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import gradio as gr
from openai import OpenAI
import os
from fpdf import FPDF
import docx
css = '''
.gradio-container{max-width: 890px !important}
h1{text-align:center}
footer {
visibility: hidden
}
'''
ACCESS_TOKEN = os.getenv("HF_TOKEN")
client = OpenAI(
base_url="https://api-inference.huggingface.co/v1/",
api_key=ACCESS_TOKEN,
)
# Function to save generated text to a file
def save_file(content, filename, file_format):
if file_format == "pdf":
pdf = FPDF()
pdf.add_page()
pdf.set_auto_page_break(auto=True, margin=15)
pdf.set_font("Arial", size=12)
for line in content.split("\n"):
pdf.multi_cell(0, 10, line)
pdf.output(f"{filename}.pdf")
return f"{filename}.pdf"
elif file_format == "docx":
doc = docx.Document()
doc.add_paragraph(content)
doc.save(f"{filename}.docx")
return f"{filename}.docx"
elif file_format == "txt":
with open(f"{filename}.txt", "w") as f:
f.write(content)
return f"{filename}.txt"
else:
raise ValueError("Unsupported file format")
# Respond function with file saving
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
filename,
file_format
):
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat.completions.create(
model="meta-llama/Meta-Llama-3.1-70B-Instruct",
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
messages=messages,
):
token = message.choices[0].delta.content
response += token
yield response
# Save the final response to the specified file format
saved_file = save_file(response, filename, file_format)
yield response, history + [(message, response)], saved_file
# Gradio interface
demo = gr.ChatInterface(
fn=respond,
additional_inputs=[
gr.Textbox(value="", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-P",
),
gr.Textbox(value="output", label="Filename"),
gr.Radio(["pdf", "docx", "txt"], label="File Format", value="pdf"),
],
outputs=[
gr.Textbox(label="Generated Text"),
gr.State(value=[]), # history
gr.File(label="Download File"),
],
css=css,
theme="allenai/gradio-theme",
)
if __name__ == "__main__":
demo.launch() |