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import os
import requests
import json
import uuid
import gradio as gr
import spaces
API_URL = os.environ.get("API_URL", "default_api_url_if_not_set")
BEARER_TOKEN = os.environ.get("BEARER_TOKEN", "default_token_if_not_set")
headers = {
"Authorization": f"Bearer {BEARER_TOKEN}",
"Content-Type": "application/json"
}
# Define a function to load topics from a JSON file
def load_topics(filename):
try:
with open(filename, 'r') as file:
data = json.load(file)
return data
except FileNotFoundError:
print(f"Error: The file {filename} was not found.")
return {}
except json.JSONDecodeError:
print("Error: Failed to decode JSON.")
return {}
# Path to your JSON file
topics_json_path = 'topics.json'
# Call the function and store the topics
topics = load_topics(topics_json_path)
userdata = dict()
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
json = response.json()
return json
@spaces.GPU
def generate(
message: str,
chat_history: list[tuple[str, str]],
system_prompt: str,
max_new_tokens: int = 1024,
temperature: float = 0.6,
top_p: float = 0.9,
top_k: int = 50,
repetition_penalty: float = 1.2,
user_id: uuid.UUID = uuid.uuid4()
) -> str:
user_id_str = user_id.hex
if user_id_str not in userdata or "topicId" not in userdata[user_id_str]:
userdata[user_id_str] = {"topicId": "0", "topic_flag": False}
topic = topics[userdata[user_id_str]["topicId"]]
result = query({
"inputs":"" ,
"message":message,
"chat_history":chat_history,
"system_prompt":system_prompt,
"instruction": topic["instruction"],
"conclusions": topic["conclusions"],
"context": topic["context"],
"max_new_tokens":max_new_tokens,
"temperature":temperature,
"top_p":top_p,
"top_k":top_k,
"repetition_penalty":repetition_penalty,
})
conclusion = result.get("conclusion")
if conclusion is not None:
next_topic_id = topic["conclusionAction"][conclusion]["next"]
extra = topic["conclusionAction"][conclusion]["extra"]
userdata[user_id_str]["topicId"] = next_topic_id
userdata[user_id_str]["topic_flag"] = True
return result.get("generated_text") + "\n" + extra + "\n" + topics[next_topic_id]["primer"]
return result.get("generated_text")
def update(chatbot_state):
# Check if the user_id exists in userdata, if not, create a default entry
if user_id.value.hex not in userdata:
userdata[user_id.value.hex] = {"topic_flag": False}
# Now you can safely get the topic_flag value
user_topic_flag = userdata[user_id.value.hex].get("topic_flag", False)
# If topic_flag is True, reset it to False and return the primer
if user_topic_flag:
userdata[user_id.value.hex]["topic_flag"] = False
return [[None, topics[userdata[user_id.value.hex]["topicId"]]["primer"]]]
# Return the original chatbot_state if topic_flag is not True
return chatbot_state
# Create Gradio interface components (inputs)
system_prompt_input = gr.Textbox(label="System prompt")
max_new_tokens_input = gr.Slider(minimum=1, maximum=2048, value=50, step=1, label="Max New Tokens")
temperature_input = gr.Slider(minimum=0.1, maximum=4.0, step=0.1, value=0.6, label="Temperature")
top_p_input = gr.Slider(minimum=0.05, maximum=1.0, step=0.05, value=0.9, label="Top-p")
top_k_input = gr.Slider(minimum=1, maximum=1000, step=1, value=50, label="Top-k")
repetition_penalty_input = gr.Slider(minimum=1.0, maximum=2.0, step=0.05, value=1.2, label="Repetition Penalty")
user_id = gr.State(uuid.uuid4())
chat_interface = gr.ChatInterface(
fn=generate,
chatbot=gr.Chatbot([[None, topics["0"]["primer"]]]),
additional_inputs=[
system_prompt_input,
max_new_tokens_input,
temperature_input,
top_p_input,
top_k_input,
repetition_penalty_input,
user_id
],
stop_btn=gr.Button("Stop"),
examples=[
#
],
)
with gr.Blocks(css="style.css") as demo:
chat_interface.render()
chat_interface.submit_btn.click(update, inputs=chat_interface.chatbot_state, outputs=chat_interface.chatbot_state)
chat_interface.textbox.input(update, inputs=chat_interface.chatbot_state, outputs=chat_interface.chatbot_state)
if __name__ == "__main__":
demo.queue(max_size=20).launch(debug=True)
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