reset theme

app.py

@@ -167,8 +167,8 @@ footer{
 
 """
 css_string2 = ""
-
-with gr.Blocks(theme=theme, css=css_string2) as demo:
+# theme=theme, 
+with gr.Blocks() as demo:
     with gr.Row(elem_id="force_black_bg"):
         with gr.Column(elem_id="force_black_bg"):
             seed = gr.Text( label="AI Safety Skepticism: What's Your Take?", placeholder="Enter an argument or something you'd like to say!")

app_2.py

@@ -0,0 +1,206 @@
+'''
+
+CONFIG AND IMPORTS
+
+'''
+from config import default_config
+
+from types import SimpleNamespace
+import gradio as gr
+import os, random
+from pathlib import Path
+import tiktoken
+from getpass import getpass
+
+import openai
+from langchain.text_splitter import MarkdownHeaderTextSplitter
+import numpy as np
+
+from langchain.embeddings import OpenAIEmbeddings
+# from langchain.vectorstores import Chroma
+from typing import Iterable
+from gradio.themes.base import Base
+from gradio.themes.utils import colors, fonts, sizes
+import time
+
+
+
+
+if os.getenv("OPENAI_API_KEY") is None:
+  if any(['VSCODE' in x for x in os.environ.keys()]):
+    print('Please enter password in the VS Code prompt at the top of your VS Code window!')
+  os.environ["OPENAI_API_KEY"] = getpass("Paste your OpenAI key from: https://platform.openai.com/account/api-keys\n")
+  openai.api_key = os.getenv("OPENAI_API_KEY", "")
+
+assert os.getenv("OPENAI_API_KEY", "").startswith("sk-"), "This doesn't look like a valid OpenAI API key"
+print("OpenAI API key configured")
+
+embeddings_model = OpenAIEmbeddings()
+
+md = ""
+directory_path = "safety_docs"
+
+for filename in os.listdir(directory_path):
+    if filename.endswith(".md"):
+        with open(os.path.join(directory_path, filename), 'r') as file:
+            content = file.read()
+            md = md + content
+
+markdown_document = md
+
+headers_to_split_on = [
+    ("#", "Header 1"),
+    ("##", "Header 2"),
+    ("###", "Header 3"),
+]
+
+markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on)
+md_header_splits = markdown_splitter.split_text(markdown_document)
+
+def find_nearest_neighbor(argument="", max_args_in_output=2):
+    '''
+        INPUT:
+            argument (string)
+
+        RETURN the nearest neighbor(s) in vectorDB to argument as string
+    '''
+
+    embeddings = embeddings_model
+    embedding_matrix = np.array([embeddings.embed_query(text.page_content) for text in md_header_splits])
+    argument_embedding = embeddings.embed_query(argument)
+
+    dot_products = np.dot(embedding_matrix, argument_embedding)
+    norms = np.linalg.norm(embedding_matrix, axis=1) * np.linalg.norm(argument_embedding)
+    cosine_similarities = dot_products / norms
+
+    nearest_indices = np.argsort(cosine_similarities)[-max_args_in_output:][::-1]
+
+    arr = [md_header_splits[index].metadata for index in nearest_indices]
+    output = ""
+    for thing in arr:
+        output = output + thing['Header 1'] + "\n"
+
+    return output
+
+def get_gpt_response(user_prompt, system_prompt=default_config.system_prompt, model=default_config.model_name, n=1, max_tokens=200):
+    '''
+    INPUT: 
+    Argument
+    user_prompt
+    system_prompt
+    model
+    '''
+
+    messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_prompt},
+            ]
+    response = openai.ChatCompletion.create(
+        model=model,
+        messages=messages,
+        n=n,
+        max_tokens=max_tokens
+    )
+    
+
+    for choice in response.choices:
+        generation = choice.message.content
+        return generation
+
+    
+# return the gpt generated response
+def greet1(argument):
+    user_prompt = default_config.user_prompt_1 + argument + default_config.user_prompt_2
+    response = get_gpt_response(user_prompt=user_prompt)
+    return response
+
+# return the nearest neighbor arguments
+def greet2(argument):
+    nearest_neighbor = find_nearest_neighbor(argument)
+    return "Your argument may fall under the common arguments against AI safety. \nIs it one of these? \n" + nearest_neighbor + "\nSee the taxonomy of arguments below"
+
+
+
+
+# theme = gr.themes.Monochrome()
+theme = gr.themes.Monochrome(
+    # neutral_hue=gr.themes.colors.red,
+
+    #                           n,     boxes,   text,       nothing                      bottom text            most text
+    neutral_hue=gr.themes.Color("red", "#636363", "#636363", "lightgrey", "lightgrey", "lightgrey", "lightgrey", "grey",        "red", "black",       "red"),
+    primary_hue=gr.themes.Color("#8c0010", "#8c0010", "#8c0010", "#8c0010", "#8c0010", "#8c0010", "#8c0010", "#8c0010", "#8c0010", "#8c0010", "#8c0010"),
+    secondary_hue=gr.themes.Color("white", "white", "white", "white", "white", "white", "white", "white", "white", "white", "white"),
+)
+
+
+theme = theme.set(
+    body_background_fill="black",
+    block_title_background_fill="black",
+    block_background_fill="black",
+    body_text_color="white",
+    link_text_color='*primary_50',
+    link_text_color_dark='*primary_50',
+    link_text_color_active='*primary_50',
+    link_text_color_active_dark='*primary_50',
+    link_text_color_hover='*primary_50',
+    link_text_color_hover_dark='*primary_50',
+    link_text_color_visited='*primary_50',
+    link_text_color_visited_dark='*primary_50'
+)
+
+css_string = """
+@import url('https://fonts.googleapis.com/css2?family=Gabarito&family=Gothic+A1:wght@100;200;300;400;500;600;700;800;900&display=swap');
+force_black_bg {
+    background-color: blue !important;
+    color: white !important;
+    font-family: 'Gabarito', cursive !important;
+}
+force_black_bg *{
+    background-color: blue !important;
+    color: white !important;
+    font-family: 'Gabarito', cursive !important;
+}
+
+footer{
+    display:none !important
+    }
+
+"""
+css_string2 = ""
+
+# with gr.Blocks(theme=theme, css=css_string2) as demo:
+#     with gr.Row(elem_id="force_black_bg"):
+#         with gr.Column(elem_id="force_black_bg"):
+#             seed = gr.Text( label="AI Safety Skepticism: What's Your Take?", placeholder="Enter an argument or something you'd like to say!")
+#             btn = gr.Button("Generate >")
+
+#             english = gr.Text(elem_id="themed_question_box", label="Common Argument Classifier")
+
+
+#         with gr.Column():
+#             german = gr.Text(label="Safetybot Response")
+#     btn.click(greet2, inputs=[seed],outputs=english)
+#     btn.click(greet1, inputs=[seed],outputs=german)
+
+
+#     gr.Examples(["AGI is far away, I'm not worried", "AI is confined to a computer and cannot interact with the physical world", "AI isn't concious", "If we don't develop AGI, China will!", "If we don't develop AGI, the Americans will!"], inputs=[seed])
+
+with gr.Blocks(css=css_string) as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.ClearButton([msg, chatbot])
+
+    def respond(message, chat_history):
+        bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"])
+        chat_history.append((message, bot_message))
+        time.sleep(2)
+        return "", chat_history
+
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+
+demo.queue()
+demo.launch()
+
+
+
+