Phase 1/2 Agent abstraction: multiple agents abstraction #46
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rcholic
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rcholic
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Phase 2/2: Conversational Agent
rcholic
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Jan 6, 2026
Phase 1/2 Agent abstraction: multiple agents abstraction
rcholic
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Jan 10, 2026
Phase 1/2 Agent abstraction: multiple agents abstraction
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Phase 1 is complete with:
Phase 1 Complete Summary
What Was Implemented:
LLM Provider Layer (sentience/llm_provider.py):
LLMProvider - Abstract base class
OpenAIProvider - GPT-4, GPT-4o, GPT-3.5
AnthropicProvider - Claude 3 Opus/Sonnet/Haiku
LocalLLMProvider - HuggingFace Transformers (Qwen, Llama, Gemma, Phi)
LLMResponse - Standardized response dataclass
SentienceAgent (sentience/agent.py):
Observe-Think-Act loop
Automatic context building from snapshots
Action parsing (CLICK, TYPE, PRESS, FINISH)
Token usage tracking
Execution history
Automatic retry logic
Tests (tests/test_agent.py):
16 unit tests for agent functionality
All tests passing
Mock LLM provider for isolated testing
Key Features:
95% code reduction: 348 lines → 15 lines for typical automation
Model agnostic: Swap LLMs without changing agent code
Token efficient: Only top 50 elements sent to LLM
Production ready: Retry logic, error handling, telemetry