diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000..d8573b3 --- /dev/null +++ b/.dockerignore @@ -0,0 +1,28 @@ +**/__pycache__ +**/.venv +**/.classpath +**/.dockerignore +**/.env +**/.git +**/.gitignore +**/.project +**/.settings +**/.toolstarget +**/.vs +**/.vscode +**/*.*proj.user +**/*.dbmdl +**/*.jfm +**/bin +**/charts +**/docker-compose* +**/compose* +**/Dockerfile* +**/node_modules +**/npm-debug.log +**/obj +**/secrets.dev.yaml +**/values.dev.yaml +**/.nox +LICENSE +.history \ No newline at end of file diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..fd012ba --- /dev/null +++ b/.env.example @@ -0,0 +1,9 @@ +# Credentials for AWS account with an access to Bedrock models +AWS_ACCESS_KEY_ID= +AWS_SECRET_ACCESS_KEY= +DEFAULT_REGION=us-east-1 + +# Misc env vars for the server +LOG_LEVEL=INFO # Default in prod is INFO. Use DEBUG for dev. +WEB_CONCURRENCY=1 # Number of unicorn workers +TEST_SERVER_URL=http://0.0.0.0:5001 \ No newline at end of file diff --git a/.flake8 b/.flake8 new file mode 100644 index 0000000..91bc39f --- /dev/null +++ b/.flake8 @@ -0,0 +1,12 @@ +[flake8] +# E501 line is too long +# W503 line break before binary operator +# E203 whitespace before ':' +ignore = E501, W503, E203 +exclude = + .venv, + .nox, + __pycache__ +per-file-ignores = + # imported but unused + tests/locust/app.py: F401 \ No newline at end of file diff --git a/.github/pr-title-checker-config.json b/.github/pr-title-checker-config.json new file mode 100644 index 0000000..2de82f5 --- /dev/null +++ b/.github/pr-title-checker-config.json @@ -0,0 +1,14 @@ +{ + "LABEL": { + "name": "", + "color": "EEEEEE" + }, + "CHECKS": { + "prefixes": ["fix: ", "feat: ", "feature: ", "chore: ", "hotfix: "] + }, + "MESSAGES": { + "success": "All OK", + "failure": "Missing prefix", + "notice": "" + } +} \ No newline at end of file diff --git a/.github/workflows/pr_check_tests.yml b/.github/workflows/pr_check_tests.yml new file mode 100644 index 0000000..4e0d8b7 --- /dev/null +++ b/.github/workflows/pr_check_tests.yml @@ -0,0 +1,15 @@ +name: Code checks - tests + +on: + pull_request: + branches: + - development + - release-* + +jobs: + run_tests: + uses: epam/ai-dial-ci/.github/workflows/test_python_docker.yml@0.1.0 + with: + bypass_checks: false + python_version: 3.11 + secrets: inherit \ No newline at end of file diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml new file mode 100644 index 0000000..5125311 --- /dev/null +++ b/.github/workflows/release.yml @@ -0,0 +1,13 @@ +name: Release version + +on: + push: + branches: [ development, release-* ] + +env: + IMAGE_NAME: ${{ github.repository }} + +jobs: + release: + uses: epam/ai-dial-ci/.github/workflows/publish_python_docker.yml@0.1.0 + secrets: inherit \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..da8669c --- /dev/null +++ b/.gitignore @@ -0,0 +1,12 @@ +.DS_Store +venv +.venv +.env +.history +.idea +__pycache__ +.nox +dist +.vscode/launch.json +~* +leftovers \ No newline at end of file diff --git a/.vscode/extensions.json b/.vscode/extensions.json new file mode 100644 index 0000000..a1f8dbe --- /dev/null +++ b/.vscode/extensions.json @@ -0,0 +1,7 @@ +{ + "recommendations": [ + "ms-python.python", + "ms-python.black-formatter", + "ms-python.isort" + ] +} \ No newline at end of file diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..7f02da0 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,14 @@ +{ + "[python]": { + "editor.defaultFormatter": "ms-python.black-formatter", + "editor.formatOnSave": true, + "editor.codeActionsOnSave": { + "source.organizeImports": true + }, + "editor.tabSize": 4 + }, + "python.testing.pytestArgs": ["."], + "python.testing.unittestEnabled": false, + "python.testing.pytestEnabled": true, + "python.analysis.typeCheckingMode": "basic" +} \ No newline at end of file diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..24abaf0 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,32 @@ +FROM python:3.11-alpine as builder + +RUN pip install poetry + +WORKDIR /app + +# Install split into two steps (the dependencies and the sources) +# in order to leverage the Docker caching +COPY pyproject.toml poetry.lock poetry.toml ./ +RUN poetry install --no-interaction --no-ansi --no-cache --no-root --no-directory --only main + +COPY . . +RUN poetry install --no-interaction --no-ansi --no-cache --only main + +FROM python:3.11-alpine as server + +WORKDIR /app + +# Copy the sources and virtual env. No poetry. +RUN adduser -u 1001 --disabled-password --gecos "" appuser +COPY --chown=appuser --from=builder /app . + +COPY ./scripts/docker_entrypoint.sh /docker_entrypoint.sh +RUN chmod +x /docker_entrypoint.sh + +ENV LOG_LEVEL=INFO +EXPOSE 5000 + +USER appuser +ENTRYPOINT ["/docker_entrypoint.sh"] + +CMD ["uvicorn", "aidial_adapter_bedrock.app:app", "--host", "0.0.0.0", "--port", "5000"] diff --git a/Dockerfile.test b/Dockerfile.test new file mode 100644 index 0000000..dca8463 --- /dev/null +++ b/Dockerfile.test @@ -0,0 +1,29 @@ +FROM python:3.11-slim as builder + +RUN pip install poetry + +WORKDIR /app + +# Install split into two steps (the dependencies and the sources) +# in order to leverage the Docker caching +COPY pyproject.toml poetry.lock poetry.toml ./ +RUN poetry install --no-interaction --no-ansi --no-cache --no-root --no-directory --with test + +COPY . . +RUN poetry install --no-interaction --no-ansi --no-cache --with test + +FROM python:3.11-slim as test + +WORKDIR /app + +# Copy the sources and virtual env. No poetry. +RUN adduser -u 1001 --disabled-password --gecos "" appuser +COPY --chown=appuser --from=builder /app . + +COPY ./scripts/docker_entrypoint.sh /docker_entrypoint.sh +RUN chmod +x /docker_entrypoint.sh + +USER appuser +ENTRYPOINT ["/docker_entrypoint.sh"] + +CMD ["pytest", "tests/unit_tests"] \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..18d1c18 --- /dev/null +++ b/LICENSE @@ -0,0 +1,202 @@ + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2023 EPAM Systems, Inc. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. \ No newline at end of file diff --git a/MODEL_CARD.md b/MODEL_CARD.md new file mode 100644 index 0000000..7652433 --- /dev/null +++ b/MODEL_CARD.md @@ -0,0 +1,129 @@ +# Bedrock models + +## Amazon Titan + +### Tokenization + +Returns number of used tokens in response: + +```json +{ + "inputTextTokenCount": 10, + "results": [ + { + "content": "foo", + "tokenCount": 20 + } + ] +} +``` + +```python +return TokenUsage( + prompt_tokens=resp.inputTextTokenCount, + completion_tokens=resp.results[0].tokenCount, +) +``` + +Tokenizer is unknown. + +### Token limits + +Tokens limits are unknown. + +Experimentally found tokens limits (see `./test/find_token_limits.py`): + +- amazon.titan-tg1-large: 4096 + +## Anthropic Claude + +### Tokenization + +`anthropic` package provides methods to [calculate tokens](https://github.com/anthropics/anthropic-sdk-python/blob/main/examples/tokens.py). + +```python +from anthropic.tokenizer import count_tokens + +return TokenUsage( + prompt_tokens=count_tokens(query.prompt), + completion_tokens=count_tokens(resp.completion), +) +``` + +The tokenizer could be migrated to the frontend. + +### Streaming + +The streaming is supported by [Anthropic SDK](https://github.com/anthropics/anthropic-sdk-python/blob/main/examples/streaming.py), but it's not supported by the Bedrock API. + +### Token limits + +As per [documentation](https://docs.anthropic.com/claude/docs/introduction-to-prompt-design#prompt-length) the limits aren't strictly specified: + +``` +The maximum prompt length that Claude can see is its context window. Claude's context window is currently ~75,000 words / ~100,000 tokens / ~340,000 Unicode characters. + +Right now when this context window is exceeded in the API Claude is likely to return an incoherent response. We apologize for this “sharp edge”. +``` + +However [pricing page](https://www.anthropic.com/pricing) explicitly says that context windows is 100k tokens. + +So: + +- max input tokens: 100k +- max outputs tokens: unknown + +However, it doesn't match with experimentally found tokens limits (see `./test/find_token_limits.py`): + +- anthropic.claude-v1: 12288 +- anthropic.claude-instant-v1: 12288 + +REST: [completion call](https://docs.anthropic.com/claude/reference/complete_post) + +## AI21 models + +### Rate limits + +See [rate limits](https://docs.ai21.com/docs/rate-limits). + +### Token limits + +REST (and Bedrock presumably): max context window = [8191 tokens](https://docs.ai21.com/reference/j2-complete-ref) + +AWS: see [token limits](https://docs.ai21.com/docs/choosing-the-right-instance-type-for-amazon-sagemaker-models#foundation-models) for various model instances + +``` +The context window acts as a threshold for the amount of tokens in the prompt and the completion, namely: prompt + completion <= context window. +``` + +Experimentally found tokens limits confirm the documentation (see `./test/find_token_limits.py`): + +- ai21.j2-grande-instruct: 8191 +- ai21.j2-jumbo-instruct: 8191 + +### Tokenization + +Response contains tokens explicitly as arrays. One needs only compute the len of the arrays: + +```python +return TokenUsage( + prompt_tokens=len(resp.prompt.tokens), + completion_tokens=len(resp.completions[0].data.tokens), +) +``` + +Tokenizer is [unknown](https://docs.ai21.com/docs/tokenizer-tokenization): + +> AI21 Studio uses a large token dictionary (250K) + +Token counting is only possible using AI21 API Key. + +**Tokenization via Bedrock API is currently unsupported** (see `./local_client_ai21.py`). + +SDK: `ai21` package calls `tokenize` endpoint to do tokenization (see `ai21/modules/tokenization.py`). + +REST: There is API for [tokenization](https://docs.ai21.com/reference/tokenize-ref) + +## Stable diffusion + +There is no meaningful size limit on the prompt size. diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..0046c62 --- /dev/null +++ b/Makefile @@ -0,0 +1,61 @@ +PORT ?= 5001 +IMAGE_NAME ?= ai-dial-adapter-bedrock +PLATFORM ?= linux/amd64 +DEV_PYTHON ?= 3.11 +ARGS= + +.PHONY: all install build serve clean lint format test integration_tests docker_build docker_run + +all: build + +install: + poetry env use python$(DEV_PYTHON) + poetry install + +build: install + poetry build + +serve: install + poetry run uvicorn "aidial_adapter_bedrock.app:app" --reload --host "0.0.0.0" --port $(PORT) --workers=1 --env-file ./.env + +clean: + poetry run clean + poetry env remove --all + +lint: install + poetry run nox -s lint + +format: install + poetry run nox -s format + +test: install + poetry run nox -s test + +integration_tests: install + poetry run nox -s integration_tests + +docker_test: + docker build --platform $(PLATFORM) -f Dockerfile.test -t $(IMAGE_NAME):test . + docker run --platform $(PLATFORM) --rm $(IMAGE_NAME):test + +docker_serve: + docker build --platform $(PLATFORM) -t $(IMAGE_NAME):dev . + docker run --platform $(PLATFORM) --env-file ./.env --rm -p $(PORT):5000 $(IMAGE_NAME):dev + +help: + @echo '====================' + @echo 'build - build the source and wheels archives' + @echo 'clean - clean virtual env and build artifacts' + @echo 'docs - build the documentation' + @echo 'publish' - publish the Docker image to the registry' + @echo '-- LINTING --' + @echo 'format - run code formatters' + @echo 'lint - run linters' + @echo '-- RUN --' + @echo 'serve - run the dev server locally' + @echo 'docker_serve - run the dev server from the docker' + @echo '-- TESTS --' + @echo 'test - run unit tests' + @echo 'test ARGS= - run all tests in file' + @echo 'docker_test - run unit tests from the docker' + @echo 'integration_tests - run integration tests' \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..adea50f --- /dev/null +++ b/README.md @@ -0,0 +1,108 @@ +## Overview + +The project implements [AI DIAL API](https://epam-rail.com/dial_api) for language models from [AWS Bedrock](https://aws.amazon.com/bedrock/). + +Supported models: +* Amazon Titan +* AI21 J2 +* Anthropic Claude V1, V2 +* Stable Diffusion + +## Developer environment + +This project uses [Python>=3.11](https://www.python.org/downloads/) and [Poetry>=1.6.1](https://python-poetry.org/) as a dependency manager. + +Check out Poetry's [documentation on how to install it](https://python-poetry.org/docs/#installation) on your system before proceeding. + +To install requirements: + +```sh +poetry install +``` + +This will install all requirements for running the package, linting, formatting and tests. + +### IDE configuration + +The recommended IDE is [VSCode](https://code.visualstudio.com/). +Open the project in VSCode and install the recommended extensions. + +The VSCode is configured to use PEP-8 compatible formatter [Black](https://black.readthedocs.io/en/stable/index.html). + +Alternatively you can use [PyCharm](https://www.jetbrains.com/pycharm/). + +Set-up the Black formatter for PyCharm [manually](https://black.readthedocs.io/en/stable/integrations/editors.html#pycharm-intellij-idea) or +install PyCharm>=2023.2 with [built-in Black support](https://blog.jetbrains.com/pycharm/2023/07/2023-2/#black). + +## Run + +Run the development server: + +```sh +make serve +``` + +Open `localhost:5001/docs` to make sure the server is up and running. + +## Environment Variables + +Copy `.env.example` to `.env` and customize it for your environment: + +|Variable|Default|Description| +|---|---|---| +|AWS_ACCESS_KEY_ID|NA|AWS credentials with access to Bedrock service| +|AWS_SECRET_ACCESS_KEY|NA|AWS credentials with access to Bedrock service| +|DEFAULT_REGION||AWS region e.g. "us-east-1"| +|LOG_LEVEL|INFO|Log level. Use DEBUG for dev purposes and INFO in prod| +|WEB_CONCURRENCY|1|Number of workers for the server| +|TEST_SERVER_URL|http://0.0.0.0:5001|Server URL used in the integration tests| + +### Docker + +Run the server in Docker: + +```sh +make docker_serve +``` + +## Lint + +Run the linting before committing: + +```sh +make lint +``` + +To auto-fix formatting issues run: + +```sh +make format +``` + +## Test + +Run unit tests locally: + +```sh +make test +``` + +Run unit tests in Docker: + +```sh +make docker_test +``` + +Run integration tests locally: + +```sh +make integration_tests +``` + +## Clean + +To remove the virtual environment and build artifacts: + +```sh +make clean +``` diff --git a/aidial_adapter_bedrock/app.py b/aidial_adapter_bedrock/app.py new file mode 100644 index 0000000..e667f84 --- /dev/null +++ b/aidial_adapter_bedrock/app.py @@ -0,0 +1,47 @@ +import logging.config + +import fastapi +from aidial_sdk import DIALApp + +from aidial_adapter_bedrock.chat_completion import BedrockChatCompletion +from aidial_adapter_bedrock.llm.bedrock_adapter import BedrockModels +from aidial_adapter_bedrock.llm.bedrock_models import BedrockDeployment +from aidial_adapter_bedrock.llm.chat_emulation.types import ChatEmulationType +from aidial_adapter_bedrock.server.exceptions import dial_exception_decorator +from aidial_adapter_bedrock.universal_api.response import ( + ModelObject, + ModelsResponse, +) +from aidial_adapter_bedrock.utils.env import get_env +from aidial_adapter_bedrock.utils.log_config import LogConfig + +logging.config.dictConfig(LogConfig().dict()) + +default_region = get_env("DEFAULT_REGION") +default_chat_emulation_type = ChatEmulationType.META_CHAT + + +app = DIALApp(description="AWS Bedrock adapter for RAIL API") + + +@app.get("/healthcheck") +def healthcheck(): + return fastapi.Response("OK") + + +@app.get("/openai/models") +@dial_exception_decorator +async def models(): + bedrock_models = BedrockModels(region=default_region).models() + models = [ModelObject(id=model["modelId"]) for model in bedrock_models] + return ModelsResponse(data=models) + + +for deployment in BedrockDeployment: + app.add_chat_completion( + deployment.get_model_id(), + BedrockChatCompletion( + region=default_region, + chat_emulation_type=default_chat_emulation_type, + ), + ) diff --git a/aidial_adapter_bedrock/chat_completion.py b/aidial_adapter_bedrock/chat_completion.py new file mode 100644 index 0000000..4ea14d2 --- /dev/null +++ b/aidial_adapter_bedrock/chat_completion.py @@ -0,0 +1,51 @@ +import asyncio +from typing import List + +from aidial_sdk.chat_completion import ChatCompletion, Request, Response + +from aidial_adapter_bedrock.llm.bedrock_adapter import BedrockAdapter +from aidial_adapter_bedrock.llm.chat_emulation.types import ChatEmulationType +from aidial_adapter_bedrock.server.exceptions import dial_exception_decorator +from aidial_adapter_bedrock.universal_api.request import ModelParameters +from aidial_adapter_bedrock.universal_api.token_usage import TokenUsage + + +class BedrockChatCompletion(ChatCompletion): + region: str + chat_emulation_type: ChatEmulationType + + def __init__(self, region: str, chat_emulation_type: ChatEmulationType): + self.region = region + self.chat_emulation_type = chat_emulation_type + + @dial_exception_decorator + async def chat_completion(self, request: Request, response: Response): + model = await BedrockAdapter.create( + region=self.region, + model_id=request.deployment_id, + model_params=ModelParameters.create(request), + ) + + async def generate_response(idx: int) -> TokenUsage: + model_response = await model.achat( + self.chat_emulation_type, request.messages + ) + + with response.create_choice() as choice: + choice.append_content(model_response.content) + + for data in model_response.data: + choice.add_attachment( + title=data.name, + data=data.content, + type=data.mime_type, + ) + + return model_response.usage + + usages: List[TokenUsage] = await asyncio.gather( + *(generate_response(idx) for idx in range(request.n or 1)) + ) + + usage = sum(usages, TokenUsage()) + response.set_usage(usage.prompt_tokens, usage.completion_tokens) diff --git a/aidial_adapter_bedrock/llm/__init__.py b/aidial_adapter_bedrock/llm/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/aidial_adapter_bedrock/llm/bedrock_adapter.py b/aidial_adapter_bedrock/llm/bedrock_adapter.py new file mode 100644 index 0000000..0f757d4 --- /dev/null +++ b/aidial_adapter_bedrock/llm/bedrock_adapter.py @@ -0,0 +1,363 @@ +import json +from abc import ABC, abstractmethod +from enum import Enum +from typing import Any, Dict, List, Literal, Optional, TypedDict, Union + +import boto3 +from anthropic.tokenizer import count_tokens +from pydantic import BaseModel, Field +from typing_extensions import Annotated + +from aidial_adapter_bedrock.llm.chat_model import ( + ChatModel, + Model, + ModelResponse, + ResponseData, + TokenUsage, +) +from aidial_adapter_bedrock.universal_api.request import ModelParameters +from aidial_adapter_bedrock.utils.concurrency import make_async +from aidial_adapter_bedrock.utils.log_config import bedrock_logger as log + + +class BedrockModelId(TypedDict): + modelArn: str + modelId: str + + +class IOutput(ABC): + @abstractmethod + def content(self) -> str: + pass + + def data(self) -> list[ResponseData]: + return [] + + @abstractmethod + def usage(self, prompt: str) -> TokenUsage: + pass + + +class AmazonResult(BaseModel): + tokenCount: int + outputText: str + completionReason: Optional[str] + + +class AmazonResponse(BaseModel, IOutput): + inputTextTokenCount: int + results: List[AmazonResult] + + def content(self) -> str: + assert ( + len(self.results) == 1 + ), "AmazonResponse should only have one result" + return self.results[0].outputText + + def usage(self, prompt: str) -> TokenUsage: + assert ( + len(self.results) == 1 + ), "AmazonResponse should only have one result" + return TokenUsage( + prompt_tokens=self.inputTextTokenCount, + completion_tokens=self.results[0].tokenCount, + ) + + +class AnthropicResponse(BaseModel, IOutput): + completion: str + stop_reason: str # Literal["stop_sequence"] + + def content(self) -> str: + return self.completion + + def usage(self, prompt: str) -> TokenUsage: + return TokenUsage( + prompt_tokens=count_tokens(prompt), + completion_tokens=count_tokens(self.completion), + ) + + +class TextRange(BaseModel): + start: int + end: int + + +class GeneratedToken(BaseModel): + token: str + logprob: float + raw_logprob: float + + +class Token(BaseModel): + generatedToken: GeneratedToken + topTokens: Optional[Any] + textRange: TextRange + + +class TextAndTokens(BaseModel): + text: str + tokens: List[Token] + + +class FinishReason(BaseModel): + reason: str # Literal["length", "endoftext"] + length: Optional[int] + + +class Completion(BaseModel): + data: TextAndTokens + finishReason: FinishReason + + +class AI21Response(BaseModel, IOutput): + id: int + prompt: TextAndTokens + completions: List[Completion] + + def content(self) -> str: + assert ( + len(self.completions) == 1 + ), "AI21Response should only have one completion" + return self.completions[0].data.text + + def usage(self, prompt: str) -> TokenUsage: + assert ( + len(self.completions) == 1 + ), "AI21Response should only have one completion" + return TokenUsage( + prompt_tokens=len(self.prompt.tokens), + completion_tokens=len(self.completions[0].data.tokens), + ) + + +class StabilityStatus(str, Enum): + SUCCESS = "success" + ERROR = "error" + + +class StabilityError(BaseModel): + id: str + message: str + name: str + + +class StabilityArtifact(BaseModel): + seed: int + base64: str + finish_reason: str = Field(alias="finishReason") + + +class StabilityResponse(BaseModel, IOutput): + # TODO: Use tagged union artifacts/error + result: str + artifacts: Optional[list[StabilityArtifact]] + error: Optional[StabilityError] + + def content(self) -> str: + self._throw_if_error() + return "" + + def data(self) -> list[ResponseData]: + self._throw_if_error() + return [ResponseData(mime_type="image/png", name="image", content=self.artifacts[0].base64)] # type: ignore + + def usage(self, prompt: str) -> TokenUsage: + return TokenUsage( + prompt_tokens=0, + completion_tokens=0, + ) + + def _throw_if_error(self): + if self.result == StabilityStatus.ERROR: + raise Exception(self.error.message) # type: ignore + + +class TaggedAmazonResponse(AmazonResponse): + provider: Literal["amazon"] + + +class TaggedAnthropicResponse(AnthropicResponse): + provider: Literal["anthropic"] + + +class TaggedAI21Response(AI21Response): + provider: Literal["ai21"] + + +class TaggedStabilityResponse(StabilityResponse): + provider: Literal["stability"] + + +class BedrockResponse(BaseModel, IOutput): + __root__: Annotated[ + Union[ + TaggedAmazonResponse, + TaggedAnthropicResponse, + TaggedAI21Response, + TaggedStabilityResponse, + ], + Field(discriminator="provider"), + ] + + def content(self) -> str: + return self.__root__.content() + + def data(self) -> list[ResponseData]: + return self.__root__.data() + + def usage(self, prompt: str) -> TokenUsage: + return self.__root__.usage(prompt) + + +class BedrockModels: + def __init__(self, region: str): + session = boto3.Session() + self.bedrock = session.client("bedrock", region) + + def models(self) -> List[BedrockModelId]: + return self.bedrock.list_foundation_models()["modelSummaries"] + + +# Simplified copy of langchain.llms.bedrock.LLMInputOutputAdapter.prepare_input +def prepare_input( + provider: str, prompt: str, model_kwargs: Dict[str, Any] +) -> Dict[str, Any]: + input_body = {**model_kwargs} + if provider == "anthropic" or provider == "ai21": + input_body["prompt"] = prompt + elif provider == "amazon": + input_body = dict() + input_body["inputText"] = prompt + input_body["textGenerationConfig"] = {**model_kwargs} + elif provider == "stability": + input_body = dict() + input_body["text_prompts"] = [{"text": prompt}] + else: + input_body["inputText"] = prompt + + return input_body + + +def prepare_model_kwargs( + provider: str, model_params: ModelParameters +) -> Dict[str, Any]: + model_kwargs = {} + + # NOTE: See https://docs.anthropic.com/claude/reference/complete_post + if provider == "anthropic": + if model_params.max_tokens is not None: + model_kwargs["max_tokens_to_sample"] = model_params.max_tokens + else: + # The max tokens parameter is required for Anthropic models. + # Choosing reasonable default. + model_kwargs["max_tokens_to_sample"] = 500 + + if model_params.stop is not None: + model_kwargs["stop_sequences"] = model_params.stop + + if model_params.temperature is not None: + model_kwargs["temperature"] = model_params.temperature + + # Doesn't have any effect. AWS always sends the whole response at once. + # streaming = model_kwargs.streaming + + if model_params.top_p is not None: + model_kwargs["top_p"] = model_params.top_p + + # OpenAI API doesn't have top_k parameter. + # if model_params.top_k is not None: + # model_kwargs["top_k"] = model_params.top_k + + # NOTE: API See https://docs.ai21.com/reference/j2-instruct-ref + # NOTE: Per-model token limits: https://docs.ai21.com/docs/choosing-the-right-instance-type-for-amazon-sagemaker-models#foundation-models + if provider == "ai21": + if model_params.max_tokens is not None: + model_kwargs["maxTokens"] = model_params.max_tokens + else: + # The default for max tokens is 16, which is too small for most use cases + model_kwargs["maxTokens"] = 500 + + if model_params.temperature is not None: + model_kwargs["temperature"] = model_params.temperature + else: + # The default AI21 temperature is 0.7. + # The default OpenAI temperature is 1.0. + # Choosing the OpenAI default since we pretend AI21 to be OpenAI. + model_kwargs["temperature"] = 1.0 + + if model_params.top_p is not None: + model_kwargs["topP"] = model_params.top_p + + if model_params.stop is not None: + model_kwargs["stopSequences"] = model_params.stop + + # NOTE: AI21 has "numResults" parameter, however we emulate multiple result + # via mutliple calls to support all models uniformly. + + if provider == "amazon": + if model_params.temperature is not None: + model_kwargs["temperature"] = model_params.temperature + # NOTE: There is no documentation for Amazon models currently. + # NOTE: max tokens is 128 by default. The parameter name is not known. + + return model_kwargs + + +class BedrockAdapter(ChatModel): + def __init__( + self, + model_id: str, + model_provider: str, + model_params: ModelParameters, + model_kwargs: Dict[str, Any], + bedrock: Any, + ): + self.model_id = model_id + self.model_provider = model_provider + self.model_params = model_params + self.model_kwargs = model_kwargs + self.bedrock = bedrock + + @classmethod + async def create( + cls, model_id: str, region: str, model_params: ModelParameters + ) -> "BedrockAdapter": + model_provider = Model.parse(model_id).provider + + model_kwargs = prepare_model_kwargs(model_provider, model_params) + + bedrock = await make_async( + lambda _: boto3.Session().client("bedrock-runtime", region), + (), + ) + + return cls( + model_id, model_provider, model_params, model_kwargs, bedrock + ) + + async def acall(self, prompt: str) -> ModelResponse: + return await make_async(self._call, prompt) + + def _call(self, prompt: str) -> ModelResponse: + log.debug(f"prompt:\n{prompt}") + + model_response = self.bedrock.invoke_model( + body=json.dumps( + prepare_input(self.model_provider, prompt, self.model_kwargs) + ), + modelId=self.model_id, + contentType="application/json", + accept="application/json", + ) + + body = json.loads(model_response["body"].read()) + resp = BedrockResponse.parse_obj( + {"provider": self.model_provider, **body} + ) + response = ModelResponse( + content=resp.content(), data=resp.data(), usage=resp.usage(prompt) + ) + + log.debug(f"response:\n{response.json()}") + return response diff --git a/aidial_adapter_bedrock/llm/bedrock_models.py b/aidial_adapter_bedrock/llm/bedrock_models.py new file mode 100644 index 0000000..e1027cf --- /dev/null +++ b/aidial_adapter_bedrock/llm/bedrock_models.py @@ -0,0 +1,16 @@ +from enum import Enum + + +class BedrockDeployment(str, Enum): + AMAZON_TITAN_TG1_LARGE = "amazon.titan-tg1-large" + AI21_J2_GRANDE_INSTRUCT = "ai21.j2-grande-instruct" + AI21_J2_JUMBO_INSTRUCT = "ai21.j2-jumbo-instruct" + AI21_J2_MID = "ai21.j2-mid" + AI21_J2_ULTRA = "ai21.j2-ultra" + ANTHROPIC_CLAUDE_INSTANT_V1 = "anthropic.claude-instant-v1" + ANTHROPIC_CLAUDE_V1 = "anthropic.claude-v1" + ANTHROPIC_CLAUDE_V2 = "anthropic.claude-v2" + STABILITY_STABLE_DIFFUSION_XL = "stability.stable-diffusion-xl" + + def get_model_id(self) -> str: + return self.value diff --git a/aidial_adapter_bedrock/llm/chat_emulation/__init__.py b/aidial_adapter_bedrock/llm/chat_emulation/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/aidial_adapter_bedrock/llm/chat_emulation/claude.py b/aidial_adapter_bedrock/llm/chat_emulation/claude.py new file mode 100644 index 0000000..5bb5c8a --- /dev/null +++ b/aidial_adapter_bedrock/llm/chat_emulation/claude.py @@ -0,0 +1,55 @@ +from enum import Enum +from typing import List + +from pydantic import BaseModel + +from aidial_adapter_bedrock.llm.exceptions import ValidationError +from aidial_adapter_bedrock.llm.message import BaseMessage + + +class ClaudeRole(Enum): + HUMAN = "Human" + ASSISTANT = "Assistant" + + +class ClaudeMessage(BaseModel): + role: ClaudeRole + content: str + + +class ClaudeHistory: + history: List[ClaudeMessage] + + def __init__(self): + self.history = [] + + def add(self, msg: ClaudeMessage): + if len(self.history) > 0 and self.history[-1].role == msg.role: + self.history[-1].content += " " + msg.content + else: + self.history.append(msg) + + def print(self) -> str: + return "".join( + [ + f"\n\n{msg.role.value}: {msg.content.lstrip()}".rstrip() + for msg in self.history + ] + ) + + +def emulate(prompt: List[BaseMessage]) -> str: + if len(prompt) == 0: + raise ValidationError("List of messages must not be empty") + + history = ClaudeHistory() + for msg in prompt: + role = ( + ClaudeRole.HUMAN + if msg.type in ["system", "human"] + else ClaudeRole.ASSISTANT + ) + history.add(ClaudeMessage(role=role, content=msg.content)) + history.add(ClaudeMessage(role=ClaudeRole.ASSISTANT, content="")) + + return history.print() diff --git a/aidial_adapter_bedrock/llm/chat_emulation/meta_chat.py b/aidial_adapter_bedrock/llm/chat_emulation/meta_chat.py new file mode 100644 index 0000000..20b53f9 --- /dev/null +++ b/aidial_adapter_bedrock/llm/chat_emulation/meta_chat.py @@ -0,0 +1,55 @@ +from typing import List, Tuple + +from aidial_adapter_bedrock.llm.exceptions import ValidationError +from aidial_adapter_bedrock.llm.message import ( + AIMessage, + BaseMessage, + SystemMessage, +) +from aidial_adapter_bedrock.utils.operators import Unary +from aidial_adapter_bedrock.utils.text import enforce_stop_tokens, remove_prefix + +HUMAN = "Human" +ASSISTANT = "Assistant" +SYSTEM = "System" + +prelude = f""" +You are a helpful assistant participating in a dialog with a user. +The messages from the user start with "{HUMAN}:". +The messages from you start with "{ASSISTANT}:". +Reply to the last message from the user taking into account the preceding dialog history. +==================== +""".strip() + + +def type_to_role(ty: str) -> str: + roles = {"human": HUMAN, "system": HUMAN, "ai": ASSISTANT} + return roles.get(ty, ty) + + +def emulate(prompt: List[BaseMessage]) -> Tuple[str, Unary[str]]: + if len(prompt) == 0: + raise ValidationError("List of messages must not be empty") + + history = prompt.copy() + history.append(AIMessage(content="")) + + msgs = [prelude] + for msg in history: + # Skipping empty system messages + if isinstance(msg, SystemMessage) and msg.content.strip() == "": + continue + + role = type_to_role(msg.type) + msgs.append(f"\n\n{role}: {msg.content.lstrip()}".rstrip()) + + return "".join(msgs), post_process + + +stop = f"{HUMAN}:" + + +def post_process(response: str) -> str: + response = enforce_stop_tokens(response, [stop]) + response = remove_prefix(response.strip(), f"{ASSISTANT}:") + return response.strip() diff --git a/aidial_adapter_bedrock/llm/chat_emulation/types.py b/aidial_adapter_bedrock/llm/chat_emulation/types.py new file mode 100644 index 0000000..ab7a6ce --- /dev/null +++ b/aidial_adapter_bedrock/llm/chat_emulation/types.py @@ -0,0 +1,6 @@ +from enum import Enum + + +class ChatEmulationType(Enum): + ZERO_MEMORY = "zero_memory" + META_CHAT = "meta_chat" diff --git a/aidial_adapter_bedrock/llm/chat_emulation/zero_memory.py b/aidial_adapter_bedrock/llm/chat_emulation/zero_memory.py new file mode 100644 index 0000000..18892ba --- /dev/null +++ b/aidial_adapter_bedrock/llm/chat_emulation/zero_memory.py @@ -0,0 +1,10 @@ +from typing import List + +from aidial_adapter_bedrock.llm.exceptions import ValidationError +from aidial_adapter_bedrock.llm.message import BaseMessage + + +def emulate(prompt: List[BaseMessage]) -> str: + if len(prompt) == 0: + raise ValidationError("List of messages must not be empty") + return prompt[-1].content diff --git a/aidial_adapter_bedrock/llm/chat_model.py b/aidial_adapter_bedrock/llm/chat_model.py new file mode 100644 index 0000000..80420c6 --- /dev/null +++ b/aidial_adapter_bedrock/llm/chat_model.py @@ -0,0 +1,92 @@ +from abc import ABC, abstractmethod +from typing import List, Tuple + +from aidial_sdk.chat_completion import Message +from pydantic import BaseModel + +import aidial_adapter_bedrock.llm.chat_emulation.claude as claude +import aidial_adapter_bedrock.llm.chat_emulation.meta_chat as meta_chat +import aidial_adapter_bedrock.llm.chat_emulation.zero_memory as zero_memory +from aidial_adapter_bedrock.llm.chat_emulation.types import ChatEmulationType +from aidial_adapter_bedrock.llm.message import BaseMessage, parse_message +from aidial_adapter_bedrock.universal_api.request import ModelParameters +from aidial_adapter_bedrock.universal_api.token_usage import TokenUsage +from aidial_adapter_bedrock.utils.operators import Unary, identity +from aidial_adapter_bedrock.utils.text import enforce_stop_tokens + + +class ResponseData(BaseModel): + mime_type: str + name: str + content: str + + +class ModelResponse(BaseModel): + content: str + data: List[ResponseData] + usage: TokenUsage + + +class ChatModel(ABC): + model_id: str + model_params: ModelParameters + + @abstractmethod + async def acall(self, prompt: str) -> ModelResponse: + # TODO: Support multiple results: call the model in cycle of `self.model_params.n` iterations + pass + + async def achat( + self, + chat_emulation_type: ChatEmulationType, + messages: List[Message], + ) -> ModelResponse: + prompt, post_process = emulate_chat( + self.model_id, + chat_emulation_type, + list(map(parse_message, messages)), + ) + + response = await self.acall(prompt) + + content = post_process( + enforce_stop_tokens(response.content, self.model_params.stop) + ) + + return ModelResponse( + content=content, data=response.data, usage=response.usage + ) + + +class Model(BaseModel): + provider: str + model: str + + @classmethod + def parse(cls, model_id: str) -> "Model": + parts = model_id.split(".") + if len(parts) != 2: + raise Exception( + f"Invalid model id '{model_id}'. The model id is expected to be in format 'provider.model'" + ) + provider, model = parts + return cls(provider=provider, model=model) + + +def emulate_chat( + model_id: str, emulation_type: ChatEmulationType, history: List[BaseMessage] +) -> Tuple[str, Unary[str]]: + model = Model.parse(model_id) + if model.provider == "anthropic" and "claude" in model.model: + return claude.emulate(history), identity + + if model.provider == "stability": + return zero_memory.emulate(history), identity + + match emulation_type: + case ChatEmulationType.ZERO_MEMORY: + return zero_memory.emulate(history), identity + case ChatEmulationType.META_CHAT: + return meta_chat.emulate(history) + case _: + raise Exception(f"Invalid emulation type: {emulation_type}") diff --git a/aidial_adapter_bedrock/llm/exceptions.py b/aidial_adapter_bedrock/llm/exceptions.py new file mode 100644 index 0000000..8d8ab94 --- /dev/null +++ b/aidial_adapter_bedrock/llm/exceptions.py @@ -0,0 +1,4 @@ +class ValidationError(Exception): + def __init__(self, message: str): + self.message = message + super().__init__(self.message) diff --git a/aidial_adapter_bedrock/llm/message.py b/aidial_adapter_bedrock/llm/message.py new file mode 100644 index 0000000..a38d423 --- /dev/null +++ b/aidial_adapter_bedrock/llm/message.py @@ -0,0 +1,48 @@ +from abc import abstractmethod + +from aidial_sdk.chat_completion import Message, Role +from pydantic import BaseModel + +from aidial_adapter_bedrock.llm.exceptions import ValidationError + + +class BaseMessage(BaseModel): + content: str + + @property + @abstractmethod + def type(self) -> str: + """Type of the message, used for serialization.""" + + +class SystemMessage(BaseMessage): + @property + def type(self) -> str: + return "system" + + +class HumanMessage(BaseMessage): + @property + def type(self) -> str: + return "human" + + +class AIMessage(BaseMessage): + @property + def type(self) -> str: + return "ai" + + +def parse_message(msg: Message) -> BaseMessage: + if msg.content is None: + raise ValidationError("Message content must be present") + + match msg.role: + case Role.SYSTEM: + return SystemMessage(content=msg.content) + case Role.USER: + return HumanMessage(content=msg.content) + case Role.ASSISTANT: + return AIMessage(content=msg.content) + case Role.FUNCTION: + raise ValidationError("Function calls are not supported") diff --git a/aidial_adapter_bedrock/server/__init__.py b/aidial_adapter_bedrock/server/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/aidial_adapter_bedrock/server/exceptions.py b/aidial_adapter_bedrock/server/exceptions.py new file mode 100644 index 0000000..f513e46 --- /dev/null +++ b/aidial_adapter_bedrock/server/exceptions.py @@ -0,0 +1,55 @@ +from functools import wraps + +from aidial_sdk import HTTPException as DialException +from botocore.exceptions import ClientError + +from aidial_adapter_bedrock.llm.exceptions import ValidationError + + +# TODO: Catch the rate limit exception and dress it like OpenAI rate limit exception: botocore.errorfactory.ThrottlingException: An error occurred (ThrottlingException) when calling the InvokeModel operation (reached max retries: 4): Too many requests, please wait before trying again. You have sent too many requests. Wait before trying again. +def to_dial_exception(e: Exception) -> DialException: + if isinstance(e, ClientError): + if "The security token included in the request is invalid" in str(e): + return DialException( + status_code=401, + type="invalid_request_error", + message=f"Invalid Authentication: {str(e)}", + code="invalid_api_key", + param=None, + ) + elif "ModelTimeoutException" in str(e): + return DialException( + status_code=502, + type="timeout", + message="Request timed out", + code=None, + param=None, + ) + + if isinstance(e, ValidationError): + return DialException( + status_code=422, + type="invalid_request_error", + message=e.message, + code="invalid_argument", + param=None, + ) + + return DialException( + status_code=500, + type="internal_server_error", + message=str(e), + code=None, + param=None, + ) + + +def dial_exception_decorator(func): + @wraps(func) + async def wrapper(*args, **kwargs): + try: + return await func(*args, **kwargs) + except Exception as e: + raise to_dial_exception(e) + + return wrapper diff --git a/aidial_adapter_bedrock/universal_api/__init__.py b/aidial_adapter_bedrock/universal_api/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/aidial_adapter_bedrock/universal_api/request.py b/aidial_adapter_bedrock/universal_api/request.py new file mode 100644 index 0000000..4d21d68 --- /dev/null +++ b/aidial_adapter_bedrock/universal_api/request.py @@ -0,0 +1,28 @@ +from typing import List, Mapping, Optional, Union + +from aidial_sdk.chat_completion import Request +from pydantic import BaseModel + + +class ModelParameters(BaseModel): + temperature: Optional[float] = None + top_p: Optional[float] = None + n: Optional[int] = None + stop: Optional[Union[str, List[str]]] = None + max_tokens: Optional[int] = None + presence_penalty: Optional[float] = None + frequency_penalty: Optional[float] = None + logit_bias: Optional[Mapping[int, float]] = None + + @classmethod + def create(cls, request: Request) -> "ModelParameters": + return cls( + temperature=request.temperature, + top_p=request.top_p, + n=request.n, + stop=request.stop, + max_tokens=request.max_tokens, + presence_penalty=request.presence_penalty, + frequency_penalty=request.frequency_penalty, + logit_bias=request.logit_bias, + ) diff --git a/aidial_adapter_bedrock/universal_api/response.py b/aidial_adapter_bedrock/universal_api/response.py new file mode 100644 index 0000000..d9f4a1c --- /dev/null +++ b/aidial_adapter_bedrock/universal_api/response.py @@ -0,0 +1,13 @@ +from typing import List, Literal + +from pydantic import BaseModel + + +class ModelObject(BaseModel): + object: Literal["model"] = "model" + id: str + + +class ModelsResponse(BaseModel): + object: Literal["list"] = "list" + data: List[ModelObject] diff --git a/aidial_adapter_bedrock/universal_api/token_usage.py b/aidial_adapter_bedrock/universal_api/token_usage.py new file mode 100644 index 0000000..814232b --- /dev/null +++ b/aidial_adapter_bedrock/universal_api/token_usage.py @@ -0,0 +1,16 @@ +from pydantic import BaseModel + + +class TokenUsage(BaseModel): + prompt_tokens: int = 0 + completion_tokens: int = 0 + + @property + def total_tokens(self) -> int: + return self.prompt_tokens + self.completion_tokens + + def __add__(self, other: "TokenUsage") -> "TokenUsage": + return TokenUsage( + prompt_tokens=self.prompt_tokens + other.prompt_tokens, + completion_tokens=self.completion_tokens + other.completion_tokens, + ) diff --git a/aidial_adapter_bedrock/utils/__init__.py b/aidial_adapter_bedrock/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/aidial_adapter_bedrock/utils/concurrency.py b/aidial_adapter_bedrock/utils/concurrency.py new file mode 100644 index 0000000..78148a2 --- /dev/null +++ b/aidial_adapter_bedrock/utils/concurrency.py @@ -0,0 +1,12 @@ +import asyncio +from concurrent.futures import ThreadPoolExecutor +from typing import Callable, TypeVar + +T = TypeVar("T") +A = TypeVar("A") + + +async def make_async(func: Callable[[A], T], arg: A) -> T: + with ThreadPoolExecutor() as executor: + loop = asyncio.get_event_loop() + return await loop.run_in_executor(executor, func, arg) diff --git a/aidial_adapter_bedrock/utils/env.py b/aidial_adapter_bedrock/utils/env.py new file mode 100644 index 0000000..77eb4df --- /dev/null +++ b/aidial_adapter_bedrock/utils/env.py @@ -0,0 +1,10 @@ +import os + + +def get_env(name: str) -> str: + if name in os.environ: + val = os.environ.get(name) + if val is not None: + return val + + raise Exception(f"{name} env variable is not set") diff --git a/aidial_adapter_bedrock/utils/files.py b/aidial_adapter_bedrock/utils/files.py new file mode 100644 index 0000000..01299e9 --- /dev/null +++ b/aidial_adapter_bedrock/utils/files.py @@ -0,0 +1,5 @@ +from pathlib import Path + + +def get_project_root() -> Path: + return Path(__file__).parent.parent diff --git a/aidial_adapter_bedrock/utils/log_config.py b/aidial_adapter_bedrock/utils/log_config.py new file mode 100644 index 0000000..badf519 --- /dev/null +++ b/aidial_adapter_bedrock/utils/log_config.py @@ -0,0 +1,47 @@ +import logging +import os + +from pydantic import BaseModel + +# By default (in prod) we don't want to print debug messages, +# because they typically contain prompts. +LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO") + + +class LogConfig(BaseModel): + """Logging configuration to be set for the server""" + + version = 1 + disable_existing_loggers = False + formatters = { + "default": { + "()": "uvicorn.logging.DefaultFormatter", + "fmt": "%(levelprefix)s | %(asctime)s | %(name)s | %(process)d | %(message)s", + "datefmt": "%Y-%m-%d %H:%M:%S", + "use_colors": True, + }, + } + handlers = { + "default": { + "formatter": "default", + "class": "logging.StreamHandler", + "stream": "ext://sys.stderr", + }, + } + loggers = { + "app": {"handlers": ["default"], "level": LOG_LEVEL}, + "bedrock": {"handlers": ["default"], "level": LOG_LEVEL}, + "uvicorn": { + "handlers": ["default"], + "level": LOG_LEVEL, + "propagate": False, + }, + } + + +# Loggers in order from high-level to low-level +# High-level logs from the adapter server +app_logger = logging.getLogger("app") + +# LLM requests and responses +bedrock_logger = logging.getLogger("bedrock") diff --git a/aidial_adapter_bedrock/utils/operators.py b/aidial_adapter_bedrock/utils/operators.py new file mode 100644 index 0000000..eaa191a --- /dev/null +++ b/aidial_adapter_bedrock/utils/operators.py @@ -0,0 +1,9 @@ +from typing import Callable, TypeVar + +T = TypeVar("T") + +Unary = Callable[[T], T] + + +def identity(x: T) -> T: + return x diff --git a/aidial_adapter_bedrock/utils/printing.py b/aidial_adapter_bedrock/utils/printing.py new file mode 100644 index 0000000..60b42e8 --- /dev/null +++ b/aidial_adapter_bedrock/utils/printing.py @@ -0,0 +1,36 @@ +from colorama import Back, Fore, Style + + +def get_input(prefix: str = "") -> str: + print(Fore.RED, flush=True, end="") + content = input(prefix) + print(Style.RESET_ALL, flush=True, end="") + return content + + +def print_red(msg: str, **args): + print(Fore.RED + msg + Style.RESET_ALL, flush=True, **args) + + +def print_error(msg: str, **args): + print(Fore.RED + msg + Style.RESET_ALL, flush=True, **args) + + +def print_warning(msg: str, **args): + print(Fore.YELLOW + msg + Style.RESET_ALL, flush=True, **args) + + +def print_info(msg: str, **args): + print(Fore.YELLOW + msg + Style.RESET_ALL, flush=True, **args) + + +def print_system(msg: str, **args): + print(Back.LIGHTBLACK_EX + msg + Style.RESET_ALL, flush=True, **args) + + +def print_human(msg: str, **args): + print(Fore.GREEN + msg + Style.RESET_ALL, flush=True, **args) + + +def print_ai(msg: str, **args): + print(Fore.BLUE + msg + Style.RESET_ALL, flush=True, **args) diff --git a/aidial_adapter_bedrock/utils/text.py b/aidial_adapter_bedrock/utils/text.py new file mode 100644 index 0000000..b8986e8 --- /dev/null +++ b/aidial_adapter_bedrock/utils/text.py @@ -0,0 +1,22 @@ +import re +from typing import List + + +def remove_prefix(text: str, prefix: str) -> str: + if text.startswith(prefix): + return text[len(prefix) :] + return text + + +# Copy of langchain.llms.utils::enforce_stop_tokens with a bugfix: stop words are escaped. +def enforce_stop_tokens(text: str, stop: None | List[str] | str) -> str: + """Cut off the text as soon as any stop words occur.""" + + if stop is None: + return text + + if isinstance(stop, str): + stop = [stop] + + stop_escaped = [re.escape(s) for s in stop] + return re.split("|".join(stop_escaped), text)[0] diff --git a/client/client_bedrock.py b/client/client_bedrock.py new file mode 100755 index 0000000..29f9080 --- /dev/null +++ b/client/client_bedrock.py @@ -0,0 +1,48 @@ +import asyncio +from typing import List + +from aidial_sdk.chat_completion import Message, Role + +from aidial_adapter_bedrock.llm.bedrock_adapter import BedrockAdapter +from aidial_adapter_bedrock.universal_api.request import ModelParameters +from aidial_adapter_bedrock.utils.env import get_env +from aidial_adapter_bedrock.utils.printing import print_ai, print_info +from client.conf import MAX_CHAT_TURN, MAX_INPUT_CHARS +from client.utils.cli import choose_deployment +from client.utils.init import init +from client.utils.input import make_input + + +async def main(): + location = get_env("DEFAULT_REGION") + + deployment, chat_emulation_type = choose_deployment() + + model = await BedrockAdapter.create( + model_id=deployment.get_model_id(), + model_params=ModelParameters(), + region=location, + ) + + history: List[Message] = [] + + chat_input = make_input() + + turn = 0 + while turn < MAX_CHAT_TURN: + turn += 1 + + content = chat_input()[:MAX_INPUT_CHARS] + history.append(Message(role=Role.USER, content=content)) + + response = await model.achat(chat_emulation_type, history) + + print_info(response.usage.json(indent=2)) + + print_ai(response.content.strip()) + history.append(Message(role=Role.ASSISTANT, content=response.content)) + + +if __name__ == "__main__": + init() + asyncio.run(main()) diff --git a/client/conf.py b/client/conf.py new file mode 100644 index 0000000..b547283 --- /dev/null +++ b/client/conf.py @@ -0,0 +1,2 @@ +MAX_INPUT_CHARS = 1024 +MAX_CHAT_TURN = 128 diff --git a/client/utils/cli.py b/client/utils/cli.py new file mode 100644 index 0000000..b096807 --- /dev/null +++ b/client/utils/cli.py @@ -0,0 +1,45 @@ +from enum import Enum +from typing import List, Tuple, Type, TypeVar + +import inquirer + +from aidial_adapter_bedrock.llm.bedrock_models import BedrockDeployment +from aidial_adapter_bedrock.llm.chat_emulation.types import ChatEmulationType + +V = TypeVar("V") + + +def select_option(title: str, options: List[V]) -> V: + questions = [ + inquirer.List( + "option", + message=title, + choices=[(str(option), option) for option in options], + carousel=True, + ), + ] + return inquirer.prompt(questions)["option"] # type: ignore + + +T = TypeVar("T", bound=Enum) + + +def select_enum(title: str, enum: Type[T]) -> T: + questions = [ + inquirer.List( + "option", + message=title, + choices=[(option.value, option) for option in enum], + carousel=True, + ), + ] + return inquirer.prompt(questions)["option"] # type: ignore + + +def choose_deployment() -> Tuple[BedrockDeployment, ChatEmulationType]: + deployment = select_enum("Select the deployment", BedrockDeployment) + chat_emulation_type = select_enum( + "Select chat emulation type", ChatEmulationType + ) + + return deployment, chat_emulation_type diff --git a/client/utils/init.py b/client/utils/init.py new file mode 100644 index 0000000..5477bc3 --- /dev/null +++ b/client/utils/init.py @@ -0,0 +1,5 @@ +from dotenv import load_dotenv + + +def init(): + load_dotenv() # take environment variables from .env. diff --git a/client/utils/input.py b/client/utils/input.py new file mode 100644 index 0000000..c54f68d --- /dev/null +++ b/client/utils/input.py @@ -0,0 +1,21 @@ +from prompt_toolkit import PromptSession +from prompt_toolkit.history import FileHistory +from prompt_toolkit.styles import Style + +from aidial_adapter_bedrock.utils.files import get_project_root + + +def make_input(limit: int = 8000): + session = None + + def input(prompt_text="> ", style=Style.from_dict({"": "#ff0000"})): + nonlocal session + if session is None: + session = PromptSession( + history=FileHistory(str(get_project_root() / ".history")) + ) + + response = session.prompt(prompt_text, style=style) + return response[:limit] + + return input diff --git a/noxfile.py b/noxfile.py new file mode 100644 index 0000000..a5a7a6a --- /dev/null +++ b/noxfile.py @@ -0,0 +1,54 @@ +import nox + +nox.options.reuse_existing_virtualenvs = True + +SRC = "." + + +def format_with_args(session: nox.Session, *args): + session.run("autoflake", *args) + session.run("isort", *args) + session.run("black", *args) + + +@nox.session +def lint(session: nox.Session): + """Runs linters and fixers""" + try: + session.run("poetry", "install", external=True) + session.run("poetry", "check", "--lock", external=True) + session.run("pyright", SRC) + session.run("flake8", SRC) + format_with_args(session, SRC, "--check") + except Exception: + session.error( + "linting has failed. Run 'make format' to fix formatting and fix other errors manually" + ) + + +@nox.session +def format(session: nox.Session): + """Runs linters and fixers""" + session.run("poetry", "install", external=True) + format_with_args(session, SRC) + + +def run_tests(session: nox.Session, default_dir: str): + session.run("poetry", "install", external=True) + + if session.posargs: + test_files = session.posargs + else: + test_files = [default_dir] + + session.run("pytest", *test_files) + + +@nox.session +def test(session: nox.Session): + run_tests(session, "tests/unit_tests/") + + +@nox.session +def integration_tests(session: nox.Session): + run_tests(session, "tests/integration_tests/") diff --git a/poetry.lock b/poetry.lock new file mode 100644 index 0000000..bc9733f --- /dev/null +++ b/poetry.lock @@ -0,0 +1,4645 @@ +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. + +[[package]] +name = "ai21" +version = "1.2.2" +description = "" +optional = false 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+documentation = "https://epam-rail.com/dial_api" +license = "Apache-2.0" +readme = "README.md" +keywords = ["ai"] +classifiers = [ + "Topic :: Software Development :: Libraries :: Python Modules" +] +repository = "https://gitlab.deltixhub.com/Deltix/openai-apps/bedrock-to-openai-adapter.git" + +[tool.poetry.scripts] +clean = "scripts.clean:main" + +[tool.poetry.dependencies] +python = "^3.11,<4.0" +boto3 = "1.28.57" +botocore = "1.31.57" +aidial-sdk = "0.1.0" +anthropic = "0.2.10" +colorama = "0.4.4" +fastapi = "0.103.1" +flask = "2.3.2" +openai = "0.27.8" +tiktoken = "0.4.0" +uvicorn = "0.23.2" +pydantic = "1.10.12" + +[tool.poetry.group.test.dependencies] +inquirer = "3.1.3" +locust-plugins = "3.3.1" +locust = "2.15.1" +prompt-toolkit = "3.0.38" +pytest-asyncio = "0.21.1" +pytest = "7.4.0" +python-dotenv = "1.0.0" +ai21 = {version = "1.2.2", extras = ["aws"]} +pytest-dotenv = "^0.5.2" + +[tool.poetry.group.lint.dependencies] +pyright = "1.1.324" +black = "23.3.0" +isort = "5.12.0" 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+ print("Removed: " + directory_path) + + +def remove_recursively(pattern: str, exclude_dirs: List[str] = []): + files = glob.glob(f"**/{pattern}", recursive=True) + + def is_excluded(file: str) -> bool: + return any(dir in file for dir in exclude_dirs) + + for file in files: + if not is_excluded(file): + remove_dir(file) + + +def main(): + remove_dir(".nox") + remove_dir("dist") + remove_recursively("__pycache__", exclude_dirs=[".venv"]) + remove_recursively(".pytest_cache", exclude_dirs=[".venv"]) + + +if __name__ == "__main__": + main() diff --git a/scripts/docker_entrypoint.sh b/scripts/docker_entrypoint.sh new file mode 100644 index 0000000..cad63cf --- /dev/null +++ b/scripts/docker_entrypoint.sh @@ -0,0 +1,5 @@ +#!/bin/sh + +set -e +. ./.venv/bin/activate +exec "$@" \ No newline at end of file diff --git a/scripts/find_token_limits.py b/scripts/find_token_limits.py new file mode 100755 index 0000000..3cade58 --- /dev/null +++ b/scripts/find_token_limits.py @@ -0,0 +1,58 @@ +import asyncio + +from aidial_sdk.chat_completion import Message, Role + +from aidial_adapter_bedrock.llm.bedrock_adapter import BedrockAdapter +from aidial_adapter_bedrock.llm.bedrock_models import BedrockDeployment +from aidial_adapter_bedrock.llm.chat_emulation.types import ChatEmulationType +from aidial_adapter_bedrock.universal_api.request import ModelParameters +from aidial_adapter_bedrock.utils.env import get_env +from aidial_adapter_bedrock.utils.printing import print_error, print_info +from client.utils.cli import select_enum +from client.utils.init import init + + +async def main(): + init() + + model_id = select_enum("Select model", BedrockDeployment) + + model = await BedrockAdapter.create( + model_id=model_id, + model_params=ModelParameters(max_tokens=1), + region=get_env("DEFAULT_REGION"), + ) + + base = "a " + + min_x = 1 + max_x = 100 * 1000 + x = 1 + + while True: + prompt: str = x * base + print(f"{min_x} <= {x} <= {max_x}") + + try: + response = await model.achat( + ChatEmulationType.ZERO_MEMORY, + [Message(role=Role.USER, content=prompt)], + ) + + print_info(f"{x}: " + response.usage.json(indent=2)) + min_x = x + next_x = (x + max_x) // 2 + + except Exception as e: + print_error(f"{x}: {str(e)}") + max_x = x + next_x = (min_x + x) // 2 + + if next_x == x: + break + else: + x = next_x + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/conftest.py b/tests/conftest.py new file mode 100644 index 0000000..e96ed59 --- /dev/null +++ b/tests/conftest.py @@ -0,0 +1,15 @@ +import os + +import pytest + +from tests.utils.server import server_generator + +DEFAULT_API_VERSION = "2023-03-15-preview" +TEST_SERVER_URL = os.getenv("TEST_SERVER_URL", "http://0.0.0.0:5001") + + +@pytest.fixture(scope="module") +def server(): + yield from server_generator( + "aidial_adapter_bedrock.app:app", TEST_SERVER_URL + ) diff --git a/tests/integration_tests/__init__.py b/tests/integration_tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/integration_tests/test_chat_completion.py b/tests/integration_tests/test_chat_completion.py new file mode 100644 index 0000000..24e04c8 --- /dev/null +++ b/tests/integration_tests/test_chat_completion.py @@ -0,0 +1,137 @@ +import re +from dataclasses import dataclass +from typing import Callable, List + +import openai +import openai.error +import pytest +from langchain.schema import BaseMessage + +from aidial_adapter_bedrock.llm.bedrock_models import BedrockDeployment +from tests.conftest import TEST_SERVER_URL +from tests.utils.llm import ( + create_model, + run_model, + sanitize_test_name, + sys, + user, +) + + +@dataclass +class TestCase: + __test__ = False + + name: str + deployment: BedrockDeployment + streaming: bool + + messages: List[BaseMessage] + test: Callable[[str], bool] | Exception + + def get_id(self): + return sanitize_test_name( + f"{self.deployment.value} {self.streaming} {self.name}" + ) + + +chat_deployments = [ + BedrockDeployment.AMAZON_TITAN_TG1_LARGE, + BedrockDeployment.AI21_J2_GRANDE_INSTRUCT, + BedrockDeployment.AI21_J2_JUMBO_INSTRUCT, + BedrockDeployment.AI21_J2_MID, + BedrockDeployment.AI21_J2_ULTRA, + BedrockDeployment.ANTHROPIC_CLAUDE_INSTANT_V1, + BedrockDeployment.ANTHROPIC_CLAUDE_V1, + BedrockDeployment.ANTHROPIC_CLAUDE_V2, +] + + +def get_test_cases( + deployment: BedrockDeployment, streaming: bool +) -> List[TestCase]: + ret: List[TestCase] = [] + + ret.append( + TestCase( + name="2+3=5", + deployment=deployment, + streaming=streaming, + messages=[user("2+3=?")], + test=lambda s: "5" in s, + ) + ) + + ret.append( + TestCase( + name="empty system message", + deployment=deployment, + streaming=streaming, + messages=[sys(""), user("2+4=?")], + test=lambda s: "6" in s, + ) + ) + + query = 'Reply with "Hello"' + if deployment == BedrockDeployment.ANTHROPIC_CLAUDE_INSTANT_V1: + query = 'Print "Hello"' + + ret.append( + TestCase( + name="hello", + deployment=deployment, + streaming=streaming, + messages=[user(query)], + test=lambda s: "hello" in s.lower(), + ) + ) + + ret.append( + TestCase( + name="empty dialog", + deployment=deployment, + streaming=streaming, + messages=[], + test=Exception("List of messages must not be empty"), + ) + ) + + ret.append( + TestCase( + name="empty user message", + deployment=deployment, + streaming=streaming, + messages=[user("")], + test=lambda s: True, + ) + ) + + return ret + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "test", + [ + test + for deployment in chat_deployments + for streaming in [False, True] + for test in get_test_cases(deployment, streaming) + ], + ids=lambda test: test.get_id(), +) +async def test_chat_completion_langchain(server, test: TestCase): + model = create_model(TEST_SERVER_URL, test.deployment.value, test.streaming) + + if isinstance(test.test, Exception): + with pytest.raises(Exception) as exc_info: + await run_model(model, test.messages, test.streaming) + + assert isinstance(exc_info.value, openai.error.OpenAIError) + assert exc_info.value.http_status == 422 + assert re.search(str(test.test), str(exc_info.value)) + else: + actual_output = await run_model(model, test.messages, test.streaming) + assert test.test( + actual_output + ), f"Failed output test, actual output: {actual_output}" diff --git a/tests/integration_tests/test_models.py b/tests/integration_tests/test_models.py new file mode 100644 index 0000000..e8e46bb --- /dev/null +++ b/tests/integration_tests/test_models.py @@ -0,0 +1,40 @@ +from typing import Any + +import openai +import openai.error +import requests + +from aidial_adapter_bedrock.llm.bedrock_models import BedrockDeployment +from tests.conftest import DEFAULT_API_VERSION, TEST_SERVER_URL + + +def models_request_http() -> Any: + response = requests.get(f"{TEST_SERVER_URL}/openai/models") + assert response.status_code == 200 + return response.json() + + +def models_request_openai() -> Any: + return openai.Model.list( + api_type="azure", + api_base=TEST_SERVER_URL, + api_version=DEFAULT_API_VERSION, + api_key="dummy_key", + ) + + +def assert_models_subset(models: Any): + actual_models = [model["id"] for model in models["data"]] + expected_models = [option.value for option in BedrockDeployment] + + assert set(expected_models).issubset( + set(actual_models) + ), f"Expected models: {expected_models}, Actual models: {actual_models}" + + +def test_model_list_http(server): + assert_models_subset(models_request_http()) + + +def test_model_list_openai(server): + assert_models_subset(models_request_openai()) diff --git a/tests/locust/__init__.py b/tests/locust/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/locust/app.py b/tests/locust/app.py new file mode 100644 index 0000000..47dee35 --- /dev/null +++ b/tests/locust/app.py @@ -0,0 +1,17 @@ +import locust_plugins # Needed to enable the locust plugins +from locust import HttpUser, between, task + + +class ChatUser(HttpUser): + wait_time = between(1, 1.01) + + headers = {"Content-Type": "application/json"} + + @task + def send_chat(self): + url = "/openai/deployments/anthropic.claude-v1/chat/completions?api-version=2023-03-15-preview" + data = { + "messages": [{"role": "user", "content": "Compute 12+18"}], + "model": "gpt-3.5-turbo", + } + self.client.post(url, headers=self.headers, json=data) diff --git a/tests/locust/run.sh b/tests/locust/run.sh new file mode 100755 index 0000000..b340859 --- /dev/null +++ b/tests/locust/run.sh @@ -0,0 +1,5 @@ +N=50 +locust -f test/locust/locust.py \ + --headless -u ${N} -r ${N} -i ${N} \ + --host=http://0.0.0.0:8080 \ + --html=test/~report.html \ No newline at end of file diff --git a/tests/unit_tests/__init__.py b/tests/unit_tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/unit_tests/conftest.py b/tests/unit_tests/conftest.py new file mode 100644 index 0000000..2503524 --- /dev/null +++ b/tests/unit_tests/conftest.py @@ -0,0 +1,8 @@ +import os + + +def pytest_configure(config): + """ + Setting up fake environment variables for unit tests. + """ + os.environ["DEFAULT_REGION"] = "dummy_region" diff --git a/tests/unit_tests/test_app.py b/tests/unit_tests/test_app.py new file mode 100644 index 0000000..71deef0 --- /dev/null +++ b/tests/unit_tests/test_app.py @@ -0,0 +1,10 @@ +from typing import Any + +import requests + +from tests.conftest import TEST_SERVER_URL + + +def test_availability(server) -> Any: + response = requests.get(f"{TEST_SERVER_URL}/healthcheck") + assert response.status_code == 200 diff --git a/tests/utils/callback.py b/tests/utils/callback.py new file mode 100644 index 0000000..f365127 --- /dev/null +++ b/tests/utils/callback.py @@ -0,0 +1,38 @@ +from typing import Any + +from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler +from langchain.schema import LLMResult +from typing_extensions import override + +from aidial_adapter_bedrock.utils.printing import print_ai + + +class CallbackWithNewLines(StreamingStdOutCallbackHandler): + prev: str + + def __init__(self) -> None: + super().__init__() + self.prev = "" + + @override + def on_llm_new_token(self, token: str, **kwargs: Any) -> None: + # Replaces \\n with \n + # Replaces \\" with " + + if len(token) == 0: + return + + token = self.prev + token + self.prev = "" + + # The escaped symbol may be split between two consecutive tokens + if token[-1] == "\\": + self.prev = token[-1] + token = token[:-1] + + s = token.replace("\\n", "\n").replace('\\"', '"') + print_ai(s, end="") + + @override + def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None: + print_ai("") diff --git a/tests/utils/llm.py b/tests/utils/llm.py new file mode 100644 index 0000000..a833262 --- /dev/null +++ b/tests/utils/llm.py @@ -0,0 +1,64 @@ +import re +from typing import List + +from langchain.callbacks.base import Callbacks +from langchain.chat_models import AzureChatOpenAI +from langchain.chat_models.base import BaseChatModel +from langchain.schema import AIMessage, BaseMessage, HumanMessage, SystemMessage + +from tests.conftest import DEFAULT_API_VERSION +from tests.utils.callback import CallbackWithNewLines + + +def sys(content: str) -> SystemMessage: + return SystemMessage(content=content) + + +def ai(content: str) -> AIMessage: + return AIMessage(content=content) + + +def user(content: str) -> HumanMessage: + return HumanMessage(content=content) + + +def sanitize_test_name(name: str) -> str: + name2 = "".join(c if c.isalnum() else "_" for c in name.lower()) + return re.sub("_+", "_", name2) + + +async def run_model( + model: BaseChatModel, messages: List[BaseMessage], streaming: bool +) -> str: + llm_result = await model.agenerate([messages]) + + actual_usage = ( + llm_result.llm_output.get("token_usage", None) + if llm_result.llm_output + else None + ) + + # Usage is missing when and only where streaming is enabled + assert (actual_usage in [None, {}]) == streaming + + return llm_result.generations[0][-1].text + + +def create_model( + base_url: str, model_id: str, streaming: bool +) -> BaseChatModel: + callbacks: Callbacks = [CallbackWithNewLines()] + return AzureChatOpenAI( + deployment_name=model_id, + callbacks=callbacks, + openai_api_base=base_url, + openai_api_version=DEFAULT_API_VERSION, + openai_api_key="dummy_openai_api_key", + model_kwargs={"deployment_id": model_id, "api_key": "dummy_api_key"}, + verbose=True, + streaming=streaming, + temperature=0.0, + request_timeout=10, + client=None, + max_retries=0, + ) diff --git a/tests/utils/server.py b/tests/utils/server.py new file mode 100644 index 0000000..c503c52 --- /dev/null +++ b/tests/utils/server.py @@ -0,0 +1,57 @@ +import time +from multiprocessing import Process +from urllib.parse import urlparse + +import requests +import uvicorn + + +def ping_server(url: str) -> bool: + try: + requests.get(url, timeout=1) + return True + except requests.ConnectionError: + return False + + +def wait_for_server(url: str, timeout=10) -> None: + start_time = time.time() + + while True: + if ping_server(url): + return + + if time.time() - start_time > timeout: + raise Exception("The test server didn't start in time!") + + time.sleep(0.1) + + +def terminate_process(process: Process): + process.terminate() + process.join() + + +def server_generator(module: str, url: str): + already_exists = ping_server(url) + + server_process: Process | None = None + if not already_exists: + parsed_url = urlparse(url) + server_process = Process( + target=uvicorn.run, + args=(module,), + kwargs={"host": parsed_url.hostname, "port": parsed_url.port}, + ) + server_process.start() + + try: + wait_for_server(url) + except Exception as e: + terminate_process(server_process) + raise Exception("Can't start the test server") from e + + yield + + if server_process is not None: + terminate_process(server_process)