ELP: two-layer activation pipeline (activate → suppress → reason → generate)
elp-input.el: replace broken engram_search_json with engram_activate_json as Layer 1. Layer 2 suppress/filter keeps nodes with non-zero salience/ importance. Reason step extracts patient from top activated node content. ELP grammar realizes the response via generate(). routes.el: add 'elp' event_type to handle_dharma_recv so the studio can route ELP requests through dharma.
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// auto-generated by elc --emit-header - do not edit
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extern fn auth_headers(tok: String) -> Map
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extern fn axon_get(path: String) -> String
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extern fn axon_post(path: String, body: String) -> String
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extern fn handle_conversations(method: String) -> String
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extern fn handle_config(method: String, body: String) -> String
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extern fn dharma_registry() -> String
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extern fn dharma_network_state() -> String
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extern fn handle_dharma(path: String, method: String, body: String) -> String
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extern fn handle_tool(path: String, method: String, body: String) -> String
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extern fn handle_nlg(path: String, method: String, body: String) -> String
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extern fn render_studio() -> String
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