5a743d1dc4
git-subtree-dir: apps/core git-subtree-mainline: a8963e11e7a5a0059acbc849ce768e1eee80df61 git-subtree-split: ea2a7395f4023f5b9fab03e6273db3b64a1181d5
64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
from urllib.parse import urljoin
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from letta.local_llm.settings.settings import get_completions_settings
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from letta.local_llm.utils import count_tokens, post_json_auth_request
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WEBUI_API_SUFFIX = "/completions"
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def get_vllm_completion(endpoint, auth_type, auth_key, model, prompt, context_window, user, grammar=None):
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"""https://github.com/vllm-project/vllm/blob/main/examples/api_client.py"""
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from letta.utils import printd
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prompt_tokens = count_tokens(prompt)
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if prompt_tokens > context_window:
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raise Exception(f"Request exceeds maximum context length ({prompt_tokens} > {context_window} tokens)")
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# Settings for the generation, includes the prompt + stop tokens, max length, etc
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settings = get_completions_settings()
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request = settings
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request["prompt"] = prompt
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request["max_tokens"] = 3000 # int(context_window - prompt_tokens)
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request["stream"] = False
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request["user"] = user
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# currently hardcoded, since we are only supporting one model with the hosted endpoint
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request["model"] = model
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# Set grammar
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if grammar is not None:
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raise NotImplementedError
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if not endpoint.startswith(("http://", "https://")):
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raise ValueError(f"Endpoint ({endpoint}) must begin with http:// or https://")
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try:
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URI = urljoin(endpoint.strip("/") + "/", WEBUI_API_SUFFIX.strip("/"))
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response = post_json_auth_request(uri=URI, json_payload=request, auth_type=auth_type, auth_key=auth_key)
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if response.status_code == 200:
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result_full = response.json()
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printd(f"JSON API response:\n{result_full}")
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result = result_full["choices"][0]["text"]
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usage = result_full.get("usage", None)
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else:
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raise Exception(
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f"API call got non-200 response code (code={response.status_code}, msg={response.text}) for address: {URI}."
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+ f" Make sure that the vLLM server is running and reachable at {URI}."
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)
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except:
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# TODO handle gracefully
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raise
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# Pass usage statistics back to main thread
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# These are used to compute memory warning messages
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completion_tokens = usage.get("completion_tokens", None) if usage is not None else None
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total_tokens = prompt_tokens + completion_tokens if completion_tokens is not None else None
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usage = {
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"prompt_tokens": prompt_tokens, # can grab from usage dict, but it's usually wrong (set to 0)
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"completion_tokens": completion_tokens,
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"total_tokens": total_tokens,
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}
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return result, usage
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