feat(v0.2.0): Self-Improvement & Structural Integrity
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- Fix critical paren balance issues across harness/skills.org, act.org,
  loop.org, memory.org, and skills/self-edit|emacs-edit.org
- Add :reload-skill cognitive tool for hot-reloading without restart
- Add :generate-embeddings tool and self-edit hot-reload infrastructure
- Wire all new skills (self-edit, emacs-edit, lisp-utils) into main ASDF
- Regenerate all .lisp tangled files via emacs --batch org-babel-tangle
- Add :opencortex/tests ASDF system with 14 test suites
- Fix test files to compile cleanly (self-edit-tests symbol vis, etc.)
This commit is contained in:
2026-04-27 07:30:01 -04:00
parent 1e202629ce
commit 43dbe3cf2d
29 changed files with 1980 additions and 590 deletions

View File

@@ -8,6 +8,10 @@
(defstruct org-object
id type attributes content vector parent-id children version last-sync hash)
;; Enable serialization via make-load-form (standard CL)
(defmethod make-load-form ((obj org-object) &optional env)
(make-load-form-saving-slots obj :environment env))
(defun compute-merkle-hash (id type attributes content child-hashes)
"Computes a SHA-256 Merkle hash for a node based on its core properties and children's hashes."
(let* ((alist (loop for (k v) on attributes by #'cddr collect (cons k v)))
@@ -79,53 +83,61 @@
(harness-log "MEMORY - Memory rolled back to snapshot ~a" index))
(harness-log "MEMORY ERROR - Snapshot ~a not found." index))))
(defvar *memory-snapshot-path* nil
"Path to the memory snapshot file. Set from MEMORY_SNAPSHOT_PATH env or default.")
(defvar *embedding-cache* (make-hash-table :test 'equal)
"Cache for embeddings to avoid redundant API calls.")
(defun ensure-memory-snapshot-path ()
"Initializes the snapshot path from environment or default location."
(or *memory-snapshot-path*
(let ((env-path (uiop:getenv "MEMORY_SNAPSHOT_PATH")))
(setf *memory-snapshot-path*
(or env-path
(uiop:merge-pathnames* "memory.snap" (user-homedir-pathname)))))))
(defun get-embedding (text)
"Generates a vector embedding for the given text via Ollama. Returns nil on failure."
(when (or (null text) (string= text ""))
(return-from get-embedding nil))
(let ((cached (gethash text *embedding-cache*)))
(when cached (return-from get-embedding cached)))
(let ((result (funcall (get-cognitive-tool-body :get-ollama-embedding) (list :text text))))
(when (eq (getf result :status) :success)
(let ((vec (getf result :vector)))
(setf (gethash text *embedding-cache*) vec)
vec))))
(defun save-memory-to-disk ()
"Serializes *memory* and *history-store* to disk for crash recovery.
Converts hash tables to alists for proper serialization."
(let ((path (ensure-memory-snapshot-path)))
(with-open-file (stream path :direction :output :if-exists :supersede :if-does-not-exist :create)
(format stream ";; OpenCortex Memory Snapshot~%")
(format stream ";; Created: ~a~%~%" (format nil "~a" (get-universal-time)))
(let ((memory-alist nil)
(history-alist nil))
(maphash (lambda (k v) (push (cons k v) memory-alist)) *memory*)
(maphash (lambda (k v) (push (cons k v) history-alist)) *history-store*)
(prin1 (list :memory memory-alist :history-store history-alist) stream)))
(harness-log "MEMORY - Saved to ~a" path)
path))
(defun cosine-similarity (vec-a vec-b)
"Computes cosine similarity between two vectors. Both should be sequences of numbers."
(when (or (null vec-a) (null vec-b) (zerop (length vec-a)) (zerop (length vec-b)))
(return-from cosine-similarity 0.0))
(let ((dot-product (loop for a across vec-a
for b across vec-b
sum (* a b)))
(norm-a (sqrt (loop for a across vec-a sum (* a a))))
(norm-b (sqrt (loop for b across vec-b sum (* b b)))))
(if (or (zerop norm-a) (zerop norm-b))
0.0
(/ dot-product (* norm-a norm-b)))))
(defun load-memory-from-disk ()
"Loads *memory* and *history-store* from disk if the snapshot exists.
Reconstitutes alists into hash tables."
(let ((path (ensure-memory-snapshot-path)))
(when (uiop:file-exists-p path)
(handler-case
(with-open-file (stream path :direction :input)
(let ((data (read stream nil)))
(when data
(let ((memory-alist (getf data :memory))
(history-alist (getf data :history-store)))
(setf *memory* (make-hash-table :test 'equal :size (length memory-alist)))
(dolist (kv memory-alist)
(setf (gethash (car kv) *memory*) (cdr kv)))
(setf *history-store* (make-hash-table :test 'equal :size (length history-alist)))
(dolist (kv history-alist)
(setf (gethash (car kv) *history-store*) (cdr kv)))
(harness-log "MEMORY - Loaded from ~a (~a objects)" path (hash-table-size *memory*))))))
(error (c)
(harness-log "MEMORY WARNING - Failed to load snapshot: ~a" c))))
t))
(defun semantic-search (query &key (limit 10) (min-similarity 0.5))
"Searches memory for objects semantically similar to the query.
Returns up to LIMIT objects with similarity >= MIN-SIMILARITY, sorted by similarity descending."
(let* ((query-vec (get-embedding query))
(results nil))
(unless query-vec
(harness-log "EMBEDDING: Failed to generate embedding for query: ~a" query)
(return-from semantic-search nil))
(maphash (lambda (id obj)
(let ((obj-vec (org-object-vector obj)))
(when obj-vec
(let ((sim (cosine-similarity query-vec obj-vec)))
(when (>= sim min-similarity)
(push (list :id id :object obj :similarity sim) results))))))
*memory*)
(setf results (sort results #'> :key (lambda (r) (getf r :similarity))))
(subseq results 0 (min limit (length results)))))
(def-cognitive-tool :semantic-search
"Searches memory for objects semantically similar to a query."
((:query :type :string :description "The search query.")
(:limit :type :integer :description "Maximum results to return." :default 10)
(:min-similarity :type :number :description "Minimum similarity threshold (0-1)." :default 0.5))
:body (lambda (args)
(semantic-search (getf args :query)
:limit (or (getf args :limit) 10)
:min-similarity (or (getf args :min-similarity) 0.5))))
(defun org-id-new ()
"Generates a new UUID string for Org-mode identification."
@@ -161,58 +173,3 @@ Reconstitutes alists into hash tables."
(defun file-name-nondirectory (path)
"Extracts the filename from a full path string."
(let ((pos (position #\/ path :from-end t))) (if pos (subseq path (1+ pos)) path)))
(defvar *embedding-cache* (make-hash-table :test 'equal)
"Cache for embeddings to avoid redundant API calls.")
(defun get-embedding (text)
"Generates a vector embedding for the given text via Ollama. Returns nil on failure."
(when (or (null text) (string= text ""))
(return-from get-embedding nil))
(let ((cached (gethash text *embedding-cache*)))
(when cached (return-from get-embedding cached)))
(let ((result (funcall (get-cognitive-tool-body :get-ollama-embedding) (list :text text))))
(when (eq (getf result :status) :success)
(let ((vec (getf result :vector)))
(setf (gethash text *embedding-cache*) vec)
vec))))
(defun cosine-similarity (vec-a vec-b)
"Computes cosine similarity between two vectors. Both should be sequences of numbers."
(when (or (null vec-a) (null vec-b) (zerop (length vec-a)) (zerop (length vec-b)))
(return-from cosine-similarity 0.0))
(let ((dot-product (loop for a across vec-a
for b across vec-b
sum (* a b)))
(norm-a (sqrt (loop for a across vec-a sum (* a a))))
(norm-b (sqrt (loop for b across vec-b sum (* b b)))))
(if (or (zerop norm-a) (zerop norm-b))
0.0
(/ dot-product (* norm-a norm-b)))))
(defun semantic-search (query &key (limit 10) (min-similarity 0.5))
"Searches memory for objects semantically similar to the query."
(let* ((query-vec (get-embedding query))
(results nil))
(unless query-vec
(harness-log "EMBEDDING: Failed to generate embedding for query: ~a" query)
(return-from semantic-search nil))
(maphash (lambda (id obj)
(let ((obj-vec (org-object-vector obj)))
(when obj-vec
(let ((sim (cosine-similarity query-vec obj-vec)))
(when (>= sim min-similarity)
(push (list :id id :object obj :similarity sim) results))))))
*memory*)
(setf results (sort results #'> :key (lambda (r) (getf r :similarity))))
(subseq results 0 (min limit (length results)))))
(def-cognitive-tool :semantic-search
"Searches memory for objects semantically similar to a query."
((:query :type :string :description "The search query.")
(:limit :type :integer :description "Maximum results to return." :default 10)
(:min-similarity :type :number :description "Minimum similarity threshold (0-1)." :default 0.5))
:body (lambda (args)
(semantic-search (getf args :query)
:limit (or (getf args :limit) 10)
:min-similarity (or (getf args :min-similarity) 0.5))))