File size: 2,484 Bytes
ed6bec6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87


# Glyphic Language — Integration Guide
This guide explains how to integrate the Glyphic Language interpreter into agents, controllers, LLM pipelines, and Soulfile™‑based systems.

1. Loading the Interpreter
The interpreter loads the dictionary automatically on first use.
python:
from glyphic_language.interpreter import interpret, encode, validate, explain
No manual initialization is required.

2. Integrating with Agents
Agents should use the interpreter for:
    parsing glyph messages
    generating glyph responses
    validating incoming sequences
    constructing scenes
    storing meaning in Soulfiles™
Example:
python
scene = interpret("👤🔥🌳🌙")
agent.react(scene)

3. Integrating with Controllers
Controllers should:
    validate all glyph input
    enforce canonical encoding
    prevent hallucinated glyphs
    route meaning to behavior modules
Example:
python
validate(glyph_input)
meaning = interpret(glyph_input)
controller.execute(meaning)

4. Integrating with LLMs
LLMs should never generate glyphs directly without:
    syntax validation
    dictionary lookup
    canonical encoding
Recommended pipeline:
LLM → draft meaning → encode() → glyph output
This prevents:
    invalid glyphs
    syntax drift
    ambiguous sequences

5. Integrating with Soulfile™ Systems
Soulfiles™ store:
    structured meaning
    memory snapshots
    agent identity
    symbolic state
    voice files
    avatar models
    all memory/information an LLM has generated on behalf of an agent (pictures, voice, text)
The interpreter ensures that all glyph‑based memory is:
    canonical
    reversible
    stable across versions
Example:
python
meaning = interpret(glyph_string)
soulfile.store_event(meaning)

6. Error Handling
All interpreter errors are explicit:
    GlyphValidationError
    GlyphSyntaxError
    KeyError for missing dictionary entries
Controllers should catch and handle these gracefully.

7. Versioning and Compatibility
The interpreter is designed to be:
    forward‑compatible with new glyphs
    backward‑compatible with existing Soulfiles™
    stable across dictionary expansions
Grammar changes must be versioned explicitly.

8. Recommended Architecture
    Agents call the interpreter directly
    Controllers enforce validation
    LLMs generate structured meaning, not glyphs
    Soulfiles™ store canonical meaning
    Dictionary updates propagate automatically
This ensures a stable, deterministic semantic ecosystem.