diff --git a/.github/workflows/pre-release.yml b/.github/workflows/pre-release.yml index 2399b5634..a013f686a 100644 --- a/.github/workflows/pre-release.yml +++ b/.github/workflows/pre-release.yml @@ -38,6 +38,7 @@ jobs: token: ${{ secrets.GITHUB_TOKEN }} draft: false generateReleaseNotes: true + prerelease: true tag: v${{ steps.check-version.outputs.version }} commit: main - name: Publish to PyPI diff --git a/Makefile b/Makefile index 6739e2c61..031c5e479 100644 --- a/Makefile +++ b/Makefile @@ -41,10 +41,10 @@ run_frontend: cd src/frontend && npm start run_cli: - poetry run langflow --path src/frontend/build + poetry run langflow run --path src/frontend/build run_cli_debug: - poetry run langflow --path src/frontend/build --log-level debug + poetry run langflow run --path src/frontend/build --log-level debug setup_devcontainer: make init @@ -69,7 +69,7 @@ backend: build_and_run: echo 'Removing dist folder' rm -rf dist - make build && poetry run pip install dist/*.tar.gz && poetry run langflow + make build && poetry run pip install dist/*.tar.gz && poetry run langflow run build_and_install: echo 'Removing dist folder' diff --git a/README.md b/README.md index 9137ea714..0f0113bac 100644 --- a/README.md +++ b/README.md @@ -245,7 +245,7 @@ print(run_flow("Your message", flow_id=FLOW_ID, tweaks=TWEAKS)) ## Deploy on Railway -[![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/Emy2sU?referralCode=MnPSdg) +[![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/JMXEWp?referralCode=MnPSdg) ## Deploy on Render diff --git a/docs/docs/components/custom.mdx b/docs/docs/components/custom.mdx index ffa747c1b..90282a73e 100644 --- a/docs/docs/components/custom.mdx +++ b/docs/docs/components/custom.mdx @@ -33,6 +33,7 @@ The CustomComponent class serves as the foundation for creating custom component | Supported Types | | --------------------------------------------------------- | | _`str`_, _`int`_, _`float`_, _`bool`_, _`list`_, _`dict`_ | + | _`langflow.field_typing.NestedDict`_ | | _`langchain.chains.base.Chain`_ | | _`langchain.PromptTemplate`_ | | _`langchain.llms.base.BaseLLM`_ | @@ -44,6 +45,8 @@ The CustomComponent class serves as the foundation for creating custom component | _`langchain.embeddings.base.Embeddings`_ | | _`langchain.schema.BaseRetriever`_ | + The difference between _`dict`_ and _`langflow.field_typing.NestedDict`_ is that one adds a simple key-value pair field, while the other opens a more robust dictionary editor. + Unlike Langchain types, base Python types do not add a [handle](../guidelines/components) to the field by default. To add handles, diff --git a/docs/docs/components/text-splitters.mdx b/docs/docs/components/text-splitters.mdx index 6c91cc1a0..c6efe4553 100644 --- a/docs/docs/components/text-splitters.mdx +++ b/docs/docs/components/text-splitters.mdx @@ -1,11 +1,13 @@ -import Admonition from '@theme/Admonition'; +import Admonition from "@theme/Admonition"; # Text Splitters -

- We appreciate your understanding as we polish our documentation – it may contain some rough edges. Share your feedback or report issues to help us improve! 🛠️📝 -

+

+ We appreciate your understanding as we polish our documentation – it may + contain some rough edges. Share your feedback or report issues to help us + improve! 🛠️📝 +

A text splitter is a tool that divides a document or text into smaller chunks or segments. It is used to break down large texts into more manageable pieces for analysis or processing. @@ -22,13 +24,13 @@ The `CharacterTextSplitter` is used to split a long text into smaller chunks bas - **chunk_overlap:** Determines the number of characters that overlap between consecutive chunks when splitting text. It specifies how much of the previous chunk should be included in the next chunk. - For example, if the `chunk_overlap` is set to 20 and the `chunk_size` is set to 100, the splitter will create chunks of 100 characters each, but the last 20 characters of each chunk will overlap with the first 20 characters of the next chunk. This allows for a smoother transition between chunks and ensures that no information is lost – defaults to `200`. + For example, if the `chunk_overlap` is set to 20 and the `chunk_size` is set to 100, the splitter will create chunks of 100 characters each, but the last 20 characters of each chunk will overlap with the first 20 characters of the next chunk. This allows for a smoother transition between chunks and ensures that no information is lost – defaults to `200`. - **chunk_size:** Determines the maximum number of characters in each chunk when splitting a text. It specifies the size or length of each chunk. - For example, if the chunk_size is set to 100, the splitter will create chunks of 100 characters each. If the text is longer than 100 characters, it will be divided into multiple chunks of equal size, except for the last chunk, which may be smaller if there are remaining characters –defaults to `1000`. + For example, if the chunk_size is set to 100, the splitter will create chunks of 100 characters each. If the text is longer than 100 characters, it will be divided into multiple chunks of equal size, except for the last chunk, which may be smaller if there are remaining characters –defaults to `1000`. -- **separator:** Specifies the character that will be used to split the text into chunks – defaults to `.` +- **separator:** Specifies the character that will be used to split the text into chunks – defaults to `.` --- @@ -44,6 +46,18 @@ The `RecursiveCharacterTextSplitter` splits the text by trying to keep paragra - **chunk_size:** Determines the maximum number of characters in each chunk when splitting a text. It specifies the size or length of each chunk. -- **separator_type:** The parameter allows the user to split the code with multiple language support. It supports various languages such as Text, Ruby, Python, Solidity, Java, and more. Defaults to `Text`. +- **separators:** The `separators` in RecursiveCharacterTextSplitter are the characters used to split the text into chunks. The text splitter tries to create chunks based on splitting on the first character in the list of `separators`. If any chunks are too large, it moves on to the next character in the list and continues splitting. Defaults to ["\n\n", "\n", " ", ""]. -- **separators:** The `separators` in RecursiveCharacterTextSplitter are the characters used to split the text into chunks. The text splitter tries to create chunks based on splitting on the first character in the list of `separators`. If any chunks are too large, it moves on to the next character in the list and continues splitting. Defaults to `.` \ No newline at end of file +### LanguageRecursiveTextSplitter + +The `LanguageRecursiveTextSplitter` is a text splitter that splits the text into smaller chunks based on the (programming) language of the text. + +**Params** + +- **Documents:** Input documents to split. + +- **chunk_overlap:** Determines the number of characters that overlap between consecutive chunks when splitting text. It specifies how much of the previous chunk should be included in the next chunk. + +- **chunk_size:** Determines the maximum number of characters in each chunk when splitting a text. It specifies the size or length of each chunk. + +- **separator_type:** The parameter allows the user to split the code with multiple language support. It supports various languages such as Ruby, Python, Solidity, Java, and more. Defaults to `Python`. diff --git a/docs/docs/guidelines/custom-component.mdx b/docs/docs/guidelines/custom-component.mdx index 816f8356b..4f18d0375 100644 --- a/docs/docs/guidelines/custom-component.mdx +++ b/docs/docs/guidelines/custom-component.mdx @@ -387,7 +387,7 @@ Your structure should look something like this: The recommended way to load custom components is to set the _`LANGFLOW_COMPONENTS_PATH`_ environment variable to the path of your custom components directory. Then, run the Langflow CLI as usual. ```bash -export LANGFLOW_COMPONENTS_PATH=/path/to/components +export LANGFLOW_COMPONENTS_PATH='["/path/to/components"]' langflow ``` diff --git a/docs/docs/guides/langfuse_integration.mdx b/docs/docs/guides/langfuse_integration.mdx new file mode 100644 index 000000000..81f06e787 --- /dev/null +++ b/docs/docs/guides/langfuse_integration.mdx @@ -0,0 +1,49 @@ +# Integrating Langfuse with Langflow + +## Introduction + +Langfuse is an open-source tracing and analytics tool designed for LLM applications. Integrating Langfuse with Langflow provides detailed production traces and granular insights into quality, cost, and latency. This integration allows you to monitor and debug your Langflow's chat or APIs easily. + +## Step-by-Step Instructions + +### Step 1: Create a Langfuse account + +1. Go to [Langfuse](https://langfuse.com) and click on the "Sign In" button in the top right corner. +2. Click on the "Sign Up" button and create an account. +3. Once logged in, click on "Settings" and then on "Create new API keys." +4. Copy the Public key and the Secret Key and save them somewhere safe. + {/* Add these keys to your environment variables in the following step. */} + +### Step 2: Set up Langfuse in Langflow + +1. **Export the Environment Variables**: You'll need to export the environment variables `LANGFLOW_LANGFUSE_SECRET_KEY` and `LANGFLOW_LANGFUSE_PUBLIC_KEY` with the values obtained in Step 1. + + You can do this by executing the following commands in your terminal: + + ```bash + export LANGFLOW_LANGFUSE_SECRET_KEY= + export LANGFLOW_LANGFUSE_PUBLIC_KEY= + ``` + + Alternatively, you can run the Langflow CLI command: + + ```bash + LANGFLOW_LANGFUSE_SECRET_KEY= LANGFLOW_LANGFUSE_PUBLIC_KEY= langflow + ``` + + If you are self-hosting Langfuse, you can also set the environment variable `LANGFLOW_LANGFUSE_HOST` to point to your Langfuse instance. By default, Langfuse points to the cloud instance at `https://cloud.langfuse.com`. + +2. **Verify Integration**: Ensure that the environment variables are set correctly by checking their existence in your environment, for example by running: + + ```bash + echo $LANGFLOW_LANGFUSE_SECRET_KEY + echo $LANGFLOW_LANGFUSE_PUBLIC_KEY + ``` + +3. **Monitor Langflow**: Now, whenever you use Langflow's chat or API, you will be able to see the tracing of your conversations in Langfuse. + +That's it! You have successfully integrated Langfuse with Langflow, enhancing observability and debugging capabilities for your LLM application. + +--- + +Note: For more details or customized configurations, please refer to the official [Langfuse documentation](https://langfuse.com/docs/integrations/langchain). diff --git a/docs/sidebars.js b/docs/sidebars.js index e44b1cf4f..bc02f7407 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -51,7 +51,11 @@ module.exports = { type: "category", label: "Step-by-Step Guides", collapsed: false, - items: ["guides/loading_document", "guides/chatprompttemplate_guide"], + items: [ + "guides/loading_document", + "guides/chatprompttemplate_guide", + "guides/langfuse_integration", + ], }, // { // type: 'category', diff --git a/poetry.lock b/poetry.lock index 53e09ac71..30efaa559 100644 --- a/poetry.lock +++ b/poetry.lock @@ -239,17 +239,6 @@ files = [ {file = "appnope-0.1.3.tar.gz", hash = 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"sha256:6aa3f7faf0ea52d728bb18c0a0d1522d9bfd8c72d26ff6f61bfc3d06a411cf40"}, - {file = "types_requests-2.31.0.2-py3-none-any.whl", hash = "sha256:56d181c85b5925cbc59f4489a57e72a8b2166f18273fd8ba7b6fe0c0b986f12a"}, + {file = "types-requests-2.31.0.3.tar.gz", hash = "sha256:d5d7a08965fca12bedf716eaf5430c6e3d0da9f3164a1dba2a7f3885f9ebe3c0"}, + {file = "types_requests-2.31.0.3-py3-none-any.whl", hash = "sha256:938f51653c757716aeca5d72c405c5e2befad8b0d330e3b385ce7f148e1b10dc"}, ] [package.dependencies] @@ -7876,13 +7919,13 @@ files = [ [[package]] name = "typing-extensions" -version = "4.7.1" -description = "Backported and Experimental Type Hints for Python 3.7+" +version = "4.8.0" +description = "Backported and Experimental Type Hints for Python 3.8+" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "typing_extensions-4.7.1-py3-none-any.whl", hash = "sha256:440d5dd3af93b060174bf433bccd69b0babc3b15b1a8dca43789fd7f61514b36"}, - {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"}, + {file = "typing_extensions-4.8.0-py3-none-any.whl", hash = "sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0"}, + {file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"}, ] [[package]] @@ -7927,50 +7970,72 @@ test = ["coverage", "pytest", "pytest-cov"] [[package]] name = "unstructured" -version = "0.7.12" +version = "0.10.16" description = "A library that prepares raw documents for downstream ML tasks." optional = false python-versions = ">=3.7.0" files = [ - {file = "unstructured-0.7.12-py3-none-any.whl", hash = "sha256:6dec4f23574e213f30bccb680a4fb84c95617092ce4abf5d8955cc71af402fef"}, - {file = "unstructured-0.7.12.tar.gz", hash = "sha256:3dcddea34f52e1070f38fd10063b3b0f64bc4cbe5b778d6b86b5d33262d625cd"}, + {file = "unstructured-0.10.16-py3-none-any.whl", hash = "sha256:f654af8f22027797a570f2de74b61d136868e2c57cc87febbe8104434c461a3e"}, + {file = "unstructured-0.10.16.tar.gz", hash = "sha256:d01fae8ff72f996b0448aab20fc616909d679fdfee38e33e0feb8ac5103eecc2"}, ] [package.dependencies] -argilla = "*" +beautifulsoup4 = "*" chardet = "*" +dataclasses-json = "*" +emoji = "*" filetype = "*" lxml = "*" -markdown = "*" -msg-parser = "*" nltk = "*" -openpyxl = "*" -pandas = "*" -pdf2image = "*" -"pdfminer.six" = "*" -pillow = "*" -pypandoc = "*" -python-docx = "*" +python-iso639 = "*" python-magic = "*" -python-pptx = "*" requests = "*" tabulate = "*" -xlrd = "*" [package.extras] -azure = ["adlfs", "fsspec"] +airtable = ["pyairtable"] +all-docs = ["ebooklib", "markdown", "msg-parser", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx", "python-pptx (<=0.6.21)", "unstructured-inference", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +azure = ["adlfs", "fsspec (==2023.9.1)"] +biomed = ["bs4"] +box = ["boxfs", "fsspec (==2023.9.1)"] +confluence = ["atlassian-python-api"] +csv = ["pandas"] +delta-table = ["deltalake", "fsspec (==2023.9.1)"] discord = ["discord-py"] -dropbox = ["dropboxdrivefs", "fsspec"] -gcs = ["fsspec", "gcsfs"] -github = ["pygithub (==1.58.2)"] +doc = ["python-docx"] +docx = ["python-docx"] +dropbox = ["dropboxdrivefs", "fsspec (==2023.9.1)"] +elasticsearch = ["elasticsearch", "jq"] +epub = ["ebooklib"] +gcs = ["bs4", "fsspec (==2023.9.1)", "gcsfs"] +github = ["pygithub (>1.58.0)"] gitlab = ["python-gitlab"] google-drive = ["google-api-python-client"] huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"] -local-inference = ["unstructured-inference (==0.5.4)"] +image = ["pdf2image", "pdfminer.six", "unstructured-inference", "unstructured.pytesseract (>=0.3.12)"] +jira = ["atlassian-python-api"] +local-inference = ["ebooklib", "markdown", "msg-parser", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx", "python-pptx (<=0.6.21)", "unstructured-inference", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +md = ["markdown"] +msg = ["msg-parser"] +notion = ["htmlBuilder", "notion-client"] +odt = ["pypandoc", "python-docx"] +onedrive = ["Office365-REST-Python-Client (<2.4.3)", "bs4", "msal"] +org = ["pypandoc"] +outlook = ["Office365-REST-Python-Client (<2.4.3)", "msal"] +paddleocr = ["unstructured.paddleocr (==2.6.1.3)"] +pdf = ["pdf2image", "pdfminer.six", "unstructured-inference", "unstructured.pytesseract (>=0.3.12)"] +ppt = ["python-pptx (<=0.6.21)"] +pptx = ["python-pptx (<=0.6.21)"] reddit = ["praw"] -s3 = ["fsspec", "s3fs"] +rst = ["pypandoc"] +rtf = ["pypandoc"] +s3 = ["fsspec (==2023.9.1)", "s3fs"] +salesforce = ["simple-salesforce"] +sharepoint = ["Office365-REST-Python-Client (<2.4.3)", "msal"] slack = ["slack-sdk"] +tsv = ["pandas"] wikipedia = ["wikipedia"] +xlsx = ["openpyxl", "pandas", "xlrd"] [[package]] name = "uritemplate" @@ -8402,33 +8467,6 @@ files = [ {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"}, ] -[[package]] -name = "xlrd" -version = "2.0.1" -description = "Library for developers to extract data from Microsoft Excel (tm) .xls spreadsheet files" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" -files = [ - {file = "xlrd-2.0.1-py2.py3-none-any.whl", hash = "sha256:6a33ee89877bd9abc1158129f6e94be74e2679636b8a205b43b85206c3f0bbdd"}, - {file = "xlrd-2.0.1.tar.gz", hash = "sha256:f72f148f54442c6b056bf931dbc34f986fd0c3b0b6b5a58d013c9aef274d0c88"}, -] - -[package.extras] -build = ["twine", "wheel"] -docs = ["sphinx"] -test = ["pytest", "pytest-cov"] - -[[package]] -name = "xlsxwriter" -version = "3.1.3" -description = "A Python module for creating Excel XLSX files." -optional = false -python-versions = ">=3.6" -files = [ - {file = "XlsxWriter-3.1.3-py3-none-any.whl", hash = "sha256:b1fde9b60dc25fff589f3baf58e95178048ba87a7916d45f6e3bce4a61f56e64"}, - {file = "XlsxWriter-3.1.3.tar.gz", hash = "sha256:696c16458d50712a3a5f902676c045ddb4c1bd1b54595f501e582d549abdbdb9"}, -] - [[package]] name = "yarl" version = "1.9.2" @@ -8518,17 +8556,17 @@ multidict = ">=4.0" [[package]] name = "zipp" -version = "3.16.2" +version = "3.17.0" description = "Backport of pathlib-compatible object wrapper for zip files" optional = false python-versions = ">=3.8" files = [ - {file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"}, - {file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"}, + {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"}, + {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"}, ] [package.extras] -docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"] testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"] [[package]] @@ -8662,4 +8700,4 @@ local = ["ctransformers", "llama-cpp-python", "sentence-transformers"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<3.11" -content-hash = "4c507c16376c14157663ca8c03ae1290349f5d90f8dd0732419324564fbe4f93" +content-hash = "ebf83fe66c2a78ceffc2c9228b439db10b37d0e444dd3f275e1a1addab1fd164" diff --git a/pyproject.toml b/pyproject.toml index ef70381b6..b39111715 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "0.5.0a0" +version = "0.5.0a1" description = "A Python package with a built-in web application" authors = ["Logspace "] maintainers = [ @@ -32,17 +32,17 @@ beautifulsoup4 = "^4.12.2" google-search-results = "^2.4.1" google-api-python-client = "^2.79.0" typer = "^0.9.0" -gunicorn = "^21.1.0" +gunicorn = "^21.2.0" langchain = "^0.0.274" openai = "^0.27.8" pandas = "2.0.3" chromadb = "^0.3.21" huggingface-hub = { version = "^0.16.0", extras = ["inference"] } -rich = "^13.4.2" +rich = "^13.5.0" llama-cpp-python = { version = "~0.1.0", optional = true } networkx = "^3.1" -unstructured = "^0.7.0" -pypdf = "^3.11.0" +unstructured = "^0.10.0" +pypdf = "^3.15.0" lxml = "^4.9.2" pysrt = "^1.1.2" fake-useragent = "^1.2.1" @@ -52,13 +52,13 @@ pyarrow = "^12.0.0" tiktoken = "~0.4.0" wikipedia = "^1.4.0" langchain-serve = { version = ">0.0.51", optional = true } -qdrant-client = "^1.3.0" +qdrant-client = "^1.4.0" websockets = "^10.3" -weaviate-client = "^3.21.0" +weaviate-client = "^3.23.0" jina = "3.15.2" sentence-transformers = { version = "^2.2.2", optional = true } ctransformers = { version = "^0.2.10", optional = true } -cohere = "^4.11.0" +cohere = "^4.21.0" python-multipart = "^0.0.6" sqlmodel = "^0.0.8" faiss-cpu = "^1.7.4" @@ -85,12 +85,16 @@ passlib = "^1.7.4" bcrypt = "^4.0.1" python-jose = "^3.3.0" metaphor-python = "^0.1.11" -markupsafe = "^2.1.3" pywin32 = { version = "^306", markers = "sys_platform == 'win32'" } loguru = "^0.7.1" +langfuse = "^1.0.13" +pillow = "^10.0.0" +metal-sdk = "^2.0.2" +markupsafe = "^2.1.3" [tool.poetry.group.dev.dependencies] +types-redis = "^4.6.0.5" black = "^23.1.0" ipykernel = "^6.21.2" mypy = "^1.1.1" @@ -110,7 +114,7 @@ locust = "^2.16.1" pytest-mock = "^3.11.1" pytest-xdist = "^3.3.1" types-pywin32 = "^306.0.0.4" -types-redis = "^4.6.0.5" +types-google-cloud-ndb = "^2.2.0.0" pytest-sugar = "^0.9.7" diff --git a/render.yaml b/render.yaml index e67da9334..4c17923c6 100644 --- a/render.yaml +++ b/render.yaml @@ -3,9 +3,14 @@ services: - type: web name: langflow runtime: docker - plan: free dockerfilePath: ./Dockerfile repo: https://github.com/logspace-ai/langflow branch: main healthCheckPath: /health autoDeploy: false + envVars: + - key: LANGFLOW_DATABASE_URL + value: sqlite:////home/user/.cache/langflow/langflow.db + disk: + name: langflow-data + mountPath: /home/user/.cache/langflow diff --git a/src/backend/langflow/__main__.py b/src/backend/langflow/__main__.py index bcc26fe8b..a6a2ea540 100644 --- a/src/backend/langflow/__main__.py +++ b/src/backend/langflow/__main__.py @@ -55,7 +55,7 @@ def display_results(results): def update_settings( config: str, - cache: str, + cache: Optional[str] = None, dev: bool = False, remove_api_keys: bool = False, components_path: Optional[Path] = None, @@ -153,10 +153,10 @@ def run( log_file: Path = typer.Option( "logs/langflow.log", help="Path to the log file.", envvar="LANGFLOW_LOG_FILE" ), - cache: str = typer.Option( + cache: Optional[str] = typer.Option( envvar="LANGFLOW_LANGCHAIN_CACHE", help="Type of cache to use. (InMemoryCache, SQLiteCache)", - default="SQLiteCache", + default=None, ), jcloud: bool = typer.Option(False, help="Deploy on Jina AI Cloud"), dev: bool = typer.Option(False, help="Run in development mode (may contain bugs)"), diff --git a/src/backend/langflow/alembic/versions/67cc006d50bf_add_profile_image_column.py b/src/backend/langflow/alembic/versions/67cc006d50bf_add_profile_image_column.py new file mode 100644 index 000000000..ca0aa0542 --- /dev/null +++ b/src/backend/langflow/alembic/versions/67cc006d50bf_add_profile_image_column.py @@ -0,0 +1,49 @@ +"""Add profile-image column + +Revision ID: 67cc006d50bf +Revises: 260dbcc8b680 +Create Date: 2023-09-08 07:36:13.387318 + +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa +import sqlmodel +from sqlalchemy.engine.reflection import Inspector + +# revision identifiers, used by Alembic. +revision: str = "67cc006d50bf" +down_revision: Union[str, None] = "260dbcc8b680" +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + conn = op.get_bind() + inspector = Inspector.from_engine(conn) + if "user" in inspector.get_table_names() and "profile_image" not in [ + column["name"] for column in inspector.get_columns("user") + ]: + with op.batch_alter_table("user", schema=None) as batch_op: + batch_op.add_column( + sa.Column( + "profile_image", sqlmodel.sql.sqltypes.AutoString(), nullable=True + ) + ) + + # ### end Alembic commands ### + + +def downgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + conn = op.get_bind() + inspector = Inspector.from_engine(conn) + if "user" in inspector.get_table_names() and "profile_image" in [ + column["name"] for column in inspector.get_columns("user") + ]: + with op.batch_alter_table("user", schema=None) as batch_op: + batch_op.drop_column("profile_image") + + # ### end Alembic commands ### diff --git a/src/backend/langflow/api/v1/users.py b/src/backend/langflow/api/v1/users.py index 517dd7f69..e68512e43 100644 --- a/src/backend/langflow/api/v1/users.py +++ b/src/backend/langflow/api/v1/users.py @@ -18,15 +18,17 @@ from langflow.services.auth.utils import ( get_current_active_superuser, get_current_active_user, get_password_hash, + verify_password, ) from langflow.services.database.models.user.crud import ( + get_user_by_id, update_user, ) -router = APIRouter(tags=["Users"]) +router = APIRouter(tags=["Users"], prefix="/users") -@router.post("/user", response_model=UserRead, status_code=201) +@router.post("/", response_model=UserRead, status_code=201) def add_user( user: UserCreate, session: Session = Depends(get_session), @@ -50,7 +52,7 @@ def add_user( return new_user -@router.get("/user", response_model=UserRead) +@router.get("/whoami", response_model=UserRead) def read_current_user( current_user: User = Depends(get_current_active_user), ) -> User: @@ -60,7 +62,7 @@ def read_current_user( return current_user -@router.get("/users", response_model=UsersResponse) +@router.get("/", response_model=UsersResponse) def read_all_users( skip: int = 0, limit: int = 10, @@ -82,20 +84,61 @@ def read_all_users( ) -@router.patch("/user/{user_id}", response_model=UserRead) +@router.patch("/{user_id}", response_model=UserRead) def patch_user( user_id: UUID, - user: UserUpdate, - _: Session = Depends(get_current_active_user), + user_update: UserUpdate, + user: User = Depends(get_current_active_user), session: Session = Depends(get_session), ) -> User: """ Update an existing user's data. """ - return update_user(user_id, user, session) + if not user.is_superuser and user.id != user_id: + raise HTTPException( + status_code=403, detail="You don't have the permission to update this user" + ) + if user_update.password: + raise HTTPException( + status_code=400, detail="You can't change your password here" + ) + + if user_db := get_user_by_id(session, user_id): + return update_user(user_db, user_update, session) + else: + raise HTTPException(status_code=404, detail="User not found") -@router.delete("/user/{user_id}") +@router.patch("/{user_id}/reset-password", response_model=UserRead) +def reset_password( + user_id: UUID, + user_update: UserUpdate, + user: User = Depends(get_current_active_user), + session: Session = Depends(get_session), +) -> User: + """ + Reset a user's password. + """ + if user_id != user.id: + raise HTTPException( + status_code=400, detail="You can't change another user's password" + ) + + if not user: + raise HTTPException(status_code=404, detail="User not found") + if verify_password(user_update.password, user.password): + raise HTTPException( + status_code=400, detail="You can't use your current password" + ) + new_password = get_password_hash(user_update.password) + user.password = new_password + session.commit() + session.refresh(user) + + return user + + +@router.delete("/{user_id}", response_model=dict) def delete_user( user_id: UUID, current_user: User = Depends(get_current_active_superuser), diff --git a/src/backend/langflow/api/v1/validate.py b/src/backend/langflow/api/v1/validate.py index 457db5bd3..65fb66bd2 100644 --- a/src/backend/langflow/api/v1/validate.py +++ b/src/backend/langflow/api/v1/validate.py @@ -58,6 +58,16 @@ def post_validate_prompt(prompt_request: ValidatePromptRequest): def get_old_custom_fields(prompt_request): try: + if ( + len(prompt_request.frontend_node.custom_fields) == 1 + and prompt_request.name == "" + ): + # If there is only one custom field and the name is empty string + # then we are dealing with the first prompt request after the node was created + prompt_request.name = list( + prompt_request.frontend_node.custom_fields.keys() + )[0] + old_custom_fields = prompt_request.frontend_node.custom_fields[ prompt_request.name ].copy() diff --git a/src/backend/langflow/components/agents/OpenAIConversationalAgent.py b/src/backend/langflow/components/agents/OpenAIConversationalAgent.py index e2b876978..ff1a993b1 100644 --- a/src/backend/langflow/components/agents/OpenAIConversationalAgent.py +++ b/src/backend/langflow/components/agents/OpenAIConversationalAgent.py @@ -42,8 +42,8 @@ class ConversationalAgent(CustomComponent): self, model_name: str, openai_api_key: str, - openai_api_base: str, tools: Tool, + openai_api_base: Optional[str] = None, memory: Optional[BaseMemory] = None, system_message: Optional[SystemMessagePromptTemplate] = None, max_token_limit: int = 2000, diff --git a/src/backend/langflow/components/chains/PromptRunner.py b/src/backend/langflow/components/chains/PromptRunner.py index 141941c38..db9283b07 100644 --- a/src/backend/langflow/components/chains/PromptRunner.py +++ b/src/backend/langflow/components/chains/PromptRunner.py @@ -16,17 +16,14 @@ class PromptRunner(CustomComponent): "info": "Make sure the prompt has all variables filled.", }, "code": {"show": False}, - "inputs": {"field_type": "code"}, } def build( - self, - llm: BaseLLM, - prompt: PromptTemplate, + self, llm: BaseLLM, prompt: PromptTemplate, inputs: dict = {} ) -> Document: chain = prompt | llm # The input is an empty dict because the prompt is already filled - result = chain.invoke({}) + result = chain.invoke(input=inputs) if hasattr(result, "content"): result = result.content self.repr_value = result diff --git a/src/backend/langflow/components/llms/HuggingFaceEndpoints.py b/src/backend/langflow/components/llms/HuggingFaceEndpoints.py new file mode 100644 index 000000000..ea2b4f20b --- /dev/null +++ b/src/backend/langflow/components/llms/HuggingFaceEndpoints.py @@ -0,0 +1,42 @@ +from typing import Optional +from langflow import CustomComponent +from langchain.llms import HuggingFaceEndpoint +from langchain.llms.base import BaseLLM + + +class HuggingFaceEndpointsComponent(CustomComponent): + display_name: str = "Hugging Face Inference API" + description: str = "LLM model from Hugging Face Inference API." + + def build_config(self): + return { + "endpoint_url": {"display_name": "Endpoint URL", "password": True}, + "task": { + "display_name": "Task", + "type": "select", + "options": ["text2text-generation", "text-generation", "summarization"], + }, + "huggingfacehub_api_token": {"display_name": "API token", "password": True}, + "model_kwargs": { + "display_name": "Model Keyword Arguments", + "field_type": "code", + }, + "code": {"show": False}, + } + + def build( + self, + endpoint_url: str, + task="text2text-generation", + huggingfacehub_api_token: Optional[str] = None, + model_kwargs: Optional[dict] = None, + ) -> BaseLLM: + try: + output = HuggingFaceEndpoint( + endpoint_url=endpoint_url, + task=task, + huggingfacehub_api_token=huggingfacehub_api_token, + ) + except Exception as e: + raise ValueError("Could not connect to HuggingFace Endpoints API.") from e + return output diff --git a/src/backend/langflow/components/llms/__init__.py b/src/backend/langflow/components/llms/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/backend/langflow/components/retrievers/MetalRetriever.py b/src/backend/langflow/components/retrievers/MetalRetriever.py new file mode 100644 index 000000000..b105cd24f --- /dev/null +++ b/src/backend/langflow/components/retrievers/MetalRetriever.py @@ -0,0 +1,28 @@ +from typing import Optional +from langflow import CustomComponent +from langchain.retrievers import MetalRetriever +from langchain.schema import BaseRetriever +from metal_sdk.metal import Metal # type: ignore + + +class MetalRetrieverComponent(CustomComponent): + display_name: str = "Metal Retriever" + description: str = "Retriever that uses the Metal API." + + def build_config(self): + return { + "api_key": {"display_name": "API Key", "password": True}, + "client_id": {"display_name": "Client ID", "password": True}, + "index_id": {"display_name": "Index ID"}, + "params": {"display_name": "Parameters"}, + "code": {"show": False}, + } + + def build( + self, api_key: str, client_id: str, index_id: str, params: Optional[dict] = None + ) -> BaseRetriever: + try: + metal = Metal(api_key=api_key, client_id=client_id, index_id=index_id) + except Exception as e: + raise ValueError("Could not connect to Metal API.") from e + return MetalRetriever(client=metal, params=params or {}) diff --git a/src/backend/langflow/components/retrievers/__init__.py b/src/backend/langflow/components/retrievers/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/backend/langflow/components/textsplitters/LanguageRecursiveTextSplitter.py b/src/backend/langflow/components/textsplitters/LanguageRecursiveTextSplitter.py new file mode 100644 index 000000000..636eb427e --- /dev/null +++ b/src/backend/langflow/components/textsplitters/LanguageRecursiveTextSplitter.py @@ -0,0 +1,80 @@ +from typing import Optional +from langflow import CustomComponent +from langchain.text_splitter import Language +from langchain.schema import Document + + +class LanguageRecursiveTextSplitterComponent(CustomComponent): + display_name: str = "Language Recursive Text Splitter" + description: str = "Split text into chunks of a specified length based on language." + documentation: str = "https://docs.langflow.org/components/text-splitters#languagerecursivetextsplitter" + + def build_config(self): + options = [x.value for x in Language] + return { + "documents": { + "display_name": "Documents", + "info": "The documents to split.", + }, + "separator_type": { + "display_name": "Separator Type", + "info": "The type of separator to use.", + "field_type": "str", + "options": options, + "value": "Python", + }, + "separators": { + "display_name": "Separators", + "info": "The characters to split on.", + "is_list": True, + }, + "chunk_size": { + "display_name": "Chunk Size", + "info": "The maximum length of each chunk.", + "field_type": "int", + "value": 1000, + }, + "chunk_overlap": { + "display_name": "Chunk Overlap", + "info": "The amount of overlap between chunks.", + "field_type": "int", + "value": 200, + }, + "code": {"show": False}, + } + + def build( + self, + documents: list[Document], + chunk_size: Optional[int] = 1000, + chunk_overlap: Optional[int] = 200, + separator_type: Optional[str] = "Python", + ) -> list[Document]: + """ + Split text into chunks of a specified length. + + Args: + separators (list[str]): The characters to split on. + chunk_size (int): The maximum length of each chunk. + chunk_overlap (int): The amount of overlap between chunks. + length_function (function): The function to use to calculate the length of the text. + + Returns: + list[str]: The chunks of text. + """ + from langchain.text_splitter import RecursiveCharacterTextSplitter + + # Make sure chunk_size and chunk_overlap are ints + if isinstance(chunk_size, str): + chunk_size = int(chunk_size) + if isinstance(chunk_overlap, str): + chunk_overlap = int(chunk_overlap) + + splitter = RecursiveCharacterTextSplitter.from_language( + language=Language(separator_type), + chunk_size=chunk_size, + chunk_overlap=chunk_overlap, + ) + + docs = splitter.split_documents(documents) + return docs diff --git a/src/backend/langflow/components/textsplitters/RecursiveCharacterTextSplitter.py b/src/backend/langflow/components/textsplitters/RecursiveCharacterTextSplitter.py new file mode 100644 index 000000000..751d2518c --- /dev/null +++ b/src/backend/langflow/components/textsplitters/RecursiveCharacterTextSplitter.py @@ -0,0 +1,79 @@ +from typing import Optional +from langflow import CustomComponent +from langchain.schema import Document +from langflow.utils.util import build_loader_repr_from_documents + + +class RecursiveCharacterTextSplitterComponent(CustomComponent): + display_name: str = "Recursive Character Text Splitter" + description: str = "Split text into chunks of a specified length." + documentation: str = "https://docs.langflow.org/components/text-splitters#recursivecharactertextsplitter" + + def build_config(self): + return { + "documents": { + "display_name": "Documents", + "info": "The documents to split.", + }, + "separators": { + "display_name": "Separators", + "info": 'The characters to split on.\nIf left empty defaults to ["\\n\\n", "\\n", " ", ""].', + "is_list": True, + }, + "chunk_size": { + "display_name": "Chunk Size", + "info": "The maximum length of each chunk.", + "field_type": "int", + "value": 1000, + }, + "chunk_overlap": { + "display_name": "Chunk Overlap", + "info": "The amount of overlap between chunks.", + "field_type": "int", + "value": 200, + }, + "code": {"show": False}, + } + + def build( + self, + documents: list[Document], + separators: Optional[list[str]] = None, + chunk_size: Optional[int] = 1000, + chunk_overlap: Optional[int] = 200, + ) -> list[Document]: + """ + Split text into chunks of a specified length. + + Args: + separators (list[str]): The characters to split on. + chunk_size (int): The maximum length of each chunk. + chunk_overlap (int): The amount of overlap between chunks. + length_function (function): The function to use to calculate the length of the text. + + Returns: + list[str]: The chunks of text. + """ + from langchain.text_splitter import RecursiveCharacterTextSplitter + + if separators == "": + separators = None + elif separators: + # check if the separators list has escaped characters + # if there are escaped characters, unescape them + separators = [x.encode().decode("unicode-escape") for x in separators] + + # Make sure chunk_size and chunk_overlap are ints + if isinstance(chunk_size, str): + chunk_size = int(chunk_size) + if isinstance(chunk_overlap, str): + chunk_overlap = int(chunk_overlap) + splitter = RecursiveCharacterTextSplitter( + separators=separators, + chunk_size=chunk_size, + chunk_overlap=chunk_overlap, + ) + + docs = splitter.split_documents(documents) + self.repr_value = build_loader_repr_from_documents(docs) + return docs diff --git a/src/backend/langflow/components/textsplitters/__init__.py b/src/backend/langflow/components/textsplitters/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/backend/langflow/components/utilities/GetRequest.py b/src/backend/langflow/components/utilities/GetRequest.py index 13ff0dc23..d5df32cca 100644 --- a/src/backend/langflow/components/utilities/GetRequest.py +++ b/src/backend/langflow/components/utilities/GetRequest.py @@ -19,7 +19,6 @@ class GetRequest(CustomComponent): }, "headers": { "display_name": "Headers", - "field_type": "code", "info": "The headers to send with the request.", }, "code": {"show": False}, diff --git a/src/backend/langflow/components/utilities/PostRequest.py b/src/backend/langflow/components/utilities/PostRequest.py index 4f7100d43..6857f4866 100644 --- a/src/backend/langflow/components/utilities/PostRequest.py +++ b/src/backend/langflow/components/utilities/PostRequest.py @@ -15,7 +15,6 @@ class PostRequest(CustomComponent): "url": {"display_name": "URL", "info": "The URL to make the request to."}, "headers": { "display_name": "Headers", - "field_type": "code", "info": "The headers to send with the request.", }, "code": {"show": False}, diff --git a/src/backend/langflow/components/utilities/UpdateRequest.py b/src/backend/langflow/components/utilities/UpdateRequest.py index 6e8991794..d18c94a56 100644 --- a/src/backend/langflow/components/utilities/UpdateRequest.py +++ b/src/backend/langflow/components/utilities/UpdateRequest.py @@ -15,7 +15,7 @@ class UpdateRequest(CustomComponent): "url": {"display_name": "URL", "info": "The URL to make the request to."}, "headers": { "display_name": "Headers", - "field_type": "code", + "field_type": "NestedDict", "info": "The headers to send with the request.", }, "code": {"show": False}, diff --git a/src/backend/langflow/config.yaml b/src/backend/langflow/config.yaml index d25893c25..48f7b1da1 100644 --- a/src/backend/langflow/config.yaml +++ b/src/backend/langflow/config.yaml @@ -171,8 +171,6 @@ prompts: textsplitters: CharacterTextSplitter: documentation: "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter" - RecursiveCharacterTextSplitter: - documentation: "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/recursive_text_splitter" toolkits: OpenAPIToolkit: documentation: "" diff --git a/src/backend/langflow/field_typing/__init__.py b/src/backend/langflow/field_typing/__init__.py new file mode 100644 index 000000000..927716b11 --- /dev/null +++ b/src/backend/langflow/field_typing/__init__.py @@ -0,0 +1,3 @@ +from .base import NestedDict + +__all__ = ["NestedDict"] diff --git a/src/backend/langflow/field_typing/base.py b/src/backend/langflow/field_typing/base.py new file mode 100644 index 000000000..ed3219888 --- /dev/null +++ b/src/backend/langflow/field_typing/base.py @@ -0,0 +1,4 @@ +from typing import Union, Dict + +# Type alias for more complex dicts +NestedDict = Dict[str, Union[str, Dict]] diff --git a/src/backend/langflow/graph/vertex/base.py b/src/backend/langflow/graph/vertex/base.py index 4c6262554..5f5f8eaa7 100644 --- a/src/backend/langflow/graph/vertex/base.py +++ b/src/backend/langflow/graph/vertex/base.py @@ -195,6 +195,19 @@ class Vertex: except Exception as exc: logger.debug(f"Error parsing code: {exc}") params[key] = value.get("value") + elif value.get("type") in ["dict", "NestedDict"]: + # When dict comes from the frontend it comes as a + # list of dicts, so we need to convert it to a dict + # before passing it to the build method + _value = value.get("value") + if isinstance(_value, list): + params[key] = { + k: v + for item in value.get("value", []) + for k, v in item.items() + } + elif isinstance(_value, dict): + params[key] = _value else: params[key] = value.get("value") diff --git a/src/backend/langflow/interface/run.py b/src/backend/langflow/interface/run.py index 8df41d3b3..531a3e247 100644 --- a/src/backend/langflow/interface/run.py +++ b/src/backend/langflow/interface/run.py @@ -45,8 +45,12 @@ def get_memory_key(langchain_object): "chat_history": "history", "history": "chat_history", } - memory_key = langchain_object.memory.memory_key - return mem_key_dict.get(memory_key) + # Check if memory_key attribute exists + if hasattr(langchain_object.memory, "memory_key"): + memory_key = langchain_object.memory.memory_key + return mem_key_dict.get(memory_key) + else: + return None # or some other default value or action def update_memory_keys(langchain_object, possible_new_mem_key): diff --git a/src/backend/langflow/interface/tools/util.py b/src/backend/langflow/interface/tools/util.py index f92386f18..fc91387ed 100644 --- a/src/backend/langflow/interface/tools/util.py +++ b/src/backend/langflow/interface/tools/util.py @@ -1,5 +1,6 @@ import ast import inspect +import textwrap from typing import Dict, Union from langchain.agents.tools import Tool @@ -7,7 +8,7 @@ from loguru import logger def get_func_tool_params(func, **kwargs) -> Union[Dict, None]: - tree = ast.parse(inspect.getsource(func)) + tree = ast.parse(textwrap.dedent(inspect.getsource(func))) # Iterate over the statements in the abstract syntax tree for node in ast.walk(tree): @@ -58,13 +59,7 @@ def get_func_tool_params(func, **kwargs) -> Union[Dict, None]: def get_class_tool_params(cls, **kwargs) -> Union[Dict, None]: - try: - tree = ast.parse(inspect.getsource(cls)) - except IndentationError: - logger.error( - f"Error parsing class {cls.__name__}. Make sure there are no tabs in the code." - ) - return None + tree = ast.parse(textwrap.dedent(inspect.getsource(cls))) tool_params = {} diff --git a/src/backend/langflow/interface/types.py b/src/backend/langflow/interface/types.py index 47743560e..fa9967649 100644 --- a/src/backend/langflow/interface/types.py +++ b/src/backend/langflow/interface/types.py @@ -5,6 +5,7 @@ from langflow.api.utils import merge_nested_dicts_with_renaming from langflow.interface.agents.base import agent_creator from langflow.interface.chains.base import chain_creator from langflow.interface.custom.constants import CUSTOM_COMPONENT_SUPPORTED_TYPES +from langflow.interface.custom.utils import extract_inner_type from langflow.interface.document_loaders.base import documentloader_creator from langflow.interface.embeddings.base import embedding_creator from langflow.interface.importing.utils import get_function_custom @@ -84,6 +85,8 @@ def build_langchain_types_dict(): # sourcery skip: dict-assign-update-to-union def process_type(field_type: str): + if field_type.startswith("list") or field_type.startswith("List"): + return extract_inner_type(field_type) return "prompt" if field_type == "Prompt" else field_type @@ -100,6 +103,7 @@ def add_new_custom_field( # if it is, update the value display_name = field_config.pop("display_name", field_name) field_type = field_config.pop("field_type", field_type) + field_contains_list = "list" in field_type.lower() field_type = process_type(field_type) field_value = field_config.pop("value", field_value) field_advanced = field_config.pop("advanced", False) @@ -110,7 +114,9 @@ def add_new_custom_field( # If options is a list, then it's a dropdown # If options is None, then it's a list of strings is_list = isinstance(field_config.get("options"), list) - field_config["is_list"] = is_list or field_config.get("is_list", False) + field_config["is_list"] = ( + is_list or field_config.get("is_list", False) or field_contains_list + ) if "name" in field_config: warnings.warn( @@ -172,7 +178,7 @@ def extract_type_from_optional(field_type): Returns: str: The extracted type, or an empty string if no type was found. """ - match = re.search(r"\[(.*?)\]", field_type) + match = re.search(r"\[(.*?)\]$", field_type) return match[1] if match else None @@ -284,31 +290,42 @@ def add_base_classes(frontend_node, return_types: List[str]): def build_langchain_template_custom_component(custom_component: CustomComponent): """Build a custom component template for the langchain""" - logger.debug("Building custom component template") - frontend_node = build_frontend_node(custom_component) + try: + logger.debug("Building custom component template") + frontend_node = build_frontend_node(custom_component) - if frontend_node is None: - return None - logger.debug("Built base frontend node") - template_config = custom_component.build_template_config + if frontend_node is None: + return None + logger.debug("Built base frontend node") + template_config = custom_component.build_template_config - update_attributes(frontend_node, template_config) - logger.debug("Updated attributes") - field_config = build_field_config(custom_component) - logger.debug("Built field config") - add_extra_fields( - frontend_node, field_config, custom_component.get_function_entrypoint_args - ) - logger.debug("Added extra fields") - frontend_node = add_code_field( - frontend_node, custom_component.code, field_config.get("code", {}) - ) - logger.debug("Added code field") - add_base_classes( - frontend_node, custom_component.get_function_entrypoint_return_type - ) - logger.debug("Added base classes") - return frontend_node + update_attributes(frontend_node, template_config) + logger.debug("Updated attributes") + field_config = build_field_config(custom_component) + logger.debug("Built field config") + add_extra_fields( + frontend_node, field_config, custom_component.get_function_entrypoint_args + ) + logger.debug("Added extra fields") + frontend_node = add_code_field( + frontend_node, custom_component.code, field_config.get("code", {}) + ) + logger.debug("Added code field") + add_base_classes( + frontend_node, custom_component.get_function_entrypoint_return_type + ) + logger.debug("Added base classes") + return frontend_node + except Exception as exc: + raise HTTPException( + status_code=400, + detail={ + "error": ( + "Invalid type convertion. Please check your code and try again." + ), + "traceback": traceback.format_exc(), + }, + ) from exc def load_files_from_path(path: str): diff --git a/src/backend/langflow/interface/utils.py b/src/backend/langflow/interface/utils.py index 26c28fe86..388697b2a 100644 --- a/src/backend/langflow/interface/utils.py +++ b/src/backend/langflow/interface/utils.py @@ -77,11 +77,16 @@ def set_langchain_cache(settings): import langchain from langflow.interface.importing.utils import import_class - langchain_cache_type = os.getenv("LANGFLOW_LANGCHAIN_CACHE") - cache_class = import_class( - f"langchain.cache.{langchain_cache_type or settings.LANGCHAIN_CACHE}" - ) + if cache_type := os.getenv("LANGFLOW_LANGCHAIN_CACHE"): + try: + cache_class = import_class( + f"langchain.cache.{cache_type or settings.LANGCHAIN_CACHE}" + ) - logger.debug(f"Setting up LLM caching with {cache_class.__name__}") - langchain.llm_cache = cache_class() - logger.info(f"LLM caching setup with {cache_class.__name__}") + logger.debug(f"Setting up LLM caching with {cache_class.__name__}") + langchain.llm_cache = cache_class() + logger.info(f"LLM caching setup with {cache_class.__name__}") + except ImportError: + logger.warning(f"Could not import {cache_type}. ") + else: + logger.info("No LLM cache set.") diff --git a/src/backend/langflow/main.py b/src/backend/langflow/main.py index f567e65bb..c869ec138 100644 --- a/src/backend/langflow/main.py +++ b/src/backend/langflow/main.py @@ -11,6 +11,7 @@ from langflow.api import router from langflow.interface.utils import setup_llm_caching from langflow.services.database.utils import initialize_database from langflow.services.manager import initialize_services, teardown_services +from langflow.services.plugins.langfuse import LangfuseInstance from langflow.utils.logger import configure @@ -41,6 +42,8 @@ def create_app(): app.on_event("startup")(initialize_database) app.on_event("startup")(setup_llm_caching) app.on_event("shutdown")(teardown_services) + app.on_event("startup")(LangfuseInstance.update) + app.on_event("shutdown")(LangfuseInstance.teardown) return app diff --git a/src/backend/langflow/processing/base.py b/src/backend/langflow/processing/base.py index c3d766f15..e5816306c 100644 --- a/src/backend/langflow/processing/base.py +++ b/src/backend/langflow/processing/base.py @@ -1,4 +1,4 @@ -from typing import Union +from typing import List, Union, TYPE_CHECKING from langflow.api.v1.callback import ( AsyncStreamingLLMCallbackHandler, StreamingLLMCallbackHandler, @@ -6,6 +6,52 @@ from langflow.api.v1.callback import ( from langflow.processing.process import fix_memory_inputs, format_actions from loguru import logger from langchain.agents.agent import AgentExecutor +from langchain.callbacks.base import BaseCallbackHandler + +if TYPE_CHECKING: + from langfuse.callback import CallbackHandler # type: ignore + + +def setup_callbacks(sync, trace_id, **kwargs): + """Setup callbacks for langchain object""" + callbacks = [] + if sync: + callbacks.append(StreamingLLMCallbackHandler(**kwargs)) + else: + callbacks.append(AsyncStreamingLLMCallbackHandler(**kwargs)) + + if langfuse_callback := get_langfuse_callback(trace_id=trace_id): + logger.debug("Langfuse callback loaded") + callbacks.append(langfuse_callback) + return callbacks + + +def get_langfuse_callback(trace_id): + from langflow.services.plugins.langfuse import LangfuseInstance + from langfuse.callback import CreateTrace + + logger.debug("Initializing langfuse callback") + if langfuse := LangfuseInstance.get(): + logger.debug("Langfuse credentials found") + try: + trace = langfuse.trace(CreateTrace(id=trace_id)) + return trace.getNewHandler() + except Exception as exc: + logger.error(f"Error initializing langfuse callback: {exc}") + + return None + + +def flush_langfuse_callback_if_present( + callbacks: List[Union[BaseCallbackHandler, "CallbackHandler"]] +): + """ + If langfuse callback is present, run callback.langfuse.flush() + """ + for callback in callbacks: + if hasattr(callback, "langfuse"): + callback.langfuse.flush() + break async def get_result_and_steps(langchain_object, inputs: Union[dict, str], **kwargs): @@ -27,13 +73,18 @@ async def get_result_and_steps(langchain_object, inputs: Union[dict, str], **kwa logger.error(f"Error fixing memory inputs: {exc}") try: - async_callbacks = [AsyncStreamingLLMCallbackHandler(**kwargs)] - output = await langchain_object.acall(inputs, callbacks=async_callbacks) + trace_id = kwargs.pop("session_id", None) + callbacks = setup_callbacks(sync=False, trace_id=trace_id, **kwargs) + output = await langchain_object.acall(inputs, callbacks=callbacks) except Exception as exc: # make the error message more informative logger.debug(f"Error: {str(exc)}") - sync_callbacks = [StreamingLLMCallbackHandler(**kwargs)] - output = langchain_object(inputs, callbacks=sync_callbacks) + trace_id = kwargs.pop("session_id", None) + callbacks = setup_callbacks(sync=True, trace_id=trace_id, **kwargs) + output = langchain_object(inputs, callbacks=callbacks) + + # if langfuse callback is present, run callback.langfuse.flush() + flush_langfuse_callback_if_present(callbacks) intermediate_steps = ( output.get("intermediate_steps", []) if isinstance(output, dict) else [] diff --git a/src/backend/langflow/processing/process.py b/src/backend/langflow/processing/process.py index b68711828..fa35bd348 100644 --- a/src/backend/langflow/processing/process.py +++ b/src/backend/langflow/processing/process.py @@ -12,6 +12,7 @@ from langflow.graph import Graph from langchain.chains.base import Chain from langchain.vectorstores.base import VectorStore from typing import Any, Dict, List, Optional, Tuple, Union +from langchain.schema import Document from pydantic import BaseModel @@ -139,10 +140,11 @@ def generate_result(langchain_object: Union[Chain, VectorStore], inputs: dict): logger.debug("Generated result and thought") elif isinstance(langchain_object, VectorStore): result = langchain_object.search(**inputs) + elif isinstance(langchain_object, Document): + result = langchain_object.dict() else: - raise ValueError( - f"Unknown langchain_object type: {type(langchain_object).__name__}" - ) + logger.warning(f"Unknown langchain_object type: {type(langchain_object)}") + result = langchain_object return result diff --git a/src/backend/langflow/services/chat/manager.py b/src/backend/langflow/services/chat/manager.py index bb86adfbd..2a2e1ce42 100644 --- a/src/backend/langflow/services/chat/manager.py +++ b/src/backend/langflow/services/chat/manager.py @@ -1,4 +1,5 @@ from collections import defaultdict +import uuid from fastapi import WebSocket, status from langflow.api.v1.schemas import ChatMessage, ChatResponse, FileResponse from langflow.interface.utils import pil_to_base64 @@ -47,6 +48,7 @@ class ChatService(Service): def __init__(self): self.active_connections: Dict[str, WebSocket] = {} + self.connection_ids: Dict[str, str] = {} self.chat_history = ChatHistory() self.chat_cache = cache_service self.chat_cache.attach(self.update) @@ -91,9 +93,13 @@ class ChatService(Service): async def connect(self, client_id: str, websocket: WebSocket): self.active_connections[client_id] = websocket + # This is to avoid having multiple clients with the same id + #! Temporary solution + self.connection_ids[client_id] = f"{client_id}-{uuid.uuid4()}" def disconnect(self, client_id: str): self.active_connections.pop(client_id, None) + self.connection_ids.pop(client_id, None) async def send_message(self, client_id: str, message: str): websocket = self.active_connections[client_id] @@ -135,6 +141,7 @@ class ChatService(Service): langchain_object=langchain_object, chat_inputs=chat_inputs, websocket=self.active_connections[client_id], + session_id=self.connection_ids[client_id], ) self.set_cache(client_id, langchain_object) except Exception as e: diff --git a/src/backend/langflow/services/chat/utils.py b/src/backend/langflow/services/chat/utils.py index d9c291757..a332e381e 100644 --- a/src/backend/langflow/services/chat/utils.py +++ b/src/backend/langflow/services/chat/utils.py @@ -9,6 +9,7 @@ async def process_graph( langchain_object, chat_inputs: ChatMessage, websocket: WebSocket, + session_id: str, ): langchain_object = try_setting_streaming_options(langchain_object, websocket) logger.debug("Loaded langchain object") @@ -27,7 +28,10 @@ async def process_graph( logger.debug("Generating result and thought") result, intermediate_steps = await get_result_and_steps( - langchain_object, chat_inputs.message, websocket=websocket + langchain_object, + chat_inputs.message, + websocket=websocket, + session_id=session_id, ) logger.debug("Generated result and intermediate_steps") return result, intermediate_steps diff --git a/src/backend/langflow/services/database/models/user/crud.py b/src/backend/langflow/services/database/models/user/crud.py index 3dc02a499..f7f5958fe 100644 --- a/src/backend/langflow/services/database/models/user/crud.py +++ b/src/backend/langflow/services/database/models/user/crud.py @@ -1,12 +1,12 @@ from datetime import datetime, timezone from typing import Union from uuid import UUID -from fastapi import Depends, HTTPException +from fastapi import Depends, HTTPException, status from langflow.services.database.models.user.user import User, UserUpdate from langflow.services.utils import get_session from sqlalchemy.exc import IntegrityError from sqlmodel import Session - +from typing import Optional from sqlalchemy.orm.attributes import flag_modified @@ -20,20 +20,26 @@ def get_user_by_id(db: Session, id: UUID) -> Union[User, None]: def update_user( - user_id: UUID, user: UserUpdate, db: Session = Depends(get_session) + user_db: Optional[User], user: UserUpdate, db: Session = Depends(get_session) ) -> User: - user_db = get_user_by_id(db, user_id) if not user_db: raise HTTPException(status_code=404, detail="User not found") - user_db_by_username = get_user_by_username(db, user.username) # type: ignore - if user_db_by_username and user_db_by_username.id != user_id: - raise HTTPException(status_code=409, detail="Username already exists") + # user_db_by_username = get_user_by_username(db, user.username) # type: ignore + # if user_db_by_username and user_db_by_username.id != user_id: + # raise HTTPException(status_code=409, detail="Username already exists") user_data = user.dict(exclude_unset=True) + changed = False for attr, value in user_data.items(): if hasattr(user_db, attr) and value is not None: setattr(user_db, attr, value) + changed = True + + if not changed: + raise HTTPException( + status_code=status.HTTP_304_NOT_MODIFIED, detail="Nothing to update" + ) user_db.updated_at = datetime.now(timezone.utc) flag_modified(user_db, "updated_at") @@ -49,5 +55,5 @@ def update_user( def update_user_last_login_at(user_id: UUID, db: Session = Depends(get_session)): user_data = UserUpdate(last_login_at=datetime.now(timezone.utc)) # type: ignore - - return update_user(user_id, user_data, db) + user = get_user_by_id(db, user_id) + return update_user(user, user_data, db) diff --git a/src/backend/langflow/services/database/models/user/user.py b/src/backend/langflow/services/database/models/user/user.py index 5f83b4d88..8bd42af00 100644 --- a/src/backend/langflow/services/database/models/user/user.py +++ b/src/backend/langflow/services/database/models/user/user.py @@ -15,6 +15,7 @@ class User(SQLModelSerializable, table=True): id: UUID = Field(default_factory=uuid4, primary_key=True, unique=True) username: str = Field(index=True, unique=True) password: str = Field() + profile_image: Optional[str] = Field(default=None) is_active: bool = Field(default=False) is_superuser: bool = Field(default=False) create_at: datetime = Field(default_factory=datetime.utcnow) @@ -32,6 +33,7 @@ class UserCreate(SQLModel): class UserRead(SQLModel): id: UUID = Field(default_factory=uuid4) username: str = Field() + profile_image: Optional[str] = Field() is_active: bool = Field() is_superuser: bool = Field() create_at: datetime = Field() @@ -40,7 +42,8 @@ class UserRead(SQLModel): class UserUpdate(SQLModel): - username: Optional[str] = Field() + profile_image: Optional[str] = Field() + password: Optional[str] = Field() is_active: Optional[bool] = Field() is_superuser: Optional[bool] = Field() last_login_at: Optional[datetime] = Field() diff --git a/src/backend/langflow/services/plugins/__init__.py b/src/backend/langflow/services/plugins/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/backend/langflow/services/plugins/langfuse.py b/src/backend/langflow/services/plugins/langfuse.py new file mode 100644 index 000000000..ce3e25c53 --- /dev/null +++ b/src/backend/langflow/services/plugins/langfuse.py @@ -0,0 +1,50 @@ +from langflow.services.utils import get_settings_manager +from langflow.utils.logger import logger + +### Temporary implementation +# This will be replaced by a plugin system once merged into 0.5.0 + + +class LangfuseInstance: + _instance = None + + @classmethod + def get(cls): + logger.debug("Getting Langfuse instance") + if cls._instance is None: + cls.create() + return cls._instance + + @classmethod + def create(cls): + logger.debug("Creating Langfuse instance") + from langfuse import Langfuse # type: ignore + + settings_manager = get_settings_manager() + + if ( + settings_manager.settings.LANGFUSE_PUBLIC_KEY + and settings_manager.settings.LANGFUSE_SECRET_KEY + ): + logger.debug("Langfuse credentials found") + cls._instance = Langfuse( + public_key=settings_manager.settings.LANGFUSE_PUBLIC_KEY, + secret_key=settings_manager.settings.LANGFUSE_SECRET_KEY, + host=settings_manager.settings.LANGFUSE_HOST, + ) + else: + logger.debug("No Langfuse credentials found") + cls._instance = None + + @classmethod + def update(cls): + logger.debug("Updating Langfuse instance") + cls._instance = None + cls.create() + + @classmethod + def teardown(cls): + logger.debug("Tearing down Langfuse instance") + if cls._instance is not None: + cls._instance.flush() + cls._instance = None diff --git a/src/backend/langflow/services/settings/auth.py b/src/backend/langflow/services/settings/auth.py index d1f8197f0..87a156df7 100644 --- a/src/backend/langflow/services/settings/auth.py +++ b/src/backend/langflow/services/settings/auth.py @@ -30,7 +30,7 @@ class AuthSettings(BaseSettings): # If AUTO_LOGIN = True # > The application does not request login and logs in automatically as a super user. - AUTO_LOGIN: bool = False + AUTO_LOGIN: bool = True FIRST_SUPERUSER: str = "langflow" FIRST_SUPERUSER_PASSWORD: str = "langflow" diff --git a/src/backend/langflow/services/settings/base.py b/src/backend/langflow/services/settings/base.py index 951859f00..14e3f9928 100644 --- a/src/backend/langflow/services/settings/base.py +++ b/src/backend/langflow/services/settings/base.py @@ -48,6 +48,10 @@ class Settings(BaseSettings): REDIS_DB: int = 0 REDIS_CACHE_EXPIRE: int = 3600 + LANGFUSE_SECRET_KEY: Optional[str] = None + LANGFUSE_PUBLIC_KEY: Optional[str] = None + LANGFUSE_HOST: Optional[str] = None + @validator("CONFIG_DIR", pre=True, allow_reuse=True) def set_langflow_dir(cls, value): if not value: diff --git a/src/backend/langflow/template/frontend_node/base.py b/src/backend/langflow/template/frontend_node/base.py index fe19b5652..442e2ffd7 100644 --- a/src/backend/langflow/template/frontend_node/base.py +++ b/src/backend/langflow/template/frontend_node/base.py @@ -140,13 +140,16 @@ class FrontendNode(BaseModel): @staticmethod def handle_dict_type(field: TemplateField, _type: str) -> str: """Handles 'dict' type by replacing it with 'code' or 'file' based on the field name.""" - if "dict" in _type.lower(): - if field.name == "dict_": - field.field_type = "file" - field.suffixes = [".json", ".yaml", ".yml"] - field.file_types = ["json", "yaml", "yml"] - else: - field.field_type = "code" + if "dict" in _type.lower() and field.name == "dict_": + field.field_type = "file" + field.suffixes = [".json", ".yaml", ".yml"] + field.file_types = ["json", "yaml", "yml"] + elif ( + _type.startswith("Dict") + or _type.startswith("Mapping") + or _type.startswith("dict") + ): + field.field_type = "dict" return _type @staticmethod @@ -240,20 +243,6 @@ class FrontendNode(BaseModel): "description", } - @staticmethod - def replace_dict_with_code_or_file( - field: TemplateField, _type: str, key: str - ) -> str: - """Replaces 'dict' type with 'code' or 'file'.""" - if "dict" in _type.lower(): - if key == "dict_": - field.field_type = "file" - field.suffixes = [".json", ".yaml", ".yml"] - field.file_types = ["json", "yaml", "yml"] - else: - field.field_type = "code" - return field.field_type - @staticmethod def set_field_default_value(field: TemplateField, value: dict, key: str) -> None: """Sets the field value with the default value if present.""" diff --git a/src/backend/langflow/template/frontend_node/documentloaders.py b/src/backend/langflow/template/frontend_node/documentloaders.py index cdf67e54a..8118593f3 100644 --- a/src/backend/langflow/template/frontend_node/documentloaders.py +++ b/src/backend/langflow/template/frontend_node/documentloaders.py @@ -170,11 +170,11 @@ class DocumentLoaderFrontNode(FrontendNode): # add a metadata field of type dict self.template.add_field( TemplateField( - field_type="code", + field_type="dict", required=True, show=True, name="metadata", - value="{}", + value={}, display_name="Metadata", multiline=False, ) diff --git a/src/backend/langflow/template/frontend_node/embeddings.py b/src/backend/langflow/template/frontend_node/embeddings.py index 4e7e25112..665328e78 100644 --- a/src/backend/langflow/template/frontend_node/embeddings.py +++ b/src/backend/langflow/template/frontend_node/embeddings.py @@ -89,7 +89,7 @@ class EmbeddingFrontendNode(FrontendNode): if field.name == "headers": field.show = False if field.name == "model_kwargs": - field.field_type = "code" + field.field_type = "dict" field.advanced = True field.show = True elif field.name in [ diff --git a/src/backend/langflow/template/frontend_node/formatter/field_formatters.py b/src/backend/langflow/template/frontend_node/formatter/field_formatters.py index 7987b134a..247f3b421 100644 --- a/src/backend/langflow/template/frontend_node/formatter/field_formatters.py +++ b/src/backend/langflow/template/frontend_node/formatter/field_formatters.py @@ -153,10 +153,13 @@ class DictCodeFileFormatter(FieldFormatter): key = field.name value = field.to_dict() _type = value["type"] - if "dict" in _type.lower(): - if key == "dict_": - field.field_type = "file" - field.suffixes = [".json", ".yaml", ".yml"] - field.file_types = ["json", "yaml", "yml"] - else: - field.field_type = "code" + if "dict" in _type.lower() and key == "dict_": + field.field_type = "file" + field.suffixes = [".json", ".yaml", ".yml"] + field.file_types = ["json", "yaml", "yml"] + elif ( + _type.startswith("Dict") + or _type.startswith("Mapping") + or _type.startswith("dict") + ): + field.field_type = "dict" diff --git a/src/backend/langflow/template/frontend_node/llms.py b/src/backend/langflow/template/frontend_node/llms.py index 01098724e..b8e007a27 100644 --- a/src/backend/langflow/template/frontend_node/llms.py +++ b/src/backend/langflow/template/frontend_node/llms.py @@ -131,7 +131,7 @@ class LLMFrontendNode(FrontendNode): if display_name := display_names_dict.get(field.name): field.display_name = display_name if field.name == "model_kwargs": - field.field_type = "code" + field.field_type = "dict" field.advanced = True field.show = True elif field.name in [ diff --git a/src/backend/langflow/template/frontend_node/prompts.py b/src/backend/langflow/template/frontend_node/prompts.py index da5d2a300..c52b1901c 100644 --- a/src/backend/langflow/template/frontend_node/prompts.py +++ b/src/backend/langflow/template/frontend_node/prompts.py @@ -15,6 +15,7 @@ from langflow.template.template.base import Template class PromptFrontendNode(FrontendNode): @staticmethod def format_field(field: TemplateField, name: Optional[str] = None) -> None: + FrontendNode.format_field(field, name) # if field.field_type == "StringPromptTemplate" # change it to str PROMPT_FIELDS = [ diff --git a/src/backend/langflow/template/frontend_node/utilities.py b/src/backend/langflow/template/frontend_node/utilities.py index 9dedacd0f..a5adb219d 100644 --- a/src/backend/langflow/template/frontend_node/utilities.py +++ b/src/backend/langflow/template/frontend_node/utilities.py @@ -21,5 +21,4 @@ class UtilitiesFrontendNode(FrontendNode): field.field_type = "str" if isinstance(field.value, dict): - field.field_type = "code" field.value = orjson_dumps(field.value) diff --git a/src/backend/langflow/template/frontend_node/vectorstores.py b/src/backend/langflow/template/frontend_node/vectorstores.py index 23c293437..73e9aaaca 100644 --- a/src/backend/langflow/template/frontend_node/vectorstores.py +++ b/src/backend/langflow/template/frontend_node/vectorstores.py @@ -56,7 +56,7 @@ class VectorStoreFrontendNode(FrontendNode): # Add search_kwargs field extra_field = TemplateField( name="search_kwargs", - field_type="code", + field_type="NestedDict", required=False, placeholder="", show=True, diff --git a/src/backend/langflow/utils/constants.py b/src/backend/langflow/utils/constants.py index adf4cf63c..0c97b56a2 100644 --- a/src/backend/langflow/utils/constants.py +++ b/src/backend/langflow/utils/constants.py @@ -48,5 +48,16 @@ def python_function(text: str) -> str: return text """ -DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any", "prompt"] + PYTHON_BASIC_TYPES = [str, bool, int, float, tuple, list, dict, set] +DIRECT_TYPES = [ + "str", + "bool", + "dict", + "int", + "float", + "Any", + "prompt", + "code", + "NestedDict", +] diff --git a/src/backend/langflow/utils/util.py b/src/backend/langflow/utils/util.py index 2c8f92ee1..4fd9350d2 100644 --- a/src/backend/langflow/utils/util.py +++ b/src/backend/langflow/utils/util.py @@ -2,12 +2,13 @@ import re import inspect import importlib from functools import wraps -from typing import Optional, Dict, Any, Union +from typing import List, Optional, Dict, Any, Union from docstring_parser import parse from langflow.template.frontend_node.constants import FORCE_SHOW_FIELDS from langflow.utils import constants +from langchain.schema import Document def build_template_from_function( @@ -275,8 +276,6 @@ def format_dict( value["password"] = is_password_field(key) value["multiline"] = is_multiline_field(key) - replace_dict_type_with_code(value) - if key == "dict_": set_dict_file_attributes(value) @@ -406,14 +405,6 @@ def is_multiline_field(key: str) -> bool: } -def replace_dict_type_with_code(value: Dict[str, Any]) -> None: - """ - Replaces the type value with 'code' if the type is a dict. - """ - if "dict" in value["type"].lower(): - value["type"] = "code" - - def set_dict_file_attributes(value: Dict[str, Any]) -> None: """ Sets the file attributes for the 'dict_' key. @@ -456,3 +447,12 @@ def add_options_to_field( value["options"] = options_map[class_name] value["list"] = True value["value"] = options_map[class_name][0] + + +def build_loader_repr_from_documents(documents: List[Document]) -> str: + if documents: + avg_length = sum(len(doc.page_content) for doc in documents) / len(documents) + return f"""{len(documents)} documents + \nAvg. Document Length (characters): {int(avg_length)} + Documents: {documents[:3]}...""" + return "0 documents" diff --git a/src/frontend/.github/workflows/playwright.yml b/src/frontend/.github/workflows/playwright.yml new file mode 100644 index 000000000..90b6b700d --- /dev/null +++ b/src/frontend/.github/workflows/playwright.yml @@ -0,0 +1,27 @@ +name: Playwright Tests +on: + push: + branches: [ main, master ] + pull_request: + branches: [ main, master ] +jobs: + test: + timeout-minutes: 60 + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + - uses: actions/setup-node@v3 + with: + node-version: 18 + - name: Install dependencies + run: npm ci + - name: Install Playwright Browsers + run: npx playwright install --with-deps + - name: Run Playwright tests + run: npx playwright test + - uses: actions/upload-artifact@v3 + if: always() + with: + name: playwright-report + path: playwright-report/ + retention-days: 30 diff --git a/src/frontend/.gitignore b/src/frontend/.gitignore index 4d29575de..9ad9e7fb4 100644 --- a/src/frontend/.gitignore +++ b/src/frontend/.gitignore @@ -21,3 +21,6 @@ npm-debug.log* yarn-debug.log* yarn-error.log* +/test-results/ +/playwright-report/ +/playwright/.cache/ diff --git a/src/frontend/harFiles/langflow.har b/src/frontend/harFiles/langflow.har new file mode 100644 index 000000000..2f73c3515 --- /dev/null +++ b/src/frontend/harFiles/langflow.har @@ -0,0 +1,229 @@ +{ + "log": { + "version": "1.2", + "creator": { + "name": "Playwright", + "version": "1.37.1" + }, + "browser": { + "name": "chromium", + "version": "116.0.5845.82" + }, + "entries": [ + { + "startedDateTime": "2023-08-31T14:55:35.502Z", + "time": 0.727, + "request": { + "method": "GET", + "url": "http://localhost:3000/api/v1/auto_login", + "httpVersion": "HTTP/1.1", + "cookies": [], + "headers": [ + { "name": "Accept", "value": "application/json, text/plain, */*" }, + { "name": "Accept-Encoding", "value": "gzip, deflate, br" }, + { "name": "Accept-Language", "value": "en-US,en;q=0.9" }, + { "name": "Connection", "value": "keep-alive" }, + { "name": "Host", "value": "localhost:3000" }, + { "name": "Referer", "value": "http://localhost:3000/" }, + { "name": "Sec-Fetch-Dest", "value": "empty" }, + { "name": "Sec-Fetch-Mode", "value": "cors" }, + { "name": "Sec-Fetch-Site", "value": "same-origin" }, + { "name": "User-Agent", "value": "Mozilla/5.0 (X11; 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retriever.\",\"base_classes\":[\"Chain\",\"BaseConversationalRetrievalChain\",\"ConversationalRetrievalChain\",\"function\"],\"display_name\":\"ConversationalRetrievalChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/chains/popular/chat_vector_db\",\"beta\":false,\"error\":null},\"LLMChain\":{\"template\":{\"callbacks\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"callbacks\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"langchain.callbacks.base.BaseCallbackHandler\",\"list\":true},\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseMemory\",\"list\":false},\"output_parser\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"output_parser\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLLMOutputParser\",\"list\":false},\"prompt\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BasePromptTemplate\",\"list\":false},\"llm_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"llm_kwargs\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"metadata\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"output_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"text\",\"password\":false,\"name\":\"output_key\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"return_final_only\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":true,\"password\":false,\"name\":\"return_final_only\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"tags\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"tags\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"verbose\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"verbose\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"LLMChain\"},\"description\":\"Chain to run queries against LLMs.\",\"base_classes\":[\"Chain\",\"LLMChain\",\"function\"],\"display_name\":\"LLMChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/chains/foundational/llm_chain\",\"beta\":false,\"error\":null},\"LLMCheckerChain\":{\"template\":{\"check_assertions_prompt\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":{\"input_variables\":[\"assertions\"],\"output_parser\":null,\"partial_variables\":{},\"template\":\"Here is a bullet point list of assertions:\\n{assertions}\\nFor each assertion, determine whether it is true or false. If it is false, explain why.\\n\\n\",\"template_format\":\"f-string\",\"validate_template\":true,\"_type\":\"prompt\"},\"password\":false,\"name\":\"check_assertions_prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"PromptTemplate\",\"list\":false},\"create_draft_answer_prompt\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":{\"input_variables\":[\"question\"],\"output_parser\":null,\"partial_variables\":{},\"template\":\"{question}\\n\\n\",\"template_format\":\"f-string\",\"validate_template\":true,\"_type\":\"prompt\"},\"password\":false,\"name\":\"create_draft_answer_prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"PromptTemplate\",\"list\":false},\"list_assertions_prompt\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":{\"input_variables\":[\"statement\"],\"output_parser\":null,\"partial_variables\":{},\"template\":\"Here is a statement:\\n{statement}\\nMake a bullet point list of the assumptions you made when producing the above statement.\\n\\n\",\"template_format\":\"f-string\",\"validate_template\":true,\"_type\":\"prompt\"},\"password\":false,\"name\":\"list_assertions_prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"PromptTemplate\",\"list\":false},\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"revised_answer_prompt\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":{\"input_variables\":[\"checked_assertions\",\"question\"],\"output_parser\":null,\"partial_variables\":{},\"template\":\"{checked_assertions}\\n\\nQuestion: In light of the above assertions and checks, how would you answer the question '{question}'?\\n\\nAnswer:\",\"template_format\":\"f-string\",\"validate_template\":true,\"_type\":\"prompt\"},\"password\":false,\"name\":\"revised_answer_prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"PromptTemplate\",\"list\":false},\"_type\":\"LLMCheckerChain\"},\"description\":\"\",\"base_classes\":[\"Chain\",\"LLMCheckerChain\",\"function\"],\"display_name\":\"LLMCheckerChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/chains/additional/llm_checker\",\"beta\":false,\"error\":null},\"LLMMathChain\":{\"template\":{\"callbacks\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"callbacks\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"langchain.callbacks.base.BaseCallbackHandler\",\"list\":true},\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"llm_chain\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm_chain\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"LLMChain\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseMemory\",\"list\":false},\"prompt\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":{\"input_variables\":[\"question\"],\"output_parser\":null,\"partial_variables\":{},\"template\":\"Translate a math problem into a expression that can be executed using Python's numexpr library. Use the output of running this code to answer the question.\\n\\nQuestion: ${{Question with math problem.}}\\n```text\\n${{single line mathematical expression that solves the problem}}\\n```\\n...numexpr.evaluate(text)...\\n```output\\n${{Output of running the code}}\\n```\\nAnswer: ${{Answer}}\\n\\nBegin.\\n\\nQuestion: What is 37593 * 67?\\n```text\\n37593 * 67\\n```\\n...numexpr.evaluate(\\\"37593 * 67\\\")...\\n```output\\n2518731\\n```\\nAnswer: 2518731\\n\\nQuestion: 37593^(1/5)\\n```text\\n37593**(1/5)\\n```\\n...numexpr.evaluate(\\\"37593**(1/5)\\\")...\\n```output\\n8.222831614237718\\n```\\nAnswer: 8.222831614237718\\n\\nQuestion: {question}\\n\",\"template_format\":\"f-string\",\"validate_template\":true,\"_type\":\"prompt\"},\"password\":false,\"name\":\"prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BasePromptTemplate\",\"list\":false},\"input_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"question\",\"password\":false,\"name\":\"input_key\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"metadata\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"output_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"answer\",\"password\":false,\"name\":\"output_key\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"tags\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"tags\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"verbose\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"verbose\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"LLMMathChain\"},\"description\":\"Chain that interprets a prompt and executes python code to do math.\",\"base_classes\":[\"Chain\",\"LLMMathChain\",\"function\"],\"display_name\":\"LLMMathChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/chains/additional/llm_math\",\"beta\":false,\"error\":null},\"RetrievalQA\":{\"template\":{\"callbacks\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"callbacks\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"langchain.callbacks.base.BaseCallbackHandler\",\"list\":true},\"combine_documents_chain\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"combine_documents_chain\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseCombineDocumentsChain\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseMemory\",\"list\":false},\"retriever\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"retriever\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseRetriever\",\"list\":false},\"input_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"query\",\"password\":false,\"name\":\"input_key\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"metadata\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"output_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"result\",\"password\":false,\"name\":\"output_key\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"return_source_documents\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":true,\"password\":false,\"name\":\"return_source_documents\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"tags\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"tags\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"verbose\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"verbose\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"RetrievalQA\"},\"description\":\"Chain for question-answering against an index.\",\"base_classes\":[\"Chain\",\"BaseRetrievalQA\",\"RetrievalQA\",\"function\"],\"display_name\":\"RetrievalQA\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/chains/popular/vector_db_qa\",\"beta\":false,\"error\":null},\"RetrievalQAWithSourcesChain\":{\"template\":{\"callbacks\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"callbacks\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"langchain.callbacks.base.BaseCallbackHandler\",\"list\":true},\"combine_documents_chain\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"combine_documents_chain\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseCombineDocumentsChain\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseMemory\",\"list\":false},\"retriever\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"retriever\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseRetriever\",\"list\":false},\"answer_key\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"answer\",\"password\":false,\"name\":\"answer_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"input_docs_key\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"docs\",\"password\":false,\"name\":\"input_docs_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"max_tokens_limit\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":3375,\"password\":false,\"name\":\"max_tokens_limit\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"metadata\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"question_key\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"question\",\"password\":false,\"name\":\"question_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"reduce_k_below_max_tokens\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"reduce_k_below_max_tokens\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"return_source_documents\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":true,\"password\":false,\"name\":\"return_source_documents\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"sources_answer_key\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"sources\",\"password\":false,\"name\":\"sources_answer_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"tags\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"tags\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"verbose\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"verbose\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"RetrievalQAWithSourcesChain\"},\"description\":\"Question-answering with sources over an index.\",\"base_classes\":[\"Chain\",\"RetrievalQAWithSourcesChain\",\"BaseQAWithSourcesChain\",\"function\"],\"display_name\":\"RetrievalQAWithSourcesChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"SQLDatabaseChain\":{\"template\":{\"db\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"db\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"SQLDatabase\",\"list\":false},\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"prompt\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BasePromptTemplate\",\"list\":false},\"_type\":\"SQLDatabaseChain\"},\"description\":\"\",\"base_classes\":[\"Chain\",\"SQLDatabaseChain\",\"function\"],\"display_name\":\"SQLDatabaseChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"CombineDocsChain\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"chain_type\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"stuff\",\"password\":false,\"options\":[\"stuff\",\"map_reduce\",\"map_rerank\",\"refine\"],\"name\":\"chain_type\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"_type\":\"load_qa_chain\"},\"description\":\"Load question answering chain.\",\"base_classes\":[\"BaseCombineDocumentsChain\",\"function\"],\"display_name\":\"CombineDocsChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"SeriesCharacterChain\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"character\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"character\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"series\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"series\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"SeriesCharacterChain\"},\"description\":\"SeriesCharacterChain is a chain you can use to have a conversation with a character from a series.\",\"base_classes\":[\"LLMChain\",\"BaseCustomChain\",\"Chain\",\"ConversationChain\",\"SeriesCharacterChain\",\"function\"],\"display_name\":\"SeriesCharacterChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"MidJourneyPromptChain\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseChatMemory\",\"list\":false},\"_type\":\"MidJourneyPromptChain\"},\"description\":\"MidJourneyPromptChain is a chain you can use to generate new MidJourney prompts.\",\"base_classes\":[\"LLMChain\",\"BaseCustomChain\",\"Chain\",\"ConversationChain\",\"MidJourneyPromptChain\"],\"display_name\":\"MidJourneyPromptChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"TimeTravelGuideChain\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseChatMemory\",\"list\":false},\"_type\":\"TimeTravelGuideChain\"},\"description\":\"Time travel guide chain.\",\"base_classes\":[\"LLMChain\",\"BaseCustomChain\",\"TimeTravelGuideChain\",\"Chain\",\"ConversationChain\"],\"display_name\":\"TimeTravelGuideChain\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"PromptRunner\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"from langflow import CustomComponent\\n\\nfrom langchain.llms.base import BaseLLM\\nfrom langchain import PromptTemplate\\nfrom langchain.schema import Document\\n\\n\\nclass PromptRunner(CustomComponent):\\n display_name: str = \\\"Prompt Runner\\\"\\n description: str = \\\"Run a Chain with the given PromptTemplate\\\"\\n beta = True\\n field_config = {\\n \\\"llm\\\": {\\\"display_name\\\": \\\"LLM\\\"},\\n \\\"prompt\\\": {\\n \\\"display_name\\\": \\\"Prompt Template\\\",\\n \\\"info\\\": \\\"Make sure the prompt has all variables filled.\\\",\\n },\\n \\\"code\\\": {\\\"show\\\": False},\\n \\\"inputs\\\": {\\\"field_type\\\": \\\"code\\\"},\\n }\\n\\n def build(\\n self,\\n llm: BaseLLM,\\n prompt: PromptTemplate,\\n ) -> Document:\\n chain = prompt | llm\\n # The input is an empty dict because the prompt is already filled\\n result = chain.invoke({})\\n if hasattr(result, \\\"content\\\"):\\n result = result.content\\n self.repr_value = result\\n return Document(page_content=str(result))\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLLM\",\"list\":false},\"prompt\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"prompt\",\"display_name\":\"Prompt Template\",\"advanced\":false,\"dynamic\":false,\"info\":\"Make sure the prompt has all variables filled.\",\"type\":\"PromptTemplate\",\"list\":false}},\"description\":\"Run a Chain with the given PromptTemplate\",\"base_classes\":[\"Document\"],\"display_name\":\"Prompt Runner\",\"custom_fields\":{\"llm\":null,\"prompt\":null},\"output_types\":[\"PromptRunner\"],\"documentation\":\"\",\"beta\":true,\"error\":null}},\"agents\":{\"ZeroShotAgent\":{\"template\":{\"callback_manager\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"callback_manager\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseCallbackManager\",\"list\":false},\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"output_parser\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"output_parser\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"AgentOutputParser\",\"list\":false},\"tools\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"tools\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseTool\",\"list\":true},\"format_instructions\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"Use the following format:\\n\\nQuestion: the input question you must answer\\nThought: you should always think about what to do\\nAction: the action to take, should be one of [{tool_names}]\\nAction Input: the input to the action\\nObservation: the result of the action\\n... (this Thought/Action/Action Input/Observation can repeat N times)\\nThought: I now know the final answer\\nFinal Answer: the final answer to the original input question\",\"password\":false,\"name\":\"format_instructions\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"input_variables\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"input_variables\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"prefix\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"Answer the following questions as best you can. You have access to the following tools:\",\"password\":false,\"name\":\"prefix\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"suffix\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"Begin!\\n\\nQuestion: {input}\\nThought:{agent_scratchpad}\",\"password\":false,\"name\":\"suffix\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"ZeroShotAgent\"},\"description\":\"Construct an agent from an LLM and tools.\",\"base_classes\":[\"ZeroShotAgent\",\"BaseSingleActionAgent\",\"Agent\",\"function\"],\"display_name\":\"ZeroShotAgent\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent\",\"beta\":false,\"error\":null},\"JsonAgent\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"toolkit\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"toolkit\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseToolkit\",\"list\":false},\"_type\":\"json_agent\"},\"description\":\"Construct a json agent from an LLM and tools.\",\"base_classes\":[\"AgentExecutor\"],\"display_name\":\"JsonAgent\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/agents/toolkits/openapi\",\"beta\":false,\"error\":null},\"CSVAgent\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"path\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"suffixes\":[\".csv\"],\"password\":false,\"name\":\"path\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"file\",\"list\":false,\"fileTypes\":[\"csv\"],\"file_path\":null},\"_type\":\"csv_agent\"},\"description\":\"Construct a CSV agent from a CSV and tools.\",\"base_classes\":[\"AgentExecutor\"],\"display_name\":\"CSVAgent\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/agents/toolkits/csv\",\"beta\":false,\"error\":null},\"AgentInitializer\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseChatMemory\",\"list\":false},\"tools\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"tools\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Tool\",\"list\":true},\"agent\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"zero-shot-react-description\",\"password\":false,\"options\":[\"zero-shot-react-description\",\"react-docstore\",\"self-ask-with-search\",\"conversational-react-description\",\"openai-functions\",\"openai-multi-functions\"],\"name\":\"agent\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"_type\":\"initialize_agent\"},\"description\":\"Construct a zero shot agent from an LLM and tools.\",\"base_classes\":[\"AgentExecutor\",\"function\"],\"display_name\":\"AgentInitializer\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/agents/agent_types/\",\"beta\":false,\"error\":null},\"VectorStoreAgent\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"vectorstoreinfo\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"vectorstoreinfo\",\"display_name\":\"Vector Store Info\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"VectorStoreInfo\",\"list\":false},\"_type\":\"vectorstore_agent\"},\"description\":\"Construct an agent from a Vector Store.\",\"base_classes\":[\"AgentExecutor\"],\"display_name\":\"VectorStoreAgent\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"VectorStoreRouterAgent\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"vectorstoreroutertoolkit\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"vectorstoreroutertoolkit\",\"display_name\":\"Vector Store Router Toolkit\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"VectorStoreRouterToolkit\",\"list\":false},\"_type\":\"vectorstorerouter_agent\"},\"description\":\"Construct an agent from a Vector Store Router.\",\"base_classes\":[\"AgentExecutor\"],\"display_name\":\"VectorStoreRouterAgent\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"SQLAgent\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"display_name\":\"LLM\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLanguageModel\",\"list\":false},\"database_uri\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"password\":false,\"name\":\"database_uri\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"sql_agent\"},\"description\":\"Construct an SQL agent from an LLM and tools.\",\"base_classes\":[\"AgentExecutor\"],\"display_name\":\"SQLAgent\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"OpenAIConversationalAgent\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"from langflow import CustomComponent\\nfrom typing import Optional\\nfrom langchain.prompts import SystemMessagePromptTemplate\\nfrom langchain.tools import Tool\\nfrom langchain.schema.memory import BaseMemory\\nfrom langchain.chat_models import ChatOpenAI\\n\\nfrom langchain.agents.agent import AgentExecutor\\nfrom langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent\\nfrom langchain.memory.token_buffer import ConversationTokenBufferMemory\\nfrom langchain.prompts.chat import MessagesPlaceholder\\nfrom langchain.agents.agent_toolkits.conversational_retrieval.openai_functions import (\\n _get_default_system_message,\\n)\\n\\n\\nclass ConversationalAgent(CustomComponent):\\n display_name: str = \\\"OpenAI Conversational Agent\\\"\\n description: str = \\\"Conversational Agent that can use OpenAI's function calling API\\\"\\n\\n def build_config(self):\\n openai_function_models = [\\n \\\"gpt-3.5-turbo-0613\\\",\\n \\\"gpt-3.5-turbo-16k-0613\\\",\\n \\\"gpt-4-0613\\\",\\n \\\"gpt-4-32k-0613\\\",\\n ]\\n return {\\n \\\"tools\\\": {\\\"is_list\\\": True, \\\"display_name\\\": \\\"Tools\\\"},\\n \\\"memory\\\": {\\\"display_name\\\": \\\"Memory\\\"},\\n \\\"system_message\\\": {\\\"display_name\\\": \\\"System Message\\\"},\\n \\\"max_token_limit\\\": {\\\"display_name\\\": \\\"Max Token Limit\\\"},\\n \\\"model_name\\\": {\\n \\\"display_name\\\": \\\"Model Name\\\",\\n \\\"options\\\": openai_function_models,\\n \\\"value\\\": openai_function_models[0],\\n },\\n \\\"code\\\": {\\\"show\\\": False},\\n }\\n\\n def build(\\n self,\\n model_name: str,\\n openai_api_key: str,\\n openai_api_base: str,\\n tools: Tool,\\n memory: Optional[BaseMemory] = None,\\n system_message: Optional[SystemMessagePromptTemplate] = None,\\n max_token_limit: int = 2000,\\n ) -> AgentExecutor:\\n llm = ChatOpenAI(\\n model=model_name,\\n openai_api_key=openai_api_key,\\n openai_api_base=openai_api_base,\\n )\\n if not memory:\\n memory_key = \\\"chat_history\\\"\\n memory = ConversationTokenBufferMemory(\\n memory_key=memory_key,\\n return_messages=True,\\n output_key=\\\"output\\\",\\n llm=llm,\\n max_token_limit=max_token_limit,\\n )\\n else:\\n memory_key = memory.memory_key # type: ignore\\n\\n _system_message = system_message or _get_default_system_message()\\n prompt = OpenAIFunctionsAgent.create_prompt(\\n system_message=_system_message, # type: ignore\\n extra_prompt_messages=[MessagesPlaceholder(variable_name=memory_key)],\\n )\\n agent = OpenAIFunctionsAgent(\\n llm=llm, tools=tools, prompt=prompt # type: ignore\\n )\\n return AgentExecutor(\\n agent=agent,\\n tools=tools, # type: ignore\\n memory=memory,\\n verbose=True,\\n return_intermediate_steps=True,\\n )\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"max_token_limit\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":2000,\"password\":false,\"name\":\"max_token_limit\",\"display_name\":\"Max Token Limit\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"memory\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"memory\",\"display_name\":\"Memory\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseMemory\",\"list\":false},\"model_name\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"gpt-3.5-turbo-0613\",\"password\":false,\"options\":[\"gpt-3.5-turbo-0613\",\"gpt-3.5-turbo-16k-0613\",\"gpt-4-0613\",\"gpt-4-32k-0613\"],\"name\":\"model_name\",\"display_name\":\"Model Name\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"openai_api_base\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"openai_api_base\",\"display_name\":\"openai_api_base\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"openai_api_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"openai_api_key\",\"display_name\":\"openai_api_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"system_message\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"system_message\",\"display_name\":\"System Message\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"SystemMessagePromptTemplate\",\"list\":false},\"tools\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"tools\",\"display_name\":\"Tools\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Tool\",\"list\":true}},\"description\":\"Conversational Agent that can use OpenAI's function calling API\",\"base_classes\":[\"AgentExecutor\",\"Chain\"],\"display_name\":\"OpenAI Conversational Agent\",\"custom_fields\":{\"max_token_limit\":null,\"memory\":null,\"model_name\":null,\"openai_api_base\":null,\"openai_api_key\":null,\"system_message\":null,\"tools\":null},\"output_types\":[\"OpenAIConversationalAgent\"],\"documentation\":\"\",\"beta\":true,\"error\":null}},\"prompts\":{\"ChatMessagePromptTemplate\":{\"template\":{\"additional_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"additional_kwargs\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"prompt\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"\\nYou are a helpful assistant that talks casually about life in general.\\nYou are a good listener and you can talk about anything.\\n\",\"password\":false,\"name\":\"prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"prompt\",\"list\":false},\"role\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"role\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"ChatMessagePromptTemplate\"},\"description\":\"Chat message prompt template.\",\"base_classes\":[\"ChatMessagePromptTemplate\",\"BaseStringMessagePromptTemplate\",\"BaseMessagePromptTemplate\"],\"display_name\":\"ChatMessagePromptTemplate\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/msg_prompt_templates\",\"beta\":false,\"error\":null},\"ChatPromptTemplate\":{\"template\":{\"messages\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"messages\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseMessagePromptTemplate\",\"list\":true},\"output_parser\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"output_parser\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseOutputParser\",\"list\":false},\"input_variables\":{\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"input_variables\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"partial_variables\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"partial_variables\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"_type\":\"ChatPromptTemplate\"},\"description\":\"A prompt template for chat models.\",\"base_classes\":[\"BasePromptTemplate\",\"ChatPromptTemplate\",\"BaseChatPromptTemplate\"],\"display_name\":\"ChatPromptTemplate\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/model_io/models/chat/how_to/prompts\",\"beta\":false,\"error\":null},\"HumanMessagePromptTemplate\":{\"template\":{\"additional_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"additional_kwargs\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"prompt\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"\\nYou are a helpful assistant that talks casually about life in general.\\nYou are a good listener and you can talk about anything.\\n\",\"password\":false,\"name\":\"prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"prompt\",\"list\":false},\"_type\":\"HumanMessagePromptTemplate\"},\"description\":\"Human message prompt template. This is a message that is sent to the user.\",\"base_classes\":[\"HumanMessagePromptTemplate\",\"BaseStringMessagePromptTemplate\",\"BaseMessagePromptTemplate\"],\"display_name\":\"HumanMessagePromptTemplate\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/model_io/models/chat/how_to/prompts\",\"beta\":false,\"error\":null},\"PromptTemplate\":{\"template\":{\"output_parser\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"output_parser\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseOutputParser\",\"list\":false},\"input_variables\":{\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"input_variables\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"partial_variables\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"partial_variables\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"template\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"password\":false,\"name\":\"template\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"prompt\",\"list\":false},\"template_format\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"f-string\",\"password\":false,\"name\":\"template_format\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"validate_template\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":true,\"password\":false,\"name\":\"validate_template\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"PromptTemplate\"},\"description\":\"A prompt template for a language model.\",\"base_classes\":[\"BasePromptTemplate\",\"StringPromptTemplate\",\"PromptTemplate\"],\"display_name\":\"PromptTemplate\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/\",\"beta\":false,\"error\":null},\"SystemMessagePromptTemplate\":{\"template\":{\"additional_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"additional_kwargs\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"prompt\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"\\nYou are a helpful assistant that talks casually about life in general.\\nYou are a good listener and you can talk about anything.\\n\",\"password\":false,\"name\":\"prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"prompt\",\"list\":false},\"_type\":\"SystemMessagePromptTemplate\"},\"description\":\"System message prompt template.\",\"base_classes\":[\"SystemMessagePromptTemplate\",\"BaseStringMessagePromptTemplate\",\"BaseMessagePromptTemplate\"],\"display_name\":\"SystemMessagePromptTemplate\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/model_io/models/chat/how_to/prompts\",\"beta\":false,\"error\":null}},\"llms\":{\"Anthropic\":{\"template\":{\"callbacks\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"callbacks\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"langchain.callbacks.base.BaseCallbackHandler\",\"list\":true},\"count_tokens\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"count_tokens\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Callable[[str], int]\",\"list\":false},\"AI_PROMPT\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"AI_PROMPT\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"HUMAN_PROMPT\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"HUMAN_PROMPT\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"anthropic_api_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"anthropic_api_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"anthropic_api_url\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"anthropic_api_url\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"async_client\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"async_client\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Any\",\"list\":false},\"cache\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"cache\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"client\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"client\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Any\",\"list\":false},\"default_request_timeout\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"default_request_timeout\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"float\",\"list\":false},\"max_tokens_to_sample\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":256,\"password\":false,\"name\":\"max_tokens_to_sample\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"metadata\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"model\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"claude-2\",\"password\":false,\"name\":\"model\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"model_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"model_kwargs\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"streaming\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"streaming\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"tags\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"tags\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"temperature\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"temperature\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"float\",\"list\":false},\"top_k\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"top_k\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"top_p\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"top_p\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"float\",\"list\":false},\"verbose\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"verbose\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"Anthropic\"},\"description\":\"Anthropic large language 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Key\\\", \\\"password\\\": True},\\n \\\"code\\\": {\\\"advanced\\\": True},\\n }\\n\\n def build(\\n self,\\n metaphor_api_key: str,\\n use_autoprompt: bool = True,\\n search_num_results: int = 5,\\n similar_num_results: int = 5,\\n ) -> Union[Tool, BaseToolkit]:\\n # If documents, then we need to create a Vectara instance using .from_documents\\n client = Metaphor(api_key=metaphor_api_key)\\n\\n @tool\\n def search(query: str):\\n \\\"\\\"\\\"Call search engine with a query.\\\"\\\"\\\"\\n return client.search(\\n query, use_autoprompt=use_autoprompt, num_results=search_num_results\\n )\\n\\n @tool\\n def get_contents(ids: List[str]):\\n \\\"\\\"\\\"Get contents of a webpage.\\n\\n The ids passed in should be a list of ids as fetched from `search`.\\n \\\"\\\"\\\"\\n return client.get_contents(ids)\\n\\n @tool\\n def find_similar(url: str):\\n \\\"\\\"\\\"Get search results similar to a given URL.\\n\\n The url passed in should be a URL returned from `search`\\n \\\"\\\"\\\"\\n return client.find_similar(url, num_results=similar_num_results)\\n\\n return [search, get_contents, find_similar] # type: ignore\\n\",\"password\":false,\"name\":\"code\",\"advanced\":true,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"metaphor_api_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"metaphor_api_key\",\"display_name\":\"Metaphor API 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documents.\",\"base_classes\":[\"Pinecone\",\"VectorStore\",\"BaseRetriever\",\"VectorStoreRetriever\"],\"display_name\":\"Pinecone\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/pinecone\",\"beta\":false,\"error\":null},\"Qdrant\":{\"template\":{\"documents\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"documents\",\"display_name\":\"Documents\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":true},\"embedding\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"embedding\",\"display_name\":\"Embedding\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Embeddings\",\"list\":false},\"hnsw_config\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"hnsw_config\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"common_types.HnswConfigDiff\",\"list\":false},\"init_from\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"init_from\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"common_types.InitFrom\",\"list\":false},\"optimizers_config\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"optimizers_config\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"common_types.OptimizersConfigDiff\",\"list\":false},\"quantization_config\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"quantization_config\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"common_types.QuantizationConfig\",\"list\":false},\"wal_config\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"wal_config\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"common_types.WalConfigDiff\",\"list\":false},\"api_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"api_key\",\"display_name\":\"API Key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"batch_size\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":64,\"password\":false,\"name\":\"batch_size\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"collection_name\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"collection_name\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"content_payload_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"page_content\",\"password\":false,\"name\":\"content_payload_key\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"distance_func\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"Cosine\",\"password\":false,\"name\":\"distance_func\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"force_recreate\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"force_recreate\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"grpc_port\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":6334,\"password\":false,\"name\":\"grpc_port\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"host\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"host\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"https\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"https\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"ids\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"ids\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"location\":{\"required\":false,\"placeholder\":\":memory:\",\"show\":true,\"multiline\":false,\"value\":\":memory:\",\"password\":false,\"name\":\"location\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"metadata_payload_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"metadata\",\"password\":false,\"name\":\"metadata_payload_key\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"metadatas\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadatas\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":true},\"on_disk\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"on_disk\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"on_disk_payload\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"on_disk_payload\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"path\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"path\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"port\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":6333,\"password\":false,\"name\":\"port\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"prefer_grpc\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"prefer_grpc\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"prefix\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"password\":false,\"name\":\"prefix\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"replication_factor\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"replication_factor\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"search_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"search_kwargs\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"shard_number\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"shard_number\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"timeout\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"timeout\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"float\",\"list\":false},\"url\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"url\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"vector_name\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"vector_name\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"write_consistency_factor\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"write_consistency_factor\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"_type\":\"Qdrant\"},\"description\":\"Construct Qdrant wrapper from a list of texts.\",\"base_classes\":[\"VectorStore\",\"Qdrant\",\"BaseRetriever\",\"VectorStoreRetriever\"],\"display_name\":\"Qdrant\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/qdrant\",\"beta\":false,\"error\":null},\"SupabaseVectorStore\":{\"template\":{\"client\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"client\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"supabase.client.Client\",\"list\":false},\"documents\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"documents\",\"display_name\":\"Documents\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":true},\"embedding\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"embedding\",\"display_name\":\"Embedding\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Embeddings\",\"list\":false},\"ids\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"ids\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"metadatas\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadatas\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":true},\"query_name\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"password\":false,\"name\":\"query_name\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"search_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"search_kwargs\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"supabase_service_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"password\":true,\"name\":\"supabase_service_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"supabase_url\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"password\":false,\"name\":\"supabase_url\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"table_name\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"password\":false,\"name\":\"table_name\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"SupabaseVectorStore\"},\"description\":\"Return VectorStore initialized from texts and embeddings.\",\"base_classes\":[\"VectorStore\",\"SupabaseVectorStore\",\"BaseRetriever\",\"VectorStoreRetriever\"],\"display_name\":\"Supabase\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/supabase\",\"beta\":false,\"error\":null},\"Weaviate\":{\"template\":{\"documents\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"documents\",\"display_name\":\"Documents\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":true},\"embedding\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"embedding\",\"display_name\":\"Embedding\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Embeddings\",\"list\":false},\"client_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"client_kwargs\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"metadatas\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"metadatas\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":true},\"search_kwargs\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"search_kwargs\",\"advanced\":true,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"weaviate_url\":{\"required\":true,\"placeholder\":\"http://localhost:8080\",\"show\":true,\"multiline\":false,\"value\":\"http://localhost:8080\",\"password\":false,\"name\":\"weaviate_url\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"Weaviate\"},\"description\":\"Construct Weaviate wrapper from raw documents.\",\"base_classes\":[\"VectorStore\",\"Weaviate\",\"BaseRetriever\",\"VectorStoreRetriever\"],\"display_name\":\"Weaviate\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/weaviate\",\"beta\":false,\"error\":null},\"Vectara\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"from typing import Optional, Union\\nfrom langflow import CustomComponent\\n\\nfrom langchain.vectorstores import Vectara\\nfrom langchain.schema import Document\\nfrom langchain.vectorstores.base import VectorStore\\nfrom langchain.schema import BaseRetriever\\nfrom langchain.embeddings.base import Embeddings\\n\\n\\nclass VectaraComponent(CustomComponent):\\n display_name: str = \\\"Vectara\\\"\\n description: str = \\\"Implementation of Vector Store using Vectara\\\"\\n documentation = (\\n \\\"https://python.langchain.com/docs/integrations/vectorstores/vectara\\\"\\n )\\n beta = True\\n # api key should be password = True\\n field_config = {\\n \\\"vectara_customer_id\\\": {\\\"display_name\\\": \\\"Vectara Customer ID\\\"},\\n \\\"vectara_corpus_id\\\": {\\\"display_name\\\": \\\"Vectara Corpus ID\\\"},\\n \\\"vectara_api_key\\\": {\\\"display_name\\\": \\\"Vectara API Key\\\", \\\"password\\\": True},\\n \\\"code\\\": {\\\"show\\\": False},\\n \\\"documents\\\": {\\\"display_name\\\": \\\"Documents\\\"},\\n \\\"embedding\\\": {\\\"display_name\\\": \\\"Embedding\\\"},\\n }\\n\\n def build(\\n self,\\n vectara_customer_id: str,\\n vectara_corpus_id: str,\\n vectara_api_key: str,\\n embedding: Optional[Embeddings] = None,\\n documents: Optional[Document] = None,\\n ) -> Union[VectorStore, BaseRetriever]:\\n # If documents, then we need to create a Vectara instance using .from_documents\\n if documents is not None and embedding is not None:\\n return Vectara.from_documents(\\n documents=documents, # type: ignore\\n vectara_customer_id=vectara_customer_id,\\n vectara_corpus_id=vectara_corpus_id,\\n vectara_api_key=vectara_api_key,\\n embedding=embedding,\\n )\\n\\n return Vectara(\\n vectara_customer_id=vectara_customer_id,\\n vectara_corpus_id=vectara_corpus_id,\\n vectara_api_key=vectara_api_key,\\n )\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"documents\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"documents\",\"display_name\":\"Documents\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":false},\"embedding\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"embedding\",\"display_name\":\"Embedding\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Embeddings\",\"list\":false},\"vectara_api_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"vectara_api_key\",\"display_name\":\"Vectara API Key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"vectara_corpus_id\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"vectara_corpus_id\",\"display_name\":\"Vectara Corpus ID\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"vectara_customer_id\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"vectara_customer_id\",\"display_name\":\"Vectara Customer ID\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false}},\"description\":\"Implementation of Vector Store using Vectara\",\"base_classes\":[\"VectorStore\",\"BaseRetriever\"],\"display_name\":\"Vectara\",\"custom_fields\":{\"documents\":null,\"embedding\":null,\"vectara_api_key\":null,\"vectara_corpus_id\":null,\"vectara_customer_id\":null},\"output_types\":[\"Vectara\"],\"documentation\":\"https://python.langchain.com/docs/integrations/vectorstores/vectara\",\"beta\":true,\"error\":null},\"Chroma (1)\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"from typing import Optional, Union\\nfrom langflow import CustomComponent\\n\\nfrom langchain.vectorstores import Chroma\\nfrom langchain.schema import Document\\nfrom langchain.vectorstores.base import VectorStore\\nfrom langchain.schema import BaseRetriever\\nfrom langchain.embeddings.base import Embeddings\\nimport chromadb # type: ignore\\n\\n\\nclass ChromaComponent(CustomComponent):\\n \\\"\\\"\\\"\\n A custom component for implementing a Vector Store using Chroma.\\n \\\"\\\"\\\"\\n\\n display_name: str = \\\"Chroma (Custom Component)\\\"\\n description: str = \\\"Implementation of Vector Store using Chroma\\\"\\n documentation = \\\"https://python.langchain.com/docs/integrations/vectorstores/chroma\\\"\\n beta = True\\n\\n def build_config(self):\\n \\\"\\\"\\\"\\n Builds the configuration for the component.\\n\\n Returns:\\n - dict: A dictionary containing the configuration options for the component.\\n \\\"\\\"\\\"\\n return {\\n \\\"collection_name\\\": {\\\"display_name\\\": \\\"Collection Name\\\", \\\"value\\\": \\\"langflow\\\"},\\n \\\"persist\\\": {\\\"display_name\\\": \\\"Persist\\\"},\\n \\\"persist_directory\\\": {\\\"display_name\\\": \\\"Persist Directory\\\"},\\n \\\"code\\\": {\\\"show\\\": False, \\\"display_name\\\": \\\"Code\\\"},\\n \\\"documents\\\": {\\\"display_name\\\": \\\"Documents\\\", \\\"is_list\\\": True},\\n \\\"embedding\\\": {\\\"display_name\\\": \\\"Embedding\\\"},\\n \\\"chroma_server_cors_allow_origins\\\": {\\n \\\"display_name\\\": \\\"Server CORS Allow Origins\\\",\\n \\\"advanced\\\": True,\\n },\\n \\\"chroma_server_host\\\": {\\\"display_name\\\": \\\"Server Host\\\", \\\"advanced\\\": True},\\n \\\"chroma_server_port\\\": {\\\"display_name\\\": \\\"Server Port\\\", \\\"advanced\\\": True},\\n \\\"chroma_server_grpc_port\\\": {\\n \\\"display_name\\\": \\\"Server gRPC Port\\\",\\n \\\"advanced\\\": True,\\n },\\n \\\"chroma_server_ssl_enabled\\\": {\\n \\\"display_name\\\": \\\"Server SSL Enabled\\\",\\n \\\"advanced\\\": True,\\n },\\n }\\n\\n def build(\\n self,\\n collection_name: str,\\n persist: bool,\\n chroma_server_ssl_enabled: bool,\\n persist_directory: Optional[str] = None,\\n embedding: Optional[Embeddings] = None,\\n documents: Optional[Document] = None,\\n chroma_server_cors_allow_origins: Optional[str] = None,\\n chroma_server_host: Optional[str] = None,\\n chroma_server_port: Optional[int] = None,\\n chroma_server_grpc_port: Optional[int] = None,\\n ) -> Union[VectorStore, BaseRetriever]:\\n \\\"\\\"\\\"\\n Builds the Vector Store or BaseRetriever object.\\n\\n Args:\\n - collection_name (str): The name of the collection.\\n - persist_directory (Optional[str]): The directory to persist the Vector Store to.\\n - chroma_server_ssl_enabled (bool): Whether to enable SSL for the Chroma server.\\n - persist (bool): Whether to persist the Vector Store or not.\\n - embedding (Optional[Embeddings]): The embeddings to use for the Vector Store.\\n - documents (Optional[Document]): The documents to use for the Vector Store.\\n - chroma_server_cors_allow_origins (Optional[str]): The CORS allow origins for the Chroma server.\\n - chroma_server_host (Optional[str]): The host for the Chroma server.\\n - chroma_server_port (Optional[int]): The port for the Chroma server.\\n - chroma_server_grpc_port (Optional[int]): The gRPC port for the Chroma server.\\n\\n Returns:\\n - Union[VectorStore, BaseRetriever]: The Vector Store or BaseRetriever object.\\n \\\"\\\"\\\"\\n\\n # Chroma settings\\n chroma_settings = None\\n\\n if chroma_server_host is not None:\\n chroma_settings = chromadb.config.Settings(\\n chroma_server_cors_allow_origins=chroma_server_cors_allow_origins\\n or None,\\n chroma_server_host=chroma_server_host,\\n chroma_server_port=chroma_server_port or None,\\n chroma_server_grpc_port=chroma_server_grpc_port or None,\\n chroma_server_ssl_enabled=chroma_server_ssl_enabled,\\n )\\n\\n # If documents, then we need to create a Chroma instance using .from_documents\\n if documents is not None and embedding is not None:\\n return Chroma.from_documents(\\n documents=documents, # type: ignore\\n persist_directory=persist_directory if persist else None,\\n collection_name=collection_name,\\n embedding=embedding,\\n client_settings=chroma_settings,\\n )\\n\\n return Chroma(\\n persist_directory=persist_directory, client_settings=chroma_settings\\n 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file.\",\"base_classes\":[\"Document\"],\"display_name\":\"TextLoader\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_loaders/\",\"beta\":false,\"error\":null},\"UnstructuredEmailLoader\":{\"template\":{\"file_path\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"suffixes\":[\".eml\"],\"password\":false,\"name\":\"file_path\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"file\",\"list\":false,\"fileTypes\":[\"eml\"],\"file_path\":null},\"metadata\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"metadata\",\"display_name\":\"Metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"_type\":\"UnstructuredEmailLoader\"},\"description\":\"Load email files using `Unstructured`.\",\"base_classes\":[\"Document\"],\"display_name\":\"UnstructuredEmailLoader\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/email\",\"beta\":false,\"error\":null},\"UnstructuredHTMLLoader\":{\"template\":{\"file_path\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"suffixes\":[\".html\"],\"password\":false,\"name\":\"file_path\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"file\",\"list\":false,\"fileTypes\":[\"html\"],\"file_path\":null},\"metadata\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"metadata\",\"display_name\":\"Metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"_type\":\"UnstructuredHTMLLoader\"},\"description\":\"Load `HTML` files using `Unstructured`.\",\"base_classes\":[\"Document\"],\"display_name\":\"UnstructuredHTMLLoader\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/html\",\"beta\":false,\"error\":null},\"UnstructuredMarkdownLoader\":{\"template\":{\"file_path\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"suffixes\":[\".md\"],\"password\":false,\"name\":\"file_path\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"file\",\"list\":false,\"fileTypes\":[\"md\"],\"file_path\":null},\"metadata\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"metadata\",\"display_name\":\"Metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"_type\":\"UnstructuredMarkdownLoader\"},\"description\":\"Load `Markdown` files using `Unstructured`.\",\"base_classes\":[\"Document\"],\"display_name\":\"UnstructuredMarkdownLoader\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/markdown\",\"beta\":false,\"error\":null},\"UnstructuredPowerPointLoader\":{\"template\":{\"file_path\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"suffixes\":[\".pptx\",\".ppt\"],\"password\":false,\"name\":\"file_path\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"file\",\"list\":false,\"fileTypes\":[\"pptx\",\"ppt\"],\"file_path\":null},\"metadata\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"metadata\",\"display_name\":\"Metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"_type\":\"UnstructuredPowerPointLoader\"},\"description\":\"Load `Microsoft PowerPoint` files using `Unstructured`.\",\"base_classes\":[\"Document\"],\"display_name\":\"UnstructuredPowerPointLoader\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_powerpoint\",\"beta\":false,\"error\":null},\"UnstructuredWordDocumentLoader\":{\"template\":{\"file_path\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"suffixes\":[\".docx\",\".doc\"],\"password\":false,\"name\":\"file_path\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"file\",\"list\":false,\"fileTypes\":[\"docx\",\"doc\"],\"file_path\":null},\"metadata\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"metadata\",\"display_name\":\"Metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"_type\":\"UnstructuredWordDocumentLoader\"},\"description\":\"Load `Microsof Word` file using `Unstructured`.\",\"base_classes\":[\"Document\"],\"display_name\":\"UnstructuredWordDocumentLoader\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_word\",\"beta\":false,\"error\":null},\"WebBaseLoader\":{\"template\":{\"metadata\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{}\",\"password\":false,\"name\":\"metadata\",\"display_name\":\"Metadata\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"web_path\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\",\"password\":false,\"name\":\"web_path\",\"display_name\":\"Web Page\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"WebBaseLoader\"},\"description\":\"Load HTML pages using `urllib` and parse them with `BeautifulSoup'.\",\"base_classes\":[\"Document\"],\"display_name\":\"WebBaseLoader\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/web_base\",\"beta\":false,\"error\":null}},\"textsplitters\":{\"CharacterTextSplitter\":{\"template\":{\"documents\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"documents\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":true},\"chunk_overlap\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":200,\"password\":false,\"name\":\"chunk_overlap\",\"display_name\":\"Chunk Overlap\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"chunk_size\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":1000,\"password\":false,\"name\":\"chunk_size\",\"display_name\":\"Chunk Size\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"separator\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\\\\n\",\"password\":false,\"name\":\"separator\",\"display_name\":\"Separator\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"CharacterTextSplitter\"},\"description\":\"Splitting text that looks at characters.\",\"base_classes\":[\"Document\"],\"display_name\":\"CharacterTextSplitter\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter\",\"beta\":false,\"error\":null},\"RecursiveCharacterTextSplitter\":{\"template\":{\"documents\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"documents\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":true},\"chunk_overlap\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":200,\"password\":false,\"name\":\"chunk_overlap\",\"display_name\":\"Chunk Overlap\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"chunk_size\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":1000,\"password\":false,\"name\":\"chunk_size\",\"display_name\":\"Chunk Size\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"separator_type\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"Text\",\"password\":false,\"options\":[\"Text\",\"cpp\",\"go\",\"html\",\"java\",\"js\",\"latex\",\"markdown\",\"php\",\"proto\",\"python\",\"rst\",\"ruby\",\"rust\",\"scala\",\"sol\",\"swift\"],\"name\":\"separator_type\",\"display_name\":\"Separator Type\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"separators\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"\\\\n\",\"password\":false,\"name\":\"separators\",\"display_name\":\"Separator\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"RecursiveCharacterTextSplitter\"},\"description\":\"Splitting text by recursively look at characters.\",\"base_classes\":[\"Document\"],\"display_name\":\"RecursiveCharacterTextSplitter\",\"custom_fields\":{},\"output_types\":[\"Document\"],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/recursive_text_splitter\",\"beta\":false,\"error\":null}},\"utilities\":{\"BingSearchAPIWrapper\":{\"template\":{\"bing_search_url\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"bing_search_url\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"bing_subscription_key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"bing_subscription_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"k\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":10,\"password\":false,\"name\":\"k\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"_type\":\"BingSearchAPIWrapper\"},\"description\":\"Wrapper for Bing Search API.\",\"base_classes\":[\"BingSearchAPIWrapper\"],\"display_name\":\"BingSearchAPIWrapper\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"GoogleSearchAPIWrapper\":{\"template\":{\"google_api_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"google_api_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"google_cse_id\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"google_cse_id\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"k\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":10,\"password\":false,\"name\":\"k\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"search_engine\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"search_engine\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Any\",\"list\":false},\"siterestrict\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"siterestrict\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"GoogleSearchAPIWrapper\"},\"description\":\"Wrapper for Google Search API.\",\"base_classes\":[\"GoogleSearchAPIWrapper\"],\"display_name\":\"GoogleSearchAPIWrapper\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"GoogleSerperAPIWrapper\":{\"template\":{\"aiosession\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"aiosession\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"ClientSession\",\"list\":false},\"gl\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"us\",\"password\":false,\"name\":\"gl\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"hl\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"en\",\"password\":false,\"name\":\"hl\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"k\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":10,\"password\":false,\"name\":\"k\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"result_key_for_type\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"{\\n \\\"news\\\": \\\"news\\\",\\n \\\"places\\\": \\\"places\\\",\\n \\\"images\\\": \\\"images\\\",\\n \\\"search\\\": \\\"organic\\\"\\n}\",\"password\":true,\"name\":\"result_key_for_type\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"serper_api_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"serper_api_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"tbs\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"tbs\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"type\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"search\",\"password\":false,\"options\":[\"news\",\"search\",\"places\",\"images\"],\"name\":\"type\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"_type\":\"GoogleSerperAPIWrapper\"},\"description\":\"Wrapper around the Serper.dev Google Search API.\",\"base_classes\":[\"GoogleSerperAPIWrapper\"],\"display_name\":\"GoogleSerperAPIWrapper\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"SearxSearchWrapper\":{\"template\":{\"aiosession\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"aiosession\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Any\",\"list\":false},\"categories\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"categories\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"engines\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"engines\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":true},\"headers\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"{'Authorization': 'Bearer '}\",\"password\":false,\"name\":\"headers\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"k\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":10,\"password\":false,\"name\":\"k\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"params\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"params\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"query_suffix\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"\",\"password\":false,\"name\":\"query_suffix\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"searx_host\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"\",\"password\":false,\"name\":\"searx_host\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"unsecure\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"unsecure\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"_type\":\"SearxSearchWrapper\"},\"description\":\"Wrapper for Searx API.\",\"base_classes\":[\"SearxSearchWrapper\"],\"display_name\":\"SearxSearchWrapper\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"SerpAPIWrapper\":{\"template\":{\"aiosession\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"aiosession\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"ClientSession\",\"list\":false},\"params\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"{\\n \\\"engine\\\": \\\"google\\\",\\n \\\"google_domain\\\": \\\"google.com\\\",\\n \\\"gl\\\": \\\"us\\\",\\n \\\"hl\\\": \\\"en\\\"\\n}\",\"password\":false,\"name\":\"params\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"code\",\"list\":false},\"search_engine\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"search_engine\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Any\",\"list\":false},\"serpapi_api_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":true,\"name\":\"serpapi_api_key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"SerpAPIWrapper\"},\"description\":\"Wrapper around SerpAPI.\",\"base_classes\":[\"SerpAPIWrapper\"],\"display_name\":\"SerpAPIWrapper\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"WikipediaAPIWrapper\":{\"template\":{\"doc_content_chars_max\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":4000,\"password\":false,\"name\":\"doc_content_chars_max\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"lang\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":\"en\",\"password\":false,\"name\":\"lang\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"load_all_available_meta\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":false,\"password\":false,\"name\":\"load_all_available_meta\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"bool\",\"list\":false},\"top_k_results\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"value\":3,\"password\":false,\"name\":\"top_k_results\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"int\",\"list\":false},\"wiki_client\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"wiki_client\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Any\",\"list\":false},\"_type\":\"WikipediaAPIWrapper\"},\"description\":\"Wrapper around WikipediaAPI.\",\"base_classes\":[\"WikipediaAPIWrapper\"],\"display_name\":\"WikipediaAPIWrapper\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"WolframAlphaAPIWrapper\":{\"template\":{\"wolfram_alpha_appid\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"wolfram_alpha_appid\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"wolfram_client\":{\"required\":false,\"placeholder\":\"\",\"show\":false,\"multiline\":false,\"password\":false,\"name\":\"wolfram_client\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Any\",\"list\":false},\"_type\":\"WolframAlphaAPIWrapper\"},\"description\":\"Wrapper for Wolfram Alpha.\",\"base_classes\":[\"WolframAlphaAPIWrapper\"],\"display_name\":\"WolframAlphaAPIWrapper\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":false,\"error\":null},\"GetRequest\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"from langflow import CustomComponent\\nfrom langchain.schema import Document\\nfrom langflow.services.database.models.base import orjson_dumps\\nimport requests\\nfrom typing import Optional\\n\\n\\nclass GetRequest(CustomComponent):\\n display_name: str = \\\"GET Request\\\"\\n description: str = \\\"Make a GET request to the given URL.\\\"\\n output_types: list[str] = [\\\"Document\\\"]\\n documentation: str = \\\"https://docs.langflow.org/components/utilities#get-request\\\"\\n beta = True\\n field_config = {\\n \\\"url\\\": {\\n \\\"display_name\\\": \\\"URL\\\",\\n \\\"info\\\": \\\"The URL to make the request to\\\",\\n \\\"is_list\\\": True,\\n },\\n \\\"headers\\\": {\\n \\\"display_name\\\": \\\"Headers\\\",\\n \\\"field_type\\\": \\\"code\\\",\\n \\\"info\\\": \\\"The headers to send with the request.\\\",\\n },\\n \\\"code\\\": {\\\"show\\\": False},\\n \\\"timeout\\\": {\\n \\\"display_name\\\": \\\"Timeout\\\",\\n \\\"field_type\\\": \\\"int\\\",\\n \\\"info\\\": \\\"The timeout to use for the request.\\\",\\n \\\"value\\\": 5,\\n },\\n }\\n\\n def get_document(\\n self, session: requests.Session, url: str, headers: Optional[dict], timeout: int\\n ) -> Document:\\n try:\\n response = session.get(url, headers=headers, timeout=int(timeout))\\n try:\\n response_json = response.json()\\n result = orjson_dumps(response_json, indent_2=False)\\n except Exception:\\n result = response.text\\n self.repr_value = result\\n return Document(\\n page_content=result,\\n metadata={\\n \\\"source\\\": url,\\n \\\"headers\\\": headers,\\n \\\"status_code\\\": response.status_code,\\n },\\n )\\n except requests.Timeout:\\n return Document(\\n page_content=\\\"Request Timed Out\\\",\\n metadata={\\\"source\\\": url, \\\"headers\\\": headers, \\\"status_code\\\": 408},\\n )\\n except Exception as exc:\\n return Document(\\n page_content=str(exc),\\n metadata={\\\"source\\\": url, \\\"headers\\\": headers, \\\"status_code\\\": 500},\\n )\\n\\n def build(\\n self,\\n url: str,\\n headers: Optional[dict] = None,\\n timeout: int = 5,\\n ) -> list[Document]:\\n if headers is None:\\n headers = {}\\n urls = url if isinstance(url, list) else [url]\\n with requests.Session() as session:\\n documents = [self.get_document(session, u, headers, timeout) for u in urls]\\n self.repr_value = documents\\n return documents\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"headers\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"headers\",\"display_name\":\"Headers\",\"advanced\":false,\"dynamic\":false,\"info\":\"The headers to send with the request.\",\"type\":\"code\",\"list\":false},\"timeout\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":5,\"password\":false,\"name\":\"timeout\",\"display_name\":\"Timeout\",\"advanced\":false,\"dynamic\":false,\"info\":\"The timeout to use for the request.\",\"type\":\"int\",\"list\":false},\"url\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"url\",\"display_name\":\"URL\",\"advanced\":false,\"dynamic\":false,\"info\":\"The URL to make the request to\",\"type\":\"str\",\"list\":true}},\"description\":\"Make a GET request to the given URL.\",\"base_classes\":[\"Document\"],\"display_name\":\"GET Request\",\"custom_fields\":{\"headers\":null,\"timeout\":null,\"url\":null},\"output_types\":[\"GetRequest\"],\"documentation\":\"https://docs.langflow.org/components/utilities#get-request\",\"beta\":true,\"error\":null},\"PostRequest\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"from langflow import CustomComponent\\nfrom langchain.schema import Document\\nfrom langflow.services.database.models.base import orjson_dumps\\nimport requests\\nfrom typing import Optional\\n\\n\\nclass PostRequest(CustomComponent):\\n display_name: str = \\\"POST Request\\\"\\n description: str = \\\"Make a POST request to the given URL.\\\"\\n output_types: list[str] = [\\\"Document\\\"]\\n documentation: str = \\\"https://docs.langflow.org/components/utilities#post-request\\\"\\n beta = True\\n field_config = {\\n \\\"url\\\": {\\\"display_name\\\": \\\"URL\\\", \\\"info\\\": \\\"The URL to make the request to.\\\"},\\n \\\"headers\\\": {\\n \\\"display_name\\\": \\\"Headers\\\",\\n \\\"field_type\\\": \\\"code\\\",\\n \\\"info\\\": \\\"The headers to send with the request.\\\",\\n },\\n \\\"code\\\": {\\\"show\\\": False},\\n \\\"document\\\": {\\\"display_name\\\": \\\"Document\\\"},\\n }\\n\\n def post_document(\\n self,\\n session: requests.Session,\\n document: Document,\\n url: str,\\n headers: Optional[dict] = None,\\n ) -> Document:\\n try:\\n response = session.post(url, headers=headers, data=document.page_content)\\n try:\\n response_json = response.json()\\n result = orjson_dumps(response_json, indent_2=False)\\n except Exception:\\n result = response.text\\n self.repr_value = result\\n return Document(\\n page_content=result,\\n metadata={\\n \\\"source\\\": url,\\n \\\"headers\\\": headers,\\n \\\"status_code\\\": response,\\n },\\n )\\n except Exception as exc:\\n return Document(\\n page_content=str(exc),\\n metadata={\\n \\\"source\\\": url,\\n \\\"headers\\\": headers,\\n \\\"status_code\\\": 500,\\n },\\n )\\n\\n def build(\\n self,\\n document: Document,\\n url: str,\\n headers: Optional[dict] = None,\\n ) -> list[Document]:\\n if headers is None:\\n headers = {}\\n\\n if not isinstance(document, list) and isinstance(document, Document):\\n documents: list[Document] = [document]\\n elif isinstance(document, list) and all(\\n isinstance(doc, Document) for doc in document\\n ):\\n documents = document\\n else:\\n raise ValueError(\\\"document must be a Document or a list of Documents\\\")\\n\\n with requests.Session() as session:\\n documents = [\\n self.post_document(session, doc, url, headers) for doc in documents\\n ]\\n self.repr_value = documents\\n return documents\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"document\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"document\",\"display_name\":\"Document\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":false},\"headers\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"headers\",\"display_name\":\"Headers\",\"advanced\":false,\"dynamic\":false,\"info\":\"The headers to send with the request.\",\"type\":\"code\",\"list\":false},\"url\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"url\",\"display_name\":\"URL\",\"advanced\":false,\"dynamic\":false,\"info\":\"The URL to make the request to.\",\"type\":\"str\",\"list\":false}},\"description\":\"Make a POST request to the given URL.\",\"base_classes\":[\"Document\"],\"display_name\":\"POST Request\",\"custom_fields\":{\"document\":null,\"headers\":null,\"url\":null},\"output_types\":[\"PostRequest\"],\"documentation\":\"https://docs.langflow.org/components/utilities#post-request\",\"beta\":true,\"error\":null},\"UpdateRequest\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":false,\"multiline\":true,\"value\":\"from typing import List, Optional\\nimport requests\\nfrom langflow import CustomComponent\\nfrom langchain.schema import Document\\nfrom langflow.services.database.models.base import orjson_dumps\\n\\n\\nclass UpdateRequest(CustomComponent):\\n display_name: str = \\\"Update Request\\\"\\n description: str = \\\"Make a PATCH request to the given URL.\\\"\\n output_types: list[str] = [\\\"Document\\\"]\\n documentation: str = \\\"https://docs.langflow.org/components/utilities#update-request\\\"\\n beta = True\\n field_config = {\\n \\\"url\\\": {\\\"display_name\\\": \\\"URL\\\", \\\"info\\\": \\\"The URL to make the request to.\\\"},\\n \\\"headers\\\": {\\n \\\"display_name\\\": \\\"Headers\\\",\\n \\\"field_type\\\": \\\"code\\\",\\n \\\"info\\\": \\\"The headers to send with the request.\\\",\\n },\\n \\\"code\\\": {\\\"show\\\": False},\\n \\\"document\\\": {\\\"display_name\\\": \\\"Document\\\"},\\n \\\"method\\\": {\\n \\\"display_name\\\": \\\"Method\\\",\\n \\\"field_type\\\": \\\"str\\\",\\n \\\"info\\\": \\\"The HTTP method to use.\\\",\\n \\\"options\\\": [\\\"PATCH\\\", \\\"PUT\\\"],\\n \\\"value\\\": \\\"PATCH\\\",\\n },\\n }\\n\\n def update_document(\\n self,\\n session: requests.Session,\\n document: Document,\\n url: str,\\n headers: Optional[dict] = None,\\n method: str = \\\"PATCH\\\",\\n ) -> Document:\\n try:\\n if method == \\\"PATCH\\\":\\n response = session.patch(\\n url, headers=headers, data=document.page_content\\n )\\n elif method == \\\"PUT\\\":\\n response = session.put(url, headers=headers, data=document.page_content)\\n else:\\n raise ValueError(f\\\"Unsupported method: {method}\\\")\\n try:\\n response_json = response.json()\\n result = orjson_dumps(response_json, indent_2=False)\\n except Exception:\\n result = response.text\\n self.repr_value = result\\n return Document(\\n page_content=result,\\n metadata={\\n \\\"source\\\": url,\\n \\\"headers\\\": headers,\\n \\\"status_code\\\": response.status_code,\\n },\\n )\\n except Exception as exc:\\n return Document(\\n page_content=str(exc),\\n metadata={\\\"source\\\": url, \\\"headers\\\": headers, \\\"status_code\\\": 500},\\n )\\n\\n def build(\\n self,\\n method: str,\\n document: Document,\\n url: str,\\n headers: Optional[dict] = None,\\n ) -> List[Document]:\\n if headers is None:\\n headers = {}\\n\\n if not isinstance(document, list) and isinstance(document, Document):\\n documents: list[Document] = [document]\\n elif isinstance(document, list) and all(\\n isinstance(doc, Document) for doc in document\\n ):\\n documents = document\\n else:\\n raise ValueError(\\\"document must be a Document or a list of Documents\\\")\\n\\n with requests.Session() as session:\\n documents = [\\n self.update_document(session, doc, url, headers, method)\\n for doc in documents\\n ]\\n self.repr_value = documents\\n return documents\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"document\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"document\",\"display_name\":\"Document\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":false},\"headers\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"headers\",\"display_name\":\"Headers\",\"advanced\":false,\"dynamic\":false,\"info\":\"The headers to send with the request.\",\"type\":\"code\",\"list\":false},\"method\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"PATCH\",\"password\":false,\"options\":[\"PATCH\",\"PUT\"],\"name\":\"method\",\"display_name\":\"Method\",\"advanced\":false,\"dynamic\":false,\"info\":\"The HTTP method to use.\",\"type\":\"str\",\"list\":true},\"url\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"url\",\"display_name\":\"URL\",\"advanced\":false,\"dynamic\":false,\"info\":\"The URL to make the request to.\",\"type\":\"str\",\"list\":false}},\"description\":\"Make a PATCH request to the given URL.\",\"base_classes\":[\"Document\"],\"display_name\":\"Update Request\",\"custom_fields\":{\"document\":null,\"headers\":null,\"method\":null,\"url\":null},\"output_types\":[\"UpdateRequest\"],\"documentation\":\"https://docs.langflow.org/components/utilities#update-request\",\"beta\":true,\"error\":null},\"JSONDocumentBuilder\":{\"template\":{\"code\":{\"dynamic\":true,\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"### JSON Document Builder\\n\\n# Build a Document containing a JSON object using a key and another Document page content.\\n\\n# **Params**\\n\\n# - **Key:** The key to use for the JSON object.\\n# - **Document:** The Document page to use for the JSON object.\\n\\n# **Output**\\n\\n# - **Document:** The Document containing the JSON object.\\n\\nfrom langflow import CustomComponent\\nfrom langchain.schema import Document\\nfrom langflow.services.database.models.base import orjson_dumps\\n\\n\\nclass JSONDocumentBuilder(CustomComponent):\\n display_name: str = \\\"JSON Document Builder\\\"\\n description: str = \\\"Build a Document containing a JSON object using a key and another Document page content.\\\"\\n output_types: list[str] = [\\\"Document\\\"]\\n beta = True\\n documentation: str = (\\n \\\"https://docs.langflow.org/components/utilities#json-document-builder\\\"\\n )\\n\\n field_config = {\\n \\\"key\\\": {\\\"display_name\\\": \\\"Key\\\"},\\n \\\"document\\\": {\\\"display_name\\\": \\\"Document\\\"},\\n }\\n\\n def build(\\n self,\\n key: str,\\n document: Document,\\n ) -> Document:\\n documents = None\\n if isinstance(document, list):\\n documents = [\\n Document(\\n page_content=orjson_dumps({key: doc.page_content}, indent_2=False)\\n )\\n for doc in document\\n ]\\n elif isinstance(document, Document):\\n documents = Document(\\n page_content=orjson_dumps({key: document.page_content}, indent_2=False)\\n )\\n else:\\n raise TypeError(\\n f\\\"Expected Document or list of Documents, got {type(document)}\\\"\\n )\\n self.repr_value = documents\\n return documents\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\",\"document\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"document\",\"display_name\":\"Document\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"Document\",\"list\":false},\"key\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"key\",\"display_name\":\"Key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false}},\"description\":\"Build a Document containing a JSON object using a key and another Document page content.\",\"base_classes\":[\"Document\"],\"display_name\":\"JSON Document Builder\",\"custom_fields\":{\"document\":null,\"key\":null},\"output_types\":[\"JSONDocumentBuilder\"],\"documentation\":\"https://docs.langflow.org/components/utilities#json-document-builder\",\"beta\":true,\"error\":null}},\"output_parsers\":{\"ResponseSchema\":{\"template\":{\"description\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"password\":false,\"name\":\"description\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"name\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"name\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"type\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"string\",\"password\":false,\"name\":\"type\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"ResponseSchema\"},\"description\":\"A schema for a response from a structured output parser.\",\"base_classes\":[\"ResponseSchema\"],\"display_name\":\"ResponseSchema\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/model_io/output_parsers/structured\",\"beta\":false,\"error\":null},\"StructuredOutputParser\":{\"template\":{\"response_schemas\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"response_schemas\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"ResponseSchema\",\"list\":true},\"_type\":\"StructuredOutputParser\"},\"description\":\"\",\"base_classes\":[\"StructuredOutputParser\",\"BaseOutputParser\",\"BaseLLMOutputParser\"],\"display_name\":\"StructuredOutputParser\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/model_io/output_parsers/structured\",\"beta\":false,\"error\":null}},\"retrievers\":{\"MultiQueryRetriever\":{\"template\":{\"llm\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"llm\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseLLM\",\"list\":false},\"prompt\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":{\"input_variables\":[\"question\"],\"output_parser\":null,\"partial_variables\":{},\"template\":\"You are an AI language model assistant. Your task is \\n to generate 3 different versions of the given user \\n question to retrieve relevant documents from a vector database. \\n By generating multiple perspectives on the user question, \\n your goal is to help the user overcome some of the limitations \\n of distance-based similarity search. Provide these alternative \\n questions separated by newlines. Original question: {question}\",\"template_format\":\"f-string\",\"validate_template\":true,\"_type\":\"prompt\"},\"password\":false,\"name\":\"prompt\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"PromptTemplate\",\"list\":false},\"retriever\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"password\":false,\"name\":\"retriever\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"BaseRetriever\",\"list\":false},\"parser_key\":{\"required\":false,\"placeholder\":\"\",\"show\":true,\"multiline\":false,\"value\":\"lines\",\"password\":false,\"name\":\"parser_key\",\"display_name\":\"Parser Key\",\"advanced\":false,\"dynamic\":false,\"info\":\"\",\"type\":\"str\",\"list\":false},\"_type\":\"MultiQueryRetriever\"},\"description\":\"Initialize from llm using default template.\",\"base_classes\":[\"BaseRetriever\",\"MultiQueryRetriever\"],\"display_name\":\"MultiQueryRetriever\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"https://python.langchain.com/docs/modules/data_connection/retrievers/how_to/MultiQueryRetriever\",\"beta\":false,\"error\":null}},\"custom_components\":{\"CustomComponent\":{\"template\":{\"code\":{\"required\":true,\"placeholder\":\"\",\"show\":true,\"multiline\":true,\"value\":\"from langflow import CustomComponent\\n\\nfrom langchain.llms.base import BaseLLM\\nfrom langchain.chains import LLMChain\\nfrom langchain import PromptTemplate\\nfrom langchain.schema import Document\\n\\nimport requests\\n\\nclass YourComponent(CustomComponent):\\n display_name: str = \\\"Custom Component\\\"\\n description: str = \\\"Create any custom component you want!\\\"\\n\\n def build_config(self):\\n return { \\\"url\\\": { \\\"multiline\\\": True, \\\"required\\\": True } }\\n\\n def build(self, url: str, llm: BaseLLM, prompt: PromptTemplate) -> Document:\\n response = requests.get(url)\\n chain = LLMChain(llm=llm, prompt=prompt)\\n result = chain.run(response.text[:300])\\n return Document(page_content=str(result))\\n\",\"password\":false,\"name\":\"code\",\"advanced\":false,\"dynamic\":true,\"info\":\"\",\"type\":\"code\",\"list\":false},\"_type\":\"CustomComponent\"},\"description\":\"Create any custom component you want!\",\"base_classes\":[],\"display_name\":\"Custom Component\",\"custom_fields\":{},\"output_types\":[],\"documentation\":\"\",\"beta\":true,\"error\":null}}}" + }, + "headersSize": -1, + "bodySize": -1, + "redirectURL": "" + }, + "cache": {}, + "timings": { "send": -1, "wait": -1, "receive": 1.031 } + }, + { + "startedDateTime": "2023-08-31T14:55:36.131Z", + "time": 0.743, + "request": { + "method": "GET", + "url": "http://localhost:3000/api/v1/flows/", + "httpVersion": "HTTP/1.1", + "cookies": [], + "headers": [ + { "name": "Accept", "value": "application/json, text/plain, */*" }, + { "name": "Accept-Encoding", "value": "gzip, deflate, br" }, + { "name": "Accept-Language", "value": "en-US,en;q=0.9" }, + { "name": "Authorization", "value": "Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiJiNWIxYjFhZC05M2VjLTRjMjgtYWMxNy01OGMxNDQ0MWI1ZGQiLCJleHAiOjE3MjUwMjk3MzV9.8qhEtryWqA9RbwEP2s20umKdVE7J7jHGoogXZqxLNWk" }, + { "name": "Connection", "value": "keep-alive" }, + { "name": "Cookie", "value": "access_token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiJiNWIxYjFhZC05M2VjLTRjMjgtYWMxNy01OGMxNDQ0MWI1ZGQiLCJleHAiOjE3MjUwMjk3MzV9.8qhEtryWqA9RbwEP2s20umKdVE7J7jHGoogXZqxLNWk; refresh_token=auto" }, + { "name": "Host", "value": "localhost:3000" }, + { "name": "Referer", "value": "http://localhost:3000/" }, + { "name": "Sec-Fetch-Dest", "value": "empty" }, + { "name": "Sec-Fetch-Mode", "value": "cors" }, + { "name": "Sec-Fetch-Site", "value": "same-origin" }, + { "name": "User-Agent", "value": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36" }, + { "name": "sec-ch-ua", "value": "\"Not)A;Brand\";v=\"24\", \"Chromium\";v=\"116\"" }, + { "name": "sec-ch-ua-mobile", "value": "?0" }, + { "name": "sec-ch-ua-platform", "value": "\"Linux\"" } + ], + "queryString": [], + "headersSize": -1, + "bodySize": -1 + }, + "response": { + "status": 200, + "statusText": "OK", + "httpVersion": "HTTP/1.1", + "cookies": [], + "headers": [ + { "name": "Access-Control-Allow-Origin", "value": "*" }, + { "name": "connection", "value": "close" }, + { "name": "content-length", "value": "2" }, + { "name": "content-type", "value": "application/json" }, + { "name": "date", "value": "Thu, 31 Aug 2023 14:55:35 GMT" }, + { "name": "server", "value": "uvicorn" } + ], + "content": { + "size": -1, + "mimeType": "application/json", + "text": "[]" + }, + "headersSize": -1, + "bodySize": -1, + "redirectURL": "" + }, + "cache": {}, + "timings": { "send": -1, "wait": -1, "receive": 0.743 } + } + ] + } + } \ No newline at end of file diff --git a/src/frontend/package-lock.json b/src/frontend/package-lock.json index 74be2d4c5..cd190db12 100644 --- a/src/frontend/package-lock.json +++ b/src/frontend/package-lock.json @@ -1,7 +1,7 @@ { "name": "langflow", "version": "0.1.2", - "lockfileVersion": 2, + "lockfileVersion": 3, "requires": true, "packages": { "": { @@ -58,6 +58,7 @@ "react-syntax-highlighter": "^15.5.0", "react-tabs": "^6.0.2", "react-tooltip": "^5.21.1", + "react18-json-view": "^0.2.3", "reactflow": "^11.8.3", "rehype-mathjax": "^4.0.3", "remark-gfm": "^3.0.1", @@ -73,6 +74,7 @@ "web-vitals": "^2.1.4" }, "devDependencies": { + "@playwright/test": "^1.38.0", "@swc/cli": "^0.1.62", "@swc/core": "^1.3.80", "@tailwindcss/typography": "^0.5.9", @@ -127,9 +129,9 @@ } }, "node_modules/@antfu/ni": { - "version": "0.21.6", - "resolved": "https://registry.npmjs.org/@antfu/ni/-/ni-0.21.6.tgz", - "integrity": "sha512-Hj0BKIOspbo+OsPT5mjONeqpuVb4bxp9jdJ4p/b5GxgYNIqJjBcJdp0DEON7CJflKoWuHf7I52wO5kOJJ4DveQ==", + "version": "0.21.8", + "resolved": "https://registry.npmjs.org/@antfu/ni/-/ni-0.21.8.tgz", + "integrity": "sha512-90X8pU2szlvw0AJo9EZMbYc2eQKkmO7mAdC4tD4r5co2Mm56MT37MIG8EyB7p4WRheuzGxuLDxJ63mF6+Zajiw==", "bin": { "na": "bin/na.mjs", "nci": "bin/nci.mjs", @@ -225,20 +227,20 @@ } }, "node_modules/@babel/core": { - "version": "7.22.11", - "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.22.11.tgz", - "integrity": "sha512-lh7RJrtPdhibbxndr6/xx0w8+CVlY5FJZiaSz908Fpy+G0xkBFTvwLcKJFF4PJxVfGhVWNebikpWGnOoC71juQ==", + "version": "7.22.17", + "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.22.17.tgz", + "integrity": "sha512-2EENLmhpwplDux5PSsZnSbnSkB3tZ6QTksgO25xwEL7pIDcNOMhF5v/s6RzwjMZzZzw9Ofc30gHv5ChCC8pifQ==", "dependencies": { "@ampproject/remapping": "^2.2.0", - "@babel/code-frame": "^7.22.10", - "@babel/generator": "^7.22.10", - "@babel/helper-compilation-targets": "^7.22.10", - "@babel/helper-module-transforms": "^7.22.9", - "@babel/helpers": "^7.22.11", - 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defineConfig, devices } from "@playwright/test"; + +/** + * Read environment variables from file. + * https://github.com/motdotla/dotenv + */ +// require('dotenv').config(); + +/** + * See https://playwright.dev/docs/test-configuration. + */ +export default defineConfig({ + testDir: "./tests", + /* Run tests in files in parallel */ + fullyParallel: true, + /* Fail the build on CI if you accidentally left test.only in the source code. */ + forbidOnly: !!process.env.CI, + /* Retry on CI only */ + retries: process.env.CI ? 2 : 0, + /* Opt out of parallel tests on CI. */ + workers: process.env.CI ? 1 : undefined, + /* Reporter to use. See https://playwright.dev/docs/test-reporters */ + reporter: "html", + /* Shared settings for all the projects below. See https://playwright.dev/docs/api/class-testoptions. */ + use: { + /* Base URL to use in actions like `await page.goto('/')`. */ + // baseURL: 'http://127.0.0.1:3000', + + /* Collect trace when retrying the failed test. See https://playwright.dev/docs/trace-viewer */ + trace: "on-first-retry", + }, + + /* Configure projects for major browsers */ + projects: [ + { + name: "chromium", + use: { ...devices["Desktop Chrome"] }, + }, + + { + name: "firefox", + use: { ...devices["Desktop Firefox"] }, + }, + + { + name: "webkit", + use: { ...devices["Desktop Safari"] }, + }, + + /* Test against mobile viewports. */ + // { + // name: 'Mobile Chrome', + // use: { ...devices['Pixel 5'] }, + // }, + // { + // name: 'Mobile Safari', + // use: { ...devices['iPhone 12'] }, + // }, + + /* Test against branded browsers. */ + // { + // name: 'Microsoft Edge', + // use: { ...devices['Desktop Edge'], channel: 'msedge' }, + // }, + // { + // name: 'Google Chrome', + // use: { ...devices['Desktop Chrome'], channel: 'chrome' }, + // }, + ], + + /* Run your local dev server before starting the tests */ + // webServer: { + // command: 'npm run start', + // url: 'http://127.0.0.1:3000', + // reuseExistingServer: !process.env.CI, + // }, +}); diff --git a/src/frontend/src/App.css b/src/frontend/src/App.css index be7173d7f..a7a8bad51 100644 --- a/src/frontend/src/App.css +++ b/src/frontend/src/App.css @@ -3,45 +3,85 @@ @tailwind utilities; .App { - text-align: center; + text-align: center; +} + +.react-flow__node { + width: auto; + height: auto; + border-radius: auto; + min-width: inherit; } .App-logo { - height: 40vmin; - pointer-events: none; + height: 40vmin; + pointer-events: none; } @media (prefers-reduced-motion: no-preference) { - .App-logo { - animation: App-logo-spin infinite 20s linear; - } + .App-logo { + animation: App-logo-spin infinite 20s linear; + } } .App-header { - background-color: #282c34; - min-height: 100vh; - display: flex; - flex-direction: column; - align-items: center; - justify-content: center; - font-size: calc(10px + 2vmin); - color: white; + background-color: #282c34; + min-height: 100vh; + display: flex; + flex-direction: column; + align-items: center; + justify-content: center; + font-size: calc(10px + 2vmin); + color: white; } .App-link { - color: #61dafb; + color: #61dafb; } @keyframes App-logo-spin { - from { - transform: rotate(0deg); - } - to { - transform: rotate(360deg); - } + from { + transform: rotate(0deg); + } + to { + transform: rotate(360deg); + } } @font-face { - font-family: text-security-disc; - src: url("assets/text-security-disc.woff") format("woff"); + font-family: text-security-disc; + src: url("assets/text-security-disc.woff") format("woff"); +} + +.json-view { + height: 370px !important; + background-color: #2c2c2c !important; + border-radius: 10px !important; + padding: 10px !important; +} + +.jv-indent { + overflow-y: auto !important; + max-height: 310px !important; + border-radius: 10px; +} + +.jv-indent::-webkit-scrollbar { + width: 8px !important; + height: 8px !important; + border-radius: 10px; +} + +.jv-indent::-webkit-scrollbar-track { + background-color: #f1f1f1 !important; + border-radius: 10px; +} + +.jv-indent::-webkit-scrollbar-thumb { + background-color: #ccc !important; + border-radius: 999px !important; +} + +.jv-indent::-webkit-scrollbar-thumb:hover { + background-color: #bbb !important; } diff --git a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx index 94cc939ff..cef56c343 100644 --- a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx @@ -9,6 +9,7 @@ import React, { import { Handle, Position, useUpdateNodeInternals } from "reactflow"; import ShadTooltip from "../../../../components/ShadTooltipComponent"; import CodeAreaComponent from "../../../../components/codeAreaComponent"; +import DictComponent from "../../../../components/dictComponent"; import Dropdown from "../../../../components/dropdownComponent"; import FloatComponent from "../../../../components/floatComponent"; import IconComponent from "../../../../components/genericIconComponent"; @@ -16,15 +17,22 @@ import InputComponent from "../../../../components/inputComponent"; import InputFileComponent from "../../../../components/inputFileComponent"; import InputListComponent from "../../../../components/inputListComponent"; import IntComponent from "../../../../components/intComponent"; +import KeypairListComponent from "../../../../components/keypairListComponent"; import PromptAreaComponent from "../../../../components/promptComponent"; import TextAreaComponent from "../../../../components/textAreaComponent"; import ToggleShadComponent from "../../../../components/toggleShadComponent"; +import { Button } from "../../../../components/ui/button"; import { TOOLTIP_EMPTY } from "../../../../constants/constants"; import { TabsContext } from "../../../../contexts/tabsContext"; import { typesContext } from "../../../../contexts/typesContext"; import { ParameterComponentType } from "../../../../types/components"; import { TabsState } from "../../../../types/tabs"; -import { isValidConnection } from "../../../../utils/reactflowUtils"; +import { + convertObjToArray, + convertValuesToNumbers, + hasDuplicateKeys, + isValidConnection, +} from "../../../../utils/reactflowUtils"; import { nodeColors, nodeIconsLucide, @@ -45,6 +53,7 @@ export default function ParameterComponent({ required = false, optionalHandle = null, info = "", + showNode, }: ParameterComponentType): JSX.Element { const ref = useRef(null); const refHtml = useRef(null); @@ -67,20 +76,27 @@ export default function ParameterComponent({ updateNodeInternals(data.id); }, [data.id, position, updateNodeInternals]); - const { reactFlowInstance } = useContext(typesContext); + const groupedEdge = useRef(null); + + const { reactFlowInstance, setFilterEdge } = useContext(typesContext); let disabled = reactFlowInstance?.getEdges().some((edge) => edge.targetHandle === id) ?? false; const { data: myData } = useContext(typesContext); - const handleOnNewValue = (newValue: string | string[] | boolean): void => { + const handleOnNewValue = ( + newValue: string | string[] | boolean | Object[] + ): void => { let newData = cloneDeep(data); newData.node!.template[name].value = newValue; setData(newData); // Set state to pending //@ts-ignore setTabsState((prev: TabsState) => { + if (!prev[tabId]) { + return prev; + } return { ...prev, [tabId]: { @@ -93,6 +109,8 @@ export default function ParameterComponent({ renderTooltips(); }; + const [errorDuplicateKey, setErrorDuplicateKey] = useState(false); + useEffect(() => { if (name === "openai_api_base") console.log(info); // @ts-ignore @@ -108,55 +126,64 @@ export default function ParameterComponent({ }, [info]); function renderTooltips() { - let groupedObj = groupByFamily(myData, tooltipTitle!, left, flow!); + let groupedObj: any = groupByFamily(myData, tooltipTitle!, left, flow!); + groupedEdge.current = groupedObj; if (groupedObj && groupedObj.length > 0) { - //@ts-ignore //@ts-ignore refHtml.current = groupedObj.map((item, index) => { const Icon: any = nodeIconsLucide[item.family] ?? nodeIconsLucide["unknown"]; return ( - 0 ? "mt-2 flex items-center" : "flex items-center" + <> + {index === 0 && ( + + {left + ? "Avaliable input components:" + : "Avaliable output components:"} + )} - > -
0 ? "mt-2 flex items-center" : "mt-3 flex items-center" + )} > - -
- - {nodeNames[item.family] ?? "Other"} - - {" "} - {item.type === "" ? "" : " - "} - {item.type.split(", ").length > 2 - ? item.type.split(", ").map((el, index) => ( - - - {index === item.type.split(", ").length - 1 - ? el - : (el += `, `)} - - - )) - : item.type} + > + + + + {nodeNames[item.family] ?? "Other"}{" "} + + {" "} + {item.type === "" ? "" : " - "} + {item.type.split(", ").length > 2 + ? item.type.split(", ").map((el, index) => ( + + + {index === item.type.split(", ").length - 1 + ? el + : (el += `, `)} + + + )) + : item.type} + - + ); }); } else { @@ -169,7 +196,43 @@ export default function ParameterComponent({ renderTooltips(); }, [tooltipTitle, flow]); - return ( + return !showNode ? ( + left && + (type === "str" || + type === "bool" || + type === "float" || + type === "code" || + type === "prompt" || + type === "file" || + type === "int") && + !optionalHandle ? ( + <> + ) : ( + + + isValidConnection(connection, reactFlowInstance!) + } + className={classNames( + left ? "my-12 -ml-0.5 " : " my-12 -mr-0.5 ", + "h-3 w-3 rounded-full border-2 bg-background" + )} + style={{ + borderColor: color, + top: position, + }} + > + + ) + ) : (
) : ( - - - isValidConnection(connection, reactFlowInstance!) - } - className={classNames( - left ? "-ml-0.5 " : "-mr-0.5 ", - "h-3 w-3 rounded-full border-2 bg-background" - )} - style={{ - borderColor: color, - top: position, - }} - > - + )} {left === true && @@ -334,11 +406,52 @@ export default function ParameterComponent({ field_name={name} setNodeClass={(nodeClass) => { data.node = nodeClass; + const clone = cloneDeep(data); + clone.node = nodeClass; + setData(clone); }} nodeClass={data.node} disabled={disabled} value={data.node?.template[name].value ?? ""} - onChange={handleOnNewValue} + onChange={(e) => { + handleOnNewValue(e); + }} + /> +
+ ) : left === true && type === "NestedDict" ? ( +
+ { + data.node!.template[name].value = newValue; + handleOnNewValue(newValue); + }} + /> +
+ ) : left === true && type === "dict" ? ( +
+ { + const valueToNumbers = convertValuesToNumbers(newValue); + data.node!.template[name].value = valueToNumbers; + setErrorDuplicateKey(hasDuplicateKeys(valueToNumbers)); + handleOnNewValue(valueToNumbers); + }} />
) : ( diff --git a/src/frontend/src/CustomNodes/GenericNode/index.tsx b/src/frontend/src/CustomNodes/GenericNode/index.tsx index 30dda4034..5f3a99d47 100644 --- a/src/frontend/src/CustomNodes/GenericNode/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/index.tsx @@ -25,10 +25,48 @@ export default function GenericNode({ const [data, setData] = useState(olddata); const { updateFlow, flows, tabId } = useContext(TabsContext); const updateNodeInternals = useUpdateNodeInternals(); - const { types, deleteNode, reactFlowInstance } = useContext(typesContext); + const { types, deleteNode, reactFlowInstance, setFilterEdge, getFilterEdge } = + useContext(typesContext); const name = nodeIconsLucide[data.type] ? data.type : types[data.type]; const [validationStatus, setValidationStatus] = useState(null); + const [showNode, setShowNode] = useState(true); + const [handles, setHandles] = useState([]); + let numberOfInputs: boolean[] = []; + + function countHandles(): void { + numberOfInputs = Object.keys(data.node!.template) + .filter((templateField) => templateField.charAt(0) !== "_") + .map((templateCamp) => { + const { template } = data.node!; + if (template[templateCamp].input_types) return true; + if (!template[templateCamp].show) return false; + switch (template[templateCamp].type) { + case "str": + return false; + case "bool": + return false; + case "float": + return false; + case "code": + return false; + case "prompt": + return false; + case "file": + return false; + case "int": + return false; + default: + return true; + } + }); + setHandles(numberOfInputs); + } + + useEffect(() => { + countHandles(); + }, []); + // State for outline color const { sseData, isBuilding } = useSSE(); useEffect(() => { @@ -50,8 +88,15 @@ export default function GenericNode({ }); updateFlow(flow); } + countHandles(); }, [data]); + useEffect(() => { + setTimeout(() => { + updateNodeInternals(data.id); + }, 300); + }, [showNode]); + // New useEffect to watch for changes in sseData and update validation status useEffect(() => { const relevantData = sseData[data.id]; @@ -70,183 +115,325 @@ export default function GenericNode({ data={data} setData={setData} deleteNode={deleteNode} + setShowNode={setShowNode} + numberOfHandles={handles} + showNode={showNode} >
- {data.node?.beta && ( + {data.node?.beta && showNode && (
BETA
)} -
-
- -
- -
- {data.node?.display_name} -
- -
-
-
-
- Building... - ) : !validationStatus ? ( - - Build{" "} - {" "} - flow to validate status. - - ) : ( -
- {typeof validationStatus.params === "string" - ? validationStatus.params - .split("\n") - .map((line: string, index: number) => ( -
{line}
- )) - : ""} -
- ) - } - > -
-
-
-
-
- -
-
-
- -
-
{data.node?.description}
- - <> - {Object.keys(data.node!.template) - .filter((templateField) => templateField.charAt(0) !== "_") - .map((templateField: string, idx) => ( -
- {data.node!.template[templateField].show && - !data.node!.template[templateField].advanced ? ( - - ) : ( - <> - )} -
- ))} +
+
- {" "} -
- 0 - ? data.node.output_types.join("|") - : data.type + className={ + "generic-node-title-arrangement rounded-full" + + (!showNode && "justify-center") } - tooltipTitle={data.node?.base_classes.join("\n")} - id={[data.type, data.id, ...data.node!.base_classes].join("|")} - type={data.node?.base_classes.join("|")} - left={false} - /> - + > + + {showNode && ( +
+ +
+ {data.node?.display_name} +
+ +
+ )} +
+
+ {!showNode && ( + <> + {Object.keys(data.node!.template) + .filter((templateField) => templateField.charAt(0) !== "_") + .map( + (templateField: string, idx) => + data.node!.template[templateField].show && + !data.node!.template[templateField].advanced && ( + + ) + )} + 0 + ? data.node.output_types.join("|") + : data.type + } + tooltipTitle={data.node?.base_classes.join("\n")} + id={[data.type, data.id, ...data.node!.base_classes].join( + "|" + )} + type={data.node?.base_classes.join("|")} + left={false} + showNode={showNode} + /> + + )} +
+ + {showNode && ( +
+
+ Building... + ) : !validationStatus ? ( + + Build{" "} + {" "} + flow to validate status. + + ) : ( +
+ {typeof validationStatus.params === "string" + ? validationStatus.params + .split("\n") + .map((line: string, index: number) => ( +
{line}
+ )) + : ""} +
+ ) + } + > +
+
+
+
+
+ +
+
+ )} +
+ + {showNode && ( +
+ {data.node?.description !== "" && showNode && ( +
+ {data.node?.description} +
+ )} + + <> + {Object.keys(data.node!.template) + .filter((templateField) => templateField.charAt(0) !== "_") + .map((templateField: string, idx) => ( +
+ {data.node!.template[templateField].show && + !data.node!.template[templateField].advanced ? ( + + ) : ( + <> + )} +
+ ))} +
+ {" "} +
+ 0 + ? data.node.output_types.join("|") + : data.type + } + tooltipTitle={data.node?.base_classes.join("\n")} + id={[data.type, data.id, ...data.node!.base_classes].join("|")} + type={data.node?.base_classes.join("|")} + left={false} + showNode={showNode} + /> + +
+ )}
); diff --git a/src/frontend/src/components/EditFlowSettingsComponent/index.tsx b/src/frontend/src/components/EditFlowSettingsComponent/index.tsx index 77fd64819..b939b4f07 100644 --- a/src/frontend/src/components/EditFlowSettingsComponent/index.tsx +++ b/src/frontend/src/components/EditFlowSettingsComponent/index.tsx @@ -47,21 +47,9 @@ export const EditFlowSettings: React.FC = ({ setInvalidName!(true); } setName(value); - setCurrentName(value); }; - const [currentName, setCurrentName] = useState(name); - - const [currentDescription, setCurrentDescription] = useState(description); - - useEffect(() => { - setCurrentName(name); - setCurrentDescription(description); - }, [name, description]); - const handleDescriptionChange = (event: ChangeEvent) => { - flows.find((f) => f.id === tabId).description = event.target.value; - setCurrentDescription(flows.find((f) => f.id === tabId).description); setDescription(event.target.value); }; @@ -82,7 +70,7 @@ export const EditFlowSettings: React.FC = ({ onChange={handleNameChange} type="text" name="name" - value={currentName ?? ""} + value={name ?? ""} placeholder="File name" id="name" maxLength={maxLength} @@ -97,7 +85,7 @@ export const EditFlowSettings: React.FC = ({ name="description" id="description" onChange={handleDescriptionChange} - value={currentDescription} + value={description} placeholder="Flow description" className="mt-2 max-h-[100px] font-normal" rows={3} diff --git a/src/frontend/src/components/PaginatorComponent/index.tsx b/src/frontend/src/components/PaginatorComponent/index.tsx index 5b285e031..fa759a8bb 100644 --- a/src/frontend/src/components/PaginatorComponent/index.tsx +++ b/src/frontend/src/components/PaginatorComponent/index.tsx @@ -12,17 +12,15 @@ import { Button } from "../ui/button"; export default function PaginatorComponent({ pageSize = 10, - pageIndex = 0, + pageIndex = 1, rowsCount = [10, 20, 50, 100], totalRowsCount = 0, paginate, }: PaginatorComponentType) { const [size, setPageSize] = useState(pageSize); - const [index, setPageIndex] = useState(pageIndex); const [maxIndex, setMaxPageIndex] = useState( Math.ceil(totalRowsCount / pageSize) ); - const [currentPage, setCurrentPage] = useState(1); useEffect(() => { setMaxPageIndex(Math.ceil(totalRowsCount / size)); @@ -39,8 +37,9 @@ export default function PaginatorComponent({ onValueChange={(pageSize: string) => { setPageSize(Number(pageSize)); setMaxPageIndex(Math.ceil(totalRowsCount / Number(pageSize))); - paginate(Number(pageSize), 0); + paginate(Number(pageSize), 1); }} + value={pageSize.toString()} > @@ -55,30 +54,25 @@ export default function PaginatorComponent({
- Page {currentPage} of {maxIndex} + Page {pageIndex} of {maxIndex}
+ ) : ( + + )} +
+ ); + }); + })} + + ); +} diff --git a/src/frontend/src/components/loadingComponent/index.tsx b/src/frontend/src/components/loadingComponent/index.tsx index 0cd3c9ef0..3ef0f8ef5 100644 --- a/src/frontend/src/components/loadingComponent/index.tsx +++ b/src/frontend/src/components/loadingComponent/index.tsx @@ -4,10 +4,10 @@ export default function LoadingComponent({ remSize, }: LoadingComponentProps): JSX.Element { return ( -
+
+
{children}
@@ -27,7 +27,7 @@ const DialogOverlay = React.forwardRef< {children} - + Close diff --git a/src/frontend/src/components/ui/select-custom.tsx b/src/frontend/src/components/ui/select-custom.tsx new file mode 100644 index 000000000..5ed2fbd45 --- /dev/null +++ b/src/frontend/src/components/ui/select-custom.tsx @@ -0,0 +1,108 @@ +"use client"; + +import * as SelectPrimitive from "@radix-ui/react-select"; +import * as React from "react"; +import { cn } from "../../utils/utils"; + +const Select = SelectPrimitive.Root; + +const SelectGroup = SelectPrimitive.Group; + +const SelectValue = SelectPrimitive.Value; + +const SelectTrigger = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, ...props }, ref) => ( + + {children} + + +)); +SelectTrigger.displayName = SelectPrimitive.Trigger.displayName; + +const SelectContent = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, position = "popper", ...props }, ref) => ( + + + + {children} + + + +)); +SelectContent.displayName = SelectPrimitive.Content.displayName; + +const SelectLabel = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); +SelectLabel.displayName = SelectPrimitive.Label.displayName; + +const SelectItem = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, ...props }, ref) => ( + + {children} + +)); +SelectItem.displayName = SelectPrimitive.Item.displayName; + +const SelectSeparator = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); +SelectSeparator.displayName = SelectPrimitive.Separator.displayName; + +export { + Select, + SelectContent, + SelectGroup, + SelectItem, + SelectLabel, + SelectSeparator, + SelectTrigger, + SelectValue, +}; diff --git a/src/frontend/src/constants/constants.ts b/src/frontend/src/constants/constants.ts index 8488ca890..d6ba802ee 100644 --- a/src/frontend/src/constants/constants.ts +++ b/src/frontend/src/constants/constants.ts @@ -115,6 +115,9 @@ export const EDIT_DIALOG_SUBTITLE = export const CODE_PROMPT_DIALOG_SUBTITLE = "Edit your Python code. This code snippet accepts module import and a single function definition. Make sure that your function returns a string."; +export const CODE_DICT_DIALOG_SUBTITLE = + "Edit your dictionary. This dialog allows you to create your own customized dictionary. You can add as many key-value pairs as you want. While in edit mode, you can enter ({}) or ([]), and this will result in adding a new object or array."; + /** * The base text for subtitle of Prompt Dialog * @constant @@ -499,6 +502,21 @@ export const NOUNS: string[] = [ */ export const USER_PROJECTS_HEADER = "My Collection"; +/** + * Header text for admin page + * @constant + * + */ +export const ADMIN_HEADER_TITLE = "Admin Page"; + +/** + * Header description for admin page + * @constant + * + */ +export const ADMIN_HEADER_DESCRIPTION = + "Navigate through this section to efficiently oversee all application users. From here, you can seamlessly manage user accounts."; + /** * URLs excluded from error retries. * @constant @@ -519,6 +537,12 @@ export const CONTROL_INPUT_STATE = { username: "", }; +export const CONTROL_PATCH_USER_STATE = { + password: "", + cnfPassword: "", + gradient: "", +}; + export const CONTROL_LOGIN_STATE = { username: "", password: "", diff --git a/src/frontend/src/contexts/authContext.tsx b/src/frontend/src/contexts/authContext.tsx index e6cd84363..c917b4ef9 100644 --- a/src/frontend/src/contexts/authContext.tsx +++ b/src/frontend/src/contexts/authContext.tsx @@ -63,7 +63,7 @@ export function AuthProvider({ children }): React.ReactElement { .then((user) => { setUserData(user); setLoading(false); - const isSuperUser = user.is_superuser; + const isSuperUser = user!.is_superuser; setIsAdmin(isSuperUser); }) .catch((error) => {}); diff --git a/src/frontend/src/contexts/darkContext.tsx b/src/frontend/src/contexts/darkContext.tsx index bfb758009..571a89b01 100644 --- a/src/frontend/src/contexts/darkContext.tsx +++ b/src/frontend/src/contexts/darkContext.tsx @@ -7,6 +7,8 @@ const initialValue = { setDark: () => {}, stars: 0, setStars: (stars) => 0, + gradientIndex: 0, + setGradientIndex: () => 0, }; export const darkContext = createContext(initialValue); @@ -16,6 +18,7 @@ export function DarkProvider({ children }) { JSON.parse(window.localStorage.getItem("isDark")!) ?? false ); const [stars, setStars] = useState(0); + const [gradientIndex, setGradientIndex] = useState(0); useEffect(() => { async function fetchStars() { @@ -23,6 +26,9 @@ export function DarkProvider({ children }) { setStars(starsCount); } fetchStars(); + const min = 0; + const max = 30; + setGradientIndex(Math.floor(Math.random() * (max - min + 1)) + min); }, []); useEffect(() => { @@ -41,6 +47,8 @@ export function DarkProvider({ children }) { stars, dark, setDark, + setGradientIndex, + gradientIndex, }} > {children} diff --git a/src/frontend/src/contexts/tabsContext.tsx b/src/frontend/src/contexts/tabsContext.tsx index 49de70974..6190a6e56 100644 --- a/src/frontend/src/contexts/tabsContext.tsx +++ b/src/frontend/src/contexts/tabsContext.tsx @@ -238,7 +238,6 @@ export function TabsProvider({ children }: { children: ReactNode }) { function hardReset() { newNodeId.current = uid(); setTabId(""); - setFlows([]); setIsLoading(true); setId(uid()); diff --git a/src/frontend/src/contexts/typesContext.tsx b/src/frontend/src/contexts/typesContext.tsx index 5521e8ebf..7caf5eccc 100644 --- a/src/frontend/src/contexts/typesContext.tsx +++ b/src/frontend/src/contexts/typesContext.tsx @@ -26,6 +26,8 @@ const initialValue: typesContextType = { setData: () => {}, setFetchError: () => {}, fetchError: false, + setFilterEdge: (filter) => {}, + getFilterEdge: [], }; export const typesContext = createContext(initialValue); @@ -39,6 +41,7 @@ export function TypesProvider({ children }: { children: ReactNode }) { const [fetchError, setFetchError] = useState(false); const { setLoading } = useContext(alertContext); const { getAuthentication } = useContext(AuthContext); + const [getFilterEdge, setFilterEdge] = useState([]); useEffect(() => { // If the user is authenticated, fetch the types. This code is important to check if the user is auth because of the execution order of the useEffect hooks. @@ -113,6 +116,8 @@ export function TypesProvider({ children }: { children: ReactNode }) { setData, fetchError, setFetchError, + setFilterEdge, + getFilterEdge, }} > {children} diff --git a/src/frontend/src/controllers/API/api.tsx b/src/frontend/src/controllers/API/api.tsx index 4c444ff37..a456f0ae7 100644 --- a/src/frontend/src/controllers/API/api.tsx +++ b/src/frontend/src/controllers/API/api.tsx @@ -33,11 +33,16 @@ function ApiInterceptor() { } const res = await renewAccessToken(refreshToken); - login(res?.data?.access_token, res?.data?.refresh_token); + if (res?.data?.access_token && res?.data?.refresh_token) { + login(res?.data?.access_token, res?.data?.refresh_token); + } + try { if (error?.config?.headers) { delete error.config.headers["Authorization"]; - error.config.headers["Authorization"] = `Bearer ${accessToken}`; + error.config.headers["Authorization"] = `Bearer ${cookies.get( + "access_token" + )}`; const response = await axios.request(error.config); return response; } diff --git a/src/frontend/src/controllers/API/index.ts b/src/frontend/src/controllers/API/index.ts index bdf7e5221..80e97a73e 100644 --- a/src/frontend/src/controllers/API/index.ts +++ b/src/frontend/src/controllers/API/index.ts @@ -6,6 +6,8 @@ import { APIObjectType, LoginType, Users, + changeUser, + resetPasswordType, sendAllProps, } from "../../types/api/index"; import { UserInputType } from "../../types/components"; @@ -393,16 +395,18 @@ export async function autoLogin() { export async function renewAccessToken(token: string) { try { - return await api.post(`${BASE_URL_API}refresh?token=${token}`); + if (token) { + return await api.post(`${BASE_URL_API}refresh?token=${token}`); + } } catch (error) { console.log("Error:", error); throw error; } } -export async function getLoggedUser(): Promise { +export async function getLoggedUser(): Promise { try { - const res = await api.get(`${BASE_URL_API}user`); + const res = await api.get(`${BASE_URL_API}users/whoami`); if (res.status === 200) { return res.data; @@ -411,14 +415,16 @@ export async function getLoggedUser(): Promise { console.log("Error:", error); throw error; } + return null; } -export async function addUser(user: UserInputType): Promise { +export async function addUser(user: UserInputType): Promise> { try { - const res = await api.post(`${BASE_URL_API}user`, user); - if (res.status === 200) { - return res.data; + const res = await api.post(`${BASE_URL_API}users/`, user); + if (res.status !== 201) { + throw new Error(res.data.detail); } + return res.data; } catch (error) { console.log("Error:", error); throw error; @@ -428,10 +434,10 @@ export async function addUser(user: UserInputType): Promise { export async function getUsersPage( skip: number, limit: number -): Promise<[Users]> { +): Promise> { try { const res = await api.get( - `${BASE_URL_API}users?skip=${skip}&limit=${limit}` + `${BASE_URL_API}users/?skip=${skip}&limit=${limit}` ); if (res.status === 200) { return res.data; @@ -440,11 +446,12 @@ export async function getUsersPage( console.log("Error:", error); throw error; } + return []; } export async function deleteUser(user_id: string) { try { - const res = await api.delete(`${BASE_URL_API}user/${user_id}`); + const res = await api.delete(`${BASE_URL_API}users/${user_id}`); if (res.status === 200) { return res.data; } @@ -454,9 +461,24 @@ export async function deleteUser(user_id: string) { } } -export async function updateUser(user_id: string, user: Users) { +export async function updateUser(user_id: string, user: changeUser) { try { - const res = await api.patch(`${BASE_URL_API}user/${user_id}`, user); + const res = await api.patch(`${BASE_URL_API}users/${user_id}`, user); + if (res.status === 200) { + return res.data; + } + } catch (error) { + console.log("Error:", error); + throw error; + } +} + +export async function resetPassword(user_id: string, user: resetPasswordType) { + try { + const res = await api.patch( + `${BASE_URL_API}users/${user_id}/reset-password`, + user + ); if (res.status === 200) { return res.data; } diff --git a/src/frontend/src/icons/GradientSparkles/index.tsx b/src/frontend/src/icons/GradientSparkles/index.tsx index b8f3534d5..6be7e7576 100644 --- a/src/frontend/src/icons/GradientSparkles/index.tsx +++ b/src/frontend/src/icons/GradientSparkles/index.tsx @@ -1,22 +1,21 @@ -import { Infinity } from "lucide-react"; +import { InfinityIcon } from "lucide-react"; import { forwardRef } from "react"; -const GradientSparkles = forwardRef>( - (props, ref) => { - return ( - <> - - - - - - - - - - - ); - } -); - -export default GradientSparkles; +export const GradientSparkles = forwardRef< + SVGSVGElement, + React.PropsWithChildren<{}> +>((props, ref) => { + return ( + <> + + + + + + + + + + + ); +}); diff --git a/src/frontend/src/modals/ApiModal/index.tsx b/src/frontend/src/modals/ApiModal/index.tsx index ac3ccf3b7..e2ffa00ca 100644 --- a/src/frontend/src/modals/ApiModal/index.tsx +++ b/src/frontend/src/modals/ApiModal/index.tsx @@ -14,6 +14,7 @@ import { import CodeTabsComponent from "../../components/codeTabsComponent"; import IconComponent from "../../components/genericIconComponent"; import { EXPORT_CODE_DIALOG } from "../../constants/constants"; +import { AuthContext } from "../../contexts/authContext"; import { TabsContext } from "../../contexts/tabsContext"; import { TemplateVariableType } from "../../types/api"; import { tweakType, uniqueTweakType } from "../../types/components"; @@ -33,23 +34,27 @@ const ApiModal = forwardRef( { flow, children, - disable, }: { flow: FlowType; children: ReactNode; - disable: boolean; }, ref ) => { + const { autoLogin } = useContext(AuthContext); const [open, setOpen] = useState(false); const [activeTab, setActiveTab] = useState("0"); const tweak = useRef([]); const tweaksList = useRef([]); const { setTweak, getTweak, tabsState } = useContext(TabsContext); - const pythonApiCode = getPythonApiCode(flow, tweak.current, tabsState); - const curl_code = getCurlCode(flow, tweak.current, tabsState); + const pythonApiCode = getPythonApiCode( + flow, + autoLogin, + tweak.current, + tabsState + ); + const curl_code = getCurlCode(flow, autoLogin, tweak.current, tabsState); const pythonCode = getPythonCode(flow, tweak.current, tabsState); - const widgetCode = getWidgetCode(flow, tabsState); + const widgetCode = getWidgetCode(flow, autoLogin, tabsState); const tweaksCode = buildTweaks(flow); const codesArray = [ curl_code, @@ -152,10 +157,15 @@ const ApiModal = forwardRef( tweak.current.push(newTweak); } - const pythonApiCode = getPythonApiCode(flow, tweak.current, tabsState); - const curl_code = getCurlCode(flow, tweak.current, tabsState); + const pythonApiCode = getPythonApiCode( + flow, + autoLogin, + tweak.current, + tabsState + ); + const curl_code = getCurlCode(flow, autoLogin, tweak.current, tabsState); const pythonCode = getPythonCode(flow, tweak.current, tabsState); - const widgetCode = getWidgetCode(flow, tabsState); + const widgetCode = getWidgetCode(flow, autoLogin, tabsState); tabs![0].code = curl_code; tabs![1].code = pythonApiCode; @@ -201,8 +211,8 @@ const ApiModal = forwardRef( } return ( - - {children} + + {children} Code - {children} + {children} {title} void; nodeLength: number; children: ReactNode; + open?: boolean; + onClose?: (close: boolean) => void; }, ref ) => { - const [modalOpen, setModalOpen] = useState(false); + const [modalOpen, setModalOpen] = useState(open ?? false); const [myData, setMyData] = useState(data); const { setTabsState, tabId } = useContext(TabsContext); const { reactFlowInstance } = useContext(typesContext); - let disabled = reactFlowInstance ?.getEdges() .some((edge) => edge.targetHandle === data.id) ?? false; - function changeAdvanced(templateParam: string): void { - setMyData((old) => { - let newData = cloneDeep(old); - newData.node!.template[templateParam].advanced = - !newData.node!.template[templateParam].advanced; - return newData; - }); + function changeAdvanced(n) { + let newData = cloneDeep(data); + newData.node!.template[n].advanced = !newData.node!.template[n].advanced; + setMyData(newData); } - const handleOnNewValue = ( - newValue: string | string[] | boolean, - name: string - ) => { - setMyData((old) => { - let newData = cloneDeep(old); - newData.node!.template[name].value = newValue; - return newData; - }); + const handleOnNewValue = (newValue: any, name) => { + let newData = cloneDeep(data); + newData.node!.template[name].value = newValue; + setMyData(newData); }; useEffect(() => { setMyData(data); // reset data to what it is on node when opening modal + onClose!(modalOpen); }, [modalOpen]); + const [obj, setObj] = useState({ + arr: ["test", 123456, false, null], + boolean: false, + longString: + "long string long string long string long string long string long string", + number: 123456, + try: { + k1: 123, + k2: "123", + k3: false, + }, + string: "string", + }); + + const [errorDuplicateKey, setErrorDuplicateKey] = useState(false); + const [dictArr, setDictArr] = useState([ + { yourKey: "yourValue" }, + ] as Object[]); + return ( - + { + let newData = cloneDeep(data); + setMyData(newData); + }} + > {children} {myData.type} @@ -166,6 +195,52 @@ const EditNodeModal = forwardRef( handleOnNewValue(value, templateParam); }} /> + ) : myData.node?.template[templateParam] + .type === "NestedDict" ? ( +
+ { + setObj(newValue); + }} + /> +
+ ) : myData.node?.template[templateParam] + .type === "dict" ? ( +
+ { + setErrorDuplicateKey( + hasDuplicateKeys(newValue) + ); + if (hasDuplicateKeys(newValue)) { + setDictArr(newValue); + } else { + setDictArr(newValue); + myData.node!.template[ + templateParam + ].value = newValue; + } + }} + /> +
) : myData.node.template[templateParam] .multiline ? ( - {children} + {children} {title} = ({ children }) => { return
{children}
; }; -const Trigger: React.FC = ({ children }) => { - return <>{children}; +const Trigger: React.FC = ({ children, asChild, disable }) => { + return ( + + ); }; const Header: React.FC<{ children: ReactNode; description: string | null }> = ({ @@ -47,7 +59,6 @@ interface BaseModalProps { ]; open?: boolean; setOpen?: (open: boolean) => void; - disable?: boolean; size?: | "x-small" | "smaller" @@ -57,13 +68,16 @@ interface BaseModalProps { | "large-h-full" | "small-h-full" | "medium-h-full"; + + disable?: boolean; + onChangeOpenModal?: (open: boolean) => void; } function BaseModal({ open, setOpen, - disable = false, children, size = "large", + onChangeOpenModal, }: BaseModalProps) { const headerChild = React.Children.toArray(children).find( (child) => (child as React.ReactElement).type === Header @@ -117,20 +131,21 @@ function BaseModal({ break; } + useEffect(() => { + if (onChangeOpenModal) { + onChangeOpenModal(open); + } + }, [open]); + //UPDATE COLORS AND STYLE CLASSSES return ( - + {triggerChild}
{headerChild}
-
+
{ContentChild}
{ContentFooter && ( diff --git a/src/frontend/src/modals/codeAreaModal/index.tsx b/src/frontend/src/modals/codeAreaModal/index.tsx index 0dc6a2a9e..903fb85b5 100644 --- a/src/frontend/src/modals/codeAreaModal/index.tsx +++ b/src/frontend/src/modals/codeAreaModal/index.tsx @@ -28,8 +28,7 @@ export default function CodeAreaModal({ const { dark } = useContext(darkContext); const { reactFlowInstance } = useContext(typesContext); const [height, setHeight] = useState(null); - const { setErrorData, setSuccessData, isTweakPage } = - useContext(alertContext); + const { setErrorData, setSuccessData } = useContext(alertContext); const [error, setError] = useState<{ detail: { error: string | undefined; traceback: string | undefined }; } | null>(null); @@ -165,18 +164,18 @@ export default function CodeAreaModal({
-
+

{error?.detail?.error}

- 
+                
                   {error?.detail?.traceback}
-
+
diff --git a/src/frontend/src/modals/dictAreaModal/index.tsx b/src/frontend/src/modals/dictAreaModal/index.tsx new file mode 100644 index 000000000..fdf0f5bb1 --- /dev/null +++ b/src/frontend/src/modals/dictAreaModal/index.tsx @@ -0,0 +1,67 @@ +import "ace-builds/src-noconflict/ace"; +import "ace-builds/src-noconflict/ext-language_tools"; +import "ace-builds/src-noconflict/mode-python"; +import "ace-builds/src-noconflict/theme-github"; +import "ace-builds/src-noconflict/theme-twilight"; +// import "ace-builds/webpack-resolver"; +import { useEffect, useState } from "react"; +import JsonView from "react18-json-view"; +import "react18-json-view/src/dark.css"; +import "react18-json-view/src/style.css"; +import IconComponent from "../../components/genericIconComponent"; +import { Button } from "../../components/ui/button"; +import { CODE_DICT_DIALOG_SUBTITLE } from "../../constants/constants"; +import BaseModal from "../baseModal"; + +export default function DictAreaModal({ + children, + onChange, + value, +}): JSX.Element { + const [open, setOpen] = useState(false); + const [dictObj, setDictObj] = useState(value); + + useEffect(() => { + if (value) setDictObj(value); + }, [value]); + + return ( + + {children} + + Edit Dictionary + + +
+ { + setDictObj(edit["src"]); + }} + src={dictObj} + /> +
+ +
+
+ + + ); +} diff --git a/src/frontend/src/modals/exportModal/index.tsx b/src/frontend/src/modals/exportModal/index.tsx index c296a1e2c..01b655b39 100644 --- a/src/frontend/src/modals/exportModal/index.tsx +++ b/src/frontend/src/modals/exportModal/index.tsx @@ -10,15 +10,15 @@ import BaseModal from "../baseModal"; const ExportModal = forwardRef( (props: { children: ReactNode }, ref): JSX.Element => { - const { flows, tabId, updateFlow, downloadFlow } = useContext(TabsContext); + const { flows, tabId, downloadFlow } = useContext(TabsContext); const [checked, setChecked] = useState(false); const flow = flows.find((f) => f.id === tabId); useEffect(() => { - setName(flow.name); - setDescription(flow.description); - }, [flow.name, flow.description]); - const [name, setName] = useState(flow.name); - const [description, setDescription] = useState(flow.description); + setName(flow!.name); + setDescription(flow!.description); + }, [flow!.name, flow!.description]); + const [name, setName] = useState(flow!.name); + const [description, setDescription] = useState(flow!.description); const [open, setOpen] = useState(false); return ( @@ -40,7 +40,6 @@ const ExportModal = forwardRef( tabId={tabId} setName={setName} setDescription={setDescription} - updateFlow={updateFlow} />
0) { //set chat history setChatHistory((_) => { let newChatHistory: ChatMessageType[] = []; @@ -313,7 +314,7 @@ export default function FormModal({ } }; // do not add connectWS on dependencies array - }, []); + }, [open]); useEffect(() => { if ( diff --git a/src/frontend/src/modals/genericModal/index.tsx b/src/frontend/src/modals/genericModal/index.tsx index b29c5acf8..baebd67ba 100644 --- a/src/frontend/src/modals/genericModal/index.tsx +++ b/src/frontend/src/modals/genericModal/index.tsx @@ -122,15 +122,22 @@ export default function GenericModal({ function validatePrompt(closeModal: boolean): void { //nodeClass is always null on tweaks + postValidatePrompt(field_name, inputValue, nodeClass!) .then((apiReturn) => { if (apiReturn.data) { + setValue(inputValue); + apiReturn.data.frontend_node["template"]["template"]["value"] = + inputValue; + setNodeClass!(apiReturn?.data?.frontend_node); + let inputVariables = apiReturn.data.input_variables ?? []; if (inputVariables && inputVariables.length === 0) { setIsEdit(true); setNoticeData({ title: "Your template does not have any variables.", }); + setModalOpen(false); } else { setIsEdit(false); setSuccessData({ @@ -163,7 +170,11 @@ export default function GenericModal({ const [modalOpen, setModalOpen] = useState(false); return ( - + {}} + open={modalOpen} + setOpen={setModalOpen} + > {children} { @@ -290,9 +301,7 @@ export default function GenericModal({ setModalOpen(false); break; case TypeModal.PROMPT: - !inputValue || inputValue === "" - ? setModalOpen(false) - : validatePrompt(false); + validatePrompt(false); break; default: diff --git a/src/frontend/src/pages/AdminPage/LoginPage/index.tsx b/src/frontend/src/pages/AdminPage/LoginPage/index.tsx index 3a56b8e99..e0ceaad49 100644 --- a/src/frontend/src/pages/AdminPage/LoginPage/index.tsx +++ b/src/frontend/src/pages/AdminPage/LoginPage/index.tsx @@ -48,7 +48,7 @@ export default function LoginAdminPage() { } function getUser() { - if (getAuthentication) { + if (getAuthentication()) { setTimeout(() => { getLoggedUser() .then((user) => { diff --git a/src/frontend/src/pages/AdminPage/index.tsx b/src/frontend/src/pages/AdminPage/index.tsx index 08e83f700..24baefb5b 100644 --- a/src/frontend/src/pages/AdminPage/index.tsx +++ b/src/frontend/src/pages/AdminPage/index.tsx @@ -1,10 +1,10 @@ import { cloneDeep } from "lodash"; -import { X } from "lucide-react"; import { useContext, useEffect, useRef, useState } from "react"; import PaginatorComponent from "../../components/PaginatorComponent"; import ShadTooltip from "../../components/ShadTooltipComponent"; import IconComponent from "../../components/genericIconComponent"; import Header from "../../components/headerComponent"; +import LoadingComponent from "../../components/loadingComponent"; import { Button } from "../../components/ui/button"; import { Checkbox } from "../../components/ui/checkbox"; import { Input } from "../../components/ui/input"; @@ -16,8 +16,13 @@ import { TableHeader, TableRow, } from "../../components/ui/table"; +import { + ADMIN_HEADER_DESCRIPTION, + ADMIN_HEADER_TITLE, +} from "../../constants/constants"; import { alertContext } from "../../contexts/alertContext"; import { AuthContext } from "../../contexts/authContext"; +import { TabsContext } from "../../contexts/tabsContext"; import { addUser, deleteUser, @@ -33,12 +38,19 @@ export default function AdminPage() { const [inputValue, setInputValue] = useState(""); const [size, setPageSize] = useState(10); - const [index, setPageIndex] = useState(0); + const [index, setPageIndex] = useState(1); const [loadingUsers, setLoadingUsers] = useState(true); const { setErrorData, setSuccessData } = useContext(alertContext); const { userData } = useContext(AuthContext); const [totalRowsCount, setTotalRowsCount] = useState(0); + const { setTabId } = useContext(TabsContext); + + // set null id + useEffect(() => { + setTabId(""); + }, []); + const userList = useRef([]); useEffect(() => { @@ -65,7 +77,9 @@ export default function AdminPage() { function handleChangePagination(pageIndex: number, pageSize: number) { setLoadingUsers(true); - getUsersPage(pageIndex, pageSize) + setPageSize(pageSize); + setPageIndex(pageIndex); + getUsersPage(pageSize * (pageIndex - 1), pageSize) .then((users) => { setTotalRowsCount(users["total_count"]); userList.current = users["users"]; @@ -78,7 +92,7 @@ export default function AdminPage() { } function resetFilter() { - setPageIndex(0); + setPageIndex(1); setPageSize(10); getUsers(); } @@ -168,270 +182,264 @@ export default function AdminPage() { function handleNewUser(user: UserInputType) { addUser(user) .then((res) => { - resetFilter(); - setSuccessData({ - title: "Success! New user added!", + updateUser(res["id"], { + is_active: user.is_active, + is_superuser: user.is_superuser, + }).then((res) => { + resetFilter(); + setSuccessData({ + title: "Success! New user added!", + }); }); }) .catch((error) => { setErrorData({ - title: "Error on add new user", - list: [error["response"]["data"]["detail"]], + title: "Error when adding new user", + list: [error.response.data.detail], }); }); } return ( <> -
-
- {userData && ( -
-
-
-
-
-
-

- Welcome back! -

-

- Navigate through this section to efficiently oversee all - application users. From here, you can seamlessly manage - user accounts. -

-
-
-
- - {userList.current.length === 0 && !loadingUsers && ( - <> -
-

There's no users registered :)

-
- - )} - <> -
-
- handleFilterUsers(e.target.value)} - /> - {inputValue.length > 0 && ( - - )} -
-
- { - handleNewUser(user); - }} - > - - -
-
- {loadingUsers && ( -
- Loading... -
- )} -
- - - - Id - Username - Active - Superuser - Created At - Updated At - - - - {!loadingUsers && ( - - {filterUserList.map( - (user: UserInputType, index) => ( - - - - - {user.id} - - - - - - - {user.username} - - - - - { - handleDisableUser( - user.is_active, - user.id, - user - ); - }} - > - - - - - { - handleSuperUserEdit( - user.is_superuser, - user.id, - user - ); - }} - > - - - - - { - new Date(user.create_at!) - .toISOString() - .split("T")[0] - } - - - { - new Date(user.updated_at!) - .toISOString() - .split("T")[0] - } - - -
- { - handleEditUser(user.id, editUser); - }} - > - - - - - - { - handleDeleteUser(user); - }} - > - - - - -
- - - ) - )} - - )} -
-
- - { - handleChangePagination(pageSize, pageIndex); - }} - > - +
+ {userData && ( +
+
+ + + {ADMIN_HEADER_TITLE} + +
+ + {ADMIN_HEADER_DESCRIPTION} + +
+
+ handleFilterUsers(e.target.value)} + /> + {inputValue.length > 0 ? ( +
{ + setInputValue(""); + setFilterUserList(userList.current); + }} + > +
-
+ ) : ( +
+ +
+ )} +
+
+ { + handleNewUser(user); + }} + asChild + > + +
- )} -
+ {loadingUsers ? ( +
+ +
+ ) : userList.current.length === 0 ? ( + <> +
+ No users registered. +
+ + ) : ( + <> +
+ + + + Id + Username + Active + Superuser + Created At + Updated At + + + + {!loadingUsers && ( + + {filterUserList.map((user: UserInputType, index) => ( + + + + {user.id} + + + + + + {user.username} + + + + + { + handleDisableUser( + user.is_active, + user.id, + user + ); + }} + > +
+ +
+ + + + { + handleSuperUserEdit( + user.is_superuser, + user.id, + user + ); + }} + > +
+ +
+ + + + { + new Date(user.create_at!) + .toISOString() + .split("T")[0] + } + + + { + new Date(user.updated_at!) + .toISOString() + .split("T")[0] + } + + +
+ { + handleEditUser(user.id, editUser); + }} + > + + + + + + { + handleDeleteUser(user); + }} + > + + + + +
+ + + ))} + + )} +
+
+ + { + handleChangePagination(pageIndex, pageSize); + }} + > + + )} +
+ )} ); } diff --git a/src/frontend/src/pages/CommunityPage/index.tsx b/src/frontend/src/pages/CommunityPage/index.tsx index c96bbdaf4..7f808f035 100644 --- a/src/frontend/src/pages/CommunityPage/index.tsx +++ b/src/frontend/src/pages/CommunityPage/index.tsx @@ -7,6 +7,7 @@ import { useNavigate } from "react-router-dom"; import { CardComponent } from "../../components/cardComponent"; import IconComponent from "../../components/genericIconComponent"; import Header from "../../components/headerComponent"; +import { SkeletonCardComponent } from "../../components/skeletonCardComponent"; import { getExamples } from "../../controllers/API"; import { FlowType } from "../../types/flow"; export default function CommunityPage(): JSX.Element { @@ -74,7 +75,14 @@ export default function CommunityPage(): JSX.Element { new and powerful features.
- {!loadingExamples && + {loadingExamples ? ( + <> + + + + + + ) : ( examples.map((flow, idx) => ( } /> - ))} + )) + )}
diff --git a/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx index 620170fbb..eae785fc7 100644 --- a/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx @@ -64,8 +64,13 @@ export default function Page({ setTabsState, tabId, } = useContext(TabsContext); - const { types, reactFlowInstance, setReactFlowInstance, templates } = - useContext(typesContext); + const { + types, + reactFlowInstance, + setReactFlowInstance, + templates, + setFilterEdge, + } = useContext(typesContext); const reactFlowWrapper = useRef(null); const { takeSnapshot } = useContext(undoRedoContext); @@ -298,7 +303,14 @@ export default function Page({ setNodes((nds) => nds.concat(newNode)); } else if (event.dataTransfer.types.some((types) => types === "Files")) { takeSnapshot(); - uploadFlow(false, event.dataTransfer.files.item(0)!); + if (event.dataTransfer.files.item(0)!.type === "application/json") { + uploadFlow(true, event.dataTransfer.files.item(0)!); + } else { + setErrorData({ + title: "Invalid file type", + list: ["Please upload a JSON file"], + }); + } } }, // Specify dependencies for useCallback @@ -375,6 +387,10 @@ export default function Page({ [] ); + const onPaneClick = useCallback((flow) => { + setFilterEdge([]); + }, []); + return (
{!view && } @@ -422,6 +438,7 @@ export default function Page({ zoomOnPinch={!view} panOnDrag={!view} proOptions={{ hideAttribution: true }} + onPaneClick={onPaneClick} > {!view && ( diff --git a/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx index 8ea74390a..d831716dc 100644 --- a/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx @@ -1,3 +1,4 @@ +import { cloneDeep } from "lodash"; import { useContext, useEffect, useState } from "react"; import ShadTooltip from "../../../../components/ShadTooltipComponent"; import IconComponent from "../../../../components/genericIconComponent"; @@ -18,7 +19,8 @@ import { classNames } from "../../../../utils/utils"; import DisclosureComponent from "../DisclosureComponent"; export default function ExtraSidebar(): JSX.Element { - const { data, templates } = useContext(typesContext); + const { data, templates, getFilterEdge, setFilterEdge } = + useContext(typesContext); const { flows, tabId, uploadFlow, tabsState, saveFlow, isBuilt } = useContext(TabsContext); const { setSuccessData, setErrorData } = useContext(alertContext); @@ -42,6 +44,10 @@ export default function ExtraSidebar(): JSX.Element { // Handle showing components after use search input function handleSearchInput(e: string) { + if (e === "") { + setFilterData(data); + return; + } setFilterData((_) => { let ret = {}; Object.keys(data).forEach((d: keyof APIObjectType, i) => { @@ -69,6 +75,57 @@ export default function ExtraSidebar(): JSX.Element { setErrorData({ title: " Components with errors: ", list: errors }); }, []); + function handleBlur() { + setFilterData(data); + setFilterEdge([]); + setSearch(""); + } + + useEffect(() => { + if (getFilterEdge.length === 0 && search === "") { + setFilterData(data); + setFilterEdge([]); + setSearch(""); + } + }, [getFilterEdge]); + + useEffect(() => { + if (getFilterEdge?.length > 0) { + setFilterData((_) => { + let dataClone = cloneDeep(data); + let ret = {}; + Object.keys(dataClone).forEach((d: keyof APIObjectType, i) => { + ret[d] = {}; + if (getFilterEdge.some((x) => x.family === d)) { + ret[d] = dataClone[d]; + + const filtered = getFilterEdge + .filter((x) => x.family === d) + .pop() + .type.split(","); + + for (let i = 0; i < filtered.length; i++) { + filtered[i] = filtered[i].trimStart(); + } + + if (filtered.some((x) => x !== "")) { + let keys = Object.keys(dataClone[d]).filter((nd) => + filtered.includes(nd) + ); + Object.keys(dataClone[d]).forEach((element) => { + if (!keys.includes(element)) { + delete ret[d][element]; + } + }); + } + } + }); + setSearch("search"); + return ret; + }); + } + }, [getFilterEdge]); + return (
@@ -99,16 +156,20 @@ export default function ExtraSidebar(): JSX.Element {
{flow && flow.data && ( - -
- -
+ + )}
@@ -137,6 +198,7 @@ export default function ExtraSidebar(): JSX.Element {
handleBlur()} type="text" name="search" id="search" diff --git a/src/frontend/src/pages/FlowPage/components/nodeToolbarComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/nodeToolbarComponent/index.tsx index c628e4003..e1e3bd5c4 100644 --- a/src/frontend/src/pages/FlowPage/components/nodeToolbarComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/nodeToolbarComponent/index.tsx @@ -1,16 +1,25 @@ import { useContext, useState } from "react"; -import { useReactFlow } from "reactflow"; +import { useReactFlow, useUpdateNodeInternals } from "reactflow"; import ShadTooltip from "../../../../components/ShadTooltipComponent"; import IconComponent from "../../../../components/genericIconComponent"; +import { + Select, + SelectContent, + SelectItem, + SelectTrigger, +} from "../../../../components/ui/select-custom"; import { TabsContext } from "../../../../contexts/tabsContext"; import EditNodeModal from "../../../../modals/EditNodeModal"; import { nodeToolbarPropsType } from "../../../../types/components"; -import { classNames } from "../../../../utils/utils"; +import { classNames, getRandomKeyByssmm } from "../../../../utils/utils"; export default function NodeToolbarComponent({ data, setData, deleteNode, + setShowNode, + numberOfHandles, + showNode, }: nodeToolbarPropsType): JSX.Element { const [nodeLength, setNodeLength] = useState( Object.keys(data.node!.template).filter( @@ -27,9 +36,34 @@ export default function NodeToolbarComponent({ data.node.template[templateField].type === "int") ).length ); + const updateNodeInternals = useUpdateNodeInternals(); + function canMinimize() { + let countHandles: number = 0; + numberOfHandles.forEach((bool) => { + if (bool) countHandles += 1; + }); + if (countHandles > 1) return false; + return true; + } + const isMinimal = canMinimize(); const { paste } = useContext(TabsContext); const reactFlowInstance = useReactFlow(); + const [showModalAdvanced, setShowModalAdvanced] = useState(false); + const [selectedValue, setSelectedValue] = useState(""); + + const handleSelectChange = (event) => { + setSelectedValue(event); + if (event.includes("advanced")) { + return setShowModalAdvanced(true); + } + setShowModalAdvanced(false); + if (event.includes("show")) { + setShowNode((prev) => !prev); + updateNodeInternals(data.id); + } + }; + return ( <>
@@ -97,6 +131,83 @@ export default function NodeToolbarComponent({ + {isMinimal ? ( + + ) : ( + +
+ +
+ + )} + + {showModalAdvanced && ( + { + setShowModalAdvanced(modal); + }} + > + <> + + )} + + {/*
- + */}
diff --git a/src/frontend/src/pages/MainPage/index.tsx b/src/frontend/src/pages/MainPage/index.tsx index 9582d4c57..f45e4cfc8 100644 --- a/src/frontend/src/pages/MainPage/index.tsx +++ b/src/frontend/src/pages/MainPage/index.tsx @@ -1,4 +1,4 @@ -import { useContext, useEffect } from "react"; +import { useContext, useEffect, useState } from "react"; import { Link, useNavigate } from "react-router-dom"; import DropdownButton from "../../components/DropdownButtonComponent"; import { CardComponent } from "../../components/cardComponent"; @@ -7,6 +7,7 @@ import Header from "../../components/headerComponent"; import { SkeletonCardComponent } from "../../components/skeletonCardComponent"; import { Button } from "../../components/ui/button"; import { USER_PROJECTS_HEADER } from "../../constants/constants"; +import { alertContext } from "../../contexts/alertContext"; import { TabsContext } from "../../contexts/tabsContext"; export default function HomePage(): JSX.Element { const { @@ -19,6 +20,7 @@ export default function HomePage(): JSX.Element { uploadFlow, isLoading, } = useContext(TabsContext); + const { setErrorData } = useContext(alertContext); const dropdownOptions = [ { name: "Import from JSON", @@ -35,9 +37,36 @@ export default function HomePage(): JSX.Element { }, []); const navigate = useNavigate(); - useEffect(() => { - console.log(isLoading); - }, [isLoading]); + const [isDragging, setIsDragging] = useState(false); + + const dragOver = (e) => { + e.preventDefault(); + setIsDragging(true); + }; + + const dragEnter = (e) => { + e.preventDefault(); + setIsDragging(true); + }; + + const dragLeave = () => { + setIsDragging(false); + }; + + const fileDrop = (e) => { + e.preventDefault(); + setIsDragging(false); + if (e.dataTransfer.types.some((types) => types === "Files")) { + if (e.dataTransfer.files.item(0).type === "application/json") { + uploadFlow(true, e.dataTransfer.files.item(0)!); + } else { + setErrorData({ + title: "Invalid file type", + list: ["Please upload a JSON file"], + }); + } + } + }; // Personal flows display return ( @@ -82,40 +111,63 @@ export default function HomePage(): JSX.Element { Manage your personal projects. Download or upload your collection. -
- {isLoading && flows.length == 0 ? ( +
+ {isDragging ? ( <> - - - - + + Drop your flow here ) : ( - flows.map((flow, idx) => ( - - - - } - onDelete={() => { - removeFlow(flow.id); - }} - /> - )) +
+ {isLoading && flows.length == 0 ? ( + <> + + + + + + ) : ( + flows.map((flow, idx) => ( + + + + } + onDelete={() => { + removeFlow(flow.id); + }} + /> + )) + )} +
)}
diff --git a/src/frontend/src/pages/ProfileSettingsPage/index.tsx b/src/frontend/src/pages/ProfileSettingsPage/index.tsx new file mode 100644 index 000000000..443de4a4b --- /dev/null +++ b/src/frontend/src/pages/ProfileSettingsPage/index.tsx @@ -0,0 +1,173 @@ +import * as Form from "@radix-ui/react-form"; +import { cloneDeep } from "lodash"; +import { useContext, useEffect, useState } from "react"; +import IconComponent from "../../components/genericIconComponent"; +import GradientChooserComponent from "../../components/gradientChooserComponent"; +import Header from "../../components/headerComponent"; +import InputComponent from "../../components/inputComponent"; +import { Button } from "../../components/ui/button"; +import { CONTROL_PATCH_USER_STATE } from "../../constants/constants"; +import { alertContext } from "../../contexts/alertContext"; +import { AuthContext } from "../../contexts/authContext"; +import { TabsContext } from "../../contexts/tabsContext"; +import { resetPassword, updateUser } from "../../controllers/API"; +import { + inputHandlerEventType, + patchUserInputStateType, +} from "../../types/components"; +import { gradients } from "../../utils/styleUtils"; +export default function ProfileSettingsPage(): JSX.Element { + const { setTabId } = useContext(TabsContext); + + const [inputState, setInputState] = useState( + CONTROL_PATCH_USER_STATE + ); + + // set null id + useEffect(() => { + setTabId(""); + }, []); + const { setErrorData, setSuccessData } = useContext(alertContext); + const { userData, setUserData } = useContext(AuthContext); + const { password, cnfPassword, gradient } = inputState; + + async function handlePatchUser() { + if (password !== cnfPassword) { + setErrorData({ + title: "Error changing password", + list: ["Passwords do not match"], + }); + return; + } + try { + if (password !== "") await resetPassword(userData!.id, { password }); + if (gradient !== "") + await updateUser(userData!.id, { profile_image: gradient }); + if (gradient !== "") { + let newUserData = cloneDeep(userData); + newUserData!.profile_image = gradient; + + setUserData(newUserData); + } + handleInput({ target: { name: "password", value: "" } }); + handleInput({ target: { name: "cnfPassword", value: "" } }); + setSuccessData({ title: "Changes saved successfully!" }); + } catch (error) { + setErrorData({ + title: "Error saving changes", + list: [(error as any).response.data.detail], + }); + } + } + + function handleInput({ + target: { name, value }, + }: inputHandlerEventType): void { + setInputState((prev) => ({ ...prev, [name]: value })); + } + + return ( + <> +
+ +
+
+ + + Profile Settings + +
+ + Change your profile settings like your password and your profile + picture. + + { + handlePatchUser(); + const data = Object.fromEntries(new FormData(event.currentTarget)); + event.preventDefault(); + }} + className="flex h-full flex-col px-6 pb-16" + > +
+
+
+ + + Password{" "} + + { + handleInput({ target: { name: "password", value } }); + }} + value={password} + isForm + password={true} + placeholder="Password" + className="w-full" + /> + + Please enter your password + + +
+
+ + + Confirm Password{" "} + + + { + handleInput({ target: { name: "cnfPassword", value } }); + }} + value={cnfPassword} + isForm + password={true} + placeholder="Confirm Password" + className="w-full" + /> + + + Please confirm your password + + +
+
+ + + Profile Gradient{" "} + + +
+ { + handleInput({ target: { name: "gradient", value } }); + }} + /> +
+ +
+ +
+
+ + + +
+
+ +
+ + ); +} diff --git a/src/frontend/src/pages/loginPage/index.tsx b/src/frontend/src/pages/loginPage/index.tsx index 061d4ac0b..ff9d53e82 100644 --- a/src/frontend/src/pages/loginPage/index.tsx +++ b/src/frontend/src/pages/loginPage/index.tsx @@ -54,7 +54,7 @@ export default function LoginPage(): JSX.Element { setTimeout(() => { getLoggedUser() .then((user) => { - const isSuperUser = user.is_superuser; + const isSuperUser = user!.is_superuser; setIsAdmin(isSuperUser); setUserData(user); }) diff --git a/src/frontend/src/pages/signUpPage/index.tsx b/src/frontend/src/pages/signUpPage/index.tsx index 4b83bc07d..d153dc522 100644 --- a/src/frontend/src/pages/signUpPage/index.tsx +++ b/src/frontend/src/pages/signUpPage/index.tsx @@ -1,5 +1,5 @@ import * as Form from "@radix-ui/react-form"; -import { FormEvent, useContext, useState } from "react"; +import { FormEvent, useContext, useEffect, useState } from "react"; import { Link, useNavigate } from "react-router-dom"; import InputComponent from "../../components/inputComponent"; import { Button } from "../../components/ui/button"; @@ -20,6 +20,8 @@ export default function SignUp(): JSX.Element { const [inputState, setInputState] = useState(CONTROL_INPUT_STATE); + const [isDisabled, setDisableBtn] = useState(true); + const { password, cnfPassword, username } = inputState; const { setErrorData, setSuccessData } = useContext(alertContext); const navigate = useNavigate(); @@ -30,6 +32,13 @@ export default function SignUp(): JSX.Element { setInputState((prev) => ({ ...prev, [name]: value })); } + useEffect(() => { + if (password !== cnfPassword) return setDisableBtn(true); + if (password === "" || cnfPassword === "") return setDisableBtn(true); + if (username === "") return setDisableBtn(true); + setDisableBtn(false); + }, [password, cnfPassword, username, handleInput]); + function handleSignup(): void { const { username, password } = inputState; const newUser: UserInputType = { @@ -158,6 +167,7 @@ export default function SignUp(): JSX.Element {