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| from huggingface_hub import InferenceClient | |
| from streaming_stt_nemo import Model | |
| import random | |
| import torch | |
| # Random seed generator | |
| def randomize_seed_fn(seed: int) -> int: | |
| seed = random.randint(0, 999999) | |
| return seed | |
| # Function to generate AI response using the selected model | |
| def call_llama(prompt, seed=42): | |
| seed = int(randomize_seed_fn(seed)) | |
| generator = torch.Generator().manual_seed(seed) | |
| client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2") | |
| prompt = [ | |
| {"role": "user", "content": f"{prompt}"} | |
| ] | |
| output = "" | |
| try: | |
| for token in client.chat_completion(prompt, max_tokens=200, stream=True): | |
| if token.choices and len(token.choices) > 0: | |
| delta_content = token.choices[0].delta.content | |
| if delta_content: | |
| output += delta_content | |
| except Exception as e: | |
| raise RuntimeError(f"Error during text generation: {e}") | |
| return output |