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import gradio as gr |
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from gpt4all import GPT4All |
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from urllib.request import urlopen |
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import json |
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import re |
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url = "https://raw.githubusercontent.com/nomic-ai/gpt4all/main/gpt4all-chat/metadata/models3.json" |
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response = urlopen(url) |
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data_json = json.loads(response.read()) |
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def model_choices(): |
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model_list = [data_json[i]['filename'] for i in range(len(data_json))] |
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return model_list |
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model_description = {model['filename']: model['description'] for model in data_json} |
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def remove_endtags(html_string, tags): |
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"""Remove rear HTML tags from the input string.""" |
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for tag in tags: |
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html_string = re.sub(fr"</{tag}>", "", html_string) |
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return html_string |
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def replace_starttags(html_string, replacements): |
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"""Replace starting HTML tags with the corresponding values.""" |
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for tag, replacement in replacements.items(): |
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html_string = html_string.replace(tag, replacement) |
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return html_string |
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def format_html_string(html_string): |
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"""Format the HTML string to a readable text format.""" |
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endtags_to_remove = ["ul", "li", "br", "strong", "a"] |
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html_string = remove_endtags(html_string, endtags_to_remove) |
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starttag_replacements = { |
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"<ul>": "", |
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"<li>": "\n➤ ", |
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"<br>": "\n", |
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"<strong>": "", |
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'<a href="https://opensource.org/license/mit">': "", |
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'<a href="https://llama.meta.com/llama3/license/">': "", |
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'<a href="https://atlas.nomic.ai/">': "", |
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} |
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formatted_string = replace_starttags(html_string, starttag_replacements) |
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return formatted_string |
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def llm_intro(selected_model): |
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html_string = model_description.get(selected_model, "No description available for this model selection.") |
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formatted_description = format_html_string(html_string) |
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return formatted_description |
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model_cache = {} |
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def load_model(model_name): |
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""" |
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This function checks the cache before loading a model. |
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If the model is cached, it returns the cached version. |
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Otherwise, it loads the model, caches it, and then returns it. |
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""" |
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if model_name not in model_cache: |
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model = GPT4All(model_name) |
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model_cache[model_name] = model |
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return model_cache[model_name] |
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