Genesis-SPT-1.0-NV25

A lightweight JSON conversational AI model. Works offline. No GPU required.

Overview

Genesis-SPT-1.0 maps user inputs to handcrafted responses. It does not use neural networks or inference engines. Just load the JSON and start chatting.

• Model: Genesis-SPT-1.0-NV25 (Legacy modal)
• Format: JSON (key to response)
• Size: ~55 KB (249 entries)
• Language: English
• License: MIT

Features

• Instant responses. No computation. Just a lookup.
• Fuzzy matching. Handles typos, contractions, and paraphrases.
• Reasoning simulation. Each response has an internal monologue using <|think|> tags. Clients can show this as chain-of-thought.
• Fully offline. No internet or API calls needed.
• Zero dependencies. Just a JSON parser and string matching.

Categories

The model covers 249 conversation patterns across 15+ categories.

Category	Count	Examples
Greetings	18	hello, hi, hey, good morning, howdy
Slang & Reactions	26	lol, haha, omg, based, no cap, fr fr
Acknowledgements	18	ok, cool, nice, wow, got it, makes sense
Farewells	14	bye, goodbye, see you, later, peace out
Capabilities	10	can you help me, can you code, can you chat
Negative Emotions	10	i'm sad, i'm stressed, i'm scared, i'm lonely
Positive Emotions	8	i'm happy, i'm excited, i'm great
Fun & Entertainment	8	tell me a joke, fun fact, tell me a riddle
Creator Info	9	who made you, what is xpdevs, what is doorsos
Nature Questions	9	are you sentient, can you think, are you real
Philosophy	7	meaning of life, what is love, consciousness
Affirmations	7	you're awesome, i love you, you rock
Identity	6	who are you, introduce yourself
Thanks	6	thanks, thank you, appreciate it
Check-ins	5	how are you, how's it going
Other	88	advice, can you explain, tell me about doorsos, etc.

Reasoning Tags

Every response includes a <|think|> tag with simulated reasoning.

{
  "hello": "<|think|>User is greeting me. Simple opener, probably just starting a conversation. I should respond warmly and invite them to share what they need.</|think|>Hey there! Genesis here, ready to help! What's on your mind?"
}

Clients can parse these tags. The thinking content can be shown before the clean response.

Usage (Python)

import json, re

with open("Genesis-SPT-1.0-original.json") as f:
    model = json.load(f)

def respond(input_text, model):
    input_lower = input_text.lower().strip()
    if input_lower in model:
        raw = model[input_lower]
        clean = re.sub(r"<\|think\|>.*?</\|think\|>", "", raw).strip()
        return clean
    best_key = None
    best_score = 0
    for key in model:
        if key in ("ver", "ModeInfo"):
            continue
        if key.lower() in input_lower:
            score = len(key) / len(input_lower)
            if score > best_score:
                best_score = score
                best_key = key
    if best_key:
        raw = model[best_key]
        clean = re.sub(r"<\|think\|>.*?</\|think\|>", "", raw).strip()
        return clean
    return "No match found."

print(respond("hello", model))

File Structure

Genesis-SPT-1.0-original.json   # Model data
README.md                       # This file

The JSON is a flat object.

{
  "ver": "Genesis-SPT-1.0-NV25 - Legacy modal",
  "hello": "<|think|>...</|think|>Hey there...",
  "bye": "<|think|>...</|think|>Take care...",
  ...
}

Limitations

• No generative capabilities. Responses are handcrafted. The model cannot answer questions outside its dataset.
• No memory. Each response is stateless. Conversation history is not considered.
• English only. Designed for English conversation patterns.
• Small scope. 249 entries cover common chat patterns but not deep knowledge.

License

MIT. Free to use, modify, and distribute.

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