diff --git a/app/config.py b/app/config.py index 82271dd7..ac1880a8 100644 --- a/app/config.py +++ b/app/config.py @@ -1,14 +1,39 @@ import os from pyaml_env import parse_config -from pydantic import BaseModel +from pydantic import BaseModel, validator + + +class LLMModelSpecs(BaseModel): + context_length: int class LLMModelConfig(BaseModel): + type: str name: str description: str + + +class OpenAIConfig(LLMModelConfig): + spec: LLMModelSpecs llm_credentials: dict + @validator("type") + def check_type(cls, v): + if v != "openai": + raise ValueError("Invalid type:" + v + " != openai") + return v + + +class StrategyLLMConfig(LLMModelConfig): + llms: list[str] + + @validator("type") + def check_type(cls, v): + if v != "strategy": + raise ValueError("Invalid type:" + v + " != strategy") + return v + class APIKeyConfig(BaseModel): token: str @@ -27,7 +52,7 @@ class CacheParams(BaseModel): class Settings(BaseModel): class PyrisSettings(BaseModel): api_keys: list[APIKeyConfig] - llms: dict[str, LLMModelConfig] + llms: dict[str, OpenAIConfig | StrategyLLMConfig] cache: CacheSettings pyris: PyrisSettings diff --git a/app/llms/__init__.py b/app/llms/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/app/llms/strategy_llm.py b/app/llms/strategy_llm.py new file mode 100644 index 00000000..d12ab456 --- /dev/null +++ b/app/llms/strategy_llm.py @@ -0,0 +1,175 @@ +import logging +from typing import Dict, Any + +from guidance.llms import LLM, OpenAI, LLMSession + +from app.config import settings, OpenAIConfig +from app.services.cache import cache_store +from app.services.circuit_breaker import CircuitBreaker + +log = logging.getLogger(__name__) +log.setLevel(logging.INFO) + + +class StrategyLLM(LLM): + llm_keys: list[str] + llm_configs: dict[str, OpenAIConfig] + llm_sessions: dict[str, LLMSession] + + def __init__(self, llm_keys: list[str]): + super().__init__() + if llm_keys.__len__() == 0: + raise ValueError("No LLMs configured") + self.llm_keys = [ + llm_keys + for llm_keys in llm_keys + if llm_keys in settings.pyris.llms + and isinstance(settings.pyris.llms[llm_keys], OpenAIConfig) + ] + self.llm_configs = { + llm_key: settings.pyris.llms[llm_key] for llm_key in self.llm_keys + } + self.llm_instances = { + llm_key: OpenAI(**llm_config.llm_credentials) + for llm_key, llm_config in self.llm_configs.items() + } + self.llm_sessions = {} + + def first_llm(self): + return self.llm_instances[self.llm_keys[0]] + + def extract_function_call(self, text): + return self.first_llm().extract_function_call(text) + + def __call__(self, *args, asynchronous=False, **kwargs): + return self.first_llm()(*args, asynchronous=asynchronous, **kwargs) + + def __getitem__(self, key): + return self.first_llm()[key] + + def session(self, asynchronous=False): + return StrategyLLMSession(self) + + def encode(self, string, **kwargs): + return self.first_llm().encode(string) + + def decode(self, tokens, **kwargs): + return self.first_llm().decode(tokens) + + def id_to_token(self, id): + return self.first_llm().id_to_token(id) + + def token_to_id(self, token): + return self.first_llm().token_to_id(token) + + def role_start(self, role_name, **kwargs): + return self.first_llm().role_start(role_name, **kwargs) + + def role_end(self, role=None): + return self.first_llm().role_end(role) + + def end_of_text(self): + return self.first_llm().end_of_text() + + +class StrategyLLMSession(LLMSession): + llm: StrategyLLM + current_session_key: str + current_session: LLMSession + + def __init__(self, llm: StrategyLLM): + super().__init__(llm) + self.llm = llm + + def get_total_context_length( + self, prompt: str, llm_key: str, max_tokens: int + ): + prompt_token_length = ( + self.llm.llm_instances[llm_key].encode(prompt).__len__() + ) + return prompt_token_length + max_tokens + + def get_llms_with_context_length( + self, prompt: str, max_tokens: int + ) -> [str]: + return [ + llm_key + for llm_key in self.llm.llm_keys + if self.llm.llm_configs[llm_key].spec.context_length + >= self.get_total_context_length(prompt, llm_key, max_tokens) + ] + + def get_available_llms(self, llms: [str]) -> [str]: + return [ + llm_key + for llm_key in llms + if cache_store.get(llm_key + ":status") != "OPEN" + ] + + def set_correct_session( + self, prompt: str, max_tokens: int, exclude_llms=None + ): + if exclude_llms is None: + exclude_llms = [] + viable_llms = self.get_llms_with_context_length(prompt, max_tokens) + viable_llms = self.get_available_llms(viable_llms) + viable_llms = [ + llm_key for llm_key in viable_llms if llm_key not in exclude_llms + ] + + if viable_llms.__len__() == 0: + log.error( + "No viable LLMs found! Using LLM with longest context length." + ) + llm_configs = self.llm.llm_configs + selected_llm = max( + llm_configs, + key=lambda llm_key: llm_configs[llm_key].spec.context_length, + ) + else: + selected_llm = viable_llms[0] + log.info("Selected LLM: " + selected_llm) + + self.current_session_key = selected_llm + if selected_llm in self.llm.llm_sessions: + self.current_session = self.llm.llm_sessions[selected_llm] + else: + self.current_session = self.llm.llm_instances[ + selected_llm + ].session(asynchronous=True) + self.llm.llm_sessions[selected_llm] = self.current_session + + async def __call__(self, *args, **kwargs): + prompt = args[0] + max_tokens = kwargs["max_tokens"] + self.set_correct_session(prompt, max_tokens) + + def call(): + return self.current_session(*args, **kwargs) + + exclude_llms = [] + + try: + response = await CircuitBreaker.protected_call( + func=call, cache_key=self.current_session_key + ) + except Exception as e: + log.error( + f"Exception {e} while making request! " + f"Trying again with a different LLM." + ) + exclude_llms.append(self.current_session_key) + self.set_correct_session(prompt, max_tokens, exclude_llms) + response = await CircuitBreaker.protected_call( + func=call, cache_key=self.current_session_key + ) + return response + + def __exit__(self, exc_type, exc_value, traceback): + return self.current_session.__exit__(exc_type, exc_value, traceback) + + def _gen_key(self, args_dict): + return self.current_session._gen_key(args_dict) + + def _cache_params(self, args_dict) -> Dict[str, Any]: + return self.current_session._cache_params(args_dict) diff --git a/app/routes/messages.py b/app/routes/messages.py index aae6279b..ee8e98d5 100644 --- a/app/routes/messages.py +++ b/app/routes/messages.py @@ -1,6 +1,7 @@ from datetime import datetime, timezone from fastapi import APIRouter, Depends +from guidance._program_executor import SyntaxException from parsimonious.exceptions import IncompleteParseError from app.core.custom_exceptions import ( @@ -37,11 +38,16 @@ def send_message(body: SendMessageRequest) -> SendMessageResponse: content = CircuitBreaker.protected_call( func=guidance.query, cache_key=body.preferred_model, - accepted_exceptions=(KeyError, SyntaxError, IncompleteParseError), + accepted_exceptions=( + KeyError, + SyntaxError, + SyntaxException, + IncompleteParseError, + ), ) except KeyError as e: raise MissingParameterException(str(e)) - except (SyntaxError, IncompleteParseError) as e: + except (SyntaxError, SyntaxException, IncompleteParseError) as e: raise InvalidTemplateException(str(e)) except Exception as e: raise InternalServerException(str(e)) diff --git a/app/services/guidance_wrapper.py b/app/services/guidance_wrapper.py index c990f47c..803387d3 100644 --- a/app/services/guidance_wrapper.py +++ b/app/services/guidance_wrapper.py @@ -1,8 +1,11 @@ +from typing import cast + import guidance -from app.config import LLMModelConfig +from app.config import LLMModelConfig, OpenAIConfig, StrategyLLMConfig from app.models.dtos import Content, ContentType from app.services.guidance_functions import truncate +from app.llms.strategy_llm import StrategyLLM class GuidanceWrapper: @@ -69,5 +72,11 @@ def is_up(self) -> bool: return content == "1" def _get_llm(self): - llm_credentials = self.model.llm_credentials - return guidance.llms.OpenAI(**llm_credentials) + if isinstance(self.model, OpenAIConfig): + return guidance.llms.OpenAI( + **cast(OpenAIConfig, self.model).llm_credentials + ) + elif isinstance(self.model, StrategyLLMConfig): + return StrategyLLM(cast(StrategyLLMConfig, self.model).llms) + else: + raise ValueError("Invalid model type: " + str(type(self.model))) diff --git a/application.example.yml b/application.example.yml index 05dca1d5..dee65a73 100644 --- a/application.example.yml +++ b/application.example.yml @@ -11,8 +11,11 @@ pyris: llms: DUMMY: + type: "openai" name: "Dummy model" description: "Dummy model for testing" + spec: + context_length: 100 llm_credentials: api_base: "" api_type: "" diff --git a/application.test.yml b/application.test.yml index 05dca1d5..dee65a73 100644 --- a/application.test.yml +++ b/application.test.yml @@ -11,8 +11,11 @@ pyris: llms: DUMMY: + type: "openai" name: "Dummy model" description: "Dummy model for testing" + spec: + context_length: 100 llm_credentials: api_base: "" api_type: "" diff --git a/poetry.lock b/poetry.lock index bbecd5c1..3de959ee 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,99 +1,99 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. 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+fastapi = "^0.103.1" +uvicorn = "^0.23.2" +httpx = "^0.25.0" orjson = "^3.9.1" pydantic = "^1.10.9" pytest-env = "^0.8.2" @@ -23,7 +23,7 @@ guidance = "0.0.64" black = "^23.3.0" flake8 = "^6.0.0" pyaml-env = "^1.2.1" -gunicorn = "^20.1.0" +gunicorn = "^21.2.0" hazelcast-python-client = "^5.3.0" parsimonious = "^0.10.0" diff --git a/tests/routes/health_test.py b/tests/routes/health_test.py index ce6fd725..526e5a5c 100644 --- a/tests/routes/health_test.py +++ b/tests/routes/health_test.py @@ -4,14 +4,26 @@ @pytest.fixture(scope="function") def model_configs(): - llm_model_config1 = config.LLMModelConfig( - name="test1", description="test", llm_credentials={} + llm_model_config1 = config.OpenAIConfig( + type="openai", + name="test1", + description="test", + spec={"context_length": 100}, + llm_credentials={}, ) - llm_model_config2 = config.LLMModelConfig( - name="test2", description="test", llm_credentials={} + llm_model_config2 = config.OpenAIConfig( + type="openai", + name="test2", + description="test", + spec={"context_length": 100}, + llm_credentials={}, ) - llm_model_config3 = config.LLMModelConfig( - name="test3", description="test", llm_credentials={} + llm_model_config3 = config.OpenAIConfig( + type="openai", + name="test3", + description="test", + spec={"context_length": 100}, + llm_credentials={}, ) config.settings.pyris.llms = { "GPT35_TURBO": llm_model_config1, diff --git a/tests/routes/messages_test.py b/tests/routes/messages_test.py index 18b2e8eb..e0f09786 100644 --- a/tests/routes/messages_test.py +++ b/tests/routes/messages_test.py @@ -7,12 +7,20 @@ @pytest.fixture(scope="function") def model_configs(): - llm_model_config = config.LLMModelConfig( - name="test", description="test", llm_credentials={} + llm_model_config = config.OpenAIConfig( + type="openai", + name="test", + description="test", + spec={"context_length": 100}, + llm_credentials={}, ) config.settings.pyris.llms = {"GPT35_TURBO": llm_model_config} api_key_config = config.APIKeyConfig( - token="secret", comment="test", llm_access=["GPT35_TURBO"] + type="openai", + token="secret", + comment="test", + spec={"context_length": 100}, + llm_access=["GPT35_TURBO"], ) config.settings.pyris.api_keys = [api_key_config] diff --git a/tests/services/guidance_wrapper_test.py b/tests/services/guidance_wrapper_test.py index 526d8e52..502da4ba 100644 --- a/tests/services/guidance_wrapper_test.py +++ b/tests/services/guidance_wrapper_test.py @@ -3,10 +3,14 @@ from app.models.dtos import Content, ContentType from app.services.guidance_wrapper import GuidanceWrapper -from app.config import LLMModelConfig - -llm_model_config = LLMModelConfig( - name="test", description="test", llm_credentials={} +from app.config import OpenAIConfig + +llm_model_config = OpenAIConfig( + type="openai", + name="test", + description="test", + spec={"context_length": 100}, + llm_credentials={}, )