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from os import getenv
import openai
import gradio as gr
import os
ASSISTANT_ID = getenv("ASSISTANT_ID")
openai_client = openai.Client(
api_key=getenv("OPENAI_API_KEY"),
)
with gr.Blocks() as demo:
# Add a title
gr.Label("ISy QM-Chat")
chatbot = gr.Chatbot()
msg = gr.Textbox()
clear = gr.ClearButton([msg, chatbot])
# Create a dictionary to store citations for each channel
global citations_dict
citations_dict = []
MAX_HISTORY = 4 # Maximum number of messages to keep in the history
async def respond(message, chat_history):
bot_message = await chat(message)
chat_history.append((message, bot_message))
return "", chat_history
async def chat(user_input):
global citations_dict
text = user_input
# If the user's message starts with "/cite", send the corresponding citation
if text.startswith("/cite"):
try:
index = int(text.split(" ", 1)[1]) # Get the index from the user's message
citation = citations_dict[index] # Get the corresponding citation
return citation # Send the citation
except (IndexError, ValueError):
return "Invalid citation index."
thread = openai_client.beta.threads.create(
messages= [
{
"role": "user",
"content": text
}
]
)
run = openai_client.beta.threads.runs.create(
thread_id=thread.id,
assistant_id=ASSISTANT_ID,
)
# Show "typing..." status while fetching response
while run.status != "completed":
run = openai_client.beta.threads.runs.retrieve(
run_id=run.id,
thread_id=thread.id,
)
messages = openai_client.beta.threads.messages.list(
thread_id=thread.id
)
message = messages.data[0]
message_content = message.content[0].text
annotations = message_content.annotations
citations = []
# Iterate over the annotations and add footnotes
for index, annotation in enumerate(annotations):
# Replace the text with a footnote
message_content.value = message_content.value.replace(annotation.text, f' [{index}]')
# Gather citations based on annotation attributes
if (file_citation := getattr(annotation, 'file_citation', None)):
cited_file = openai_client.files.retrieve(file_citation.file_id)
citations.append(f'> Zitat: "{file_citation.quote}"\n> Quelle: {cited_file.filename}')
# elif (file_path := getattr(annotation, 'file_path', None)):
# cited_file = openai_client.files.retrieve(file_path.file_id)
# citations.append(f'> Download: [Link]({cited_file.filename})\n')
# Note: File download functionality not implemented above for brevity
# Store the citations for this channel
citations_dict = citations
# Add the assistant's response to the conversation history
# conversations.append({"role": "assistant", "content": message_content.value})
return message_content.value
msg.submit(respond, [msg, chatbot], [msg, chatbot])
demo.launch()
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