From 93f766f40dcb1369ef26ba35103288e8ea95f6f0 Mon Sep 17 00:00:00 2001 From: LUIS NOVO Date: Tue, 22 Oct 2024 16:41:20 -0300 Subject: [PATCH] add support for vertex, anthropic, litellm, ollama and open router --- .env.example | 17 +- open_notebook/language_models.py | 243 +++++++++ open_notebook/model_configs.py | 78 +++ poetry.lock | 852 ++++++++++++++++++++++++++++++- pyproject.toml | 4 + 5 files changed, 1191 insertions(+), 3 deletions(-) create mode 100644 open_notebook/language_models.py create mode 100644 open_notebook/model_configs.py diff --git a/.env.example b/.env.example index 8557f70..3f60403 100644 --- a/.env.example +++ b/.env.example @@ -1,5 +1,6 @@ # YOUR LLM API KEYS -OPENAI_API_KEY=API_KEY +OPENAI_API_KEY= +ANTHROPIC_API_KEY= # MODEL_CONFIGURATIONS # Only OpenAI models are supported for now @@ -7,6 +8,19 @@ DEFAULT_MODEL="gpt-4o-mini" # This is the default model used for all the feature SUMMARIZATION_MODEL="gpt-4o-mini" # This is the model used for summarization, defaults to the DEFAULT_MODEL if empty RETRIEVAL_MODEL="gpt-4o-mini" # This is the model used for retrieval, defaults to the DEFAULT_MODEL if empty +# OLLAMA +OLLAMA_API_BASE="http://10.20.30.20:11434" + +# OPEN ROUTER +OPENROUTER_BASE_URL="https://openrouter.ai/api/v1" +OPENROUTER_API_KEY= + +# USE THIS IF YOU WANT TO DEBUG THE APP ON LANGSMITH +# LANGCHAIN_TRACING_V2=true +# LANGCHAIN_ENDPOINT="https://api.smith.langchain.com" +# LANGCHAIN_API_KEY= +# LANGCHAIN_PROJECT="Open Notebook" + # CONNECTION DETAILS FOR YOUR SURREAL DB SURREAL_ADDRESS="ws://localhost:8000/rpc" @@ -24,4 +38,3 @@ SUMMARY_CHUNK_OVERLAP=1000 # It is measured in characters, not tokens. EMBEDDING_CHUNK_SIZE=1000 EMBEDDING_CHUNK_OVERLAP=50 - diff --git a/open_notebook/language_models.py b/open_notebook/language_models.py new file mode 100644 index 0000000..1f82ac7 --- /dev/null +++ b/open_notebook/language_models.py @@ -0,0 +1,243 @@ +""" +Classes for supporting different language and vector models +""" + +import os +from abc import ABC, abstractmethod +from dataclasses import dataclass, field +from typing import Any, Dict, Optional + +from langchain_anthropic import ChatAnthropic +from langchain_community.chat_models import ChatLiteLLM +from langchain_core.language_models.chat_models import BaseChatModel +from langchain_google_vertexai import ChatVertexAI +from langchain_google_vertexai.model_garden import ChatAnthropicVertex +from langchain_ollama.chat_models import ChatOllama +from langchain_openai.chat_models import ChatOpenAI + +# from redisvl.utils.vectorize import BaseVectorizer +# from redisvl.utils.vectorize.text.openai import OpenAITextVectorizer + + +@dataclass +class LanguageModel(ABC): + """ + Abstract base class for language models. + """ + + model_name: Optional[str] = None + max_tokens: Optional[int] = 850 + temperature: Optional[float] = 1.0 + streaming: bool = True + top_p: Optional[float] = 0.9 + kwargs: Dict[str, Any] = field(default_factory=dict) + json: bool = False + + @abstractmethod + def to_langchain(self) -> BaseChatModel: + """ + Convert the language model to a LangChain chat model. + """ + raise NotImplementedError + + +@dataclass +class OllamaLanguageModel(LanguageModel): + """ + Language model that uses the Ollama chat model. + """ + + model_name: str + base_url: str = os.environ.get("OLLAMA_API_BASE", "http://localhost:11434") + max_tokens: Optional[int] = 650 + json: bool = False + + def to_langchain(self) -> ChatOllama: + """ + Convert the language model to a LangChain chat model. + """ + return ChatOllama( + # api_key="ollama", + model=self.model_name, + base_url=self.base_url, + # keep_alive="10m", + num_predict=self.max_tokens, + temperature=self.temperature, + verbose=True, + top_p=self.top_p, + ) + + +@dataclass +class VertexAnthropicLanguageModel(LanguageModel): + """ + Language model that uses the Vertex Anthropic chat model. + """ + + model_name: str + project: Optional[str] = os.environ.get("VERTEX_PROJECT", "no-project") + location: Optional[str] = os.environ.get("VERTEX_LOCATION", "us-central1") + + def to_langchain(self) -> ChatAnthropicVertex: + """ + Convert the language model to a LangChain chat model. + """ + return ChatAnthropicVertex( + model=self.model_name, + project=self.project, + location=self.location, + max_tokens=self.max_tokens, + streaming=False, + kwargs=self.kwargs, + top_p=self.top_p, + ) + + +@dataclass +class LiteLLMLanguageModel(LanguageModel): + """ + Language model that uses the LiteLLM chat model. + """ + + model_name: str + + def to_langchain(self) -> ChatLiteLLM: + """ + Convert the language model to a LangChain chat model. + """ + return ChatLiteLLM( + model=self.model_name, + temperature=self.temperature or 0.5, + max_tokens=self.max_tokens, + streaming=self.streaming, + top_p=self.top_p, + ) + + +@dataclass +class VertexAILanguageModel(LanguageModel): + """ + Language model that uses the Vertex AI chat model. + """ + + model_name: str + project: Optional[str] = os.environ.get("VERTEX_PROJECT", "no-project") + location: Optional[str] = os.environ.get("VERTEX_LOCATION", "us-central1") + + def to_langchain(self) -> ChatVertexAI: + """ + Convert the language model to a LangChain chat model. + """ + return ChatVertexAI( + model=self.model_name, + streaming=self.streaming, + max_tokens=self.max_tokens, + top_p=self.top_p, + location=self.location, + project=self.project, + safety_settings=None, + api_key="AIzaSyCt4zB5eZVZPh7WRxIh9oY_rwblP6BOyWE", + ) + + +@dataclass +class OpenRouterLanguageModel(LanguageModel): + """ + Language model that uses the OpenAI chat model. + """ + + model_name: str + + def to_langchain(self) -> ChatOpenAI: + """ + Convert the language model to a LangChain chat model. + """ + kwargs = self.kwargs + if self.json: + kwargs["response_format"] = {"type": "json_object"} + + return ChatOpenAI( + model=self.model_name, + temperature=self.temperature or 0.5, + base_url=os.environ.get( + "OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1" + ), + max_tokens=self.max_tokens, + model_kwargs=kwargs, + streaming=self.streaming, + api_key=os.environ.get("OPENROUTER_API_KEY", "openrouter"), + top_p=self.top_p, + ) + + +@dataclass +class AnthropicLanguageModel(LanguageModel): + """ + Language model that uses the Anthropic chat model. + """ + + model_name: str + + def to_langchain(self) -> ChatAnthropic: + """ + Convert the language model to a LangChain chat model. + """ + return ChatAnthropic( # type: ignore[call-arg] + model_name=self.model_name, + max_tokens_to_sample=self.max_tokens or 850, + model_kwargs=self.kwargs, + streaming=False, + timeout=30, + top_p=self.top_p, + ) + + +@dataclass +class OpenAILanguageModel(LanguageModel): + """ + Language model that uses the OpenAI chat model. + """ + + model_name: str + + def to_langchain(self) -> ChatOpenAI: + """ + Convert the language model to a LangChain chat model. + """ + kwargs = self.kwargs + if self.json: + kwargs["response_format"] = {"type": "json_object"} + + return ChatOpenAI( + model=self.model_name, + temperature=self.temperature or 0.5, + max_tokens=self.max_tokens, + model_kwargs=kwargs, + streaming=self.streaming, + top_p=self.top_p, + ) + + +# @dataclass +# class EmbeddingModel(ABC): +# model_name: str +# dimensions: int + +# def to_redis_vectorizer(self) -> BaseVectorizer: +# raise NotImplementedError + + +# @dataclass +# class OpenAIEmbeddingModel(EmbeddingModel): +# """ +# Embedding model that uses the OpenAI text embedding model. +# """ + +# model_name: str +# dimensions: int + +# def to_redis_vectorizer(self) -> OpenAITextVectorizer: +# """ +# Convert the embedding model to a Redis vectorizer. +# """ +# return OpenAITextVectorizer(model=self.model_name) diff --git a/open_notebook/model_configs.py b/open_notebook/model_configs.py new file mode 100644 index 0000000..ce9fdd1 --- /dev/null +++ b/open_notebook/model_configs.py @@ -0,0 +1,78 @@ +from open_notebook.language_models import ( + AnthropicLanguageModel, + LiteLLMLanguageModel, + OllamaLanguageModel, + OpenAILanguageModel, + OpenRouterLanguageModel, + VertexAILanguageModel, + VertexAnthropicLanguageModel, +) + +LANGUAGE_MODEL_CONFIG = { + "OLLAMA": { + "class": OllamaLanguageModel, + "models": [ + "mistral-nemo:latest", + "llama3.1:8b", + "qwen2.5:32b", + "nemotron-mini:latest", + "phi3.5:latest", + "gemma2", + "bling-phi-3.gguf", + "granite3-dense:8b", + "granite3-moe:latest", + "hermes3", + "llama3.2", + "phi3.5:3.8b-mini-instruct-fp16", + "phi3:14b", + "wizardlm2", + "zephyr", + "solar-pro", + ], + }, + "OPEN_ROUTER": { + "class": OpenRouterLanguageModel, + "models": [ + "nvidia/llama-3.1-nemotron-70b-instruct", + "anthropic/claude-3.5-sonnet", + "google/gemini-flash-1.5", + ], + }, + "VERTEX_ANTHROPIC": { + "class": VertexAnthropicLanguageModel, + "models": ["claude-3-5-sonnet@20240620"], + }, + "LITELLM": { + "class": LiteLLMLanguageModel, + "models": ["ollama/mistral-nemo:latest", "ollama/llama3.1:8b"], + }, + "VERTEX_AI": { + "class": VertexAILanguageModel, + "models": ["gemini-1.5-flash-001", "gemini-1.5-pro-001"], + }, + "ANTHROPIC": { + "class": AnthropicLanguageModel, + "models": ["claude-3-5-sonnet-20240620"], + }, + "OPEN_AI": {"class": OpenAILanguageModel, "models": ["gpt-4o-mini", "gpt-4o"]}, +} + +# EMBEDDING_MODEL_CONFIG = { +# "OPEN_AI": { +# "class": OpenAIEmbeddingModel, +# "models": ["text-embedding-3-large"], +# "dimensions": [3072], +# }, +# } + + +def get_model_class(model_name): + for config in LANGUAGE_MODEL_CONFIG.values(): + if model_name in config["models"]: + return config["class"] + raise ValueError(f"Model {model_name} not found in config") + + +def get_langchain_model(model_name, json=False): + model_class = get_model_class(model_name=model_name) + return model_class(model_name=model_name, json=json).to_langchain() diff --git a/poetry.lock b/poetry.lock index ea38ca9..28940ac 100644 --- a/poetry.lock +++ b/poetry.lock @@ -188,6 +188,31 @@ files = [ {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, ] +[[package]] +name = "anthropic" +version = "0.37.0" +description = "The official Python library for the anthropic API" +optional = false +python-versions = ">=3.7" +files = [ + {file = "anthropic-0.37.0-py3-none-any.whl", hash = "sha256:3f57b9fdbc1aa43e00468d0690d71e5fde668dc489e5a48d1d20c955e8ce18f3"}, + {file = "anthropic-0.37.0.tar.gz", hash = "sha256:fa01f2cc947cfe05c7f3fbbc939efb37add77e598ce91818e46aa1a240cb7ada"}, +] + +[package.dependencies] +anyio = ">=3.5.0,<5" +distro = ">=1.7.0,<2" +httpx = ">=0.23.0,<1" +jiter = ">=0.4.0,<1" +pydantic = ">=1.9.0,<3" +sniffio = "*" +tokenizers = ">=0.13.0" +typing-extensions = ">=4.7,<5" + +[package.extras] +bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"] +vertex = ["google-auth (>=2,<3)"] + [[package]] name = "anyio" version = "4.6.2.post1" @@ -596,6 +621,17 @@ files = [ {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"}, ] +[[package]] +name = "defusedxml" +version = "0.7.1" +description = "XML bomb protection for Python stdlib modules" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +files = [ + {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"}, + {file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"}, +] + [[package]] name = "distlib" version = "0.3.9" @@ -618,6 +654,17 @@ files = [ {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"}, ] +[[package]] +name = "docstring-parser" +version = "0.16" +description = "Parse Python docstrings in reST, Google and Numpydoc format" +optional = false +python-versions = ">=3.6,<4.0" +files = [ + {file = "docstring_parser-0.16-py3-none-any.whl", hash = "sha256:bf0a1387354d3691d102edef7ec124f219ef639982d096e26e3b60aeffa90637"}, + {file = "docstring_parser-0.16.tar.gz", hash = "sha256:538beabd0af1e2db0146b6bd3caa526c35a34d61af9fd2887f3a8a27a739aa6e"}, +] + [[package]] name = "executing" version = "2.1.0" @@ -734,6 +781,45 @@ files = [ {file = "frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b"}, ] +[[package]] +name = "fsspec" +version = "2024.10.0" +description = "File-system specification" +optional = false +python-versions = ">=3.8" +files = [ + {file = "fsspec-2024.10.0-py3-none-any.whl", hash = "sha256:03b9a6785766a4de40368b88906366755e2819e758b83705c88cd7cb5fe81871"}, + {file = "fsspec-2024.10.0.tar.gz", hash = "sha256:eda2d8a4116d4f2429db8550f2457da57279247dd930bb12f821b58391359493"}, +] + +[package.extras] +abfs = ["adlfs"] +adl = ["adlfs"] +arrow = ["pyarrow (>=1)"] +dask = ["dask", "distributed"] +dev = ["pre-commit", "ruff"] +doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"] +dropbox = ["dropbox", "dropboxdrivefs", "requests"] +full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"] +fuse = ["fusepy"] +gcs = ["gcsfs"] +git = ["pygit2"] +github = ["requests"] +gs = ["gcsfs"] +gui = ["panel"] +hdfs = ["pyarrow (>=1)"] +http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"] +libarchive = ["libarchive-c"] +oci = ["ocifs"] +s3 = ["s3fs"] +sftp = ["paramiko"] +smb = ["smbprotocol"] +ssh = ["paramiko"] +test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"] +test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"] +test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"] +tqdm = ["tqdm"] + [[package]] name = "gitdb" version = "4.0.11" @@ -766,6 +852,267 @@ gitdb = ">=4.0.1,<5" doc = 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