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| #import libraries here | |
| import gradio as gr | |
| import random | |
| from huggingface_hub import InferenceClient | |
| #AI API being used | |
| client= InferenceClient("openai/gpt-oss-20b") | |
| response="" | |
| #defining role of AI and user | |
| def respond(message,history): | |
| system_message="You are acting like a comforting, guiding parent helping their child navigate academia." | |
| messages = [{"role": "system", "content": system_message}] | |
| if history: | |
| messages.extend(history) #keep adding history | |
| messages.append({"role":"user", "content": message}) | |
| response=client.chat_completion(messages, temperature=0.8, stream=True, max_tokens=100) #capping how many words the LLM is allowed to generate as a respond (300 words) | |
| for message in client.chat_completion(messages): | |
| token=message.choices[0].delta.content | |
| response+=token | |
| yield response['choices'][0]['message']['content'].strip() #storing value of response in a readable format to display | |
| #Defining chatbot giving user a UI to interact, see their conversation history, and see new messages using built in gr feature | |
| #ChatInterface requires at least one parameter(a function) | |
| chatbot = gr.ChatInterface(respond,type="messages", title="AI Chatbot", theme="Taithrah/Minimal") | |
| #launching chatbot | |
| chatbot.launch() | |
| #You may run into errors when you're trying different models. To see the error messages, set debug to True in launch() | |