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+dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.14,<0.19)", "urllib3 (<2.0.0)"] +dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm", "tokenizers (>=0.14,<0.19)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] +docs = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "hf-doc-builder", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm", "tokenizers (>=0.14,<0.19)", "torch", "torchaudio", "torchvision"] docs-specific = ["hf-doc-builder"] flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)"] flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] @@ -9402,16 +9429,16 @@ serving = ["fastapi", "pydantic", "starlette", "uvicorn"] sigopt = ["sigopt"] sklearn = ["scikit-learn"] speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] -testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] +testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.1.5)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "tensorboard", "timeout-decorator"] tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"] tf-cpu = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>=2.6,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"] tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] timm = ["timm"] -tokenizers = ["tokenizers (>=0.19,<0.20)"] +tokenizers = ["tokenizers (>=0.14,<0.19)"] torch = ["accelerate (>=0.21.0)", "torch"] torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"] -torchhub = ["filelock", "huggingface-hub (>=0.19.3,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"] +torchhub = ["filelock", "huggingface-hub (>=0.19.3,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.14,<0.19)", "torch", "tqdm (>=4.27)"] video = ["av (==9.2.0)", "decord (==0.6.0)"] vision = ["Pillow (>=10.0.1,<=15.0)"] @@ -10721,4 +10748,4 @@ local = ["ctransformers", "llama-cpp-python", "sentence-transformers"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.12" -content-hash = "3355376a653b6ca7884c09be576958a121ab965927e5e22f20a98ea387497f03" +content-hash = "d3ac1c13a79e0c368642bacb2907061361b7865b5136fdc969f5f5a28c7d2322" diff --git a/pyproject.toml b/pyproject.toml index ef058b219..dbfcee43b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -85,6 +85,8 @@ zep-python = { version = "^2.0.0rc5", allow-prereleases = true } langchain-google-vertexai = "^1.0.3" langchain-groq = "^0.1.3" langchain-pinecone = "^0.1.0" +langchain-mistralai ="^0.1.6" + [tool.poetry.group.dev.dependencies] types-redis = "^4.6.0.5" diff --git a/src/backend/base/langflow/components/embeddings/MistalAIEmbeddings.py b/src/backend/base/langflow/components/embeddings/MistalAIEmbeddings.py new file mode 100644 index 000000000..4088d4839 --- /dev/null +++ b/src/backend/base/langflow/components/embeddings/MistalAIEmbeddings.py @@ -0,0 +1,69 @@ +from typing import List, Optional +from pydantic.v1 import SecretStr + +from langchain_mistralai.embeddings import MistralAIEmbeddings +from langflow.interface.custom.custom_component import CustomComponent +from langflow.field_typing import Embeddings, NestedDict + +class MistralAIEmbeddingsComponent(CustomComponent): + display_name = "MistralAI Embeddings" + description = "Generate embeddings using MistralAI models." + + def build_config(self): + return { + "model": { + "display_name": "Model", + "advanced": False, + "options": ["mistral-embed"], + "value": "mistral-embed", + }, + "mistral_api_key": { + "display_name": "Mistral API Key", + "password": True, + "advanced": False, + }, + "max_concurrent_requests": { + "display_name": "Max Concurrent Requests", + "advanced": True, + "value": 64, + }, + "max_retries": { + "display_name": "Max Retries", + "advanced": True, + "value": 5, + }, + "timeout": { + "display_name": "Request Timeout", + "advanced": True, + "value": 120, + }, + "endpoint": { + "display_name": "API Endpoint", + "advanced": True, + "value": "https://api.mistral.ai/v1/" + } + } + + def build( + self, + mistral_api_key: str, + model: str = "mistral-embed", + max_concurrent_requests: int = 64, + max_retries: int = 5, + timeout: int = 120, + endpoint: str = "https://api.mistral.ai/v1/" + ) -> Embeddings: + if mistral_api_key: + api_key = SecretStr(mistral_api_key) + else: + api_key = None + + return MistralAIEmbeddings( + api_key=api_key, + model=model, + endpoint=endpoint, + max_concurrent_requests=max_concurrent_requests, + max_retries=max_retries, + timeout=timeout + ) + diff --git a/src/backend/base/langflow/components/model_specs/ChatMistralSpecs.py b/src/backend/base/langflow/components/model_specs/ChatMistralSpecs.py new file mode 100644 index 000000000..2bfab4f6a --- /dev/null +++ b/src/backend/base/langflow/components/model_specs/ChatMistralSpecs.py @@ -0,0 +1,87 @@ +from typing import Optional + +from langchain_mistralai import ChatMistralAI +from pydantic.v1 import SecretStr + +from langflow.custom import CustomComponent +from langflow.field_typing import BaseLanguageModel + + +class MistralAIModelComponent(CustomComponent): + display_name: str = "MistralAI" + description: str = "Generate text using MistralAI LLMs." + icon = "MistralAI" + + field_order = [ + "model", + "mistral_api_key", + "max_tokens", + "temperature", + "mistral_api_base", + ] + + def build_config(self): + return { + "model": { + "display_name": "Model Name", + "options": [ + "open-mistral-7b", + "open-mixtral-8x7b", + "open-mixtral-8x22b", + "mistral-small-latest", + "mistral-medium-latest", + "mistral-large-latest" + ], + "info": "Name of the model to use.", + "required": True, + "value": "open-mistral-7b", + }, + "mistral_api_key": { + "display_name": "Mistral API Key", + "required": True, + "password": True, + "info": "Your Mistral API key.", + }, + "max_tokens": { + "display_name": "Max Tokens", + "field_type": "int", + "advanced": True, + "value": 256, + }, + "temperature": { + "display_name": "Temperature", + "field_type": "float", + "value": 0.1, + }, + "mistral_api_base": { + "display_name": "Mistral API Base", + "advanced": True, + "info": "Endpoint of the Mistral API. Defaults to 'https://api.mistral.ai' if not specified.", + }, + "code": {"show": False}, + } + + def build( + self, + model: str, + mistral_api_key: Optional[str] = None, + max_tokens: Optional[int] = None, + temperature: Optional[float] = None, + mistral_api_base: Optional[str] = None, + ) -> BaseLanguageModel: + # Set default API endpoint if not provided + if not mistral_api_base: + mistral_api_base = "https://api.mistral.ai" + + try: + output = ChatMistralAI( + model=model, + api_key=(SecretStr(mistral_api_key) if mistral_api_key else None), + max_tokens=max_tokens, + temperature=temperature, + base_url=mistral_api_base, + ) + except Exception as e: + raise ValueError("Could not connect to Mistral API.") from e + + return output diff --git a/src/backend/base/langflow/components/models/MistralModel.py b/src/backend/base/langflow/components/models/MistralModel.py new file mode 100644 index 000000000..d6e3a27f0 --- /dev/null +++ b/src/backend/base/langflow/components/models/MistralModel.py @@ -0,0 +1,111 @@ +from typing import Optional + +from langchain_mistralai import ChatMistralAI +from pydantic.v1 import SecretStr + +from langflow.base.constants import STREAM_INFO_TEXT +from langflow.base.models.model import LCModelComponent +from langflow.field_typing import NestedDict, Text + + +class MistralAIModelComponent(LCModelComponent): + display_name = "MistralAI" + description = "Generates text using MistralAI LLMs." + icon = "MistralAI" + + field_order = [ + "max_tokens", + "model_kwargs", + "model_name", + "mistral_api_base", + "mistral_api_key", + "temperature", + "input_value", + "system_message", + "stream", + ] + + def build_config(self): + return { + "input_value": {"display_name": "Input"}, + "max_tokens": { + "display_name": "Max Tokens", + "advanced": True, + }, + "model_kwargs": { + "display_name": "Model Kwargs", + "advanced": True, + }, + "model_name": { + "display_name": "Model Name", + "advanced": False, + "options": [ + "open-mistral-7b", + "open-mixtral-8x7b", + "open-mixtral-8x22b", + "mistral-small-latest", + "mistral-medium-latest", + "mistral-large-latest" + ], + "value": "open-mistral-7b", + }, + "mistral_api_base": { + "display_name": "Mistral API Base", + "advanced": True, + "info": ( + "The base URL of the Mistral API. Defaults to https://api.mistral.ai.\n\n" + "You can change this to use other APIs like JinaChat, LocalAI and Prem." + ), + }, + "mistral_api_key": { + "display_name": "Mistral API Key", + "info": "The Mistral API Key to use for the Mistral model.", + "advanced": False, + "password": True, + }, + "temperature": { + "display_name": "Temperature", + "advanced": False, + "value": 0.1, + }, + "stream": { + "display_name": "Stream", + "info": STREAM_INFO_TEXT, + "advanced": True, + }, + "system_message": { + "display_name": "System Message", + "info": "System message to pass to the model.", + "advanced": True, + }, + } + + def build( + self, + input_value: Text, + mistral_api_key: str, + temperature: float, + model_name: str, + max_tokens: Optional[int] = 256, + model_kwargs: NestedDict = {}, + mistral_api_base: Optional[str] = None, + stream: bool = False, + system_message: Optional[str] = None, + ) -> Text: + if not mistral_api_base: + mistral_api_base = "https://api.mistral.ai" + if mistral_api_key: + api_key = SecretStr(mistral_api_key) + else: + api_key = None + + chat_model = ChatMistralAI( + max_tokens=max_tokens, + model_kwargs=model_kwargs, + model=model_name, + base_url=mistral_api_base, + api_key=api_key, + temperature=temperature, + ) + + return self.get_chat_result(chat_model, stream, input_value, system_message)