* fix: apply context compression to prevent token overflow (Issue #721)
- Add token_limit configuration to conf.yaml.example for BASIC_MODEL and REASONING_MODEL
- Implement context compression in _execute_agent_step() before agent invocation
- Preserve first 3 messages (system prompt + context) during compression
- Enhance ContextManager logging with better token count reporting
- Prevent 400 Input tokens exceeded errors by automatically compressing message history
* feat: add model-based token limit inference for Issue #721
- Add smart default token limits based on common LLM models
- Support model name inference when token_limit not explicitly configured
- Models include: OpenAI (GPT-4o, GPT-4, etc.), Claude, Gemini, Doubao, DeepSeek, etc.
- Conservative defaults prevent token overflow even without explicit configuration
- Priority: explicit config > model inference > safe default (100,000 tokens)
- Ensures Issue #721 protection for all users, not just those with token_limit set
* feat:Add context compress
* feat: Add unit test
* feat: add unit test for context manager
* feat: add postprocessor param && code format
* feat: add configuration guide
* fix: fix the configuration_guide
* fix: fix the unit test
* fix: fix the default value
* feat: add test and log for context_manager
* feat: add Google AI Studio API support with platform-based detection
* chore: update configuration_guide.md
* fix the uv.lock formate error
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Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix: update README and configuration guide for new model support and reasoning capabilities
* fix: format code for consistency in agent and node files
* fix: update test cases for environment variable handling in llm configuration
* fix: refactor message chunk conversion functions for improved clarity and maintainability
* refactor: remove enable_thinking parameter from LLM configuration functions
* chore: update agent-LLM mapping for consistency
* chore: update LLM configuration handling for improved clarity
* test: add unit tests for Dashscope message chunk conversion and LLM configuration
* test: add unit tests for message chunk conversion in Dashscope
* test: add unit tests for message chunk conversion in Dashscope
* chore: remove unused imports from test_dashscope.py
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Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat(llm): Add retry mechanism for LLM API calls
* feat: configure max_retries for LLM calls via conf.yaml
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Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* Add support for self-signed certs from model providers
* cleanup
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Co-authored-by: tonydoesathing <tmastromarino@cpacket.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* test: add background node unit test
Change-Id: Ia99f5a1687464387dcb01bbee04deaa371c6e490
* test: add background node unit test
Change-Id: I9aabcf02ff04fda40c56f3ea22abe6b8f93bf9b6
* test: fix test error
Change-Id: I3997dc53a2cfaa35501a1fbda5902ee15528124e
* test: fix unit test error
Change-Id: If4c4cd10673e76a30945674c7cda198aeabf28d0
* test: fix unit test error
Change-Id: I3dd7a6179132e5497a30ada443d88de0c47af3d4
