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107 lines
2.9 KiB
Python
Executable file
107 lines
2.9 KiB
Python
Executable file
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"""
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Simple LLM service, performs text prompt completion using an Ollama service.
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Input is prompt, output is response.
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"""
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from langchain_community.llms import Ollama
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from prometheus_client import Histogram, Info, Counter
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from .... schema import TextCompletionRequest, TextCompletionResponse
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from .... schema import text_completion_request_queue
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from .... schema import text_completion_response_queue
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from .... log_level import LogLevel
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from .... base import ConsumerProducer
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module = ".".join(__name__.split(".")[1:-1])
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default_input_queue = text_completion_request_queue
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default_output_queue = text_completion_response_queue
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default_subscriber = module
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default_model = 'gemma2'
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default_ollama = 'http://localhost:11434'
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class Processor(ConsumerProducer):
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def __init__(self, **params):
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input_queue = params.get("input_queue", default_input_queue)
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output_queue = params.get("output_queue", default_output_queue)
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subscriber = params.get("subscriber", default_subscriber)
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model = params.get("model", default_model)
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ollama = params.get("ollama", default_ollama)
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super(Processor, self).__init__(
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**params | {
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"input_queue": input_queue,
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"output_queue": output_queue,
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"subscriber": subscriber,
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"model": model,
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"ollama": ollama,
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"input_schema": TextCompletionRequest,
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"output_schema": TextCompletionResponse,
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}
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)
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if not hasattr(__class__, "model_metric"):
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__class__.model_metric = Info(
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'model', 'Model information'
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)
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__class__.model_metric.info({
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"model": model,
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"ollama": ollama,
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})
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self.llm = Ollama(base_url=ollama, model=model)
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def handle(self, msg):
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v = msg.value()
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# Sender-produced ID
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id = msg.properties()["id"]
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print(f"Handling prompt {id}...", flush=True)
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prompt = v.prompt
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# FIXME: Rate limits?
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response = self.llm.invoke(prompt)
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print("Send response...", flush=True)
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resp = response.replace("```json", "")
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resp = response.replace("```", "")
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r = TextCompletionResponse(response=resp)
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self.send(r, properties={"id": id})
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print("Done.", flush=True)
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@staticmethod
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def add_args(parser):
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ConsumerProducer.add_args(
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parser, default_input_queue, default_subscriber,
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default_output_queue,
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)
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parser.add_argument(
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'-m', '--model',
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default="gemma2",
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help=f'LLM model (default: gemma2)'
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)
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parser.add_argument(
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'-r', '--ollama',
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default=default_ollama,
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help=f'ollama (default: {default_ollama})'
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)
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def run():
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Processor.start(module, __doc__)
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