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import gradio as gr
import openai
from openai import OpenAI
import os
import base64
# Set API key and organization ID from environment variables
openai.api_key = os.getenv('OPENAI_API_KEY')
openai.organization = os.getenv('OPENAI_ORG_ID')
client = OpenAI(api_key= os.getenv('OPENAI_API_KEY'), organization=os.getenv('OPENAI_ORG_ID'))
# Define the model to be used
MODEL = "gpt-4o"
def process_text(text_input):
if text_input:
completion = client.chat.completions.create(
model=MODEL,
messages=[
{"role": "system", "content": "You are a helpful assistant. Help me with my math homework!"},
{"role": "user", "content": f"Hello! Could you solve {text_input}?"}
]
)
return "Assistant: " + completion.choices[0].message.content
def process_image(image_input):
if image_input is not None:
with open(image_input.name, "rb") as f:
base64_image = base64.b64encode(f.read()).decode("utf-8")
response = client.chat.completions.create(
model=MODEL,
messages=[
{"role": "system", "content": "You are a helpful assistant that responds in Markdown."},
{"role": "user", "content": [
{"type": "text", "text": "Help me understand what is it"},
{"type": "image_url", "image_url": {
"url": f"data:image/png;base64,{base64_image}"}
}
]}
],
temperature=0.0,
)
return response.choices[0].message.content
def main(text_input="", image_input=None):
if text_input and image_input is None:
return process_text(text_input)
elif image_input is not None:
return process_image(image_input)
iface = gr.Interface(fn=main, inputs=["text", gr.inputs.Image()], outputs="text")
iface.launch()
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