- solve_task.py: add fetch_todo_tasks(), _parse_todo_tasks(), run_all()
- run_all() auto-fetches all todo tasks from BroJS and solves each one
- run_pipeline.py: rewrite to just call run_all() from solve_task
- supports: python run_pipeline.py (auto), run_pipeline.py <id...> (targeted)
- TARGET_IDS list for hardcoded targets without CLI args
- no deepagents imports = no double MCP load on startup
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Switch transport to streamable_http (matches solve_task.py)
- Add _persistent_client global to reuse MultiServerMCPClient across calls
- Add exponential backoff 15→30→60→120→240s on 429 responses
- Add _INTER_CALL_DELAY=1.5s between consecutive MCP calls to prevent burst
- Add _is_429() helper for clean 429 detection
- Recreate client on non-429 errors to recover from stale sessions
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Added _force_submit() and _is_submitted() helpers. After the agent
finishes writing code, the pipeline checks if the task was actually
submitted. If not (LLM failed to call tools), the pipeline submits
directly via MCP — no LLM involved in the critical submit step.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Token usage is now tracked on platform.brojs.ru.
Uses the same JOURNAL_TOKEN (jrnl_...) for both MCP and inference.
Removed OPENAI_API_KEY from .env.example.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Changed homework_doing_instructions delimiter from """ to ''' to avoid
SyntaxError caused by docstrings inside code examples within the string.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
prompts.py:
- Added detailed technical patterns for deepagents, FastMCP, LangGraph,
HumanInTheLoop, RAG with Qdrant, stream mode, text game
- LLM always via OpenRouter (never hub.pull/Ollama/hardcode)
- FastMCP correct pattern (module-level, NOT inside class)
- create_agent not compatible with AgentExecutor - documented
- DuckDuckGo search pattern (no API key needed)
pipeline.py:
- Added _invoke_with_retry: auto-retry on 429 rate limit (up to 5x, 90s backoff)
- Added TASK_PAUSE (15s) between tasks to reduce rate limit pressure
- Progress logging: per-task status messages
- Imported asyncio and re
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
AgentMiddleware is a plain Generic class, not a Pydantic BaseModel,
so class-level field declarations don't work. Explicit __init__ required.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Glevel