import gradio as gr
import openai
import requests
import csv
prompt_templates = {"Default ChatGPT": ""}
def get_empty_state():
return {"total_tokens": 0, "messages": []}
def download_prompt_templates():
url = "https://raw.githubusercontent.com/EsoCoding/AiAstroPrompts/main/prompts.csv"
try:
response = requests.get(url)
reader = csv.reader(response.text.splitlines())
next(reader) # skip the header row
for row in reader:
if len(row) >= 2:
act = row[0].strip('"')
prompt = row[1].strip('"')
prompt_templates[act] = prompt
except requests.exceptions.RequestException as e:
print(f"An error occurred while downloading prompt templates: {e}")
return
choices = list(prompt_templates.keys())
choices = choices[:1] + sorted(choices[1:])
return gr.update(value=choices[0], choices=choices)
def on_token_change(user_token):
openai.api_key = user_token
def on_prompt_template_change(prompt_template):
if not isinstance(prompt_template, str): return
return prompt_templates[prompt_template]
def submit_message(user_token, prompt, prompt_template, temperature, max_tokens, context_length, state):
history = state['messages']
if not prompt:
return gr.update(value=''), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: {state['total_tokens']}", state
prompt_template = prompt_templates[prompt_template]
system_prompt = []
if prompt_template:
system_prompt = [{ "role": "system", "content": prompt_template }]
prompt_msg = { "role": "user", "content": prompt }
if not user_token:
history.append(prompt_msg)
history.append({
"role": "system",
"content": "Error: OpenAI API Key is not set."
})
return '', [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: 0", state
try:
completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=system_prompt + history[-context_length*2:] + [prompt_msg], temperature=temperature, max_tokens=max_tokens)
history.append(prompt_msg)
history.append(completion.choices[0].message.to_dict())
state['total_tokens'] += completion['usage']['total_tokens']
except Exception as e:
history.append(prompt_msg)
history.append({
"role": "system",
"content": f"Error: {e}"
})
total_tokens_used_msg = f"Total tokens used: {state['total_tokens']}"
chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)]
return '', chat_messages, total_tokens_used_msg, state
def clear_conversation():
return gr.update(value=None, visible=True), None, "", get_empty_state()
css = """
#col-container {max-width: 80%; margin-left: auto; margin-right: auto;}
#chatbox {min-height: 400px;}
#header {text-align: center;}
#prompt_template_preview {padding: 1em; border-width: 1px; border-style: solid; border-color: #e0e0e0; border-radius: 4px;}
#total_tokens_str {text-align: right; font-size: 0.8em; color: #666;}
#label {font-size: 0.8em; padding: 0.5em; margin: 0;}
.message { font-size: 1.2em; }
"""
with gr.Blocks(css=css) as demo:
state = gr.State(get_empty_state())
with gr.Column(elem_id="col-container"):
gr.Markdown("""## OpenAi AstroBot
Using the ofiicial API (gpt-3.5-turbo model)""",
elem_id="header")
with gr.Row():
with gr.Column():
chatbot = gr.Chatbot(elem_id="chatbox")
input_message = gr.Textbox(show_label=False, placeholder="Enter text and press enter", visible=True).style(container=False)
btn_submit = gr.Button("Submit")
total_tokens_str = gr.Markdown(elem_id="total_tokens_str")
btn_clear_conversation = gr.Button("🔃 Start New Conversation")
with gr.Column():
user_token = gr.Textbox(value='', placeholder="OpenAI API Key", type="password", show_label=False)
prompt_template = gr.Dropdown(label="Set a custom insruction for the chatbot:", choices=list(prompt_templates.keys()))
prompt_template_preview = gr.Textbox(value="prompt_template_preview", type="text", show_label=False)
with gr.Accordion("Advanced parameters", open=False):
temperature = gr.Slider(minimum=0, maximum=2.0, value=0.7, step=0.1, label="Temperature", info="Higher = more creative/chaotic")
max_tokens = gr.Slider(minimum=100, maximum=4096, value=1000, step=1, label="Max tokens per response")
context_length = gr.Slider(minimum=1, maximum=10, value=2, step=1, label="Context length", info="Number of previous messages to send to the chatbot. Be careful with high values, it can blow up the token budget quickly.")
gr.HTML('''