLAR local LLM agent platform.
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