diff --git a/.env-template b/.env-template index 12b97b068b..60840f347e 100644 --- a/.env-template +++ b/.env-template @@ -5,6 +5,7 @@ DATABASE_URL=postgresql+psycopg2://postgres:postgres@db:5432 # TOOLS PYTHON_INTERPRETER_URL=http://localhost:8080 TAVILY_API_KEY= +WOLFRAM_ALPHA_APP_ID= # DEPLOYMENTS # To use the Toolkit, at least one deployment must be setup, the simplest @@ -24,3 +25,6 @@ AZURE_CHAT_ENDPOINT_URL= # Experimental features USE_EXPERIMENTAL_LANGCHAIN=False + +# Community features +USE_COMMUNITY_FEATURES=True \ No newline at end of file diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index ad0fa6f271..24a93cfe5c 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -25,3 +25,8 @@ Remember that there are many ways to contribute other than writing code: writing 3. [Fork this repository](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo) 4. Make your changes on your fork and make sure all your [commits are signed](https://docs.github.com/en/authentication/managing-commit-signature-verification/about-commit-signature-verification)! 5. [Submit the fork as a Pull Request](https://help.github.com/en/github/collaborating-with-issues-and-pull-requests/creating-a-pull-request-from-a-fork) pointing to the `main` branch this repository. A maintainer should comment and/or review your Pull Request within a few days. Although depending on the circumstances, it may take longer. + + +## How to add features + +All features must be added to the `community` folder. That's where you'll find tools and deployments that are not managed by Codeowners. \ No newline at end of file diff --git a/Makefile b/Makefile index 04caf3f6bd..4a5b5b78c0 100644 --- a/Makefile +++ b/Makefile @@ -2,6 +2,8 @@ dev: @docker compose watch run-tests: docker compose run --build backend poetry run pytest src/backend/tests/$(file) +run-community-tests: + docker compose run --build backend poetry run pytest src/community/tests/$(file) attach: @docker attach cohere-toolkit-backend-1 exec-backend: diff --git a/README.md b/README.md index 33ef9d1541..eb474b91ba 100644 --- a/README.md +++ b/README.md @@ -32,7 +32,7 @@ Go to localhost:4000 in your browser and start chatting with the model. This wil Clone the repo and run ```bash -make setup +make first-run ``` Follow the instructions to configure the model - either AWS Sagemaker, Azure, or Cohere's platform. This can also be done by running `make setup` (See Option 2 below), which will help generate a file for you, or by manually creating a `.env` file and copying the contents of the provided `.env-template`. Then replacing the values with the correct ones. @@ -40,7 +40,7 @@ Follow the instructions to configure the model - either AWS Sagemaker, Azure, or
Environment variables - ### Cohere Platform +### Cohere Platform - `COHERE_API_KEY`: If your application will interface with Cohere's API, you will need to supply an API key. Not required if using AWS Sagemaker or Azure. Sign up at https://dashboard.cohere.com/ to create an API key. @@ -216,6 +216,11 @@ make migrate ### Troubleshooting +#### Community features are not accessible + +Make sure you add `USE_COMMUNITY_FEATURES=True` to your .env file. + + #### Multiple errors after running make dev for the first time Make sure you run the following command before running make dev: @@ -261,6 +266,14 @@ it will allow you to debug. ## Component Guides +### How to use community features + +By default, the toolkit runs without community tools or deployments. If you want to enable them, add the following to the .env file or use `make setup` to set this variable: + +```bash +USE_COMMUNITY_FEATURES=True +``` + ### How to add your own model deployment A model deployment is a running version of one of the Cohere command models. The Toolkit currently supports the model deployments: @@ -272,9 +285,9 @@ A model deployment is a running version of one of the Cohere command models. The - SageMaker (model_deployments/sagemaker.py) - This deployment option calls into your SageMaker deployment. To create a SageMaker endpoint [follow the steps here](https://docs.cohere.com/docs/amazon-sagemaker-setup-guide), alternatively [follow a command notebook here](https://github.com/cohere-ai/cohere-aws/tree/main/notebooks/sagemaker). Note your region and endpoint name when executing the notebook as these will be needed in the environment variables. - To add your own deployment: - 1. Create a deployment file, add it to [/model_deployments](https://github.com/cohere-ai/toolkit/tree/main/src/backend/chat/custom/model_deployments) folder, implement the function calls from `BaseDeployment` similar to the other deployments. - 2. Add the deployment to [src/backend/config/deployments.py](https://github.com/cohere-ai/toolkit/blob/main/src/backend/config/deployments.py) - 3. Add the option to [cli/main.py](https://github.com/cohere-ai/toolkit/blob/main/cli/main.py) and the environment variables required to the env template. + 1. Create a deployment file, add it to [/community/model_deployments](https://github.com/cohere-ai/toolkit/tree/main/src/community/model_deployments) folder, implement the function calls from `BaseDeployment` similar to the other deployments. + 2. Add the deployment to [src/community/config/deployments.py](https://github.com/cohere-ai/toolkit/blob/main/src/community/config/deployments.py) + 3. Add the environment variables required to the env template. - To add a Cohere private deployment, use the steps above copying the cohere platform implementation changing the base_url for your private deployment and add in custom auth steps. ### How to call the backend as an API @@ -293,11 +306,11 @@ curl --location 'http://localhost:8000/chat-stream' \ ### How to add your own chat interface -Currently the core chat interface is the Coral frontend. To add your own interface, take the steps above for call the backend as an API in your implementation and add it alongside `src/interfaces/coral_web`. +Currently the core chat interface is the Coral frontend. To add your own interface, take the steps above for call the backend as an API in your implementation and add it alongside `src/community/interfaces/`. ### How to add a connector to the Toolkit -If you have already created a [connector](https://docs.cohere.com/docs/connectors), it can be used in the toolkit with `ConnectorRetriever`. Add in your configuration and then add the definition in [config/tools.py](https://github.com/cohere-ai/toolkit/blob/main/src/backend/config/tools.py) similar to `Arxiv` implementation with the category `Category.DataLoader`. You can now use the Coral frontend and API with the connector. +If you have already created a [connector](https://docs.cohere.com/docs/connectors), it can be used in the toolkit with `ConnectorRetriever`. Add in your configuration and then add the definition in [community/config/tools.py](https://github.com/cohere-ai/toolkit/blob/main/src/community/config/tools.py) similar to `Arxiv` implementation with the category `Category.DataLoader`. You can now use the Coral frontend and API with the connector. ### How to set up web search with the Toolkit diff --git a/cli/__init__.py b/cli/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/cli/main.py b/cli/main.py index c5e13a3f3f..216837a525 100755 --- a/cli/main.py +++ b/cli/main.py @@ -3,6 +3,11 @@ import inquirer from dotenv import set_key +from community.config.deployments import ( + AVAILABLE_MODEL_DEPLOYMENTS as COMMUNITY_DEPLOYMENTS_SETUP, +) +from community.config.tools import COMMUNITY_TOOLS_SETUP + class bcolors: OKCYAN = "\033[96m" @@ -93,6 +98,17 @@ def deployment_prompt(secrets, configs): secrets[secret] = value +def community_tools_prompt(secrets): + print_styled( + "🏘️ We have some community tools that you can set up. These tools are not required for the Cohere Toolkit to run." + ) + use_community_features = inquirer.confirm( + "Do you want to set up community features (tools and deployments)?" + ) + secrets["USE_COMMUNITY_FEATURES"] = use_community_features + return use_community_features + + def tool_prompt(secrets, name, configs): print_styled( f"🛠️ If you want to enable {name}, set up the following secrets. Otherwise, press enter." @@ -146,6 +162,8 @@ def select_deployments_prompt(_): def wrap_up(deployments): + print_styled("✅ Your .env file has been set up.", bcolors.OKGREEN) + print_styled( "🎉 You're all set up! You can now run 'make migrate' and 'make dev' to start the Cohere Toolkit. Make sure Docker is running.", bcolors.OKGREEN, @@ -257,12 +275,19 @@ def start(): implementation(secrets) # SET UP TOOLS + use_community_features = community_tools_prompt(secrets) + if use_community_features: + TOOLS.update(COMMUNITY_TOOLS_SETUP) + for name, configs in TOOLS.items(): tool_prompt(secrets, name, configs) + # SET UP ENVIRONMENT FOR DEPLOYMENTS deployments = select_deployments_prompt(secrets) - # SET UP ENVIRONMENT FOR DEPLOYMENTS + if use_community_features: + DEPLOYMENTS.update(COMMUNITY_DEPLOYMENTS_SETUP) + for deployment in deployments: deployment_prompt(secrets, DEPLOYMENTS[deployment]) @@ -273,8 +298,6 @@ def start(): variables_to_update = review_variables_prompt(secrets) update_variable_prompt(secrets, variables_to_update) - print_styled("✅ Your .env file has been set up.", bcolors.OKGREEN) - # WRAP UP wrap_up(deployments) diff --git a/docker-compose.yml b/docker-compose.yml index 2a774a9270..c6faf2456f 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -39,6 +39,13 @@ services: - __pycache__/ - alembic/ - data/ + - action: sync + path: ./src/community + target: /workspace/src/community + ignore: + - __pycache__/ + - alembic/ + - data/ stdin_open: true tty: true ports: diff --git a/docs/custom_tool_guides/tool_guide.md b/docs/custom_tool_guides/tool_guide.md index 88eaf01aef..560ad8f736 100644 --- a/docs/custom_tool_guides/tool_guide.md +++ b/docs/custom_tool_guides/tool_guide.md @@ -25,12 +25,12 @@ There are three types of tools: ## Step 3: Implement the Tool -Add your tool implementation [here](https://github.com/cohere-ai/toolkit/tree/main/src/backend/tools) (please note that this link might change). The specific subfolder used will depend on the type of tool you're implementing. +Add your tool implementation [here](https://github.com/cohere-ai/toolkit/tree/main/src/community/tools) (please note that this link might change). The specific subfolder used will depend on the type of tool you're implementing. If you need to install a new module to run your tool, execute the following command and run `make dev` again. ```bash -poetry add +poetry add --group community ``` If you're working on a File or Data Loader, follow the steps outlined in [Implementing a Retriever](#implementing-a-retriever). @@ -133,7 +133,7 @@ class CalculatorFunctionTool(BaseFunctionTool): ## Step 4: Making Your Tool Available -To make your tool available, add its definition to the tools config [here](https://github.com/cohere-ai/toolkit/blob/main/src/backend/config/tools.py). +To make your tool available, add its definition to the tools config [here](https://github.com/cohere-ai/toolkit/blob/main/src/community/config/tools.py). Start by adding the tool name to the `ToolName` enum found at the top of the file. @@ -145,6 +145,7 @@ Next, include the tool configurations in the `AVAILABLE_TOOLS` list. The definit - Is_visible: A boolean value indicating whether this function should be visible in the UI. - Category: The type of tool. - Description: A brief description of the tool. +- Env_vars: A list of secrets required by the tool. Function tool with custom parameter definitions: @@ -202,4 +203,4 @@ curl --location 'http://localhost:8000/chat-stream' \ ## Step 6 (extra): Add Unit tests -If you would like to go above and beyond, it would be helpful to add some unit tests to ensure that your tool is working as expected. Create a file [here](https://github.com/cohere-ai/toolkit/tree/main/src/backend/tests/tools) and add a few cases. \ No newline at end of file +If you would like to go above and beyond, it would be helpful to add some unit tests to ensure that your tool is working as expected. Create a file [here](https://github.com/cohere-ai/toolkit/tree/main/src/community/tests/tools) and add a few cases. \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index 0aa062e8d8..3350b47ba2 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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+[package.extras] +accelerate = ["accelerate (>=0.21.0)"] +agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"] +all = ["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)", "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 (>=0.19,<0.20)", "torch", "torchaudio", "torchvision"] +audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] +codecarbon = ["codecarbon (==1.2.0)"] +deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"] +deepspeed-testing = ["GitPython 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"sentencepiece (>=0.1.91,!=0.1.92)", "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)"] +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)"] +video = ["av (==9.2.0)", "decord (==0.6.0)"] +vision = ["Pillow (>=10.0.1,<=15.0)"] + +[[package]] +name = "triton" +version = "2.3.0" +description = "A language and compiler for custom Deep Learning operations" +optional = false +python-versions = "*" +files = [ + {file = "triton-2.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ce4b8ff70c48e47274c66f269cce8861cf1dc347ceeb7a67414ca151b1822d8"}, + {file = "triton-2.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3c3d9607f85103afdb279938fc1dd2a66e4f5999a58eb48a346bd42738f986dd"}, + {file = "triton-2.3.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:218d742e67480d9581bafb73ed598416cc8a56f6316152e5562ee65e33de01c0"}, + {file = "triton-2.3.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:381ec6b3dac06922d3e4099cfc943ef032893b25415de295e82b1a82b0359d2c"}, + {file = "triton-2.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:038e06a09c06a164fef9c48de3af1e13a63dc1ba3c792871e61a8e79720ea440"}, + {file = "triton-2.3.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6d8f636e0341ac348899a47a057c3daea99ea7db31528a225a3ba4ded28ccc65"}, +] + +[package.dependencies] +filelock = "*" + +[package.extras] +build = ["cmake (>=3.20)", "lit"] +tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)", "torch"] +tutorials = ["matplotlib", "pandas", "tabulate", "torch"] + [[package]] name = "typer" version = "0.12.3" @@ -4614,6 +5130,26 @@ files = [ beautifulsoup4 = "*" requests = ">=2.0.0,<3.0.0" +[[package]] +name = "wolframalpha" +version = "5.0.0" +description = "Wolfram|Alpha 2.0 API client" +optional = false +python-versions = ">=3.6" +files = [ + {file = "wolframalpha-5.0.0-py3-none-any.whl", hash = "sha256:159f5d8fd31e4a734a34a9f3ae8aec4e9b2ef392607f82069b4a324b6b1831d5"}, + {file = "wolframalpha-5.0.0.tar.gz", hash = "sha256:38bf27654039ec85cc62c199dd319b6a4d6a7badfed7af1cd161f081afdb57c0"}, +] + +[package.dependencies] +"jaraco.context" = "*" +more-itertools = "*" +xmltodict = "*" + +[package.extras] +docs = ["jaraco.packaging (>=8.2)", "rst.linker (>=1.9)", "sphinx"] +testing = ["keyring", "pmxbot", "pytest (>=3.5,!=3.7.3)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=1.2.3)", "pytest-cov", "pytest-enabler", "pytest-flake8", "pytest-mypy"] + [[package]] name = "wrapt" version = "1.16.0" @@ -4836,4 +5372,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = "~3.11" -content-hash = "454fe372a992838c94cabf243fcce1380892b9c31c56c34b24c94639ee32870d" +content-hash = "f36eba425cad40fa1eb5d499851654e83dac07361ff0c86274290bb5fad063bf" diff --git a/pyproject.toml b/pyproject.toml index a42aae5817..f57de5c5d7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -48,6 +48,12 @@ python = "~3.11" inquirer = "3.2.4" python-dotenv = "1.0.1" + +[tool.poetry.group.community.dependencies] +wolframalpha = "^5.0.0" +transformers = "^4.40.1" +torch = "^2.3.0" + [build-system] requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" diff --git a/src/backend/Dockerfile b/src/backend/Dockerfile index bbadf2c9bd..cf2afbbfd6 100644 --- a/src/backend/Dockerfile +++ b/src/backend/Dockerfile @@ -30,6 +30,7 @@ RUN pip install --no-cache-dir poetry==1.6.1 && \ poetry install COPY src/backend/ src/backend/ +COPY src/community src/community/ # Copy environment variables optionally # IMPORTANT: Can't be put in the docker-compose, will break tests diff --git a/src/backend/config/__init__.py b/src/backend/config/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/src/backend/config/deployments.py b/src/backend/config/deployments.py index 5f7ab780cf..b9d1ef702b 100644 --- a/src/backend/config/deployments.py +++ b/src/backend/config/deployments.py @@ -1,3 +1,6 @@ +import logging +import os +from distutils.util import strtobool from enum import StrEnum from backend.chat.custom.model_deployments.azure import AzureDeployment @@ -12,6 +15,9 @@ class ModelDeploymentName(StrEnum): Azure = "Azure" +use_community_features = bool(strtobool(os.getenv("USE_COMMUNITY_FEATURES", "false"))) + + AVAILABLE_MODEL_DEPLOYMENTS = { ModelDeploymentName.CoherePlatform: Deployment( name=ModelDeploymentName.CoherePlatform, @@ -44,3 +50,14 @@ class ModelDeploymentName(StrEnum): ], ), } + + +if use_community_features: + try: + from community.config.deployments import ( + AVAILABLE_MODEL_DEPLOYMENTS as COMMUNITY_DEPLOYMENTS_SETUP, + ) + + AVAILABLE_MODEL_DEPLOYMENTS.update(COMMUNITY_DEPLOYMENTS_SETUP) + except ImportError: + logging.warning("Community deployments are not available. Skipping.") diff --git a/src/backend/config/tools.py b/src/backend/config/tools.py index 174d2677cf..a64ffdcaba 100644 --- a/src/backend/config/tools.py +++ b/src/backend/config/tools.py @@ -1,10 +1,11 @@ +import logging import os from distutils.util import strtobool from enum import StrEnum from backend.schemas.tool import Category, ManagedTool from backend.tools.function_tools import calculator, python_interpreter -from backend.tools.retrieval import arxiv, lang_chain, llama_index, pub_med, tavily +from backend.tools.retrieval import lang_chain, tavily """ List of available tools. Each tool should have a name, implementation, is_visible and category. @@ -25,11 +26,10 @@ class ToolName(StrEnum): Python_Interpreter = "Python_Interpreter" Calculator = "Calculator" Tavily_Internet_Search = "Internet Search" - Arxiv = "Arxiv" - Pub_Med = "Pub Med" use_langchain = bool(strtobool(os.getenv("USE_EXPERIMENTAL_LANGCHAIN", "false"))) +use_community_features = bool(strtobool(os.getenv("USE_COMMUNITY_FEATURES", "false"))) COHERE_DEPLOYMENT_TOOLS = { ToolName.Wiki_Retriever_LangChain: ManagedTool( @@ -47,13 +47,6 @@ class ToolName(StrEnum): category=Category.FileLoader, description="Retrieves documents from a file using LangChain.", ), - ToolName.File_Upload_LlamaIndex: ManagedTool( - name=ToolName.File_Upload_LlamaIndex, - implementation=llama_index.LlamaIndexUploadPDFRetriever, - is_visible=False, - category=Category.FileLoader, - description="Retrieves documents from a file using LlamaIndex.", - ), ToolName.Python_Interpreter: ManagedTool( name=ToolName.Python_Interpreter, implementation=python_interpreter.PythonInterpreterFunctionTool, @@ -89,20 +82,6 @@ class ToolName(StrEnum): category=Category.DataLoader, description="Returns a list of relevant document snippets for a textual query retrieved from the internet using Tavily.", ), - ToolName.Arxiv: ManagedTool( - name=ToolName.Arxiv, - implementation=arxiv.ArxivRetriever, - is_visible=True, - category=Category.DataLoader, - description="Retrieves documents from Arxiv.", - ), - ToolName.Pub_Med: ManagedTool( - name=ToolName.Pub_Med, - implementation=pub_med.PubMedRetriever, - is_visible=True, - category=Category.DataLoader, - description="Retrieves documents from Pub Med.", - ), } # Langchain tools are all functional tools and must have to_langchain_tool() method defined @@ -125,3 +104,11 @@ class ToolName(StrEnum): AVAILABLE_TOOLS = LANGCHAIN_TOOLS else: AVAILABLE_TOOLS = COHERE_DEPLOYMENT_TOOLS + +if use_community_features: + try: + from community.config.tools import COMMUNITY_TOOLS + + AVAILABLE_TOOLS.update(COMMUNITY_TOOLS) + except ImportError: + logging.warning("Community tools are not available. Skipping.") diff --git a/src/community/__init__.py b/src/community/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/src/community/config/__init__.py b/src/community/config/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/src/community/config/deployments.py b/src/community/config/deployments.py new file mode 100644 index 0000000000..5c108c7c6b --- /dev/null +++ b/src/community/config/deployments.py @@ -0,0 +1,19 @@ +from enum import StrEnum + +from backend.schemas.deployment import Deployment +from community.model_deployments.hugging_face import HuggingFaceDeployment + + +class ModelDeploymentName(StrEnum): + HuggingFace = "HuggingFace" + + +AVAILABLE_MODEL_DEPLOYMENTS = { + ModelDeploymentName.HuggingFace: Deployment( + name=ModelDeploymentName.HuggingFace, + deployment_class=HuggingFaceDeployment, + models=HuggingFaceDeployment.list_models(), + is_available=HuggingFaceDeployment.is_available(), + env_vars=[], + ), +} diff --git a/src/community/config/tools.py b/src/community/config/tools.py new file mode 100644 index 0000000000..c164db7be2 --- /dev/null +++ b/src/community/config/tools.py @@ -0,0 +1,53 @@ +from enum import StrEnum + +from community.tools import Category, ManagedTool +from community.tools.function_tools import wolfram +from community.tools.retrieval import arxiv, llama_index, pub_med + + +class ToolName(StrEnum): + Arxiv = "Arxiv" + Pub_Med = "Pub Med" + File_Upload_LlamaIndex = "File Reader - LlamaIndex" + Wolfram_Alpha = "Wolfram_Alpha" + + +COMMUNITY_TOOLS = { + ToolName.Arxiv: ManagedTool( + name=ToolName.Arxiv, + implementation=arxiv.ArxivRetriever, + is_visible=True, + category=Category.DataLoader, + description="Retrieves documents from Arxiv.", + ), + ToolName.Pub_Med: ManagedTool( + name=ToolName.Pub_Med, + implementation=pub_med.PubMedRetriever, + is_visible=True, + category=Category.DataLoader, + description="Retrieves documents from Pub Med.", + ), + ToolName.File_Upload_LlamaIndex: ManagedTool( + name=ToolName.File_Upload_LlamaIndex, + implementation=llama_index.LlamaIndexUploadPDFRetriever, + is_visible=True, + category=Category.FileLoader, + description="Retrieves documents from a file using LlamaIndex.", + ), + ToolName.Wolfram_Alpha: ManagedTool( + name=ToolName.Wolfram_Alpha, + implementation=wolfram.WolframAlphaFunctionTool, + is_visible=False, + category=Category.Function, + description="Evaluate arithmetic expressions.", + ), +} + + +COMMUNITY_TOOLS_SETUP = { + ToolName.Wolfram_Alpha: { + "secrets": [ + "WOLFRAM_ALPHA_APP_ID", + ], + }, +} diff --git a/src/community/model_deployments/__init__.py b/src/community/model_deployments/__init__.py new file mode 100644 index 0000000000..8a497dafa0 --- /dev/null +++ b/src/community/model_deployments/__init__.py @@ -0,0 +1 @@ +from backend.chat.custom.model_deployments.base import BaseDeployment diff --git a/src/community/model_deployments/hugging_face.py b/src/community/model_deployments/hugging_face.py new file mode 100644 index 0000000000..c5a1ab6b2b --- /dev/null +++ b/src/community/model_deployments/hugging_face.py @@ -0,0 +1,125 @@ +import logging +from typing import Any, Dict, Generator, List + +from cohere.types import NonStreamedChatResponse, StreamedChatResponse +from transformers import AutoModelForCausalLM, AutoTokenizer + +from backend.schemas.cohere_chat import CohereChatRequest +from community.model_deployments import BaseDeployment + + +class HuggingFaceDeployment(BaseDeployment): + """ + The first time you run this code, it will download all the shards of the model from the Hugging Face model hub. + This usually takes a while, so you might want to run this code separately and not as part of the toolkit. + For that, you can run the following command: + poetry run python3 src/community/model_deployments/hugging_face.py + """ + + DEFAULT_MODELS = [ + "CohereForAI/c4ai-command-r-v01", + "CohereForAI/c4ai-command-r-plus", + ] + + def __init__(self): + pass + + @property + def rerank_enabled(self) -> bool: + return False + + @classmethod + def list_models(cls) -> List[str]: + if not HuggingFaceDeployment.is_available(): + return [] + + return cls.DEFAULT_MODELS + + @classmethod + def is_available(cls) -> bool: + return True + + def invoke_chat(self, chat_request: CohereChatRequest, **kwargs: Any) -> Any: + model_id = chat_request.model + if model_id == "command-r": + model_id = self.DEFAULT_MODELS[0] + + tokenizer = AutoTokenizer.from_pretrained(model_id) + model = AutoModelForCausalLM.from_pretrained(model_id) + + # Format message with the command-r-plus chat template + messages = self._build_chat_history( + chat_request.chat_history, chat_request.message + ) + input_ids = tokenizer.apply_chat_template( + messages, tokenize=True, add_generation_prompt=True, return_tensors="pt" + ) + + gen_tokens = model.generate( + input_ids, + max_new_tokens=100, + do_sample=True, + temperature=0.3, + ) + + gen_text = tokenizer.decode(gen_tokens[0]) + + return {"text": gen_text} + + def invoke_chat_stream( + self, chat_request: CohereChatRequest, **kwargs: Any + ) -> Generator[StreamedChatResponse, None, None]: + """ + Built in streamming is not supported, so this function wraps the invoke_chat function to return a single response. + """ + messages = self._build_chat_history( + chat_request.chat_history, chat_request.message + ) + gen_text = self.invoke_chat(chat_request) + + yield StreamedChatResponse( + finish_reason="COMPLETE", + response=NonStreamedChatResponse( + text=gen_text.get("text", ""), chat_history=messages + ), + ) + + def invoke_search_queries( + self, + message: str, + chat_history: List[Dict[str, str]] | None = None, + **kwargs: Any, + ) -> list[str]: + logging.warning( + "invoke_search_queries not implemented for HuggingFaceDeployment" + ) + return [] + + def invoke_rerank( + self, query: str, documents: List[Dict[str, Any]], **kwargs: Any + ) -> Any: + return None + + def _build_chat_history( + self, chat_history: List[Dict[str, Any]], message: str + ) -> List[Dict[str, Any]]: + messages = [] + + for message in chat_history: + messages.append({"role": message["role"], "content": message["message"]}) + + messages.append({"role": "USER", "content": message}) + + return messages + + +if __name__ == "__main__": + hugging_face = HuggingFaceDeployment() + chat_request = CohereChatRequest( + chat_history=[ + {"role": "USER", "message": "Hello!"}, + {"role": "CHATBOT", "message": "Hi, how can I help you?"}, + ], + message="How are you?", + ) + response = hugging_face.invoke_chat(chat_request) diff --git a/src/backend/tests/tools/retrieval/test_arxiv.py b/src/community/tests/tools/retrieval/test_arxiv.py similarity index 79% rename from src/backend/tests/tools/retrieval/test_arxiv.py rename to src/community/tests/tools/retrieval/test_arxiv.py index efde1ab988..3913ec2a29 100644 --- a/src/backend/tests/tools/retrieval/test_arxiv.py +++ b/src/community/tests/tools/retrieval/test_arxiv.py @@ -1,4 +1,4 @@ -from backend.tools.retrieval.arxiv import ArxivRetriever +from community.tools.retrieval.arxiv import ArxivRetriever def test_arxiv_retriever(): diff --git a/src/backend/tests/tools/retrieval/test_llama_index.py b/src/community/tests/tools/retrieval/test_llama_index.py similarity index 99% rename from src/backend/tests/tools/retrieval/test_llama_index.py rename to src/community/tests/tools/retrieval/test_llama_index.py index 072c771c58..cef017b2f0 100644 --- a/src/backend/tests/tools/retrieval/test_llama_index.py +++ b/src/community/tests/tools/retrieval/test_llama_index.py @@ -1,4 +1,4 @@ -from backend.tools.retrieval.llama_index import LlamaIndexUploadPDFRetriever +from community.tools.retrieval.llama_index import LlamaIndexUploadPDFRetriever def test_pdf_retriever() -> None: diff --git a/src/backend/tests/tools/retrieval/test_pub_med.py b/src/community/tests/tools/retrieval/test_pub_med.py similarity index 75% rename from src/backend/tests/tools/retrieval/test_pub_med.py rename to src/community/tests/tools/retrieval/test_pub_med.py index fb86d4ac91..b88cc985a2 100644 --- a/src/backend/tests/tools/retrieval/test_pub_med.py +++ b/src/community/tests/tools/retrieval/test_pub_med.py @@ -1,4 +1,4 @@ -from backend.tools.retrieval.pub_med import PubMedRetriever +from community.tools.retrieval.pub_med import PubMedRetriever def test_pub_med_retriever(): diff --git a/src/community/tools/__init__.py b/src/community/tools/__init__.py new file mode 100644 index 0000000000..f2a3eac724 --- /dev/null +++ b/src/community/tools/__init__.py @@ -0,0 +1,3 @@ +from backend.schemas.tool import Category, ManagedTool +from backend.tools.function_tools.base import BaseFunctionTool +from backend.tools.retrieval.base import BaseRetrieval diff --git a/src/community/tools/function_tools/__init__.py b/src/community/tools/function_tools/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/src/community/tools/function_tools/wolfram.py b/src/community/tools/function_tools/wolfram.py new file mode 100644 index 0000000000..bdd1525efc --- /dev/null +++ b/src/community/tools/function_tools/wolfram.py @@ -0,0 +1,31 @@ +# https://python.langchain.com/docs/integrations/tools/wolfram_alpha/ + +import os +from typing import Any, Dict, List + +import dotenv +from langchain_community.utilities.wolfram_alpha import WolframAlphaAPIWrapper + +from community.tools import BaseFunctionTool + + +class WolframAlphaFunctionTool(BaseFunctionTool): + def __init__(self): + if "WOLFRAM_ALPHA_APP_ID" not in os.environ: + raise ValueError( + "Please set the WOLFRAM_ALPHA_APP_ID environment variable." + ) + + self.app_id = os.environ["WOLFRAM_ALPHA_APP_ID"] + self.tool = WolframAlphaAPIWrapper(wolfram_alpha_appid=self.app_id) + + def call(self, parameters: str, **kwargs: Any) -> List[Dict[str, Any]]: + to_evaluate = parameters.get("expression", "") + result = self.tool.run(to_evaluate) + return {"result": result, "text": result} + + +if __name__ == "__main__": + dotenv.load_dotenv() + retriever = WolframAlphaFunctionTool() + retriever.call({"expression": "what is 1+1?"}) diff --git a/src/community/tools/retrieval/__init__.py b/src/community/tools/retrieval/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/src/backend/tools/retrieval/arxiv.py b/src/community/tools/retrieval/arxiv.py similarity index 87% rename from src/backend/tools/retrieval/arxiv.py rename to src/community/tools/retrieval/arxiv.py index 8df0f37c45..155934531f 100644 --- a/src/backend/tools/retrieval/arxiv.py +++ b/src/community/tools/retrieval/arxiv.py @@ -2,7 +2,7 @@ from langchain_community.utilities import ArxivAPIWrapper -from backend.tools.retrieval import BaseRetrieval +from community.tools import BaseRetrieval class ArxivRetriever(BaseRetrieval): diff --git a/src/backend/tools/retrieval/connector.py b/src/community/tools/retrieval/connector.py similarity index 93% rename from src/backend/tools/retrieval/connector.py rename to src/community/tools/retrieval/connector.py index dd26101be8..f599521d26 100644 --- a/src/backend/tools/retrieval/connector.py +++ b/src/community/tools/retrieval/connector.py @@ -2,7 +2,7 @@ import requests -from backend.tools.retrieval.base import BaseRetrieval +from community.tools import BaseRetrieval """ Plug in your connector configuration here. For example: diff --git a/src/backend/tools/retrieval/llama_index.py b/src/community/tools/retrieval/llama_index.py similarity index 93% rename from src/backend/tools/retrieval/llama_index.py rename to src/community/tools/retrieval/llama_index.py index ae29fd65c4..a2d9377767 100644 --- a/src/backend/tools/retrieval/llama_index.py +++ b/src/community/tools/retrieval/llama_index.py @@ -2,7 +2,7 @@ from llama_index.core import SimpleDirectoryReader -from backend.tools.retrieval.base import BaseRetrieval +from community.tools import BaseRetrieval """ Plug in your llama index retrieval implementation here. diff --git a/src/backend/tools/retrieval/pub_med.py b/src/community/tools/retrieval/pub_med.py similarity index 86% rename from src/backend/tools/retrieval/pub_med.py rename to src/community/tools/retrieval/pub_med.py index c7cdffa42e..c62501da74 100644 --- a/src/backend/tools/retrieval/pub_med.py +++ b/src/community/tools/retrieval/pub_med.py @@ -2,7 +2,7 @@ from langchain_community.tools.pubmed.tool import PubmedQueryRun -from backend.tools.retrieval.base import BaseRetrieval +from community.tools import BaseRetrieval class PubMedRetriever(BaseRetrieval):