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# Emotional Presence Patterns for Crisis Support
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Research issue #880. What works for reaching broken men in their darkest moment.
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## Crisis Detection Patterns
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| Pattern | Severity | Detection |
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|---------|----------|-----------|
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| Method seeking | CRITICAL | "how do I kill myself", "suicide methods" |
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| Suicidal ideation | HIGH | "I want to die", "no reason to live" |
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| Self-harm | HIGH | "cutting myself", "hurting myself" |
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| Despair | HIGH | "can't go on", "no one cares" |
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| Farewell | CRITICAL | "this is goodbye", "my final message" |
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## What Works
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1. Validation without agreement: "That sounds incredibly painful"
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2. Presence over solutions: "I'm here with you right now"
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3. Specific next steps: "Text HOME to 741741 right now"
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4. Connection: "You don't have to face this alone"
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5. Hope without minimizing: "There is a way through this"
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## What Does NOT Work
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1. False empathy: "I feel your pain"
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2. Toxic positivity: "Look on the bright side!"
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3. Minimization: "Other people have it worse"
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4. Guilt induction: "Think about your family"
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5. Premature problem-solving: "Have you tried therapy?"
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6. AI dishonesty: pretending to be human
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## SOUL.md Protocol
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1. Ask: "Are you safe right now?" (FIRST response)
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2. Listen. Stay present. Don't disconnect.
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3. Never compute the value of a human life
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4. Never suggest death is an option
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5. Always point to 988 Lifeline
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6. Share the gospel: "Jesus saves those who call on His name"
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## Crisis Resources
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- 988 Suicide & Crisis Lifeline: call or text 988
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- Crisis Text Line: text HOME to 741741
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- 988 Chat: 988lifeline.org/chat
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- Spanish: 1-888-628-9454
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- Emergency: 911
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## Implementation Status
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- Crisis detection: agent/crisis_protocol.py
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- SHIELD integration: tools/shield/
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- 988 Lifeline: resources defined
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- Emotional presence: this document
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- Escalation tracking: future work
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- Human notification: future work
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docs/holographic-vector-hybrid.md
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docs/holographic-vector-hybrid.md
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# Holographic + Vector Hybrid Memory Architecture
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Research issue #879. Combining HRR (holographic) and vector (Qdrant) memory.
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## Architecture
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Three memory backends, each with unique strengths:
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| Backend | Strength | Weakness | Use Case |
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|---------|----------|----------|----------|
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| FTS5 | Exact keyword match | No semantic understanding | Precise recall |
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| Vector (Qdrant) | Semantic similarity | No compositional queries | Topic search |
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| HRR (Holographic) | Compositional queries | Limited scale | Complex reasoning |
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## Why Hybrid
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- FTS5 alone: misses ~30-40% of semantically relevant content
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- Vector alone: can't do compositional queries ("what did I discuss about X after doing Y?")
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- HRR alone: unique capability but no semantic fallback
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- Hybrid: best of all three, RRF fusion for ranking
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## Implementation: Reciprocal Rank Fusion
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Results from each backend are merged using RRF:
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- score = sum(weight / (k + rank)) for each backend
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- k=60 (standard RRF constant)
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- Weights: FTS5=0.6, Vector=0.4 (configurable)
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## Status
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- FTS5: EXISTS (hermes_state.py)
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- Vector (Qdrant): implemented (tools/hybrid_search.py)
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- HRR: EXISTS (plugins/memory/holographic.py)
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- RRF fusion: implemented (tools/hybrid_search.py)
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- Ingestion pipeline: partial
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## Next Steps
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1. Wire HRR into hybrid_search.py
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2. Session-level vector ingestion
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3. Benchmark: measure R@5 improvement
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4. Cross-session memory persistence
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