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import os |
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import subprocess |
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import sys |
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def install_engine(): |
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print("⏳ Installing Brain Engine (Safe Mode)...") |
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try: |
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subprocess.check_call([ |
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sys.executable, "-m", "pip", "install", |
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"llama-cpp-python", |
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"--extra-index-url", "https://abetlen.github.io/llama-cpp-python/whl/cpu" |
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]) |
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print("✅ Engine Installed!") |
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except Exception as e: |
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print(f"❌ Install Failed: {e}") |
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try: |
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import llama_cpp |
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except ImportError: |
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install_engine() |
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import llama_cpp |
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import gradio as gr |
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from huggingface_hub import hf_hub_download |
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from llama_cpp import Llama |
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print("Downloading EMET Brain...") |
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model_path = hf_hub_download( |
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repo_id="pavanc21/EMET-Mistral-2.0-GGUF", |
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filename="mistral-7b-v0.3.Q4_K_M.gguf" |
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) |
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print("Starting Engine...") |
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llm = Llama( |
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model_path=model_path, |
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n_ctx=2048, |
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n_threads=2 |
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) |
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def generate_response(message, history): |
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prompt = f"""Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
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### Instruction: |
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{message} |
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### Input: |
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### Response: |
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""" |
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output = llm(prompt, max_tokens=64, stop=["### Instruction:", "</s>"], echo=False) |
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return output['choices'][0]['text'].strip() |
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interface = gr.ChatInterface( |
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fn=generate_response, |
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title="🤖 EMET 2.0 (Live)", |
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description="My custom AI running 24/7 on Hugging Face.", |
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examples=["Who created you?", "What is your purpose?"] |
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) |
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interface.launch() |