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@ -1,21 +1,16 @@
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"""
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"""
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title: MLX Pipeline
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Plugin Name: MLX Pipeline
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author: justinh-rahb
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Description: A pipeline for running the mlx-lm server with a specified model and dynamically allocated port.
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date: 2024-05-22
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Author: justinh-rahb
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version: 1.0
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License: MIT
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license: MIT
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Python Dependencies: requests, subprocess, os, socket, schemas
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description: A pipeline for running the mlx-lm server with a specified model.
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dependencies: requests, mlx-lm, huggingface_hub
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environment_variables: MLX_MODEL, MLX_STOP, HUGGINGFACE_TOKEN
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"""
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"""
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from typing import List, Union, Generator, Iterator
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from typing import List, Union, Generator, Iterator
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import requests
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import subprocess
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import subprocess
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import os
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import os
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import socket
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import socket
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import time
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import requests
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from huggingface_hub import login
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from schemas import OpenAIChatMessage
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from schemas import OpenAIChatMessage
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@ -28,11 +23,6 @@ class Pipeline:
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self.model = os.getenv('MLX_MODEL', 'mistralai/Mistral-7B-Instruct-v0.2') # Default model if not set in environment variable
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self.model = os.getenv('MLX_MODEL', 'mistralai/Mistral-7B-Instruct-v0.2') # Default model if not set in environment variable
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self.port = self.find_free_port()
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self.port = self.find_free_port()
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self.stop_sequences = os.getenv('MLX_STOP', '[INST]') # Stop sequences from environment variable
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self.stop_sequences = os.getenv('MLX_STOP', '[INST]') # Stop sequences from environment variable
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self.hf_token = os.getenv('HUGGINGFACE_TOKEN', None) # Hugging Face token from environment variable
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# Authenticate with Hugging Face if a token is provided
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if self.hf_token:
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self.authenticate_huggingface(self.hf_token)
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@staticmethod
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@staticmethod
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def find_free_port():
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def find_free_port():
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@ -41,14 +31,6 @@ class Pipeline:
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s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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return s.getsockname()[1]
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return s.getsockname()[1]
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@staticmethod
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def authenticate_huggingface(token: str):
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try:
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login(token)
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print("Successfully authenticated with Hugging Face.")
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except Exception as e:
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print(f"Failed to authenticate with Hugging Face: {e}")
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async def on_startup(self):
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async def on_startup(self):
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# This function is called when the server is started.
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# This function is called when the server is started.
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print(f"on_startup:{__name__}")
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print(f"on_startup:{__name__}")
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@ -68,15 +50,8 @@ class Pipeline:
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stderr=subprocess.PIPE
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stderr=subprocess.PIPE
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)
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)
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print(f"Subprocess started with PID: {self.process.pid} on port {self.port}")
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print(f"Subprocess started with PID: {self.process.pid} on port {self.port}")
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# Check if the process has started correctly
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time.sleep(2) # Give it a moment to start
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if self.process.poll() is not None:
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raise RuntimeError(f"Subprocess failed to start. Return code: {self.process.returncode}")
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except Exception as e:
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except Exception as e:
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print(f"Failed to start subprocess: {e}")
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print(f"Failed to start subprocess: {e}")
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self.process = None
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def stop_subprocess(self):
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def stop_subprocess(self):
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# Stop the subprocess if it is running
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# Stop the subprocess if it is running
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@ -87,8 +62,6 @@ class Pipeline:
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print(f"Subprocess with PID {self.process.pid} terminated")
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print(f"Subprocess with PID {self.process.pid} terminated")
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except Exception as e:
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except Exception as e:
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print(f"Failed to terminate subprocess: {e}")
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print(f"Failed to terminate subprocess: {e}")
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finally:
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self.process = None
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def get_response(
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def get_response(
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self, user_message: str, messages: List[OpenAIChatMessage], body: dict
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self, user_message: str, messages: List[OpenAIChatMessage], body: dict
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@ -96,9 +69,6 @@ class Pipeline:
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# This is where you can add your custom pipelines like RAG.'
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# This is where you can add your custom pipelines like RAG.'
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print(f"get_response:{__name__}")
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print(f"get_response:{__name__}")
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if not self.process or self.process.poll() is not None:
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return "Error: Subprocess is not running."
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MLX_BASE_URL = f"http://localhost:{self.port}"
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MLX_BASE_URL = f"http://localhost:{self.port}"
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MODEL = self.model
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MODEL = self.model
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@ -106,8 +76,8 @@ class Pipeline:
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messages_dict = [{"role": message.role, "content": message.content} for message in messages]
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messages_dict = [{"role": message.role, "content": message.content} for message in messages]
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# Extract additional parameters from the body
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# Extract additional parameters from the body
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temperature = body.get("temperature", 0.8)
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temperature = body.get("temperature", 1.0)
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max_tokens = body.get("max_tokens", 1000)
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max_tokens = body.get("max_tokens", 100)
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top_p = body.get("top_p", 1.0)
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top_p = body.get("top_p", 1.0)
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repetition_penalty = body.get("repetition_penalty", 1.0)
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repetition_penalty = body.get("repetition_penalty", 1.0)
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stop = self.stop_sequences
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stop = self.stop_sequences
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