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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() | |