ec2bda4966
* mark depricated API section * CLI bug fixes for azure * check azure before running * Update README.md * Update README.md * bug fix with persona loading * remove print * make errors for cli flags more clear * format * fix imports * fix imports * add prints * update lock * update config fields * cleanup config loading * commit * remove asserts * refactor configure * put into different functions * add embedding default * pass in config * fixes * allow overriding openai embedding endpoint * black * trying to patch tests (some circular import errors) * update flags and docs * patched support for local llms using endpoint and endpoint type passed via configs, not env vars * missing files * fix naming * fix import * fix two runtime errors * patch ollama typo, move ollama model question pre-wrapper, modify question phrasing to include link to readthedocs, also have a default ollama model that has a tag included * disable debug messages * made error message for failed load more informative * don't print dynamic linking function warning unless --debug * updated tests to work with new cli workflow (disabled openai config test for now) * added skips for tests when vars are missing * update bad arg * revise test to soft pass on empty string too * don't run configure twice * extend timeout (try to pass against nltk download) * update defaults * typo with endpoint type default * patch runtime errors for when model is None * catching another case of 'x in model' when model is None (preemptively) * allow overrides to local llm related config params * made model wrapper selection from a list vs raw input * update test for select instead of input * Fixed bug in endpoint when using local->openai selection, also added validation loop to manual endpoint entry * updated error messages to be more informative with links to readthedocs * add back gpt3.5-turbo --------- Co-authored-by: cpacker <packercharles@gmail.com>
66 lines
3.0 KiB
Python
66 lines
3.0 KiB
Python
import os
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from urllib.parse import urljoin
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import requests
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from .settings import SIMPLE
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from ..utils import count_tokens
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LMSTUDIO_API_CHAT_SUFFIX = "/v1/chat/completions"
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LMSTUDIO_API_COMPLETIONS_SUFFIX = "/v1/completions"
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DEBUG = False
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def get_lmstudio_completion(endpoint, prompt, context_window, settings=SIMPLE, api="chat"):
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"""Based on the example for using LM Studio as a backend from https://github.com/lmstudio-ai/examples/tree/main/Hello%2C%20world%20-%20OpenAI%20python%20client"""
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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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request = settings
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request["max_tokens"] = context_window
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if api == "chat":
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# Uses the ChatCompletions API style
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# Seems to work better, probably because it's applying some extra settings under-the-hood?
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URI = urljoin(endpoint.strip("/") + "/", LMSTUDIO_API_CHAT_SUFFIX.strip("/"))
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message_structure = [{"role": "user", "content": prompt}]
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request["messages"] = message_structure
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elif api == "completions":
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# Uses basic string completions (string in, string out)
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# Does not work as well as ChatCompletions for some reason
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URI = urljoin(endpoint.strip("/") + "/", LMSTUDIO_API_COMPLETIONS_SUFFIX.strip("/"))
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request["prompt"] = prompt
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else:
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raise ValueError(api)
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if not endpoint.startswith(("http://", "https://")):
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raise ValueError(f"Provided OPENAI_API_BASE value ({endpoint}) must begin with http:// or https://")
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try:
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response = requests.post(URI, json=request)
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if response.status_code == 200:
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result = response.json()
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if api == "chat":
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result = result["choices"][0]["message"]["content"]
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elif api == "completions":
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result = result["choices"][0]["text"]
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if DEBUG:
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print(f"json API response.text: {result}")
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else:
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# Example error: msg={"error":"Context length exceeded. Tokens in context: 8000, Context length: 8000"}
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if "context length" in str(response.text).lower():
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# "exceeds context length" is what appears in the LM Studio error message
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# raise an alternate exception that matches OpenAI's message, which is "maximum context length"
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raise Exception(f"Request exceeds maximum context length (code={response.status_code}, msg={response.text}, URI={URI})")
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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 LM Studio local inference 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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return result
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