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import numpy as np |
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from numba import njit |
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import math |
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import random |
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import pickle |
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import gradio as gr |
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def text_to_arr(text: str): |
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return np.array([ord(x) for x in text.lower()]) |
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@njit |
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def longest_common_substring(s1, s2): |
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current_match_start = -1 |
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current_match_end = -1 |
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best_match_start = current_match_start |
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best_match_end = current_match_end |
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min_len = min(len(s1), len(s2)) |
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for i in range(min_len): |
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if s1[i] == s2[i]: |
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current_match_start = current_match_end = i |
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j = 0 |
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while s1[i+j] == s2[i+j] and i+j < min_len: |
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j += 1 |
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current_match_end = current_match_start + j |
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if current_match_end - current_match_start > best_match_end - best_match_start: |
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best_match_start = current_match_start |
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best_match_end = current_match_end |
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return s1[best_match_start:best_match_end] |
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def not_found_in(q, data): |
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for l in data: |
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count = 0 |
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lq = len(q)-1 |
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for v in l: |
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if v == q[count]: |
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count += 1 |
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else: |
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count = 0 |
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if count == lq: |
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return False |
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return True |
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class Layer: |
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def __init__(self, mem_len: int = 100, max_size: int = 6): |
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self.mem_len = mem_len |
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self.common_strings = [] |
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self.previously_seen = [] |
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self.max_size = max_size+1 |
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def __call__(self, input_arr, training: bool = True): |
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o = [] |
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li = len(input_arr) |
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for i in range(li): |
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for y, common_substring in enumerate(self.common_strings): |
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if (i+common_substring.shape[0]) <= li and (input_arr[i:i+common_substring.shape[0]] == common_substring).all(): |
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o.append(y) |
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if training: |
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current_max_len = 0 |
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n = None |
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for i, line in enumerate(self.previously_seen): |
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t = longest_common_substring(input_arr, line) |
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l = len(t) |
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if l > current_max_len and l < self.max_size: |
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current_max_len = l |
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n = i |
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result = t |
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if self.previously_seen != []: |
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if n is not None and len(result) > 1: |
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self.previously_seen.pop(n) |
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if not_found_in(result, self.common_strings): |
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self.common_strings.append(result) |
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self.previously_seen = self.previously_seen[-self.mem_len:] |
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self.previously_seen.append(input_arr) |
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return o |
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with open("l1_large.pckl", "rb") as f: layer = pickle.load(f) |
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with open("l2_large.pckl", "rb") as f: layer2 = pickle.load(f) |
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with open("w1_large.pckl", "rb") as f: w = pickle.load(f) |
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with open("w2_large.pckl", "rb") as f: w2 = pickle.load(f) |
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def generate(msg): |
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if len(msg) < 4: |
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return threeletterai.getresp(msg) |
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processed = layer(text_to_arr(msg), training=False) |
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processed = np.array(processed) |
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processed2 = layer2(processed, training=False) |
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o = np.zeros(len(lines), dtype=np.int16) |
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for a in processed: |
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if a in w: |
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o[w[a]] += 1 |
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for a in processed2: |
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if a in w2: |
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o[w2[a]] += 1 |
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return lines[np.argmax(o)] |
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app = gr.Interface(fn=generate, inputs="text", outputs="text") |
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app.launch() |
