Update app.py
Browse files
app.py
CHANGED
@@ -42,84 +42,206 @@ def process_nlp(system_message):
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colorized_text = colorize_text(system_message['content'])
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return colorized_text
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# define color combinations for different parts of speech
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COLORS = {
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-
"NOUN": "#
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"VERB": "#
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"ADJ": "#
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"ADV": "#
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"digit": "#
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"punct": "#
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"quote": "#
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}
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# define color combinations for individuals with dyslexia
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DYSLEXIA_COLORS = {
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"NOUN": "#
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"VERB": "#
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"ADJ": "#
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"ADV": "#
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"digit": "#
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"punct": "#
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"quote": "#
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}
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# define a muted background color
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BACKGROUND_COLOR = "#
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# define font and size
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FONT = "
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FONT_SIZE = "
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-
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# load the English language model
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nlp = spacy.load('en_core_web_sm')
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def colorize_text(text, colors=
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if colors is None:
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colors = COLORS
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colorized_text = ""
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lines = text.split("\n")
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-
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# set background color
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if background_color is None:
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background_color = BACKGROUND_COLOR
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-
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# iterate over the lines in the text
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for line in lines:
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# parse the line with the language model
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doc = nlp(line)
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# iterate over the tokens in the line
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for token in doc:
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# check if the token is an entity
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if token.ent_type_:
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# use dyslexia colors for entity if available
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if colors == COLORS:
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color = DYSLEXIA_COLORS.get(token.pos_, None)
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else:
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color = colors.get(token.pos_, None)
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-
# check if a color is available for the token
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if color is not None:
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colorized_text += (
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f'<span style="color: {color}; '
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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-
f'
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f'text-decoration: none; '
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f'padding-right: 0.5em;">' # Add space between tokens
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f"{token.text}</span>"
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)
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else:
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colorized_text += (
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f'<span style="font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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-
f'
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f'text-decoration: none; '
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f'padding-right: 0.5em;">' # Add space between tokens
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f"{token.text}</span>"
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)
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else:
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-
# check if a color is available for the token
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color = colors.get(token.pos_, None)
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if color is not None:
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colorized_text += (
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@@ -127,9 +249,7 @@ def colorize_text(text, colors=DYSLEXIA_COLORS, background_color=None):
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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-
f'
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f'text-decoration: none; '
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f'padding-right: 0.5em;">' # Add space between tokens
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f"{token.text}</span>"
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)
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elif token.is_digit:
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@@ -138,9 +258,7 @@ def colorize_text(text, colors=DYSLEXIA_COLORS, background_color=None):
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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-
f'
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f'text-decoration: none; '
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-
f'padding-right: 0.5em;">' # Add space between tokens
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f"{token.text}</span>"
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)
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elif token.is_punct:
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@@ -149,9 +267,7 @@ def colorize_text(text, colors=DYSLEXIA_COLORS, background_color=None):
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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-
f'
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-
f'text-decoration: none; '
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-
f'padding-right: 0.5em;">' # Add space between tokens
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f"{token.text}</span>"
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)
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elif token.is_quote:
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@@ -160,25 +276,20 @@ def colorize_text(text, colors=DYSLEXIA_COLORS, background_color=None):
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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-
f'text-decoration:
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f'padding-right: 0.5em;">' # Add space between tokens
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f"{token.text}</span>"
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)
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else:
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colorized_text += (
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f'<span style="font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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-
f'
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-
f'text-decoration: none; '
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-
f'padding-right: 0.5em;">' # Add space between tokens
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f"{token.text}</span>"
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)
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colorized_text += "<br>"
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-
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return colorized_text
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-
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-
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# def colorize_text(text):
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# colorized_text = ""
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# lines = text.split("\n")
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@@ -300,7 +411,7 @@ def transcribe(audio, text, submit_update=None):
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with concurrent.futures.ThreadPoolExecutor() as executor:
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prompt = [{"text": f"{message['role']}: {message['content']}\n\n"} for message in messages]
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system_message = openai.ChatCompletion.create(
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model="gpt-
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messages=messages,
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max_tokens=2000
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)["choices"][0]["message"]
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colorized_text = colorize_text(system_message['content'])
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return colorized_text
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+
# # define color combinations for different parts of speech
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+
# COLORS = {
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# "NOUN": "#5e5e5e", # Dark gray
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# "VERB": "#ff6936", # Orange
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# "ADJ": "#4363d8", # Blue
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# "ADV": "#228b22", # Green
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# "digit": "#9a45d6", # Purple
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# "punct": "#ffcc00", # Yellow
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# "quote": "#b300b3" # Magenta
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# }
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# # define color combinations for individuals with dyslexia
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# DYSLEXIA_COLORS = {
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# "NOUN": "#5e5e5e",
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# "VERB": "#ff6936",
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# "ADJ": "#4363d8",
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# "ADV": "#228b22",
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# "digit": "#9a45d6",
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# "punct": "#ffcc00",
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# "quote": "#b300b3"
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# }
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+
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# # define a muted background color
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# BACKGROUND_COLOR = "#f5f5f5" # Light gray
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# # define font and size
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# FONT = "Arial"
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# FONT_SIZE = "14px"
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# # load the English language model
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# nlp = spacy.load('en_core_web_sm')
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+
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# def colorize_text(text, colors=DYSLEXIA_COLORS, background_color=None):
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# if colors is None:
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# colors = COLORS
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# colorized_text = ""
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# lines = text.split("\n")
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+
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# # set background color
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# if background_color is None:
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# background_color = BACKGROUND_COLOR
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+
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# # iterate over the lines in the text
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# for line in lines:
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# # parse the line with the language model
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# doc = nlp(line)
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# # iterate over the tokens in the line
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# for token in doc:
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# # check if the token is an entity
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# if token.ent_type_:
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# # use dyslexia colors for entity if available
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# if colors == COLORS:
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# color = DYSLEXIA_COLORS.get(token.pos_, None)
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# else:
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# color = colors.get(token.pos_, None)
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# # check if a color is available for the token
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# if color is not None:
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# colorized_text += (
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# f'<span style="color: {color}; '
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# f'background-color: {background_color}; '
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+
# f'font-family: {FONT}; '
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# f'font-size: {FONT_SIZE}; '
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+
# f'font-weight: bold; '
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+
# f'text-decoration: none; '
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# f'padding-right: 0.5em;">' # Add space between tokens
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# f"{token.text}</span>"
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# )
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# else:
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# colorized_text += (
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+
# f'<span style="font-family: {FONT}; '
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+
# f'font-size: {FONT_SIZE}; '
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+
# f'font-weight: bold; '
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+
# f'text-decoration: none; '
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+
# f'padding-right: 0.5em;">' # Add space between tokens
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# f"{token.text}</span>"
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# )
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# else:
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# # check if a color is available for the token
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# color = colors.get(token.pos_, None)
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# if color is not None:
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# colorized_text += (
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+
# f'<span style="color: {color}; '
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+
# f'background-color: {background_color}; '
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+
# f'font-family: {FONT}; '
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+
# f'font-size: {FONT_SIZE}; '
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+
# f'font-weight: bold; '
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+
# f'text-decoration: none; '
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+
# f'padding-right: 0.5em;">' # Add space between tokens
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# f"{token.text}</span>"
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# )
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# elif token.is_digit:
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# colorized_text += (
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+
# f'<span style="color: {colors["digit"]}; '
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# f'background-color: {background_color}; '
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# f'font-family: {FONT}; '
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+
# f'font-size: {FONT_SIZE}; '
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+
# f'font-weight: bold; '
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+
# f'text-decoration: none; '
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# f'padding-right: 0.5em;">' # Add space between tokens
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# f"{token.text}</span>"
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# )
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# elif token.is_punct:
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# colorized_text += (
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# f'<span style="color: {colors["punct"]}; '
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# f'background-color: {background_color}; '
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# f'font-family: {FONT}; '
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# f'font-size: {FONT_SIZE}; '
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+
# f'font-weight: bold; '
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+
# f'text-decoration: none; '
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# f'padding-right: 0.5em;">' # Add space between tokens
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# f"{token.text}</span>"
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# )
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# elif token.is_quote:
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# colorized_text += (
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# f'<span style="color: {colors["quote"]}; '
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# f'background-color: {background_color}; '
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# f'font-family: {FONT}; '
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# f'font-size: {FONT_SIZE}; '
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+
# f'text-decoration: none; '
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# f'padding-right: 0.5em;">' # Add space between tokens
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# f"{token.text}</span>"
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# )
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# else:
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# colorized_text += (
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# f'<span style="font-family: {FONT}; '
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# f'font-size: {FONT_SIZE}; '
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+
# f'font-weight: bold; '
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+
# f'text-decoration: none; '
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# f'padding-right: 0.5em;">' # Add space between tokens
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# f"{token.text}</span>"
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# )
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# colorized_text += "<br>"
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+
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# return colorized_text
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+
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# define color combinations for different parts of speech
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COLORS = {
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"NOUN": "#FF3300",
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"VERB": "#008000",
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"ADJ": "#1E90FF",
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"ADV": "#FF8C00",
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"digit": "#FF1493",
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"punct": "#8B0000",
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"quote": "#800080",
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}
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# define color combinations for individuals with dyslexia
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DYSLEXIA_COLORS = {
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+
"NOUN": "#1E90FF",
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"VERB": "#006400",
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"ADJ": "#00CED1",
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"ADV": "#FF8C00",
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"digit": "#FF1493",
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"punct": "#A0522D",
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"quote": "#800080",
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}
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# define a muted background color
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BACKGROUND_COLOR = "#EAEAEA"
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# define font and size
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FONT = "Georgia"
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FONT_SIZE = "18px"
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+
def colorize_text(text, colors=None, background_color=None):
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if colors is None:
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colors = COLORS
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colorized_text = ""
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lines = text.split("\n")
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+
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# set background color
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if background_color is None:
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background_color = BACKGROUND_COLOR
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+
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for line in lines:
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doc = nlp(line)
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for token in doc:
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if token.ent_type_:
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# use dyslexia colors for entity if available
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if colors == COLORS:
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color = DYSLEXIA_COLORS.get(token.pos_, None)
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else:
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color = colors.get(token.pos_, None)
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if color is not None:
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colorized_text += (
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f'<span style="color: {color}; '
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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+
f'text-decoration: underline;">'
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f"{token.text}</span>"
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)
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else:
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colorized_text += (
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f'<span style="font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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+
f'text-decoration: underline;">'
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f"{token.text}</span>"
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)
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else:
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color = colors.get(token.pos_, None)
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if color is not None:
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colorized_text += (
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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+
f'text-decoration: underline;">'
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f"{token.text}</span>"
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)
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elif token.is_digit:
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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+
f'text-decoration: underline;">'
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f"{token.text}</span>"
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)
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elif token.is_punct:
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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+
f'text-decoration: underline;">'
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f"{token.text}</span>"
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)
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elif token.is_quote:
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f'background-color: {background_color}; '
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f'font-family: {FONT}; '
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f'font-size: {FONT_SIZE}; '
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279 |
+
f'text-decoration: underline;">'
|
|
|
280 |
f"{token.text}</span>"
|
281 |
)
|
282 |
else:
|
283 |
colorized_text += (
|
284 |
f'<span style="font-family: {FONT}; '
|
285 |
f'font-size: {FONT_SIZE}; '
|
286 |
+
f'text-decoration: underline;">'
|
|
|
|
|
287 |
f"{token.text}</span>"
|
288 |
)
|
289 |
+
colorized_text += " "
|
290 |
colorized_text += "<br>"
|
|
|
291 |
return colorized_text
|
292 |
|
|
|
|
|
293 |
# def colorize_text(text):
|
294 |
# colorized_text = ""
|
295 |
# lines = text.split("\n")
|
|
|
411 |
with concurrent.futures.ThreadPoolExecutor() as executor:
|
412 |
prompt = [{"text": f"{message['role']}: {message['content']}\n\n"} for message in messages]
|
413 |
system_message = openai.ChatCompletion.create(
|
414 |
+
model="gpt-4",
|
415 |
messages=messages,
|
416 |
max_tokens=2000
|
417 |
)["choices"][0]["message"]
|