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import gradio as gr | |
from huggingface_hub import InferenceClient | |
from web import search # This will now use the `web` tool correctly | |
client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf") | |
def is_uncertain(question, response): | |
"""Check if the model's response is unreliable.""" | |
if len(response.split()) < 4: # Too short = likely incorrect | |
return True | |
if response.lower() in question.lower(): # Repeats question = unsure | |
return True | |
uncertain_phrases = [ | |
"Kulingana na utafiti", "Inaaminika kuwa", "Ninadhani", | |
"It is believed that", "Some people say", "Inasemekana kuwa" | |
] | |
if any(phrase.lower() in response.lower() for phrase in uncertain_phrases): | |
return True | |
return False | |
def google_search(query): | |
"""Fetch search results using web search.""" | |
results = search(query) # This calls the web tool | |
if results: | |
return results[0] # Return first result | |
return "Sorry, I couldn't find an answer on Google." | |
def respond(message, history, system_message, max_tokens, temperature, top_p): | |
messages = [{"role": "system", "content": system_message}] | |
for val in history: | |
if val[0]: messages.append({"role": "user", "content": val[0]}) | |
if val[1]: messages.append({"role": "assistant", "content": val[1]}) | |
messages.append({"role": "user", "content": message}) | |
response = "" | |
for message in client.chat_completion(messages, max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p): | |
token = message.choices[0].delta.content | |
response += token | |
yield response # Stream the response | |
# If the model's response is unreliable, fetch from Google | |
if is_uncertain(message, response): | |
google_response = google_search(message) | |
yield f"π€ AI: {response}\n\nπ Google: {google_response}" | |
demo = gr.ChatInterface( | |
respond, | |
additional_inputs=[ | |
gr.Textbox(value="You are a friendly Chatbot.", label="System message"), | |
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), | |
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), | |
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"), | |
], | |
) | |
if __name__ == "__main__": | |
demo.launch() | |