mirror of
https://github.com/trustgraph-ai/trustgraph.git
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155 lines
4.2 KiB
Python
Executable file
155 lines
4.2 KiB
Python
Executable file
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"""
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Simple LLM service, performs text prompt completion using Cohere.
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Input is prompt, output is response.
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"""
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import cohere
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from .... schema import TextCompletionRequest, TextCompletionResponse, Error
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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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from .... exceptions import TooManyRequests
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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 = 'c4ai-aya-23-8b'
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default_temperature = 0.0
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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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api_key = params.get("api_key")
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temperature = params.get("temperature", default_temperature)
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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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"input_schema": TextCompletionRequest,
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"output_schema": TextCompletionResponse,
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"model": model,
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"temperature": temperature,
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}
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)
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self.model = model
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self.temperature = temperature
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self.cohere = cohere.Client(api_key=api_key)
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print("Initialised", flush=True)
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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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try:
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output = self.cohere.chat(
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model=self.model,
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message=prompt,
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preamble = "You are a helpful AI-assistant.",
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temperature=self.temperature,
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chat_history=[],
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prompt_truncation='auto',
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connectors=[]
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)
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resp = output.text
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print(resp, flush=True)
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resp = resp.replace("```json", "")
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resp = resp.replace("```", "")
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print("Send response...", flush=True)
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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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# FIXME: Wrong exception, don't know what this LLM throws
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# for a rate limit
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except TooManyRequests:
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print("Send rate limit response...", flush=True)
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r = TextCompletionResponse(
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error=Error(
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type = "rate-limit",
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message = str(e),
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),
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response=None,
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)
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self.producer.send(r, properties={"id": id})
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self.consumer.acknowledge(msg)
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except Exception as e:
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print(f"Exception: {e}")
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print("Send error response...", flush=True)
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r = TextCompletionResponse(
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error=Error(
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type = "llm-error",
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message = str(e),
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),
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response=None,
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)
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self.producer.send(r, properties={"id": id})
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self.consumer.acknowledge(msg)
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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="c4ai-aya-23-8b",
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help=f'Cohere model (default: c4ai-aya-23-8b)'
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)
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parser.add_argument(
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'-k', '--api-key',
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help=f'Cohere API key'
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)
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parser.add_argument(
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'-t', '--temperature',
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type=float,
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default=default_temperature,
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help=f'LLM temperature parameter (default: {default_temperature})'
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)
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def run():
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Processor.start(module, __doc__)
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