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Update app.py
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app.py
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model = "gemma2:27b"
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import os
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os.system("
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import nest_asyncio
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nest_asyncio.apply()
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import asyncio
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# Run Async Ollama
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# Taken from: https://stackoverflow.com/questions/77697302/how-to-run-ollama-in-google-colab
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# NB: You may need to set these depending and get cuda working depending which backend you are running.
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# Set environment variable for NVIDIA library
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# Set environment variables for CUDA
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os.environ['PATH'] += ':/usr/local/cuda/bin'
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# Set LD_LIBRARY_PATH to include both /usr/lib64-nvidia and CUDA lib directories
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os.environ['LD_LIBRARY_PATH'] = '/usr/lib64-nvidia:/usr/local/cuda/lib64'
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async def run_process(cmd):
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print('>>> starting', *cmd)
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process = await asyncio.create_subprocess_exec(
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*cmd,
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE
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)
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# define an async pipe function
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async def pipe(lines):
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async for line in lines:
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print(line.decode().strip())
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await asyncio.gather(
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pipe(process.stdout),
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pipe(process.stderr),
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)
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# call it
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await asyncio.gather(pipe(process.stdout), pipe(process.stderr))
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import threading
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async def start_ollama_serve():
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await run_process(['ollama', 'serve'])
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def run_async_in_thread(loop, coro):
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asyncio.set_event_loop(loop)
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loop.run_until_complete(coro)
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loop.close()
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# Create a new event loop that will run in a new thread
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new_loop = asyncio.new_event_loop()
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# Start ollama serve in a separate thread so the cell won't block execution
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thread = threading.Thread(target=run_async_in_thread, args=(new_loop, start_ollama_serve()))
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thread.start()
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# Load up model
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os.system(f"ollama pull {model}")
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import copy
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import gradio as gr
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model = "gemma2:27b"
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import ollama
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import os
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ollama_path="/usr/local/lib/python3.10/site-packages/ollama"
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os.system(f"{ollama_path} ollama pull {model}")
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import copy
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import gradio as gr
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