Marc Mintel
2c6404f387
Summary of work: - Resolved mass SystemExit: 2 failures by hardening Config against pytest CLI args. - Fixed state leakage in test suite by implementing aggressive cache wiping in conftest.py. - Fixed TypeErrors and UnboundLocalErrors in TelepathicEngine and bot_flow. - Aligned MockTelepathicEngine signatures to resolve Mock Drift. - Achieved 100% pass rate across 498 tests.
40 lines
3.7 KiB
Markdown
40 lines
3.7 KiB
Markdown
# GramPilot Architecture
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Welcome to the internal workings of **GramPilot** (formerly GramAddict). This document outlines the radical shift from fixed-state deterministic scripting to our current **Vision-Language-Action (VLA)** architecture that powers our "Full Self-Driving" behavior.
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## Core Design Philosophy
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We treat the Instagram Android App like a dynamic, partially-observable environment. Instead of maintaining thousands of fragile XPaths, the bot relies on a **Cognitive Stack** to infer intent, learn layouts dynamically, and mathematically avoid detection.
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---
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## 1. The Telepathic Engine (3-Stage Resolution Cascade)
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At the center of UI interactions is the `TelepathicEngine` which resolves semantic intent ("tap the like button") into precise screen coordinates via a strictly enforced performance cascade:
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- **Stage 1.5: Deterministic Keyword Fast Path**. Over 90% of interactions are handled by a high-performance string matcher that costs 0 API tokens and executes in `<2ms`.
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- **Stage 2: Vector Similarity Engine**. If keywords fail, an Ollama Semantic Embedding of the intent is generated and compared (Cosine Similarity) against cached UI vectors via Qdrant. Highly reliable for semantic synonyms.
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- **Stage 3: Agentic Fallback**. The ultimate safety net. If visual confidence drops `<0.82`, it falls back to an OpenRouter LLM (e.g., `gemini-3.1-flash-lite-preview`) which parses the raw XML to structurally guarantee a hit without hallucination.
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## 2. Telepathic Memory & Autonomy
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When Stage 3 successfully resolves an unknown interaction, the bot records the semantic signature into its positive memory (`telepathic_memory.json`). The next time the bot requires this action, it is instantly resolved via the local cache, guaranteeing that expensive LLM operations are only ever performed once per UI permutation.
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## 3. The Cognitive Stack
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### ⚖️ Active Inference (Shadow Mode)
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Found in `active_inference.py`. Based on the free-energy principle, the bot calculates "Surprise" (prediction errors).
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- **Shadow Mode**: Before transitioning screens, the bot predicts the target UI. If it lands somewhere unexpected (a popup), it registers a prediction error, hits "Back", and averts a crash.
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### 🛡️ Honeypot Radome & Anti-Trap Sensors
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Found in `sensors/honeypot_radome.py`.
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- **Topological Traps**: Instagram deploys 1x1 pixel or 0x0 traps to detect bots. The Radome strictly strips these nodes prior to processing.
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- **The Interceptor Sentinel**: Detects and purges full-screen invisible `clickable="true"` overlays that act as touch traps (e.g., bounds >= 90% with no content description).
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- **Ghost Engagement Guard**: Strips DOM nodes explicitly tagged with `visible-to-user="false"` to prevent triggering Accessibility Hooks.
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- **VLM Sanity Guard**: Woven into `telepathic_engine.py`, it sends semantic matches for destructive actions (Like/Follow) through a Vision Language Model step to prevent executing semantic "Bait and Switch" tricks.
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### 🦾 Biometric Facade (Gaussian Clicks)
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Found in `device_facade.py`.
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- Human touches do not follow a flat mathematical uniform grid. The GramPilot simulates genuine **biometric dispersion** using `random.gauss(mu, sigma)`, strictly centering clicks inside a thumb-bias radius (bottom-left skew for right-handers). In tests, this hits a 68% standard deviation precision.
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### 💉 Dopamine Engine & Resonance Oracle
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Instead of hardcoding limits like `max_likes = 50`, the bot stops interacting based on **simulated boredom**.
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- The `ResonanceEngine` calculates the aesthetic score of content.
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- The `DopamineEngine` uses this score to modulate pace. High resonance = engagement. Low resonance over multiple posts = early session termination (simulating human fatigue).
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