I want to buy it. But I want to know if can user local llm models
not atm, but ollama support is in the works, so far the most stable option for local llm I have found. If you know coding, you can also send generated responses to vtspog through our local api, but the setup may be a bit complex unless you are confident in your python (given most local llm model solutions run in python)
for the openai stuff why just make the b ase url customizable so we can use lmstudios server
# Chat with an intelligent assistant in your terminal from openai import OpenAI # Point to the local server client = OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio") history = [ {"role": "system", "content": "You are an intelligent assistant. You always provide well-reasoned answers that are both correct and helpful."}, {"role": "user", "content": "Hello, introduce yourself to someone opening this program for the first time. Be concise."}, ] while True: completion = client.chat.completions.create( model="model-identifier", messages=history, temperature=0.7, stream=True, ) new_message = {"role": "assistant", "content": ""} for chunk in completion: if chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) new_message["content"] += chunk.choices[0].delta.content history.append(new_message) # Uncomment to see chat history # import json # gray_color = "\033[90m" # reset_color = "\033[0m" # print(f"{gray_color}\n{'-'*20} History dump {'-'*20}\n") # print(json.dumps(history, indent=2)) # print(f"\n{'-'*55}\n{reset_color}") print() history.append({"role": "user", "content": input("> ")})also add support for coqui tts or add support to use use xtts-api-server https://github.com/daswer123/xtts-api-server