Merge branch 'zustand/io/migration' into globalVariables
This commit is contained in:
Lucas Oliveira
commit
6c9a87bed7
529 changed files with 26323 additions and 10993 deletions
|
|
@ -56,6 +56,13 @@ LANGFLOW_REMOVE_API_KEYS=
|
|||
# LANGFLOW_REDIS_CACHE_EXPIRE (default: 3600)
|
||||
LANGFLOW_CACHE_TYPE=
|
||||
|
||||
|
||||
# Set AUTO_LOGIN to false if you want to disable auto login
|
||||
# and use the login form to login. LANGFLOW_SUPERUSER and LANGFLOW_SUPERUSER_PASSWORD
|
||||
# must be set if AUTO_LOGIN is set to false
|
||||
# Values: true, false
|
||||
LANGFLOW_AUTO_LOGIN=
|
||||
|
||||
# Superuser username
|
||||
# Example: LANGFLOW_SUPERUSER=admin
|
||||
LANGFLOW_SUPERUSER=
|
||||
|
|
|
|||
|
|
@ -1,6 +0,0 @@
|
|||
#!/bin/sh
|
||||
|
||||
added_files=$(git diff --name-only --cached --diff-filter=d)
|
||||
|
||||
make format
|
||||
git add ${added_files}
|
||||
11
.github/dependabot.yml
vendored
Normal file
11
.github/dependabot.yml
vendored
Normal file
|
|
@ -0,0 +1,11 @@
|
|||
# Set update schedule for GitHub Actions
|
||||
|
||||
version: 2
|
||||
updates:
|
||||
|
||||
- package-ecosystem: "github-actions"
|
||||
directory: "/"
|
||||
schedule:
|
||||
# Check for updates to GitHub Actions every week
|
||||
interval: "monthly"
|
||||
|
||||
4
.github/workflows/ci.yml
vendored
4
.github/workflows/ci.yml
vendored
|
|
@ -16,10 +16,10 @@ jobs:
|
|||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v2
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Cache Docker layers
|
||||
uses: actions/cache@v2
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: /tmp/.buildx-cache
|
||||
key: ${{ runner.os }}-buildx-${{ github.sha }}
|
||||
|
|
|
|||
8
.github/workflows/codeql.yml
vendored
8
.github/workflows/codeql.yml
vendored
|
|
@ -30,11 +30,11 @@ jobs:
|
|||
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v3
|
||||
uses: actions/checkout@v4
|
||||
|
||||
# Initializes the CodeQL tools for scanning.
|
||||
- name: Initialize CodeQL
|
||||
uses: github/codeql-action/init@v2
|
||||
uses: github/codeql-action/init@v3
|
||||
with:
|
||||
languages: ${{ matrix.language }}
|
||||
# If you wish to specify custom queries, you can do so here or in a config file.
|
||||
|
|
@ -48,7 +48,7 @@ jobs:
|
|||
# Autobuild attempts to build any compiled languages (C/C++, C#, Go, Java, or Swift).
|
||||
# If this step fails, then you should remove it and run the build manually (see below)
|
||||
- name: Autobuild
|
||||
uses: github/codeql-action/autobuild@v2
|
||||
uses: github/codeql-action/autobuild@v3
|
||||
|
||||
# ℹ️ Command-line programs to run using the OS shell.
|
||||
# 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
|
||||
|
|
@ -61,6 +61,6 @@ jobs:
|
|||
# ./location_of_script_within_repo/buildscript.sh
|
||||
|
||||
- name: Perform CodeQL Analysis
|
||||
uses: github/codeql-action/analyze@v2
|
||||
uses: github/codeql-action/analyze@v3
|
||||
with:
|
||||
category: "/language:${{matrix.language}}"
|
||||
|
|
|
|||
4
.github/workflows/deploy_gh-pages.yml
vendored
4
.github/workflows/deploy_gh-pages.yml
vendored
|
|
@ -12,8 +12,8 @@ jobs:
|
|||
name: Deploy to GitHub Pages
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/setup-node@v3
|
||||
- uses: actions/checkout@v4
|
||||
- uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: 18
|
||||
cache: npm
|
||||
|
|
|
|||
13
.github/workflows/lint.yml
vendored
13
.github/workflows/lint.yml
vendored
|
|
@ -3,7 +3,15 @@ name: lint
|
|||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
paths:
|
||||
- "poetry.lock"
|
||||
- "pyproject.toml"
|
||||
- "src/backend/**"
|
||||
pull_request:
|
||||
paths:
|
||||
- "poetry.lock"
|
||||
- "pyproject.toml"
|
||||
- "src/backend/**"
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.7.0"
|
||||
|
|
@ -16,13 +24,14 @@ jobs:
|
|||
python-version:
|
||||
- "3.9"
|
||||
- "3.10"
|
||||
- "3.11"
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: |
|
||||
pipx install poetry==$POETRY_VERSION
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v4
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
cache: poetry
|
||||
|
|
|
|||
4
.github/workflows/pre-release.yml
vendored
4
.github/workflows/pre-release.yml
vendored
|
|
@ -18,11 +18,11 @@ jobs:
|
|||
if: ${{ (github.event.pull_request.merged == true) && contains(github.event.pull_request.labels.*.name, 'pre-release') }}
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v4
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.10"
|
||||
cache: "poetry"
|
||||
|
|
|
|||
4
.github/workflows/release.yml
vendored
4
.github/workflows/release.yml
vendored
|
|
@ -17,11 +17,11 @@ jobs:
|
|||
if: ${{ (github.event.pull_request.merged == true) && contains(github.event.pull_request.labels.*.name, 'Release') }}
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
- name: Set up Python 3.10
|
||||
uses: actions/setup-python@v4
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.10"
|
||||
cache: "poetry"
|
||||
|
|
|
|||
13
.github/workflows/test.yml
vendored
13
.github/workflows/test.yml
vendored
|
|
@ -3,8 +3,16 @@ name: test
|
|||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
paths:
|
||||
- "poetry.lock"
|
||||
- "pyproject.toml"
|
||||
- "src/backend/**"
|
||||
pull_request:
|
||||
branches: [dev]
|
||||
paths:
|
||||
- "poetry.lock"
|
||||
- "pyproject.toml"
|
||||
- "src/backend/**"
|
||||
|
||||
env:
|
||||
POETRY_VERSION: "1.5.0"
|
||||
|
|
@ -16,14 +24,15 @@ jobs:
|
|||
matrix:
|
||||
python-version:
|
||||
- "3.10"
|
||||
- "3.11"
|
||||
env:
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install poetry
|
||||
run: pipx install poetry==$POETRY_VERSION
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v4
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
cache: "poetry"
|
||||
|
|
|
|||
1
.gitignore
vendored
1
.gitignore
vendored
|
|
@ -260,3 +260,4 @@ langflow.db
|
|||
src/backend/langflow/frontend/
|
||||
.docker
|
||||
scratchpad*
|
||||
chroma*/*
|
||||
|
|
|
|||
3
.vscode/launch.json
vendored
3
.vscode/launch.json
vendored
|
|
@ -17,6 +17,9 @@
|
|||
],
|
||||
"jinja": true,
|
||||
"justMyCode": true,
|
||||
"env": {
|
||||
"LANGFLOW_LOG_LEVEL": "debug"
|
||||
},
|
||||
"envFile": "${workspaceFolder}/.env"
|
||||
},
|
||||
{
|
||||
|
|
|
|||
4
Makefile
4
Makefile
|
|
@ -3,10 +3,6 @@
|
|||
all: help
|
||||
|
||||
init:
|
||||
@echo 'Installing pre-commit hooks'
|
||||
git config core.hooksPath .githooks
|
||||
@echo 'Making pre-commit hook executable'
|
||||
chmod +x .githooks/pre-commit
|
||||
@echo 'Installing backend dependencies'
|
||||
make install_backend
|
||||
@echo 'Installing frontend dependencies'
|
||||
|
|
|
|||
80
README.md
80
README.md
|
|
@ -1,46 +1,27 @@
|
|||
<!-- Title -->
|
||||
<!-- markdownlint-disable MD030 -->
|
||||
|
||||
# ⛓️ Langflow
|
||||
|
||||
~ An effortless way to experiment and prototype [LangChain](https://github.com/hwchase17/langchain) pipelines ~
|
||||
<h3>Discover a simpler & smarter way to build around Foundation Models</h3>
|
||||
|
||||
<p>
|
||||
<img alt="GitHub Contributors" src="https://img.shields.io/github/contributors/logspace-ai/langflow" />
|
||||
<img alt="GitHub Last Commit" src="https://img.shields.io/github/last-commit/logspace-ai/langflow" />
|
||||
<img alt="" src="https://img.shields.io/github/repo-size/logspace-ai/langflow" />
|
||||
<img alt="GitHub Issues" src="https://img.shields.io/github/issues/logspace-ai/langflow" />
|
||||
<img alt="GitHub Pull Requests" src="https://img.shields.io/github/issues-pr/logspace-ai/langflow" />
|
||||
<img alt="Github License" src="https://img.shields.io/github/license/logspace-ai/langflow" />
|
||||
</p>
|
||||
[](https://github.com/logspace-ai/langflow/releases)
|
||||
[](https://github.com/logspace-ai/langflow/contributors)
|
||||
[](https://github.com/logspace-ai/langflow/last-commit)
|
||||
[](https://github.com/logspace-ai/langflow/issues)
|
||||
[](https://github.com/logspace-ai/langflow/repo-size)
|
||||
[](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/logspace-ai/langflow)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://star-history.com/#logspace-ai/langflow)
|
||||
[](https://github.com/logspace-ai/langflow/fork)
|
||||
[](https://twitter.com/langflow_ai)
|
||||
[](https://discord.com/invite/EqksyE2EX9)
|
||||
[](https://huggingface.co/spaces/Logspace/Langflow)
|
||||
[](https://codespaces.new/logspace-ai/langflow)
|
||||
|
||||
<p>
|
||||
<a href="https://discord.gg/EqksyE2EX9"><img alt="Discord Server" src="https://dcbadge.vercel.app/api/server/EqksyE2EX9?compact=true&style=flat"/></a>
|
||||
<a href="https://huggingface.co/spaces/Logspace/Langflow"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg" alt="HuggingFace Spaces"></a>
|
||||
</p>
|
||||
The easiest way to create and customize your flow
|
||||
|
||||
<a href="https://github.com/logspace-ai/langflow">
|
||||
<img width="100%" src="https://github.com/logspace-ai/langflow/blob/dev/img/langflow-demo.gif?raw=true"></a>
|
||||
|
||||
<p>
|
||||
</p>
|
||||
|
||||
# Table of Contents
|
||||
|
||||
- [⛓️ Langflow](#️-langflow)
|
||||
- [Table of Contents](#table-of-contents)
|
||||
- [📦 Installation](#-installation)
|
||||
- [Locally](#locally)
|
||||
- [HuggingFace Spaces](#huggingface-spaces)
|
||||
- [🖥️ Command Line Interface (CLI)](#️-command-line-interface-cli)
|
||||
- [Usage](#usage)
|
||||
- [Environment Variables](#environment-variables)
|
||||
- [Deployment](#deployment)
|
||||
- [Deploy Langflow on Google Cloud Platform](#deploy-langflow-on-google-cloud-platform)
|
||||
- [Deploy on Railway](#deploy-on-railway)
|
||||
- [Deploy on Render](#deploy-on-render)
|
||||
- [🎨 Creating Flows](#-creating-flows)
|
||||
- [👋 Contributing](#-contributing)
|
||||
- [📄 License](#-license)
|
||||
<img width="100%" src="https://github.com/logspace-ai/langflow/blob/dev/docs/static/img/new_langflow_demo.gif"></a>
|
||||
|
||||
# 📦 Installation
|
||||
|
||||
|
|
@ -65,7 +46,7 @@ This will install the following dependencies:
|
|||
- [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
|
||||
- [sentence-transformers](https://github.com/UKPLab/sentence-transformers)
|
||||
|
||||
You can still use models from projects like LocalAI
|
||||
You can still use models from projects like LocalAI, Ollama, LM Studio, Jan and others.
|
||||
|
||||
Next, run:
|
||||
|
||||
|
|
@ -117,7 +98,7 @@ Each option is detailed below:
|
|||
- `--backend-only`: This parameter, with a default value of `False`, allows running only the backend server without the frontend. It can also be set using the `LANGFLOW_BACKEND_ONLY` environment variable.
|
||||
- `--store`: This parameter, with a default value of `True`, enables the store features, use `--no-store` to deactivate it. It can be configured using the `LANGFLOW_STORE` environment variable.
|
||||
|
||||
These parameters are important for users who need to customize the behavior of Langflow, especially in development or specialized deployment scenarios. You may want to update the documentation to include these parameters for completeness and clarity.
|
||||
These parameters are important for users who need to customize the behavior of Langflow, especially in development or specialized deployment scenarios.
|
||||
|
||||
### Environment Variables
|
||||
|
||||
|
|
@ -147,19 +128,19 @@ Alternatively, click the **"Open in Cloud Shell"** button below to launch Google
|
|||
|
||||
# 🎨 Creating Flows
|
||||
|
||||
Creating flows with Langflow is easy. Simply drag sidebar components onto the canvas and connect them together to create your pipeline. Langflow provides a range of [LangChain components](https://python.langchain.com/docs/integrations/components) to choose from, including LLMs, prompt serializers, agents, and chains.
|
||||
Creating flows with Langflow is easy. Simply drag components from the sidebar onto the canvas and connect them to start building your application.
|
||||
|
||||
Explore by editing prompt parameters, link chains and agents, track an agent's thought process, and export your flow.
|
||||
Explore by editing prompt parameters, grouping components into a single high-level component, and building your own Custom Components.
|
||||
|
||||
Once you're done, you can export your flow as a JSON file to use with LangChain.
|
||||
To do so, click the "Export" button in the top right corner of the canvas, then
|
||||
in Python, you can load the flow with:
|
||||
Once you’re done, you can export your flow as a JSON file.
|
||||
|
||||
Load the flow with:
|
||||
|
||||
```python
|
||||
from langflow import load_flow_from_json
|
||||
|
||||
flow = load_flow_from_json("path/to/flow.json")
|
||||
# Now you can use it like any chain
|
||||
# Now you can use it
|
||||
flow("Hey, have you heard of Langflow?")
|
||||
```
|
||||
|
||||
|
|
@ -167,15 +148,16 @@ flow("Hey, have you heard of Langflow?")
|
|||
|
||||
We welcome contributions from developers of all levels to our open-source project on GitHub. If you'd like to contribute, please check our [contributing guidelines](./CONTRIBUTING.md) and help make Langflow more accessible.
|
||||
|
||||
Join our [Discord](https://discord.com/invite/EqksyE2EX9) server to ask questions, make suggestions, and showcase your projects! 🦾
|
||||
|
||||
---
|
||||
|
||||
Join our [Discord](https://discord.com/invite/EqksyE2EX9) server to ask questions, make suggestions and showcase your projects! 🦾
|
||||
|
||||
<p>
|
||||
</p>
|
||||
|
||||
[](https://star-history.com/#logspace-ai/langflow&Date)
|
||||
|
||||
# 🌟 Contributors
|
||||
|
||||
[](https://github.com/logspace-ai/langflow/graphs/contributors)
|
||||
|
||||
# 📄 License
|
||||
|
||||
Langflow is released under the MIT License. See the LICENSE file for details.
|
||||
|
|
|
|||
|
|
@ -22,6 +22,8 @@ services:
|
|||
dockerfile: ./cdk.Dockerfile
|
||||
args:
|
||||
- BACKEND_URL=http://backend:7860
|
||||
depends_on:
|
||||
- backend
|
||||
environment:
|
||||
- VITE_PROXY_TARGET=http://backend:7860
|
||||
ports:
|
||||
|
|
|
|||
|
|
@ -81,7 +81,17 @@ The CustomComponent class serves as the foundation for creating custom component
|
|||
| _`required: bool`_ | Makes the field required. |
|
||||
| _`info: str`_ | Adds a tooltip to the field. |
|
||||
| _`file_types: List[str]`_ | This is a requirement if the _`field_type`_ is _file_. Defines which file types will be accepted. For example, _json_, _yaml_ or _yml_. |
|
||||
| _`range_spec: langflow.field_typing.RangeSpec`_ | This is a requirement if the _`field_type`_ is _`float`_. Defines the range of values accepted and the step size. If none is defined, the default is _`[-1, 1, 0.1]`_. |
|
||||
| _`range_spec: langflow.field_typing.RangeSpec`_ | This is a requirement if the _`field_type`_ is _`float`_. Defines the range of values accepted and the step size. If none is defined, the default is _`[-1, 1, 0.1]`_. |
|
||||
| _`title_case: bool`_ | Formats the name of the field when _`display_name`_ is not defined. Set it to False to keep the name as you set it in the _`build`_ method. |
|
||||
| _`refresh_button: bool`_ | If set to True a button will appear to the right of the field, and when clicked, it will call the _`update_build_config`_ method which takes in the _`build_config`_, the name of the field (_`field_name`_) and the latest value of the field (_`field_value`_). This is useful when you want to update the _`build_config`_ based on the value of the field. |
|
||||
| _`real_time_refresh: bool`_ | If set to True, the _`update_build_config`_ method will be called every time the field value changes. |
|
||||
|
||||
<Admonition type="info" label="Tip">
|
||||
|
||||
By using the _`update_build_config`_ method, you can update the _`build_config`_ in whatever way you want based on the value of the field or not.
|
||||
|
||||
</Admonition>
|
||||
|
||||
- The CustomComponent class also provides helpful methods for specific tasks (e.g., to load and use other flows from the Langflow platform):
|
||||
|
||||
| Method Name | Description |
|
||||
|
|
@ -94,7 +104,9 @@ The CustomComponent class serves as the foundation for creating custom component
|
|||
|
||||
| Attribute Name | Description |
|
||||
| -------------- | ----------------------------------------------------------------------------- |
|
||||
| _`repr_value`_ | Displays the value it receives in the _`build`_ method. Useful for debugging. |
|
||||
| _`status`_ | Displays the value it receives in the _`build`_ method. Useful for debugging. |
|
||||
| _`field_order`_ | Defines the order the fields will be displayed in the canvas. |
|
||||
| _`icon`_ | Defines the emoji (for example, _`:rocket:`_) that will be displayed in the canvas. |
|
||||
|
||||
<Admonition type="info" label="Tip">
|
||||
|
||||
|
|
|
|||
|
|
@ -98,9 +98,9 @@ Used to load [OpenAI’s](https://openai.com/) embedding models.
|
|||
|
||||
Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) [Embeddings API](https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings).
|
||||
|
||||
:::info
|
||||
<Admonition type="info">
|
||||
Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
|
||||
:::
|
||||
</Admonition>
|
||||
|
||||
- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
|
||||
- **location:** The default location to use when making API calls – defaults to `us-central1`.
|
||||
|
|
|
|||
0
docs/docs/components/helpers.mdx
Normal file
0
docs/docs/components/helpers.mdx
Normal file
39
docs/docs/components/inputs.mdx
Normal file
39
docs/docs/components/inputs.mdx
Normal file
|
|
@ -0,0 +1,39 @@
|
|||
import Admonition from '@theme/Admonition';
|
||||
|
||||
# Inputs
|
||||
|
||||
### ChatInput
|
||||
|
||||
This component is designed to get user input from the chat.
|
||||
|
||||
**Params**
|
||||
|
||||
- **Sender Type:** specifies the sender type. Defaults to _`"User"`_. Options are _`"Machine"`_ and _`"User"`_.
|
||||
|
||||
- **Sender Name:** specifies the name of the sender. Defaults to _`"User"`_.
|
||||
|
||||
- **Message:** specifies the message text. It is a multiline text input.
|
||||
|
||||
- **Session ID:** specifies the session ID of the chat history. If provided, the message will be saved in the Message History.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
If _`As Record`_ is _`true`_ and the _`Message`_ is a _`Record`_, the data of the _`Record`_ will be updated with the _`Sender`_, _`Sender Name`_, and _`Session ID`_.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
### TextInput
|
||||
|
||||
This component is designed for simple text input, allowing users to pass textual data to subsequent components in the workflow. It's particularly useful for scenarios where a brief user input is required to initiate or influence the flow.
|
||||
|
||||
|
||||
**Params**
|
||||
|
||||
- **Value:** Specifies the text input value. This is where the user can input the text data that will be passed to the next component in the sequence. If no value is provided, it defaults to an empty string.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
The `TextInput` component serves as a straightforward means for setting Text input values in the chat window. It ensures that textual data can be seamlessly passed to subsequent components in the flow.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
|
|
@ -12,6 +12,26 @@ Memory is a concept in chat-based applications that allows the system to remembe
|
|||
|
||||
---
|
||||
|
||||
### MessageHistory
|
||||
|
||||
This component is designed to retrieve stored messages based on various filters such as sender type, sender name, session ID, and a specific file path where messages are stored. It allows for a flexible retrieval of chat history, providing insights into past interactions.
|
||||
|
||||
**Params**
|
||||
|
||||
- **Sender Type:** (Optional) Specifies the type of the sender. Options are _`"Machine"`_, _`"User"`_, or _`"Machine and User"`_. Filters the messages by the type of the sender.
|
||||
|
||||
- **Sender Name:** (Optional) Specifies the name of the sender. Filters the messages by the name of the sender.
|
||||
|
||||
- **Session ID:** (Optional) Specifies the session ID of the chat history. Filters the messages belonging to a specific session.
|
||||
|
||||
- **Number of Messages:** Specifies the number of messages to retrieve. Defaults to _`5`_. Determines how many recent messages from the chat history to fetch.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
The component retrieves messages based on the provided criteria, including the specific file path for stored messages. If no specific criteria are provided, it will return the most recent messages up to the specified limit. This component can be used to review past interactions and analyze the flow of conversations.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
### ConversationBufferMemory
|
||||
|
||||
The `ConversationBufferMemory` component is a type of memory system that plainly stores the last few inputs and outputs of a conversation.
|
||||
|
|
@ -27,7 +47,7 @@ The `ConversationBufferMemory` component is a type of memory system that plainly
|
|||
|
||||
### ConversationBufferWindowMemory
|
||||
|
||||
`ConversationBufferWindowMemory` is a variation of the `ConversationBufferMemory` that maintains a list of the recent interactions in a conversation. It only keeps the last K interactions in memory, which can be useful for maintaining a sliding window of the most recent interactions without letting the buffer get too large.
|
||||
`ConversationBufferWindowMemory` is a variation of the `ConversationBufferMemory` that maintains a list of the recent interactions in a conversation. It only keeps the last K interactions in memory, which can be useful for maintaining a sliding window of the most recent interactions without letting the buffer get too large.
|
||||
|
||||
**Params**
|
||||
|
||||
|
|
@ -72,7 +92,7 @@ The `ConversationEntityMemory` component incorporates intricate memory structure
|
|||
|
||||
### ConversationSummaryMemory
|
||||
|
||||
The `ConversationSummaryMemory` is a memory component that creates a summary of the conversation over time. It condenses information from the conversation and stores the current summary in memory. It is particularly useful for longer conversations where keeping the entire message history in the prompt would take up too many tokens.
|
||||
The `ConversationSummaryMemory` is a memory component that creates a summary of the conversation over time. It condenses information from the conversation and stores the current summary in memory. It is particularly useful for longer conversations where keeping the entire message history in the prompt would take up too many tokens.
|
||||
|
||||
**Params**
|
||||
|
||||
|
|
|
|||
|
|
@ -40,9 +40,10 @@ Wrapper around Anthropic's large language model used for chat-based interactions
|
|||
|
||||
The `CTransformers` component provides access to the Transformer models implemented in C/C++ using the [GGML](https://github.com/ggerganov/ggml) library.
|
||||
|
||||
:::info
|
||||
<Admonition type="info">
|
||||
|
||||
Make sure to have the `ctransformers` python package installed. Learn more about installation, supported models, and usage [here](https://github.com/marella/ctransformers).
|
||||
:::
|
||||
</Admonition>
|
||||
|
||||
**config:** Configuration for the Transformer models. Check out [config](https://github.com/marella/ctransformers#config). Defaults to:
|
||||
|
||||
|
|
@ -115,9 +116,9 @@ Wrapper around [Cohere's](https://cohere.com) large language models.
|
|||
|
||||
Wrapper around [HuggingFace](https://www.huggingface.co/models) models.
|
||||
|
||||
:::info
|
||||
<Admonition type="info">
|
||||
The HuggingFace Hub is an online platform that hosts over 120k models, 20k datasets, and 50k demo apps, all of which are open-source and publicly available. Discover more at [HuggingFace](http://www.huggingface.co).
|
||||
:::
|
||||
</Admonition>
|
||||
|
||||
- **huggingfacehub_api_token:** Token needed to authenticate the API.
|
||||
- **model_kwargs:** Keyword arguments to pass to the model.
|
||||
|
|
@ -130,9 +131,9 @@ The HuggingFace Hub is an online platform that hosts over 120k models, 20k datas
|
|||
|
||||
The `LlamaCpp` component provides access to the `llama.cpp` models.
|
||||
|
||||
:::info
|
||||
<Admonition type="info">
|
||||
Make sure to have the `llama.cpp` python package installed. Learn more about installation, supported models, and usage [here](https://github.com/ggerganov/llama.cpp).
|
||||
:::
|
||||
</Admonition>
|
||||
|
||||
- **echo:** Whether to echo the prompt – defaults to `False`.
|
||||
- **f16_kv:** Use half-precision for key/value cache – defaults to `True`.
|
||||
|
|
@ -181,9 +182,9 @@ Wrapper around [OpenAI's](https://openai.com) large language models.
|
|||
|
||||
Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) large language models.
|
||||
|
||||
:::info
|
||||
<Admonition type="info">
|
||||
Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
|
||||
:::
|
||||
</Admonition>
|
||||
|
||||
- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
|
||||
- **location:** The default location to use when making API calls – defaults to `us-central1`.
|
||||
|
|
@ -203,9 +204,9 @@ Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP).
|
|||
|
||||
Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) large language models.
|
||||
|
||||
:::info
|
||||
<Admonition type="info">
|
||||
Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
|
||||
:::
|
||||
</Admonition>
|
||||
|
||||
- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
|
||||
- **location:** The default location to use when making API calls – defaults to `us-central1`.
|
||||
0
docs/docs/components/models.mdx
Normal file
0
docs/docs/components/models.mdx
Normal file
37
docs/docs/components/outputs.mdx
Normal file
37
docs/docs/components/outputs.mdx
Normal file
|
|
@ -0,0 +1,37 @@
|
|||
import Admonition from '@theme/Admonition';
|
||||
|
||||
# Outputs
|
||||
|
||||
### ChatOutput
|
||||
|
||||
This component is designed to send a message to the chat.
|
||||
|
||||
**Params**
|
||||
|
||||
- **Sender Type:** specifies the sender type. Defaults to _`"Machine"`_. Options are _`"Machine"`_ and _`"User"`_.
|
||||
|
||||
- **Sender Name:** specifies the name of the sender. Defaults to _`"AI"`_.
|
||||
|
||||
- **Session ID:** specifies the session ID of the chat history. If provided, the message will be saved in the Message History.
|
||||
|
||||
- **Message:** specifies the message text.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
If _`As Record`_ is _`true`_ and the _`Message`_ is a _`Record`_, the data of the _`Record`_ will be updated with the _`Sender`_, _`Sender Name`_, and _`Session ID`_.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
### TextOutput
|
||||
|
||||
This component is designed to display text data to the user. It's particularly useful for scenarios where you don't want to send the text data to the chat, but still want to display it.
|
||||
|
||||
**Params**
|
||||
|
||||
- **Value:** Specifies the text data to be displayed. This is where the text data to be displayed is provided. If no value is provided, it defaults to an empty string.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
The `TextOutput` component serves as a straightforward means for displaying text data. It ensures that textual data can be seamlessly observed in the chat window throughout your flow.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
|
@ -21,7 +21,7 @@ The `PromptTemplate` component allows users to create prompts and define variabl
|
|||
<Admonition type="info">
|
||||
Once a variable is defined in the prompt template, it becomes a component
|
||||
input of its own. Check out [Prompt
|
||||
Customization](../guidelines/prompt-customization.mdx) to learn more.
|
||||
Customization](../docs/guidelines/prompt-customization.mdx) to learn more.
|
||||
</Admonition>
|
||||
|
||||
- **template:** Template used to format an individual request.
|
||||
|
|
|
|||
|
|
@ -9,6 +9,21 @@ import Admonition from '@theme/Admonition';
|
|||
</Admonition>
|
||||
|
||||
|
||||
### SearchApi
|
||||
|
||||
Real-time search engine results API. Returns structured JSON data that includes answer box, knowledge graph, organic results, and more.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- **Api Key:** A unique identifier for the SearchApi, necessary for authenticating requests to real-time search engines. This key can be retrieved from the [SearchApi dashboard](https://www.searchapi.io/).
|
||||
- **Engine:** Specifies the search engine. For instance: google, google_scholar, bing, youtube, and youtube_transcripts. A full list of supported engines is available in the [documentation](https://www.searchapi.io/docs/google).
|
||||
- **Parameters:** Allows the selection of any parameters recognized by SearchApi, with some being required and others optional.
|
||||
|
||||
**Output**
|
||||
|
||||
- **Document:** The JSON response from the request as a Document.
|
||||
|
||||
|
||||
### BingSearchRun
|
||||
|
||||
Bing Search is a web search engine owned and operated by Microsoft. It provides search results for various types of content, including web pages, images, videos, and news articles. It uses a combination of algorithms and human editors to deliver search results to users.
|
||||
|
|
@ -60,4 +75,4 @@ Tool for getting metadata about a SQL database. The input to this tool is a comm
|
|||
|
||||
**Params**
|
||||
|
||||
- **Db:** SQLDatabase to query.
|
||||
- **Db:** SQLDatabase to query.
|
||||
|
|
|
|||
|
|
@ -74,3 +74,23 @@ Build a Document containing a JSON object using a key and another Document page
|
|||
**Output**
|
||||
|
||||
- **List of Documents:** A list containing the Document with the JSON object.
|
||||
|
||||
## Unique ID Generator
|
||||
|
||||
Generates a unique identifier (UUID) for each instance it is invoked, providing a distinct and reliable identifier suitable for a variety of applications.
|
||||
|
||||
**Params**
|
||||
|
||||
- **Value:** This field displays the generated unique identifier (UUID). The UUID is generated dynamically for each instance of the component, ensuring uniqueness across different uses.
|
||||
|
||||
**Output**
|
||||
|
||||
- Returns a unique identifier (UUID) as a string. This UUID is generated using Python's `uuid` module, ensuring that each identifier is unique and can be used as a reliable reference in your application.
|
||||
|
||||
<Admonition type="note" title="Note">
|
||||
<p>
|
||||
The Unique ID Generator is crucial for scenarios requiring distinct identifiers, such as session management, transaction tracking, or any context where different instances or entities must be uniquely identified. The generated UUID is provided as a hexadecimal string, offering a high level of uniqueness and security for identification purposes.
|
||||
</p>
|
||||
</Admonition>
|
||||
|
||||
For additional information and examples, please consult the [Langflow Components Custom Documentation](http://docs.langflow.org/components/custom).
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@
|
|||
|
||||
## 🐦 Stay tunned for **Langflow** on Twitter
|
||||
|
||||
Follow [@logspace_ai](https://twitter.com/logspace_ai) on **Twitter** to get the latest news about **Langflow**.
|
||||
Follow [@langflow_ai](https://twitter.com/langflow_ai) on **Twitter** to get the latest news about **Langflow**.
|
||||
|
||||
---
|
||||
## ⭐️ Star **Langflow** on GitHub
|
||||
|
|
|
|||
|
|
@ -4,9 +4,8 @@
|
|||
|
||||
This guide will help you set up a Langflow development VM in a Google Cloud Platform project using Google Cloud Shell.
|
||||
|
||||
:::note
|
||||
When Cloud Shell opens, be sure to select **Trust repo**. Some `gcloud` commands might not run in an ephemeral Cloud Shell environment.
|
||||
:::
|
||||
> Note: When Cloud Shell opens, be sure to select **Trust repo**. Some `gcloud` commands might not run in an ephemeral Cloud Shell environment.
|
||||
|
||||
|
||||
|
||||
## Standard VM
|
||||
|
|
|
|||
|
|
@ -14,6 +14,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/buffer-memory.png",
|
||||
dark: "img/buffer-memory.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/basic-chat.png",
|
||||
dark: "img/basic-chat.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
|
|
|
|||
|
|
@ -32,6 +32,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/csv-loader.png",
|
||||
dark: "img/csv-loader.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
|
|
@ -39,12 +40,12 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
|
||||
<Admonition type="note" title="LangChain Components 🦜🔗">
|
||||
|
||||
- [`CSVLoader`](https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/csv)
|
||||
- [`CSVLoader`](https://python.langchain.com/docs/integrations/document_loaders/csv)
|
||||
- [`CharacterTextSplitter`](https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter)
|
||||
- [`OpenAIEmbedding`](https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/openai)
|
||||
- [`Chroma`](https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/chroma)
|
||||
- [`OpenAIEmbedding`](https://python.langchain.com/docs/integrations/text_embedding/openai)
|
||||
- [`Chroma`](https://python.langchain.com/docs/integrations/vectorstores/chroma)
|
||||
- [`VectorStoreInfo`](https://python.langchain.com/docs/modules/data_connection/vectorstores/)
|
||||
- [`OpenAI`](https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai)
|
||||
- [`VectorStoreAgent`](https://python.langchain.com/docs/modules/agents/toolkits/vectorstore)
|
||||
- [`VectorStoreAgent`](https://js.langchain.com/docs/modules/agents/tools/how_to/agents_with_vectorstores)
|
||||
|
||||
</Admonition>
|
||||
|
|
|
|||
|
|
@ -14,6 +14,7 @@ The CustomComponent class allows us to create components that interact with Lang
|
|||
alt="Document Processor Component"
|
||||
sources={{
|
||||
light: "img/flow_runner.png",
|
||||
dark: "img/flow_runner.png",
|
||||
}}
|
||||
style={{
|
||||
width: "30%",
|
||||
|
|
@ -339,6 +340,7 @@ Done! This is what our script and custom component looks like:
|
|||
alt="Document Processor Code"
|
||||
sources={{
|
||||
light: "img/flow_runner_code.png",
|
||||
dark: "img/flow_runner_code.png",
|
||||
}}
|
||||
style={{
|
||||
maxWidth: "100%",
|
||||
|
|
@ -353,6 +355,7 @@ Done! This is what our script and custom component looks like:
|
|||
alt="Document Processor Component"
|
||||
sources={{
|
||||
light: "img/flow_runner.png",
|
||||
dark: "img/flow_runner.png",
|
||||
}}
|
||||
style={{
|
||||
width: "40%",
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ Langflow Examples is a repository on [GitHub](https://github.com/logspace-ai/lan
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/community-examples.png",
|
||||
dark: "img/community-examples.png",
|
||||
}}
|
||||
style={{ width: "100%" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -32,6 +32,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/midjourney-prompt-chain.png",
|
||||
dark: "img/midjourney-prompt-chain.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
|
|
@ -40,6 +41,6 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
<Admonition type="note" title="LangChain Components 🦜🔗">
|
||||
|
||||
- [`OpenAI`](https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai)
|
||||
- [`ConversationSummaryMemory`](https://python.langchain.com/docs/modules/memory/how_to/summary)
|
||||
- [`ConversationSummaryMemory`](https://python.langchain.com/docs/modules/memory/types/summary)
|
||||
|
||||
</Admonition>
|
||||
|
|
|
|||
|
|
@ -24,7 +24,7 @@ https://pt.wikipedia.org/wiki/Harry_Potter
|
|||
|
||||
<Admonition type="info">
|
||||
Learn more about Multiple Vector Stores
|
||||
[here](https://python.langchain.com/docs/modules/agents/toolkits/vectorstore?highlight=Multiple%20Vector%20Stores#multiple-vectorstores).
|
||||
[here](https://python.langchain.com/docs/modules/data_connection/vectorstores/).
|
||||
</Admonition>
|
||||
|
||||
## ⛓️ Langflow Example
|
||||
|
|
@ -37,6 +37,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/multiple-vectorstores.png",
|
||||
dark: "img/multiple-vectorstores.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
|
|
@ -44,14 +45,14 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
|
||||
<Admonition type="note" title="LangChain Components 🦜🔗">
|
||||
|
||||
- [`WebBaseLoader`](https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/web_base)
|
||||
- [`TextLoader`](https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/unstructured_file)
|
||||
- [`WebBaseLoader`](https://python.langchain.com/docs/integrations/document_loaders/web_base)
|
||||
- [`TextLoader`](https://python.langchain.com/docs/modules/data_connection/document_loaders/)
|
||||
- [`CharacterTextSplitter`](https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter)
|
||||
- [`OpenAIEmbedding`](https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/openai)
|
||||
- [`Chroma`](https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/chroma)
|
||||
- [`OpenAIEmbedding`](https://python.langchain.com/docs/integrations/text_embedding/openai)
|
||||
- [`Chroma`](https://python.langchain.com/docs/integrations/vectorstores/chroma)
|
||||
- [`VectorStoreInfo`](https://python.langchain.com/docs/modules/data_connection/vectorstores/)
|
||||
- [`OpenAI`](https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai)
|
||||
- [`VectorStoreRouterToolkit`](https://python.langchain.com/docs/modules/agents/toolkits/vectorstore)
|
||||
- [`VectorStoreRouterAgent`](https://python.langchain.com/docs/modules/agents/toolkits/vectorstore)
|
||||
- [`VectorStoreRouterToolkit`](https://js.langchain.com/docs/modules/agents/tools/how_to/agents_with_vectorstores)
|
||||
- [`VectorStoreRouterAgent`](https://js.langchain.com/docs/modules/agents/tools/how_to/agents_with_vectorstores)
|
||||
|
||||
</Admonition>
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ The `AgentInitializer` component is a quick way to construct an agent from the m
|
|||
<Admonition type="info">
|
||||
The `PythonFunction` is a custom component that uses the LangChain 🦜🔗 tool
|
||||
decorator. Learn more about it
|
||||
[here](https://python.langchain.com/docs/modules/agents/tools/how_to/custom_tools).
|
||||
[here](https://python.langchain.com/docs/modules/agents/tools/custom_tools).
|
||||
</Admonition>
|
||||
|
||||
## ⛓️ Langflow Example
|
||||
|
|
@ -41,6 +41,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/python-function.png",
|
||||
dark: "img/python-function.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
|
|
@ -48,7 +49,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
|
||||
<Admonition type="note" title="LangChain Components 🦜🔗">
|
||||
|
||||
- [`PythonFunctionTool`](https://python.langchain.com/docs/modules/agents/tools/how_to/custom_tools)
|
||||
- [`PythonFunctionTool`](https://python.langchain.com/docs/modules/agents/tools/custom_tools)
|
||||
- [`ChatOpenAI`](https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai)
|
||||
- [`AgentInitializer`](https://python.langchain.com/docs/modules/agents/)
|
||||
|
||||
|
|
|
|||
52
docs/docs/examples/searchapi-tool.mdx
Normal file
52
docs/docs/examples/searchapi-tool.mdx
Normal file
|
|
@ -0,0 +1,52 @@
|
|||
import Admonition from "@theme/Admonition";
|
||||
|
||||
# SearchApi Tool
|
||||
|
||||
The [SearchApi](https://www.searchapi.io/) allows developers to retrieve results from search engines such as Google, Google Scholar, YouTube, YouTube transcripts, and more, and can be used as in Langflow through the `SearchApi` tool.
|
||||
|
||||
<Admonition type="info">
|
||||
To use the SearchApi, you must first obtain an API key by registering at [SearchApi's website](https://www.searchapi.io/).
|
||||
</Admonition>
|
||||
|
||||
In the given example, we specify `engine` as `youtube_transcripts` and provide a `video_id`.
|
||||
|
||||
<Admonition type="info">
|
||||
All engines and parameters can be found in [SearchApi documentation](https://www.searchapi.io/docs/google).
|
||||
</Admonition>
|
||||
|
||||
The `RetrievalQA` chain processes a `Document` along with a user's question to return an answer.
|
||||
|
||||
<Admonition type="tip">
|
||||
In this example, we used [`ChatOpenAI`](https://platform.openai.com/) as the
|
||||
LLM, but feel free to experiment with other Language Models!
|
||||
</Admonition>
|
||||
|
||||
The `RetrievalQA` takes `CombineDocsChain` and `SearchApi` tool as inputs, using the tool as a `Document` to answer questions.
|
||||
|
||||
<Admonition type="info">
|
||||
Learn more about the SearchApi
|
||||
[here](https://python.langchain.com/docs/integrations/tools/searchapi).
|
||||
</Admonition>
|
||||
|
||||
## ⛓️ Langflow Example
|
||||
|
||||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/searchapi-tool.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/SearchApi_Tool.json" download>Download Flow</a>
|
||||
|
||||
<Admonition type="note" title="LangChain Components 🦜🔗">
|
||||
|
||||
- [`OpenAI`](https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai)
|
||||
- [`SearchApiAPIWrapper`](https://python.langchain.com/docs/integrations/providers/searchapi#wrappers)
|
||||
- [`ZeroShotAgent`](https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent)
|
||||
|
||||
</Admonition>
|
||||
|
|
@ -22,7 +22,7 @@ The `ZeroShotAgent` takes the `LLMChain` and the `Search` tool as inputs, using
|
|||
|
||||
<Admonition type="info">
|
||||
Learn more about the Serp API
|
||||
[here](https://python.langchain.com/docs/modules/agents/tools/integrations/serpapi).
|
||||
[here](https://python.langchain.com/docs/integrations/providers/serpapi ).
|
||||
</Admonition>
|
||||
|
||||
## ⛓️ Langflow Example
|
||||
|
|
@ -35,6 +35,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/serp-api-tool.png",
|
||||
dark: "img/serp-api-tool.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
|
|
@ -45,7 +46,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
- [`ZeroShotPrompt`](https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/)
|
||||
- [`OpenAI`](https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai)
|
||||
- [`LLMChain`](https://python.langchain.com/docs/modules/chains/foundational/llm_chain)
|
||||
- [`Search`](https://python.langchain.com/docs/modules/agents/tools/integrations/serpapi)
|
||||
- [`Search`](https://python.langchain.com/docs/integrations/providers/serpapi)
|
||||
- [`ZeroShotAgent`](https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent)
|
||||
|
||||
</Admonition>
|
||||
|
|
|
|||
|
|
@ -7,18 +7,20 @@ import ReactPlayer from "react-player";
|
|||
|
||||
## Compose
|
||||
|
||||
Creating flows with Langflow is easy. Drag sidebar components onto the canvas and connect them together to create your pipeline. Langflow provides a range of [LangChain components](https://python.langchain.com/docs/modules/) to choose from, including LLMs, prompt serializers, agents, and chains.
|
||||
Creating flows with Langflow is easy. Drag sidebar components onto the canvas and connect them together to create your pipeline.
|
||||
Langflow provides a range of Components to choose from, including **Chat Input**, **Chat Output**, **API Request** and **Prompt**.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/langflow_canvas.png",
|
||||
dark: "img/langflow_canvas.png"
|
||||
}}
|
||||
/>
|
||||
|
||||
## Fork
|
||||
## Starter Flows
|
||||
|
||||
The easiest way to start with Langflow is by forking a **community example**. Forking an example stores a copy in your project collection, allowing you to edit and save the modified version as a new flow.
|
||||
Langflow provides a range of starter flows to help you get started. These flows are pre-built and can be used as a starting point for your own flows.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
|
|
@ -26,9 +28,21 @@ The easiest way to start with Langflow is by forking a **community example**. Fo
|
|||
<ReactPlayer playing controls url="/videos/langflow_fork.mp4" />
|
||||
</div>
|
||||
|
||||
## Build
|
||||
## Defining Inputs and Outputs
|
||||
|
||||
Each flow can have multiple inputs and outputs. These can be defined by placing **Inputs** and **Outputs** components on the canvas.
|
||||
|
||||
The **Inputs** components define the inputs to the flow.
|
||||
Whenever you place an Input component on the canvas, it will allow you to interactively define change its value
|
||||
from the Interactive Panel.
|
||||
|
||||
The **Text Input** component allows you to define a text input, and the **Chat Input** component allows you to use the chat input from the Interactive Panel.
|
||||
|
||||
The **Outputs** components define the outputs of the flow and work similarly to the Inputs components.
|
||||
|
||||
Both Inputs and Outputs components can be connected to other components on the canvas and are used to define how the API works too.
|
||||
|
||||
|
||||
Building a flow means validating if the components have prerequisites fulfilled and are properly instantiated. When a chat message is sent, the flow will run for the first time, executing the pipeline.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/hugging-face.png",
|
||||
dark: "img/hugging-face.png",
|
||||
}}
|
||||
style={{ width: "100%" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -17,6 +17,7 @@ Langflow offers an API Key functionality that allows users to access their indiv
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/api-key.png"),
|
||||
dark: useBaseUrl("img/api-key.png"),
|
||||
}}
|
||||
style={{ width: "50%", maxWidth: "600px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -13,6 +13,7 @@ Langflow’s chat interface provides a user-friendly experience and functionalit
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/chat_interface.png"),
|
||||
dark: useBaseUrl("img/chat_interface.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -25,6 +26,7 @@ Notice that editing variables in the chat interface take place temporarily and w
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/chat_interface2.png"),
|
||||
dark: useBaseUrl("img/chat_interface2.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -36,6 +38,7 @@ To view the complete prompt in its original, structured format, click the "Displ
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/chat_interface3.png"),
|
||||
dark: useBaseUrl("img/chat_interface3.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -47,6 +50,7 @@ In the chat interface, you can redefine which variable should be interpreted as
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/chat_interface4.png"),
|
||||
dark: useBaseUrl("img/chat_interface4.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -38,6 +38,7 @@ import Admonition from "@theme/Admonition";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/widget-sidebar.png"),
|
||||
dark: useBaseUrl("img/widget-sidebar.png"),
|
||||
}}
|
||||
style={{ width: "50%", maxWidth: "600px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -53,6 +54,7 @@ import Admonition from "@theme/Admonition";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/widget-code.png"),
|
||||
dark: useBaseUrl("img/widget-code.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -30,6 +30,7 @@ Components are the building blocks of the flows. They are made of inputs, output
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/single-compenent.png"),
|
||||
dark: useBaseUrl("img/single-compenent.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -63,6 +63,7 @@ class DocumentProcessor(CustomComponent):
|
|||
alt="Document Processor Component"
|
||||
sources={{
|
||||
light: "img/document_processor.png",
|
||||
dark: "img/document_processor.png",
|
||||
}}
|
||||
style={{
|
||||
margin: "0 auto",
|
||||
|
|
@ -330,6 +331,7 @@ All done! This is what our script and brand-new custom component look like:
|
|||
alt="Document Processor Code"
|
||||
sources={{
|
||||
light: "img/document_processor_code.png",
|
||||
dark: "img/document_processor_code.png",
|
||||
}}
|
||||
style={{
|
||||
maxWidth: "100%",
|
||||
|
|
@ -344,6 +346,7 @@ All done! This is what our script and brand-new custom component look like:
|
|||
alt="Document Processor Component"
|
||||
sources={{
|
||||
light: "img/document_processor.png",
|
||||
dark: "img/document_processor.png",
|
||||
}}
|
||||
style={{
|
||||
width: "40%",
|
||||
|
|
|
|||
|
|
@ -18,6 +18,7 @@ import Admonition from "@theme/Admonition";
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/features.png"),
|
||||
dark: useBaseUrl("img/features.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -86,6 +86,7 @@ With _`LANGFLOW_AUTO_LOGIN`_ set to _`False`_, Langflow requires users to sign u
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/sign-up.png"),
|
||||
dark: useBaseUrl("img/sign-up.png"),
|
||||
}}
|
||||
style={{ width: "50%", maxWidth: "600px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -102,6 +103,7 @@ Users can change their profile settings by clicking on the profile icon in the t
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/my-account.png"),
|
||||
dark: useBaseUrl("img/my-account.png"),
|
||||
}}
|
||||
style={{ width: "50%", maxWidth: "600px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -112,6 +114,7 @@ By clicking on **Profile Settings**, the user is taken to the profile settings p
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/profile-settings.png"),
|
||||
dark: useBaseUrl("img/profile-settings.png"),
|
||||
}}
|
||||
style={{ maxWidth: "600px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -122,6 +125,7 @@ By clicking on **Admin Page**, the superuser is taken to the admin page, where t
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/admin-page.png"),
|
||||
dark: useBaseUrl("img/admin-page.png"),
|
||||
}}
|
||||
style={{ maxWidth: "600px", margin: "0 auto" }}
|
||||
|
||||
|
|
|
|||
|
|
@ -13,6 +13,7 @@ The prompt template allows users to create prompts and define variables that pro
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/prompt_customization.png"),
|
||||
dark: useBaseUrl("img/prompt_customization.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -25,6 +26,7 @@ Variables can be used to define instructions, questions, context, inputs, or exa
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/prompt_customization2.png"),
|
||||
dark: useBaseUrl("img/prompt_customization2.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -37,6 +39,7 @@ Once inserted, these variables are immediately recognized as new fields in the p
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/prompt_customization3.png"),
|
||||
dark: useBaseUrl("img/prompt_customization3.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -49,6 +52,7 @@ You can also use documents or output parsers as prompt variables. By plugging th
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/prompt_customization4.png"),
|
||||
dark: useBaseUrl("img/prompt_customization4.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
@ -63,6 +67,7 @@ If working with an interactive (chat-like) flow, remember to keep one of the inp
|
|||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/prompt_customization5.png"),
|
||||
dark: useBaseUrl("img/prompt_customization5.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
# 👋 Welcome to Langflow
|
||||
|
||||
Langflow is an easy way to prototype [LangChain](https://github.com/hwchase17/langchain) flows. The drag-and-drop feature allows quick and effortless experimentation, while the built-in chat interface facilitates real-time interaction. It provides options to edit prompt parameters, create chains and agents, track thought processes, and export flows.
|
||||
Langflow is an easy way to create flows. The drag-and-drop feature allows quick and effortless experimentation, while the built-in chat interface facilitates real-time interaction. It provides options to edit prompt parameters, create chains and agents, track thought processes, and export flows.
|
||||
|
||||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
|
|
@ -11,7 +11,8 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
|
|||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/new_langflow.gif",
|
||||
light: "img/new_langflow_demo.gif",
|
||||
dark: "img/new_langflow_demo.gif",
|
||||
}}
|
||||
style={{ width: "100%" }}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -90,7 +90,7 @@ module.exports = {
|
|||
},
|
||||
{
|
||||
position: "right",
|
||||
href: "https://twitter.com/logspace_ai",
|
||||
href: "https://twitter.com/langflow_ai",
|
||||
position: "right",
|
||||
className: "header-twitter-link",
|
||||
target: "_blank",
|
||||
|
|
|
|||
|
|
@ -33,11 +33,18 @@ module.exports = {
|
|||
label: "Component Reference",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"components/inputs",
|
||||
"components/outputs",
|
||||
"components/data",
|
||||
"components/prompts",
|
||||
"components/models",
|
||||
"components/helpers",
|
||||
"components/experimental",
|
||||
"components/agents",
|
||||
"components/chains",
|
||||
"components/custom",
|
||||
"components/embeddings",
|
||||
"components/llms",
|
||||
"components/model_specs",
|
||||
"components/loaders",
|
||||
"components/memories",
|
||||
"components/prompts",
|
||||
|
|
@ -81,6 +88,7 @@ module.exports = {
|
|||
"examples/buffer-memory",
|
||||
"examples/midjourney-prompt-chain",
|
||||
"examples/csv-loader",
|
||||
"examples/searchapi-tool",
|
||||
"examples/serp-api-tool",
|
||||
"examples/multiple-vectorstores",
|
||||
"examples/python-function",
|
||||
|
|
|
|||
BIN
docs/static/img/new_langflow_demo.gif
vendored
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docs/static/img/new_langflow_demo.gif
vendored
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|
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docs/static/img/searchapi-tool.png
vendored
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vendored
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|
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1
docs/static/json_files/SearchApi_Tool.json
vendored
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1
docs/static/json_files/SearchApi_Tool.json
vendored
Normal file
File diff suppressed because one or more lines are too long
BIN
docs/static/videos/langflow_api.mp4
vendored
BIN
docs/static/videos/langflow_api.mp4
vendored
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docs/static/videos/langflow_build.mp4
vendored
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vendored
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docs/static/videos/langflow_collection.mp4
vendored
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vendored
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BIN
docs/static/videos/langflow_collection_example.mp4
vendored
BIN
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vendored
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docs/static/videos/langflow_fork.mp4
vendored
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vendored
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docs/static/videos/langflow_parameters.mp4
vendored
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docs/static/videos/langflow_parameters.mp4
vendored
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docs/static/videos/langflow_widget.mp4
vendored
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vendored
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|
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|
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5959
poetry.lock
generated
5959
poetry.lock
generated
File diff suppressed because it is too large
Load diff
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow"
|
||||
version = "0.6.5a13"
|
||||
version = "0.7.0a0"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Logspace <contact@logspace.ai>"]
|
||||
maintainers = [
|
||||
|
|
@ -25,59 +25,57 @@ documentation = "https://docs.langflow.org"
|
|||
langflow = "langflow.__main__:main"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.9,<3.11"
|
||||
fastapi = "^0.108.0"
|
||||
uvicorn = "^0.25.0"
|
||||
|
||||
|
||||
python = ">=3.9,<3.12"
|
||||
duckdb = "^0.9.2"
|
||||
fastapi = "^0.109.0"
|
||||
uvicorn = "^0.27.0"
|
||||
beautifulsoup4 = "^4.12.2"
|
||||
google-search-results = "^2.4.1"
|
||||
google-api-python-client = "^2.79.0"
|
||||
google-api-python-client = "^2.118.0"
|
||||
typer = "^0.9.0"
|
||||
gunicorn = "^21.2.0"
|
||||
langchain = "~0.1.0"
|
||||
openai = "^1.10.0"
|
||||
pandas = "2.0.3"
|
||||
chromadb = "^0.4.0"
|
||||
huggingface-hub = { version = "^0.19.0", extras = ["inference"] }
|
||||
openai = "^1.12.0"
|
||||
pandas = "2.2.0"
|
||||
chromadb = "^0.4.23"
|
||||
huggingface-hub = { version = "^0.20.0", extras = ["inference"] }
|
||||
rich = "^13.7.0"
|
||||
llama-cpp-python = { version = "~0.2.0", optional = true }
|
||||
networkx = "^3.1"
|
||||
unstructured = "^0.11.0"
|
||||
pypdf = "^3.17.0"
|
||||
lxml = "^4.9.2"
|
||||
pypdf = "^4.0.0"
|
||||
pysrt = "^1.1.2"
|
||||
fake-useragent = "^1.4.0"
|
||||
docstring-parser = "^0.15"
|
||||
psycopg2-binary = "^2.9.6"
|
||||
pyarrow = "^14.0.0"
|
||||
tiktoken = "~0.5.0"
|
||||
tiktoken = "~0.6.0"
|
||||
wikipedia = "^1.4.0"
|
||||
qdrant-client = "^1.7.0"
|
||||
websockets = "^10.3"
|
||||
weaviate-client = "*"
|
||||
jina = "*"
|
||||
sentence-transformers = { version = "^2.2.2", optional = true }
|
||||
sentence-transformers = { version = "^2.3.1", optional = true }
|
||||
ctransformers = { version = "^0.2.10", optional = true }
|
||||
cohere = "^4.39.0"
|
||||
python-multipart = "^0.0.6"
|
||||
cohere = "^4.47.0"
|
||||
python-multipart = "^0.0.7"
|
||||
sqlmodel = "^0.0.14"
|
||||
faiss-cpu = "^1.7.4"
|
||||
anthropic = "^0.13.0"
|
||||
orjson = "3.9.3"
|
||||
anthropic = "^0.15.0"
|
||||
orjson = "3.9.15"
|
||||
multiprocess = "^0.70.14"
|
||||
cachetools = "^5.3.1"
|
||||
types-cachetools = "^5.3.0.5"
|
||||
platformdirs = "^4.1.0"
|
||||
pinecone-client = "^2.2.2"
|
||||
platformdirs = "^4.2.0"
|
||||
pinecone-client = "^3.0.3"
|
||||
pymongo = "^4.6.0"
|
||||
supabase = "^2.3.0"
|
||||
certifi = "^2023.11.17"
|
||||
google-cloud-aiplatform = "^1.36.0"
|
||||
psycopg = "^3.1.9"
|
||||
psycopg-binary = "^3.1.9"
|
||||
fastavro = "^1.8.0"
|
||||
langchain-experimental = "*"
|
||||
celery = { extras = ["redis"], version = "^5.3.6", optional = true }
|
||||
redis = { version = "^4.6.0", optional = true }
|
||||
redis = { version = "^5.0.1", optional = true }
|
||||
flower = { version = "^2.0.0", optional = true }
|
||||
alembic = "^1.13.0"
|
||||
passlib = "^1.7.4"
|
||||
|
|
@ -86,50 +84,54 @@ python-jose = "^3.3.0"
|
|||
metaphor-python = "^0.1.11"
|
||||
pydantic = "^2.5.0"
|
||||
pydantic-settings = "^2.1.0"
|
||||
zep-python = "*"
|
||||
zep-python = "1.5.0"
|
||||
pywin32 = { version = "^306", markers = "sys_platform == 'win32'" }
|
||||
loguru = "^0.7.1"
|
||||
langfuse = "^1.1.11"
|
||||
pillow = "^10.0.0"
|
||||
metal-sdk = "^2.4.0"
|
||||
langfuse = "^2.9.0"
|
||||
pillow = "^10.2.0"
|
||||
metal-sdk = "^2.5.0"
|
||||
markupsafe = "^2.1.3"
|
||||
extract-msg = "^0.45.0"
|
||||
extract-msg = "^0.47.0"
|
||||
# jq is not available for windows
|
||||
jq = { version = "^1.6.0", markers = "sys_platform != 'win32'" }
|
||||
boto3 = "^1.34.0"
|
||||
numexpr = "^2.8.6"
|
||||
qianfan = "0.2.0"
|
||||
qianfan = "0.3.0"
|
||||
pgvector = "^0.2.3"
|
||||
pyautogen = "^0.2.0"
|
||||
langchain-google-genai = "^0.0.2"
|
||||
elasticsearch = "^8.11.1"
|
||||
langchain-google-genai = "^0.0.6"
|
||||
elasticsearch = "^8.12.0"
|
||||
pytube = "^15.0.0"
|
||||
llama-index = "^0.9.24"
|
||||
langchain-openai = "^0.0.2"
|
||||
python-socketio = "^5.11.0"
|
||||
llama-index = "^0.10.13"
|
||||
langchain-openai = "^0.0.6"
|
||||
unstructured = { extras = ["md"], version = "^0.12.4" }
|
||||
dspy-ai = "^2.4.0"
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest-asyncio = "^0.23.1"
|
||||
types-redis = "^4.6.0.5"
|
||||
ipykernel = "^6.27.0"
|
||||
ipykernel = "^6.29.0"
|
||||
mypy = "^1.8.0"
|
||||
ruff = "^0.1.5"
|
||||
ruff = "^0.2.1"
|
||||
httpx = "*"
|
||||
pytest = "^7.4.2"
|
||||
pytest = "^8.0.0"
|
||||
types-requests = "^2.31.0"
|
||||
requests = "^2.31.0"
|
||||
pytest-cov = "^4.1.0"
|
||||
pandas-stubs = "^2.0.0.230412"
|
||||
types-pillow = "^9.5.0.2"
|
||||
pandas-stubs = "^2.1.4.231227"
|
||||
types-pillow = "^10.2.0.20240213"
|
||||
types-pyyaml = "^6.0.12.8"
|
||||
types-python-jose = "^3.3.4.8"
|
||||
types-passlib = "^1.7.7.13"
|
||||
locust = "^2.19.1"
|
||||
locust = "^2.23.1"
|
||||
pytest-mock = "^3.12.0"
|
||||
pytest-xdist = "^3.5.0"
|
||||
types-pywin32 = "^306.0.0.4"
|
||||
types-google-cloud-ndb = "^2.2.0.0"
|
||||
pytest-sugar = "^0.9.7"
|
||||
pytest-sugar = "^1.0.0"
|
||||
pytest-instafail = "^0.5.0"
|
||||
respx = "^0.20.2"
|
||||
|
||||
|
||||
[tool.poetry.extras]
|
||||
|
|
|
|||
|
|
@ -109,7 +109,11 @@ def version_callback(value: bool):
|
|||
@app.callback()
|
||||
def main_entry_point(
|
||||
version: bool = typer.Option(
|
||||
None, "--version", callback=version_callback, is_eager=True, help="Show the version and exit."
|
||||
None,
|
||||
"--version",
|
||||
callback=version_callback,
|
||||
is_eager=True,
|
||||
help="Show the version and exit.",
|
||||
),
|
||||
):
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -63,7 +63,7 @@ version_path_separator = os # Use os.pathsep. Default configuration used for ne
|
|||
# This is the path to the db in the root of the project.
|
||||
# When the user runs the Langflow the database url will
|
||||
# be set dinamically.
|
||||
sqlalchemy.url = sqlite:///../../../langflow.db
|
||||
sqlalchemy.url = sqlite:///./langflow.db
|
||||
|
||||
|
||||
[post_write_hooks]
|
||||
|
|
@ -98,7 +98,7 @@ handlers =
|
|||
qualname = sqlalchemy.engine
|
||||
|
||||
[logger_alembic]
|
||||
level = INFO
|
||||
level = DEBUG
|
||||
handlers =
|
||||
qualname = alembic
|
||||
|
||||
|
|
|
|||
|
|
@ -1,10 +1,11 @@
|
|||
import os
|
||||
from logging.config import fileConfig
|
||||
|
||||
from sqlalchemy import engine_from_config
|
||||
from sqlalchemy import pool
|
||||
|
||||
from alembic import context
|
||||
from loguru import logger
|
||||
from sqlalchemy import engine_from_config, pool
|
||||
|
||||
from langflow.services.database.models import * # noqa
|
||||
from langflow.services.database.service import SQLModel
|
||||
|
||||
# this is the Alembic Config object, which provides
|
||||
|
|
@ -40,7 +41,8 @@ def run_migrations_offline() -> None:
|
|||
script output.
|
||||
|
||||
"""
|
||||
url = config.get_main_option("sqlalchemy.url")
|
||||
url = os.getenv("LANGFLOW_DATABASE_URL")
|
||||
url = url or config.get_main_option("sqlalchemy.url")
|
||||
context.configure(
|
||||
url=url,
|
||||
target_metadata=target_metadata,
|
||||
|
|
@ -60,12 +62,32 @@ def run_migrations_online() -> None:
|
|||
and associate a connection with the context.
|
||||
|
||||
"""
|
||||
connectable = engine_from_config(
|
||||
config.get_section(config.config_ini_section, {}),
|
||||
prefix="sqlalchemy.",
|
||||
poolclass=pool.NullPool,
|
||||
)
|
||||
|
||||
try:
|
||||
from langflow.services.database.factory import DatabaseServiceFactory
|
||||
from langflow.services.deps import get_db_service
|
||||
from langflow.services.manager import (
|
||||
initialize_settings_service,
|
||||
service_manager,
|
||||
)
|
||||
from langflow.services.schema import ServiceType
|
||||
|
||||
initialize_settings_service()
|
||||
service_manager.register_factory(
|
||||
DatabaseServiceFactory(), [ServiceType.SETTINGS_SERVICE]
|
||||
)
|
||||
connectable = get_db_service().engine
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting database engine: {e}")
|
||||
url = os.getenv("LANGFLOW_DATABASE_URL")
|
||||
url = url or config.get_main_option("sqlalchemy.url")
|
||||
if url:
|
||||
config.set_main_option("sqlalchemy.url", url)
|
||||
connectable = engine_from_config(
|
||||
config.get_section(config.config_ini_section, {}),
|
||||
prefix="sqlalchemy.",
|
||||
poolclass=pool.NullPool,
|
||||
)
|
||||
with connectable.connect() as connection:
|
||||
context.configure(
|
||||
connection=connection, target_metadata=target_metadata, render_as_batch=True
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ from typing import Sequence, Union
|
|||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
import sqlmodel
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
${imports if imports else ""}
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
|
|
@ -20,8 +21,14 @@ depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
|
|||
|
||||
|
||||
def upgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
table_names = inspector.get_table_names()
|
||||
${upgrades if upgrades else "pass"}
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
table_names = inspector.get_table_names()
|
||||
${downgrades if downgrades else "pass"}
|
||||
|
|
|
|||
|
|
@ -5,28 +5,43 @@ Revises: 1ef9c4f3765d
|
|||
Create Date: 2023-12-13 18:55:52.587360
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '006b3990db50'
|
||||
down_revision: Union[str, None] = '1ef9c4f3765d'
|
||||
revision: str = "006b3990db50"
|
||||
down_revision: Union[str, None] = "1ef9c4f3765d"
|
||||
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) # type: ignore
|
||||
api_key_constraints = inspector.get_unique_constraints("apikey")
|
||||
flow_constraints = inspector.get_unique_constraints("flow")
|
||||
user_constraints = inspector.get_unique_constraints("user")
|
||||
try:
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.create_unique_constraint('uq_apikey_id', ['id'])
|
||||
if not any(
|
||||
constraint["name"] == "uq_apikey_id" for constraint in api_key_constraints
|
||||
):
|
||||
with op.batch_alter_table("apikey", schema=None) as batch_op:
|
||||
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.create_unique_constraint('uq_flow_id', ['id'])
|
||||
|
||||
with op.batch_alter_table('user', schema=None) as batch_op:
|
||||
batch_op.create_unique_constraint('uq_user_id', ['id'])
|
||||
batch_op.create_unique_constraint("uq_apikey_id", ["id"])
|
||||
if not any(
|
||||
constraint["name"] == "uq_flow_id" for constraint in flow_constraints
|
||||
):
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
batch_op.create_unique_constraint("uq_flow_id", ["id"])
|
||||
if not any(
|
||||
constraint["name"] == "uq_user_id" for constraint in user_constraints
|
||||
):
|
||||
with op.batch_alter_table("user", schema=None) as batch_op:
|
||||
batch_op.create_unique_constraint("uq_user_id", ["id"])
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
|
@ -36,15 +51,24 @@ def upgrade() -> None:
|
|||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
api_key_constraints = inspector.get_unique_constraints("apikey")
|
||||
flow_constraints = inspector.get_unique_constraints("flow")
|
||||
user_constraints = inspector.get_unique_constraints("user")
|
||||
try:
|
||||
with op.batch_alter_table('user', schema=None) as batch_op:
|
||||
batch_op.drop_constraint('uq_user_id', type_='unique')
|
||||
if any(
|
||||
constraint["name"] == "uq_apikey_id" for constraint in api_key_constraints
|
||||
):
|
||||
with op.batch_alter_table("user", schema=None) as batch_op:
|
||||
batch_op.drop_constraint("uq_user_id", type_="unique")
|
||||
if any(constraint["name"] == "uq_flow_id" for constraint in flow_constraints):
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
batch_op.drop_constraint("uq_flow_id", type_="unique")
|
||||
if any(constraint["name"] == "uq_user_id" for constraint in user_constraints):
|
||||
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.drop_constraint('uq_flow_id', type_='unique')
|
||||
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.drop_constraint('uq_apikey_id', type_='unique')
|
||||
with op.batch_alter_table("apikey", schema=None) as batch_op:
|
||||
batch_op.drop_constraint("uq_apikey_id", type_="unique")
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
|
|
|||
|
|
@ -5,67 +5,25 @@ Revises: 006b3990db50
|
|||
Create Date: 2024-01-17 10:32:56.686287
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '0b8757876a7c'
|
||||
down_revision: Union[str, None] = '006b3990db50'
|
||||
revision: str = "0b8757876a7c"
|
||||
down_revision: Union[str, None] = "006b3990db50"
|
||||
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! ###
|
||||
try:
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.create_index(batch_op.f('ix_apikey_api_key'), ['api_key'], unique=True)
|
||||
batch_op.create_index(batch_op.f('ix_apikey_name'), ['name'], unique=False)
|
||||
batch_op.create_index(batch_op.f('ix_apikey_user_id'), ['user_id'], unique=False)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
try:
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.create_index(batch_op.f('ix_flow_description'), ['description'], unique=False)
|
||||
batch_op.create_index(batch_op.f('ix_flow_name'), ['name'], unique=False)
|
||||
batch_op.create_index(batch_op.f('ix_flow_user_id'), ['user_id'], unique=False)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
pass
|
||||
|
||||
try:
|
||||
with op.batch_alter_table('user', schema=None) as batch_op:
|
||||
batch_op.create_index(batch_op.f('ix_user_username'), ['username'], unique=True)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
with op.batch_alter_table('user', schema=None) as batch_op:
|
||||
batch_op.drop_index(batch_op.f('ix_user_username'))
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
try:
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.drop_index(batch_op.f('ix_flow_user_id'))
|
||||
batch_op.drop_index(batch_op.f('ix_flow_name'))
|
||||
batch_op.drop_index(batch_op.f('ix_flow_description'))
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
try:
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.drop_index(batch_op.f('ix_apikey_user_id'))
|
||||
batch_op.drop_index(batch_op.f('ix_apikey_name'))
|
||||
batch_op.drop_index(batch_op.f('ix_apikey_api_key'))
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ Revises: fd531f8868b1
|
|||
Create Date: 2023-12-04 15:00:27.968998
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
|
@ -13,8 +14,8 @@ import sqlmodel
|
|||
from alembic import op
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '1ef9c4f3765d'
|
||||
down_revision: Union[str, None] = 'fd531f8868b1'
|
||||
revision: str = "1ef9c4f3765d"
|
||||
down_revision: Union[str, None] = "fd531f8868b1"
|
||||
branch_labels: Union[str, Sequence[str], None] = None
|
||||
depends_on: Union[str, Sequence[str], None] = None
|
||||
|
||||
|
|
@ -22,10 +23,10 @@ depends_on: Union[str, Sequence[str], None] = None
|
|||
def upgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.alter_column('name',
|
||||
existing_type=sqlmodel.sql.sqltypes.AutoString(),
|
||||
nullable=True)
|
||||
with op.batch_alter_table("apikey", schema=None) as batch_op:
|
||||
batch_op.alter_column(
|
||||
"name", existing_type=sqlmodel.sql.sqltypes.AutoString(), nullable=True
|
||||
)
|
||||
except Exception as e:
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
|
@ -34,10 +35,8 @@ def upgrade() -> None:
|
|||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.alter_column('name',
|
||||
existing_type=sa.VARCHAR(),
|
||||
nullable=False)
|
||||
with op.batch_alter_table("apikey", schema=None) as batch_op:
|
||||
batch_op.alter_column("name", existing_type=sa.VARCHAR(), nullable=False)
|
||||
except Exception as e:
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ Revises:
|
|||
Create Date: 2023-08-27 19:49:02.681355
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
|
@ -33,7 +34,9 @@ def upgrade() -> None:
|
|||
if "ix_flowstyle_flow_id" in [
|
||||
index["name"] for index in inspector.get_indexes("flowstyle")
|
||||
]:
|
||||
op.drop_index("ix_flowstyle_flow_id", table_name="flowstyle")
|
||||
op.drop_index(
|
||||
"ix_flowstyle_flow_id", table_name="flowstyle", if_exists=True
|
||||
)
|
||||
|
||||
existing_indices_flow = []
|
||||
existing_fks_flow = []
|
||||
|
|
@ -80,8 +83,7 @@ def upgrade() -> None:
|
|||
sa.Column("api_key", sqlmodel.sql.sqltypes.AutoString(), nullable=False),
|
||||
sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.ForeignKeyConstraint(
|
||||
["user_id"],
|
||||
["user.id"],
|
||||
["user_id"], ["user.id"], name="fk_apikey_user_id_user"
|
||||
),
|
||||
sa.PrimaryKeyConstraint("id", name="pk_apikey"),
|
||||
sa.UniqueConstraint("id", name="uq_apikey_id"),
|
||||
|
|
@ -103,8 +105,7 @@ def upgrade() -> None:
|
|||
sa.Column("id", sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.ForeignKeyConstraint(
|
||||
["user_id"],
|
||||
["user.id"],
|
||||
["user_id"], ["user.id"], name="fk_flow_user_id_user"
|
||||
),
|
||||
sa.PrimaryKeyConstraint("id", name="pk_flow"),
|
||||
sa.UniqueConstraint("id", name="uq_flow_id"),
|
||||
|
|
@ -151,21 +152,21 @@ def downgrade() -> None:
|
|||
existing_tables = inspector.get_table_names()
|
||||
if "flow" in existing_tables:
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
batch_op.drop_index(batch_op.f("ix_flow_user_id"))
|
||||
batch_op.drop_index(batch_op.f("ix_flow_name"))
|
||||
batch_op.drop_index(batch_op.f("ix_flow_description"))
|
||||
batch_op.drop_index(batch_op.f("ix_flow_user_id"), if_exists=True)
|
||||
batch_op.drop_index(batch_op.f("ix_flow_name"), if_exists=True)
|
||||
batch_op.drop_index(batch_op.f("ix_flow_description"), if_exists=True)
|
||||
|
||||
op.drop_table("flow")
|
||||
if "apikey" in existing_tables:
|
||||
with op.batch_alter_table("apikey", schema=None) as batch_op:
|
||||
batch_op.drop_index(batch_op.f("ix_apikey_user_id"))
|
||||
batch_op.drop_index(batch_op.f("ix_apikey_name"))
|
||||
batch_op.drop_index(batch_op.f("ix_apikey_api_key"))
|
||||
batch_op.drop_index(batch_op.f("ix_apikey_user_id"), if_exists=True)
|
||||
batch_op.drop_index(batch_op.f("ix_apikey_name"), if_exists=True)
|
||||
batch_op.drop_index(batch_op.f("ix_apikey_api_key"), if_exists=True)
|
||||
|
||||
op.drop_table("apikey")
|
||||
if "user" in existing_tables:
|
||||
with op.batch_alter_table("user", schema=None) as batch_op:
|
||||
batch_op.drop_index(batch_op.f("ix_user_username"))
|
||||
batch_op.drop_index(batch_op.f("ix_user_username"), if_exists=True)
|
||||
|
||||
op.drop_table("user")
|
||||
|
||||
|
|
|
|||
|
|
@ -5,34 +5,44 @@ Revises: 7d2162acc8b2
|
|||
Create Date: 2023-11-24 10:45:38.465302
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
import sqlmodel
|
||||
from alembic import op
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '2ac71eb9c3ae'
|
||||
down_revision: Union[str, None] = '7d2162acc8b2'
|
||||
revision: str = "2ac71eb9c3ae"
|
||||
down_revision: Union[str, None] = "7d2162acc8b2"
|
||||
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) # type: ignore
|
||||
tables = inspector.get_table_names()
|
||||
try:
|
||||
op.create_table('credential',
|
||||
sa.Column('name', sqlmodel.sql.sqltypes.AutoString(), nullable=True),
|
||||
sa.Column('value', sqlmodel.sql.sqltypes.AutoString(), nullable=True),
|
||||
sa.Column('provider', sqlmodel.sql.sqltypes.AutoString(), nullable=True),
|
||||
sa.Column('user_id', sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.Column('id', sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id'),
|
||||
)
|
||||
if "credential" not in tables:
|
||||
op.create_table(
|
||||
"credential",
|
||||
sa.Column("name", sqlmodel.sql.sqltypes.AutoString(), nullable=True),
|
||||
sa.Column("value", sqlmodel.sql.sqltypes.AutoString(), nullable=True),
|
||||
sa.Column(
|
||||
"provider", sqlmodel.sql.sqltypes.AutoString(), nullable=True
|
||||
),
|
||||
sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.Column("id", sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.Column("created_at", sa.DateTime(), nullable=False),
|
||||
sa.Column("updated_at", sa.DateTime(), nullable=True),
|
||||
sa.PrimaryKeyConstraint("id"),
|
||||
)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
|
@ -40,7 +50,7 @@ def upgrade() -> None:
|
|||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
op.drop_table('credential')
|
||||
op.drop_table("credential")
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
|
|
|||
|
|
@ -0,0 +1,56 @@
|
|||
"""Add icon and icon_bg_color to Flow
|
||||
|
||||
Revision ID: 63b9c451fd30
|
||||
Revises: bc2f01c40e4a
|
||||
Create Date: 2024-03-06 10:53:47.148658
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
import sqlmodel
|
||||
from alembic import op
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = "63b9c451fd30"
|
||||
down_revision: Union[str, None] = "bc2f01c40e4a"
|
||||
branch_labels: Union[str, Sequence[str], None] = None
|
||||
depends_on: Union[str, Sequence[str], None] = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
table_names = inspector.get_table_names()
|
||||
column_names = [column["name"] for column in inspector.get_columns("flow")]
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
if "icon" not in column_names:
|
||||
batch_op.add_column(
|
||||
sa.Column("icon", sqlmodel.sql.sqltypes.AutoString(), nullable=True)
|
||||
)
|
||||
if "icon_bg_color" not in column_names:
|
||||
batch_op.add_column(
|
||||
sa.Column(
|
||||
"icon_bg_color", sqlmodel.sql.sqltypes.AutoString(), nullable=True
|
||||
)
|
||||
)
|
||||
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
table_names = inspector.get_table_names()
|
||||
column_names = [column["name"] for column in inspector.get_columns("flow")]
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
if "icon" in column_names:
|
||||
batch_op.drop_column("icon")
|
||||
if "icon_bg_color" in column_names:
|
||||
batch_op.drop_column("icon_bg_color")
|
||||
|
||||
# ### end Alembic commands ###
|
||||
|
|
@ -5,6 +5,7 @@ Revises: 260dbcc8b680
|
|||
Create Date: 2023-09-08 07:36:13.387318
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
|
@ -21,29 +22,36 @@ 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) # type: ignore
|
||||
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
|
||||
try:
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
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,
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
print(e)
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
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")
|
||||
try:
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
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")
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
# ### end Alembic commands ###
|
||||
|
|
|
|||
|
|
@ -5,12 +5,13 @@ Revises: eb5866d51fd2
|
|||
Create Date: 2023-10-18 23:08:57.744906
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
import sqlmodel
|
||||
from alembic import op
|
||||
from loguru import logger
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = "7843803a87b5"
|
||||
|
|
@ -21,19 +22,26 @@ 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) # type: ignore
|
||||
flow_columns = [column["name"] for column in inspector.get_columns("flow")]
|
||||
user_columns = [column["name"] for column in inspector.get_columns("user")]
|
||||
try:
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
batch_op.add_column(sa.Column("is_component", sa.Boolean(), nullable=True))
|
||||
|
||||
with op.batch_alter_table("user", schema=None) as batch_op:
|
||||
batch_op.add_column(
|
||||
sa.Column(
|
||||
"store_api_key", sqlmodel.AutoString(), nullable=True
|
||||
if "is_component" not in flow_columns:
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
batch_op.add_column(
|
||||
sa.Column("is_component", sa.Boolean(), nullable=True)
|
||||
)
|
||||
)
|
||||
except Exception as e:
|
||||
logger.exception(e)
|
||||
|
||||
pass
|
||||
try:
|
||||
if "store_api_key" not in user_columns:
|
||||
with op.batch_alter_table("user", schema=None) as batch_op:
|
||||
batch_op.add_column(
|
||||
sa.Column("store_api_key", sqlmodel.AutoString(), nullable=True)
|
||||
)
|
||||
except Exception as e:
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -5,88 +5,74 @@ Revises: f5ee9749d1a6
|
|||
Create Date: 2023-11-21 20:56:53.998781
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
import sqlmodel
|
||||
from alembic import op
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '7d2162acc8b2'
|
||||
down_revision: Union[str, None] = 'f5ee9749d1a6'
|
||||
revision: str = "7d2162acc8b2"
|
||||
down_revision: Union[str, None] = "f5ee9749d1a6"
|
||||
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) # type: ignore
|
||||
api_key_columns = [column["name"] for column in inspector.get_columns("apikey")]
|
||||
flow_columns = [column["name"] for column in inspector.get_columns("flow")]
|
||||
|
||||
try:
|
||||
with op.batch_alter_table('component', schema=None) as batch_op:
|
||||
batch_op.drop_index('ix_component_frontend_node_id')
|
||||
batch_op.drop_index('ix_component_name')
|
||||
op.drop_table('component')
|
||||
op.drop_table('flowstyle')
|
||||
if "name" in api_key_columns:
|
||||
with op.batch_alter_table("apikey", schema=None) as batch_op:
|
||||
batch_op.alter_column(
|
||||
"name", existing_type=sa.VARCHAR(), nullable=False
|
||||
)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.alter_column('name',
|
||||
existing_type=sa.VARCHAR(),
|
||||
nullable=False)
|
||||
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.add_column(sa.Column('updated_at', sa.DateTime(), nullable=True))
|
||||
batch_op.add_column(sa.Column('folder', sqlmodel.sql.sqltypes.AutoString(), nullable=True))
|
||||
pass
|
||||
try:
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
if "updated_at" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column("updated_at", sa.DateTime(), nullable=True)
|
||||
)
|
||||
if "folder" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column(
|
||||
"folder", sqlmodel.sql.sqltypes.AutoString(), nullable=True
|
||||
)
|
||||
)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
pass
|
||||
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.drop_column('folder')
|
||||
batch_op.drop_column('updated_at')
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
batch_op.drop_column("folder")
|
||||
batch_op.drop_column("updated_at")
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
||||
try:
|
||||
|
||||
with op.batch_alter_table('apikey', schema=None) as batch_op:
|
||||
batch_op.alter_column('name',
|
||||
existing_type=sa.VARCHAR(),
|
||||
nullable=True)
|
||||
with op.batch_alter_table("apikey", schema=None) as batch_op:
|
||||
batch_op.alter_column("name", existing_type=sa.VARCHAR(), nullable=True)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
try:
|
||||
op.create_table('flowstyle',
|
||||
sa.Column('color', sa.VARCHAR(), nullable=False),
|
||||
sa.Column('emoji', sa.VARCHAR(), nullable=False),
|
||||
sa.Column('flow_id', sa.CHAR(length=32), nullable=True),
|
||||
sa.Column('id', sa.CHAR(length=32), nullable=False),
|
||||
sa.ForeignKeyConstraint(['flow_id'], ['flow.id'], ),
|
||||
sa.PrimaryKeyConstraint('id'),
|
||||
sa.UniqueConstraint('id')
|
||||
)
|
||||
op.create_table('component',
|
||||
sa.Column('id', sa.CHAR(length=32), nullable=False),
|
||||
sa.Column('frontend_node_id', sa.CHAR(length=32), nullable=False),
|
||||
sa.Column('name', sa.VARCHAR(), nullable=False),
|
||||
sa.Column('description', sa.VARCHAR(), nullable=True),
|
||||
sa.Column('python_code', sa.VARCHAR(), nullable=True),
|
||||
sa.Column('return_type', sa.VARCHAR(), nullable=True),
|
||||
sa.Column('is_disabled', sa.BOOLEAN(), nullable=False),
|
||||
sa.Column('is_read_only', sa.BOOLEAN(), nullable=False),
|
||||
sa.Column('create_at', sa.DATETIME(), nullable=False),
|
||||
sa.Column('update_at', sa.DATETIME(), nullable=False),
|
||||
sa.PrimaryKeyConstraint('id')
|
||||
)
|
||||
|
||||
with op.batch_alter_table('component', schema=None) as batch_op:
|
||||
batch_op.create_index('ix_component_name', ['name'], unique=False)
|
||||
batch_op.create_index('ix_component_frontend_node_id', ['frontend_node_id'], unique=False)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
|
|
|||
|
|
@ -5,55 +5,105 @@ Revises: 0b8757876a7c
|
|||
Create Date: 2024-01-26 13:31:14.797548
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
import sqlmodel
|
||||
from alembic import op
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = 'b2fa308044b5'
|
||||
down_revision: Union[str, None] = '0b8757876a7c'
|
||||
revision: str = "b2fa308044b5"
|
||||
down_revision: Union[str, None] = "0b8757876a7c"
|
||||
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) # type: ignore
|
||||
tables = inspector.get_table_names()
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
op.drop_table('flowstyle')
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.add_column(sa.Column('is_component', sa.Boolean(), nullable=True))
|
||||
batch_op.add_column(sa.Column('updated_at', sa.DateTime(), nullable=True))
|
||||
batch_op.add_column(sa.Column('folder', sqlmodel.sql.sqltypes.AutoString(), nullable=True))
|
||||
batch_op.add_column(sa.Column('user_id', sqlmodel.sql.sqltypes.GUID(), nullable=True))
|
||||
batch_op.create_index(batch_op.f('ix_flow_user_id'), ['user_id'], unique=False)
|
||||
batch_op.create_foreign_key('fk_flow_user_id_user', 'user', ['user_id'], ['id'])
|
||||
if "flowstyle" in tables:
|
||||
op.drop_table("flowstyle")
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
flow_columns = [column["name"] for column in inspector.get_columns("flow")]
|
||||
if "is_component" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column("is_component", sa.Boolean(), nullable=True)
|
||||
)
|
||||
if "updated_at" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column("updated_at", sa.DateTime(), nullable=True)
|
||||
)
|
||||
if "folder" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column(
|
||||
"folder", sqlmodel.sql.sqltypes.AutoString(), nullable=True
|
||||
)
|
||||
)
|
||||
if "user_id" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=True)
|
||||
)
|
||||
indices = inspector.get_indexes("flow")
|
||||
indices_names = [index["name"] for index in indices]
|
||||
if "ix_flow_user_id" not in indices_names:
|
||||
batch_op.create_index(
|
||||
batch_op.f("ix_flow_user_id"), ["user_id"], unique=False
|
||||
)
|
||||
if "fk_flow_user_id_user" not in indices_names:
|
||||
batch_op.create_foreign_key(
|
||||
"fk_flow_user_id_user", "user", ["user_id"], ["id"]
|
||||
)
|
||||
|
||||
except Exception:
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
try:
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.drop_constraint('fk_flow_user_id_user', type_='foreignkey')
|
||||
batch_op.drop_index(batch_op.f('ix_flow_user_id'))
|
||||
batch_op.drop_column('user_id')
|
||||
batch_op.drop_column('folder')
|
||||
batch_op.drop_column('updated_at')
|
||||
batch_op.drop_column('is_component')
|
||||
# Re-create the dropped table 'flowstyle' if it was previously dropped in upgrade
|
||||
if "flowstyle" not in inspector.get_table_names():
|
||||
op.create_table(
|
||||
"flowstyle",
|
||||
sa.Column("color", sa.String(), nullable=False),
|
||||
sa.Column("emoji", sa.String(), nullable=False),
|
||||
sa.Column("flow_id", sqlmodel.sql.sqltypes.GUID(), nullable=True),
|
||||
sa.Column("id", sqlmodel.sql.sqltypes.GUID(), nullable=False),
|
||||
sa.ForeignKeyConstraint(["flow_id"], ["flow.id"]),
|
||||
sa.PrimaryKeyConstraint("id"),
|
||||
sa.UniqueConstraint("id"),
|
||||
)
|
||||
|
||||
op.create_table('flowstyle',
|
||||
sa.Column('color', sa.VARCHAR(), nullable=False),
|
||||
sa.Column('emoji', sa.VARCHAR(), nullable=False),
|
||||
sa.Column('flow_id', sa.CHAR(length=32), nullable=True),
|
||||
sa.Column('id', sa.CHAR(length=32), nullable=False),
|
||||
sa.ForeignKeyConstraint(['flow_id'], ['flow.id'], ),
|
||||
sa.PrimaryKeyConstraint('id'),
|
||||
sa.UniqueConstraint('id')
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
# Check and remove newly added columns and constraints in upgrade
|
||||
flow_columns = [column["name"] for column in inspector.get_columns("flow")]
|
||||
if "user_id" in flow_columns:
|
||||
batch_op.drop_column("user_id")
|
||||
if "folder" in flow_columns:
|
||||
batch_op.drop_column("folder")
|
||||
if "updated_at" in flow_columns:
|
||||
batch_op.drop_column("updated_at")
|
||||
if "is_component" in flow_columns:
|
||||
batch_op.drop_column("is_component")
|
||||
|
||||
indices = inspector.get_indexes("flow")
|
||||
indices_names = [index["name"] for index in indices]
|
||||
if "ix_flow_user_id" in indices_names:
|
||||
batch_op.drop_index("ix_flow_user_id")
|
||||
# Assuming fk_flow_user_id_user is a foreign key constraint's name, not an index
|
||||
constraints = inspector.get_foreign_keys("flow")
|
||||
constraint_names = [constraint["name"] for constraint in constraints]
|
||||
if "fk_flow_user_id_user" in constraint_names:
|
||||
batch_op.drop_constraint("fk_flow_user_id_user", type_="foreignkey")
|
||||
|
||||
except Exception as e:
|
||||
# It's generally a good idea to log the exception or handle it in a way other than a bare pass
|
||||
print(f"Error during downgrade: {e}")
|
||||
|
|
|
|||
|
|
@ -5,46 +5,68 @@ Revises: b2fa308044b5
|
|||
Create Date: 2024-01-26 13:34:14.496769
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
import sqlmodel
|
||||
from alembic import op
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = 'bc2f01c40e4a'
|
||||
down_revision: Union[str, None] = 'b2fa308044b5'
|
||||
revision: str = "bc2f01c40e4a"
|
||||
down_revision: Union[str, None] = "b2fa308044b5"
|
||||
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! ###
|
||||
try:
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.add_column(sa.Column('is_component', sa.Boolean(), nullable=True))
|
||||
batch_op.add_column(sa.Column('updated_at', sa.DateTime(), nullable=True))
|
||||
batch_op.add_column(sa.Column('folder', sqlmodel.sql.sqltypes.AutoString(), nullable=True))
|
||||
batch_op.add_column(sa.Column('user_id', sqlmodel.sql.sqltypes.GUID(), nullable=True))
|
||||
batch_op.create_index(batch_op.f('ix_flow_user_id'), ['user_id'], unique=False)
|
||||
batch_op.create_foreign_key('flow_user_id_fkey'
|
||||
, 'user', ['user_id'], ['id'])
|
||||
except Exception:
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
flow_columns = {column["name"] for column in inspector.get_columns("flow")}
|
||||
flow_indexes = {index["name"] for index in inspector.get_indexes("flow")}
|
||||
flow_fks = {fk["name"] for fk in inspector.get_foreign_keys("flow")}
|
||||
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
if "is_component" not in flow_columns:
|
||||
batch_op.add_column(sa.Column("is_component", sa.Boolean(), nullable=True))
|
||||
if "updated_at" not in flow_columns:
|
||||
batch_op.add_column(sa.Column("updated_at", sa.DateTime(), nullable=True))
|
||||
if "folder" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column("folder", sqlmodel.sql.sqltypes.AutoString(), nullable=True)
|
||||
)
|
||||
if "user_id" not in flow_columns:
|
||||
batch_op.add_column(
|
||||
sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=True)
|
||||
)
|
||||
if "ix_flow_user_id" not in flow_indexes:
|
||||
batch_op.create_index(
|
||||
batch_op.f("ix_flow_user_id"), ["user_id"], unique=False
|
||||
)
|
||||
if "flow_user_id_fkey" not in flow_fks:
|
||||
batch_op.create_foreign_key(
|
||||
"flow_user_id_fkey", "user", ["user_id"], ["id"]
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
with op.batch_alter_table('flow', schema=None) as batch_op:
|
||||
batch_op.drop_constraint('flow_user_id_fkey', type_='foreignkey')
|
||||
batch_op.drop_index(batch_op.f('ix_flow_user_id'))
|
||||
batch_op.drop_column('user_id')
|
||||
batch_op.drop_column('folder')
|
||||
batch_op.drop_column('updated_at')
|
||||
batch_op.drop_column('is_component')
|
||||
except Exception:
|
||||
pass
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
flow_columns = {column["name"] for column in inspector.get_columns("flow")}
|
||||
flow_indexes = {index["name"] for index in inspector.get_indexes("flow")}
|
||||
flow_fks = {fk["name"] for fk in inspector.get_foreign_keys("flow")}
|
||||
|
||||
# ### end Alembic commands ###
|
||||
with op.batch_alter_table("flow", schema=None) as batch_op:
|
||||
if "flow_user_id_fkey" in flow_fks:
|
||||
batch_op.drop_constraint("flow_user_id_fkey", type_="foreignkey")
|
||||
if "ix_flow_user_id" in flow_indexes:
|
||||
batch_op.drop_index(batch_op.f("ix_flow_user_id"))
|
||||
if "user_id" in flow_columns:
|
||||
batch_op.drop_column("user_id")
|
||||
if "folder" in flow_columns:
|
||||
batch_op.drop_column("folder")
|
||||
if "updated_at" in flow_columns:
|
||||
batch_op.drop_column("updated_at")
|
||||
if "is_component" in flow_columns:
|
||||
batch_op.drop_column("is_component")
|
||||
|
|
|
|||
|
|
@ -5,11 +5,10 @@ Revises: 67cc006d50bf
|
|||
Create Date: 2023-10-04 10:18:25.640458
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
from alembic import op
|
||||
from sqlalchemy import exc
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = "eb5866d51fd2"
|
||||
|
|
@ -21,70 +20,12 @@ depends_on: Union[str, Sequence[str], None] = None
|
|||
def upgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
connection = op.get_bind()
|
||||
try:
|
||||
op.drop_table("flowstyle")
|
||||
with op.batch_alter_table("component", schema=None) as batch_op:
|
||||
batch_op.drop_index("ix_component_frontend_node_id")
|
||||
batch_op.drop_index("ix_component_name")
|
||||
except exc.SQLAlchemyError:
|
||||
# connection.execute(text("ROLLBACK"))
|
||||
pass
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
||||
try:
|
||||
op.drop_table("component")
|
||||
except exc.SQLAlchemyError:
|
||||
# connection.execute(text("ROLLBACK"))
|
||||
pass
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
try:
|
||||
op.create_table(
|
||||
"component",
|
||||
sa.Column("id", sa.CHAR(length=32), nullable=False),
|
||||
sa.Column("frontend_node_id", sa.CHAR(length=32), nullable=False),
|
||||
sa.Column("name", sa.VARCHAR(), nullable=False),
|
||||
sa.Column("description", sa.VARCHAR(), nullable=True),
|
||||
sa.Column("python_code", sa.VARCHAR(), nullable=True),
|
||||
sa.Column("return_type", sa.VARCHAR(), nullable=True),
|
||||
sa.Column("is_disabled", sa.BOOLEAN(), nullable=False),
|
||||
sa.Column("is_read_only", sa.BOOLEAN(), nullable=False),
|
||||
sa.Column("create_at", sa.DATETIME(), nullable=False),
|
||||
sa.Column("update_at", sa.DATETIME(), nullable=False),
|
||||
sa.PrimaryKeyConstraint("id", name="pk_component"),
|
||||
)
|
||||
with op.batch_alter_table("component", schema=None) as batch_op:
|
||||
batch_op.create_index("ix_component_name", ["name"], unique=False)
|
||||
batch_op.create_index(
|
||||
"ix_component_frontend_node_id", ["frontend_node_id"], unique=False
|
||||
)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
||||
try:
|
||||
op.create_table(
|
||||
"flowstyle",
|
||||
sa.Column("color", sa.VARCHAR(), nullable=False),
|
||||
sa.Column("emoji", sa.VARCHAR(), nullable=False),
|
||||
sa.Column("flow_id", sa.CHAR(length=32), nullable=True),
|
||||
sa.Column("id", sa.CHAR(length=32), nullable=False),
|
||||
sa.ForeignKeyConstraint(
|
||||
["flow_id"],
|
||||
["flow.id"],
|
||||
),
|
||||
sa.PrimaryKeyConstraint("id", name="pk_flowstyle"),
|
||||
sa.UniqueConstraint("id", name="uq_flowstyle_id"),
|
||||
)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ Revises: 7843803a87b5
|
|||
Create Date: 2023-10-18 23:12:27.297016
|
||||
|
||||
"""
|
||||
|
||||
from typing import Sequence, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
|
|
|||
|
|
@ -5,22 +5,35 @@ Revises: 2ac71eb9c3ae
|
|||
Create Date: 2023-11-24 15:07:37.566516
|
||||
|
||||
"""
|
||||
from typing import Sequence, Union
|
||||
|
||||
from typing import Optional, Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
from sqlalchemy.engine.reflection import Inspector
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = 'fd531f8868b1'
|
||||
down_revision: Union[str, None] = '2ac71eb9c3ae'
|
||||
revision: str = "fd531f8868b1"
|
||||
down_revision: Union[str, None] = "2ac71eb9c3ae"
|
||||
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) # type: ignore
|
||||
tables = inspector.get_table_names()
|
||||
foreign_keys_names = []
|
||||
if "credential" in tables:
|
||||
foreign_keys = inspector.get_foreign_keys("credential")
|
||||
foreign_keys_names = [fk["name"] for fk in foreign_keys]
|
||||
|
||||
try:
|
||||
with op.batch_alter_table('credential', schema=None) as batch_op:
|
||||
batch_op.create_foreign_key("fk_credential_user_id", 'user', ['user_id'], ['id'])
|
||||
if "credential" in tables and "fk_credential_user_id" not in foreign_keys_names:
|
||||
with op.batch_alter_table("credential", schema=None) as batch_op:
|
||||
batch_op.create_foreign_key(
|
||||
"fk_credential_user_id", "user", ["user_id"], ["id"]
|
||||
)
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
|
@ -30,9 +43,17 @@ def upgrade() -> None:
|
|||
|
||||
def downgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
conn = op.get_bind()
|
||||
inspector = Inspector.from_engine(conn) # type: ignore
|
||||
tables = inspector.get_table_names()
|
||||
foreign_keys_names: list[Optional[str]] = []
|
||||
if "credential" in tables:
|
||||
foreign_keys = inspector.get_foreign_keys("credential")
|
||||
foreign_keys_names = [fk["name"] for fk in foreign_keys]
|
||||
try:
|
||||
with op.batch_alter_table('credential', schema=None) as batch_op:
|
||||
batch_op.drop_constraint("fk_credential_user_id", type_='foreignkey')
|
||||
if "credential" in tables and "fk_credential_user_id" in foreign_keys_names:
|
||||
with op.batch_alter_table("credential", schema=None) as batch_op:
|
||||
batch_op.drop_constraint("fk_credential_user_id", type_="foreignkey")
|
||||
except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
|
|
|||
|
|
@ -6,8 +6,10 @@ from langflow.api.v1 import (
|
|||
chat_router,
|
||||
credentials_router,
|
||||
endpoints_router,
|
||||
files_router,
|
||||
flows_router,
|
||||
login_router,
|
||||
monitor_router,
|
||||
store_router,
|
||||
users_router,
|
||||
validate_router,
|
||||
|
|
@ -25,3 +27,5 @@ router.include_router(users_router)
|
|||
router.include_router(api_key_router)
|
||||
router.include_router(login_router)
|
||||
router.include_router(credentials_router)
|
||||
router.include_router(files_router)
|
||||
router.include_router(monitor_router)
|
||||
|
|
|
|||
|
|
@ -1,10 +1,14 @@
|
|||
import warnings
|
||||
from pathlib import Path
|
||||
from typing import TYPE_CHECKING, List
|
||||
from typing import TYPE_CHECKING, Optional
|
||||
|
||||
from fastapi import HTTPException
|
||||
from platformdirs import user_cache_dir
|
||||
from sqlmodel import Session
|
||||
|
||||
from langflow.graph.graph.base import Graph
|
||||
from langflow.services.chat.service import ChatService
|
||||
from langflow.services.database.models.flow import Flow
|
||||
from langflow.services.store.schema import StoreComponentCreate
|
||||
from langflow.services.store.utils import get_lf_version_from_pypi
|
||||
|
||||
|
|
@ -137,7 +141,7 @@ def get_file_path_value(file_path):
|
|||
return file_path
|
||||
|
||||
|
||||
def validate_is_component(flows: List["Flow"]):
|
||||
def validate_is_component(flows: list["Flow"]):
|
||||
for flow in flows:
|
||||
if not flow.data or flow.is_component is not None:
|
||||
continue
|
||||
|
|
@ -171,19 +175,66 @@ async def check_langflow_version(component: StoreComponentCreate):
|
|||
)
|
||||
|
||||
|
||||
def format_elapsed_time(elapsed_time) -> str:
|
||||
# Format elapsed time to human readable format coming from
|
||||
# perf_counter()
|
||||
# If the elapsed time is less than 1 second, return ms
|
||||
# If the elapsed time is less than 1 minute, return seconds rounded to 2 decimals
|
||||
time_str = ""
|
||||
def format_elapsed_time(elapsed_time: float) -> str:
|
||||
"""Format elapsed time to a human-readable format coming from perf_counter().
|
||||
|
||||
- Less than 1 second: returns milliseconds
|
||||
- Less than 1 minute: returns seconds rounded to 2 decimals
|
||||
- 1 minute or more: returns minutes and seconds
|
||||
"""
|
||||
if elapsed_time < 1:
|
||||
elapsed_time = int(round(elapsed_time * 1000))
|
||||
time_str = f"{elapsed_time} ms"
|
||||
milliseconds = int(round(elapsed_time * 1000))
|
||||
return f"{milliseconds} ms"
|
||||
elif elapsed_time < 60:
|
||||
elapsed_time = round(elapsed_time, 2)
|
||||
time_str = f"{elapsed_time} seconds"
|
||||
seconds = round(elapsed_time, 2)
|
||||
unit = "second" if seconds == 1 else "seconds"
|
||||
return f"{seconds} {unit}"
|
||||
else:
|
||||
elapsed_time = round(elapsed_time / 60, 2)
|
||||
time_str = f"{elapsed_time} minutes"
|
||||
return time_str
|
||||
minutes = int(elapsed_time // 60)
|
||||
seconds = round(elapsed_time % 60, 2)
|
||||
minutes_unit = "minute" if minutes == 1 else "minutes"
|
||||
seconds_unit = "second" if seconds == 1 else "seconds"
|
||||
return f"{minutes} {minutes_unit}, {seconds} {seconds_unit}"
|
||||
|
||||
|
||||
async def build_and_cache_graph(
|
||||
flow_id: str,
|
||||
session: Session,
|
||||
chat_service: "ChatService",
|
||||
graph: Optional[Graph] = None,
|
||||
):
|
||||
"""Build and cache the graph."""
|
||||
flow: Optional[Flow] = session.get(Flow, flow_id)
|
||||
if not flow or not flow.data:
|
||||
raise ValueError("Invalid flow ID")
|
||||
other_graph = Graph.from_payload(flow.data, flow_id)
|
||||
if graph is None:
|
||||
graph = other_graph
|
||||
else:
|
||||
graph = graph.update(other_graph)
|
||||
await chat_service.set_cache(flow_id, graph)
|
||||
return graph
|
||||
|
||||
|
||||
def format_syntax_error_message(exc: SyntaxError) -> str:
|
||||
"""Format a SyntaxError message for returning to the frontend."""
|
||||
if exc.text is None:
|
||||
return f"Syntax error in code. Error on line {exc.lineno}"
|
||||
return f"Syntax error in code. Error on line {exc.lineno}: {exc.text.strip()}"
|
||||
|
||||
|
||||
def get_causing_exception(exc: BaseException) -> BaseException:
|
||||
"""Get the causing exception from an exception."""
|
||||
if hasattr(exc, "__cause__") and exc.__cause__:
|
||||
return get_causing_exception(exc.__cause__)
|
||||
return exc
|
||||
|
||||
|
||||
def format_exception_message(exc: Exception) -> str:
|
||||
"""Format an exception message for returning to the frontend."""
|
||||
# We need to check if the __cause__ is a SyntaxError
|
||||
# If it is, we need to return the message of the SyntaxError
|
||||
causing_exception = get_causing_exception(exc)
|
||||
if isinstance(causing_exception, SyntaxError):
|
||||
return format_syntax_error_message(causing_exception)
|
||||
return str(exc)
|
||||
|
|
|
|||
|
|
@ -2,8 +2,10 @@ from langflow.api.v1.api_key import router as api_key_router
|
|||
from langflow.api.v1.chat import router as chat_router
|
||||
from langflow.api.v1.credential import router as credentials_router
|
||||
from langflow.api.v1.endpoints import router as endpoints_router
|
||||
from langflow.api.v1.files import router as files_router
|
||||
from langflow.api.v1.flows import router as flows_router
|
||||
from langflow.api.v1.login import router as login_router
|
||||
from langflow.api.v1.monitor import router as monitor_router
|
||||
from langflow.api.v1.store import router as store_router
|
||||
from langflow.api.v1.users import router as users_router
|
||||
from langflow.api.v1.validate import router as validate_router
|
||||
|
|
@ -18,4 +20,6 @@ __all__ = [
|
|||
"api_key_router",
|
||||
"login_router",
|
||||
"credentials_router",
|
||||
"monitor_router",
|
||||
"files_router",
|
||||
]
|
||||
|
|
|
|||
|
|
@ -1,9 +1,7 @@
|
|||
from typing import Optional
|
||||
|
||||
from langchain.prompts import PromptTemplate
|
||||
from pydantic import BaseModel, field_validator, model_serializer
|
||||
|
||||
from langflow.interface.utils import extract_input_variables_from_prompt
|
||||
from langflow.template.frontend_node.base import FrontendNode
|
||||
|
||||
|
||||
|
|
@ -28,7 +26,7 @@ class FrontendNodeRequest(FrontendNode):
|
|||
class ValidatePromptRequest(BaseModel):
|
||||
name: str
|
||||
template: str
|
||||
# optional for tweak call
|
||||
custom_fields: Optional[dict] = None
|
||||
frontend_node: Optional[FrontendNodeRequest] = None
|
||||
|
||||
|
||||
|
|
@ -68,8 +66,6 @@ INVALID_CHARACTERS = {
|
|||
")",
|
||||
"[",
|
||||
"]",
|
||||
"{",
|
||||
"}",
|
||||
}
|
||||
|
||||
INVALID_NAMES = {
|
||||
|
|
@ -82,79 +78,88 @@ INVALID_NAMES = {
|
|||
}
|
||||
|
||||
|
||||
def validate_prompt(template: str):
|
||||
input_variables = extract_input_variables_from_prompt(template)
|
||||
|
||||
# Check if there are invalid characters in the input_variables
|
||||
input_variables = check_input_variables(input_variables)
|
||||
if any(var in INVALID_NAMES for var in input_variables):
|
||||
raise ValueError(f"Invalid input variables. None of the variables can be named {', '.join(input_variables)}. ")
|
||||
|
||||
try:
|
||||
PromptTemplate(template=template, input_variables=input_variables)
|
||||
except Exception as exc:
|
||||
raise ValueError(str(exc)) from exc
|
||||
|
||||
return input_variables
|
||||
def is_json_like(var):
|
||||
if var.startswith("{{") and var.endswith("}}"):
|
||||
# If it is a double brance variable
|
||||
# we don't want to validate any of its content
|
||||
return True
|
||||
# the above doesn't work on all cases because the json string can be multiline
|
||||
# or indented which can add \n or spaces at the start or end of the string
|
||||
# test_case_3 new_var == '\n{{\n "test": "hello",\n "text": "world"\n}}\n'
|
||||
# what we can do is to remove the \n and spaces from the start and end of the string
|
||||
# and then check if the string starts with {{ and ends with }}
|
||||
var = var.strip()
|
||||
var = var.replace("\n", "")
|
||||
var = var.replace(" ", "")
|
||||
# Now it should be a valid json string
|
||||
return var.startswith("{{") and var.endswith("}}")
|
||||
|
||||
|
||||
def check_input_variables(input_variables: list):
|
||||
def fix_variable(var, invalid_chars, wrong_variables):
|
||||
if not var:
|
||||
return var, invalid_chars, wrong_variables
|
||||
new_var = var
|
||||
|
||||
# Handle variables starting with a number
|
||||
if var[0].isdigit():
|
||||
invalid_chars.append(var[0])
|
||||
new_var, invalid_chars, wrong_variables = fix_variable(var[1:], invalid_chars, wrong_variables)
|
||||
|
||||
# Temporarily replace {{ and }} to avoid treating them as invalid
|
||||
new_var = new_var.replace("{{", "ᴛᴇᴍᴘᴏᴘᴇɴ").replace("}}", "ᴛᴇᴍᴘᴄʟᴏsᴇ")
|
||||
|
||||
# Remove invalid characters
|
||||
for char in new_var:
|
||||
if char in INVALID_CHARACTERS:
|
||||
invalid_chars.append(char)
|
||||
new_var = new_var.replace(char, "")
|
||||
if var not in wrong_variables: # Avoid duplicating entries
|
||||
wrong_variables.append(var)
|
||||
|
||||
# Restore {{ and }}
|
||||
new_var = new_var.replace("ᴛᴇᴍᴘᴏᴘᴇɴ", "{{").replace("ᴛᴇᴍᴘᴄʟᴏsᴇ", "}}")
|
||||
|
||||
return new_var, invalid_chars, wrong_variables
|
||||
|
||||
|
||||
def check_variable(var, invalid_chars, wrong_variables, empty_variables):
|
||||
if any(char in invalid_chars for char in var):
|
||||
wrong_variables.append(var)
|
||||
elif var == "":
|
||||
empty_variables.append(var)
|
||||
return wrong_variables, empty_variables
|
||||
|
||||
|
||||
def check_for_errors(input_variables, fixed_variables, wrong_variables, empty_variables):
|
||||
if any(var for var in input_variables if var not in fixed_variables):
|
||||
error_message = (
|
||||
f"Error: Input variables contain invalid characters or formats. \n"
|
||||
f"Invalid variables: {', '.join(wrong_variables)}.\n"
|
||||
f"Empty variables: {', '.join(empty_variables)}. \n"
|
||||
f"Fixed variables: {', '.join(fixed_variables)}."
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
|
||||
|
||||
def check_input_variables(input_variables):
|
||||
invalid_chars = []
|
||||
fixed_variables = []
|
||||
wrong_variables = []
|
||||
empty_variables = []
|
||||
for variable in input_variables:
|
||||
new_var = variable
|
||||
variables_to_check = []
|
||||
|
||||
# if variable is empty, then we should add that to the wrong variables
|
||||
if not variable:
|
||||
empty_variables.append(variable)
|
||||
for var in input_variables:
|
||||
# First, let's check if the variable is a JSON string
|
||||
# because if it is, it won't be considered a variable
|
||||
# and we don't need to validate it
|
||||
if is_json_like(var):
|
||||
continue
|
||||
|
||||
# if variable starts with a number we should add that to the invalid chars
|
||||
# and wrong variables
|
||||
if variable[0].isdigit():
|
||||
invalid_chars.append(variable[0])
|
||||
new_var = new_var.replace(variable[0], "")
|
||||
wrong_variables.append(variable)
|
||||
else:
|
||||
for char in INVALID_CHARACTERS:
|
||||
if char in variable:
|
||||
invalid_chars.append(char)
|
||||
new_var = new_var.replace(char, "")
|
||||
wrong_variables.append(variable)
|
||||
new_var, wrong_variables, empty_variables = fix_variable(var, invalid_chars, wrong_variables)
|
||||
wrong_variables, empty_variables = check_variable(var, INVALID_CHARACTERS, wrong_variables, empty_variables)
|
||||
fixed_variables.append(new_var)
|
||||
# If any of the input_variables is not in the fixed_variables, then it means that
|
||||
# there are invalid characters in the input_variables
|
||||
variables_to_check.append(var)
|
||||
|
||||
if any(var not in fixed_variables for var in input_variables):
|
||||
error_message = build_error_message(
|
||||
input_variables,
|
||||
invalid_chars,
|
||||
wrong_variables,
|
||||
fixed_variables,
|
||||
empty_variables,
|
||||
)
|
||||
raise ValueError(error_message)
|
||||
return input_variables
|
||||
check_for_errors(variables_to_check, fixed_variables, wrong_variables, empty_variables)
|
||||
|
||||
|
||||
def build_error_message(input_variables, invalid_chars, wrong_variables, fixed_variables, empty_variables):
|
||||
input_variables_str = ", ".join([f"'{var}'" for var in input_variables])
|
||||
error_string = f"Invalid input variables: {input_variables_str}. "
|
||||
|
||||
if wrong_variables and invalid_chars:
|
||||
# fix the wrong variables replacing invalid chars and find them in the fixed variables
|
||||
error_string_vars = "You can fix them by replacing the invalid characters: "
|
||||
wvars = wrong_variables.copy()
|
||||
for i, wrong_var in enumerate(wvars):
|
||||
for char in invalid_chars:
|
||||
wrong_var = wrong_var.replace(char, "")
|
||||
if wrong_var in fixed_variables:
|
||||
error_string_vars += f"'{wrong_variables[i]}' -> '{wrong_var}'"
|
||||
error_string += error_string_vars
|
||||
elif empty_variables:
|
||||
error_string += f" There are {len(empty_variables)} empty variable{'s' if len(empty_variables) > 1 else ''}."
|
||||
elif len(set(fixed_variables)) != len(fixed_variables):
|
||||
error_string += "There are duplicate variables."
|
||||
return error_string
|
||||
return fixed_variables
|
||||
|
|
|
|||
|
|
@ -1,28 +1,37 @@
|
|||
import asyncio
|
||||
from typing import Any, Dict, List, Optional
|
||||
from typing import TYPE_CHECKING, Any, Dict, List, Optional
|
||||
from uuid import UUID
|
||||
|
||||
from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler
|
||||
from langchain.schema import AgentAction, AgentFinish
|
||||
from langchain_core.callbacks.base import AsyncCallbackHandler
|
||||
from loguru import logger
|
||||
|
||||
from langflow.api.v1.schemas import ChatResponse, PromptResponse
|
||||
from langflow.services.deps import get_chat_service
|
||||
from langflow.services.deps import get_chat_service, get_socket_service
|
||||
from langflow.utils.util import remove_ansi_escape_codes
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.services.socket.service import SocketIOService
|
||||
|
||||
|
||||
# https://github.com/hwchase17/chat-langchain/blob/master/callback.py
|
||||
class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler):
|
||||
class AsyncStreamingLLMCallbackHandleSIO(AsyncCallbackHandler):
|
||||
"""Callback handler for streaming LLM responses."""
|
||||
|
||||
def __init__(self, client_id: str):
|
||||
@property
|
||||
def ignore_chain(self) -> bool:
|
||||
"""Whether to ignore chain callbacks."""
|
||||
return False
|
||||
|
||||
def __init__(self, session_id: str):
|
||||
self.chat_service = get_chat_service()
|
||||
self.client_id = client_id
|
||||
self.websocket = self.chat_service.active_connections[self.client_id]
|
||||
self.client_id = session_id
|
||||
self.socketio_service: "SocketIOService" = get_socket_service()
|
||||
self.sid = session_id
|
||||
# self.socketio_service = self.chat_service.active_connections[self.client_id]
|
||||
|
||||
async def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
|
||||
resp = ChatResponse(message=token, type="stream", intermediate_steps="")
|
||||
await self.websocket.send_json(resp.model_dump())
|
||||
await self.socketio_service.emit_token(to=self.sid, data=resp.model_dump())
|
||||
|
||||
async def on_tool_start(self, serialized: Dict[str, Any], input_str: str, **kwargs: Any) -> Any:
|
||||
"""Run when tool starts running."""
|
||||
|
|
@ -31,7 +40,7 @@ class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler):
|
|||
type="stream",
|
||||
intermediate_steps=f"Tool input: {input_str}",
|
||||
)
|
||||
await self.websocket.send_json(resp.model_dump())
|
||||
await self.socketio_service.emit_token(to=self.sid, data=resp.model_dump())
|
||||
|
||||
async def on_tool_end(self, output: str, **kwargs: Any) -> Any:
|
||||
"""Run when tool ends running."""
|
||||
|
|
@ -62,7 +71,7 @@ class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler):
|
|||
try:
|
||||
# This is to emulate the stream of tokens
|
||||
for resp in resps:
|
||||
await self.websocket.send_json(resp.model_dump())
|
||||
await self.socketio_service.emit_token(to=self.sid, data=resp.model_dump())
|
||||
except Exception as exc:
|
||||
logger.error(f"Error sending response: {exc}")
|
||||
|
||||
|
|
@ -88,8 +97,7 @@ class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler):
|
|||
resp = PromptResponse(
|
||||
prompt=text,
|
||||
)
|
||||
await self.websocket.send_json(resp.model_dump())
|
||||
self.chat_service.chat_history.add_message(self.client_id, resp)
|
||||
await self.socketio_service.emit_message(to=self.sid, data=resp.model_dump())
|
||||
|
||||
async def on_agent_action(self, action: AgentAction, **kwargs: Any):
|
||||
log = f"Thought: {action.log}"
|
||||
|
|
@ -99,10 +107,10 @@ class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler):
|
|||
logs = log.split("\n")
|
||||
for log in logs:
|
||||
resp = ChatResponse(message="", type="stream", intermediate_steps=log)
|
||||
await self.websocket.send_json(resp.model_dump())
|
||||
await self.socketio_service.emit_token(to=self.sid, data=resp.model_dump())
|
||||
else:
|
||||
resp = ChatResponse(message="", type="stream", intermediate_steps=log)
|
||||
await self.websocket.send_json(resp.model_dump())
|
||||
await self.socketio_service.emit_token(to=self.sid, data=resp.model_dump())
|
||||
|
||||
async def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> Any:
|
||||
"""Run on agent end."""
|
||||
|
|
@ -111,20 +119,4 @@ class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler):
|
|||
type="stream",
|
||||
intermediate_steps=finish.log,
|
||||
)
|
||||
await self.websocket.send_json(resp.model_dump())
|
||||
|
||||
|
||||
class StreamingLLMCallbackHandler(BaseCallbackHandler):
|
||||
"""Callback handler for streaming LLM responses."""
|
||||
|
||||
def __init__(self, client_id: str):
|
||||
self.chat_service = get_chat_service()
|
||||
self.client_id = client_id
|
||||
self.websocket = self.chat_service.active_connections[self.client_id]
|
||||
|
||||
def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
|
||||
resp = ChatResponse(message=token, type="stream", intermediate_steps="")
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
coroutine = self.websocket.send_json(resp.model_dump())
|
||||
asyncio.run_coroutine_threadsafe(coroutine, loop)
|
||||
await self.socketio_service.emit_token(to=self.sid, data=resp.model_dump())
|
||||
|
|
|
|||
|
|
@ -1,223 +1,35 @@
|
|||
import time
|
||||
import uuid
|
||||
from typing import TYPE_CHECKING, Annotated, Optional
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, WebSocket, WebSocketException, status
|
||||
from fastapi import APIRouter, BackgroundTasks, Body, Depends, HTTPException
|
||||
from fastapi.responses import StreamingResponse
|
||||
from langflow.api.utils import build_input_keys_response, format_elapsed_time
|
||||
from langflow.api.v1.schemas import BuildStatus, BuiltResponse, InitResponse, StreamData
|
||||
from langflow.graph.graph.base import Graph
|
||||
from langflow.services.auth.utils import get_current_active_user, get_current_user_for_websocket
|
||||
from langflow.services.cache.service import BaseCacheService
|
||||
from langflow.services.cache.utils import update_build_status
|
||||
from langflow.services.chat.service import ChatService
|
||||
from langflow.services.deps import get_cache_service, get_chat_service, get_session
|
||||
from loguru import logger
|
||||
from sqlmodel import Session
|
||||
|
||||
from langflow.api.utils import (
|
||||
build_and_cache_graph,
|
||||
format_elapsed_time,
|
||||
format_exception_message,
|
||||
)
|
||||
from langflow.api.v1.schemas import (
|
||||
InputValueRequest,
|
||||
ResultDataResponse,
|
||||
StreamData,
|
||||
VertexBuildResponse,
|
||||
VerticesOrderResponse,
|
||||
)
|
||||
from langflow.services.auth.utils import get_current_active_user
|
||||
from langflow.services.chat.service import ChatService
|
||||
from langflow.services.deps import get_chat_service, get_session, get_session_service
|
||||
from langflow.services.monitor.utils import log_vertex_build
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.graph.vertex.types import ChatVertex
|
||||
from langflow.services.session.service import SessionService
|
||||
|
||||
router = APIRouter(tags=["Chat"])
|
||||
|
||||
|
||||
@router.websocket("/chat/{client_id}")
|
||||
async def chat(
|
||||
client_id: str,
|
||||
websocket: WebSocket,
|
||||
db: Session = Depends(get_session),
|
||||
chat_service: "ChatService" = Depends(get_chat_service),
|
||||
):
|
||||
"""Websocket endpoint for chat."""
|
||||
try:
|
||||
user = await get_current_user_for_websocket(websocket, db)
|
||||
await websocket.accept()
|
||||
if not user:
|
||||
await websocket.close(code=status.WS_1008_POLICY_VIOLATION, reason="Unauthorized")
|
||||
elif not user.is_active:
|
||||
await websocket.close(code=status.WS_1008_POLICY_VIOLATION, reason="Unauthorized")
|
||||
|
||||
if client_id in chat_service.cache_service:
|
||||
await chat_service.handle_websocket(client_id, websocket)
|
||||
else:
|
||||
# We accept the connection but close it immediately
|
||||
# if the flow is not built yet
|
||||
message = "Please, build the flow before sending messages"
|
||||
await websocket.close(code=status.WS_1011_INTERNAL_ERROR, reason=message)
|
||||
except WebSocketException as exc:
|
||||
logger.error(f"Websocket exrror: {exc}")
|
||||
await websocket.close(code=status.WS_1011_INTERNAL_ERROR, reason=str(exc))
|
||||
except Exception as exc:
|
||||
logger.error(f"Error in chat websocket: {exc}")
|
||||
messsage = exc.detail if isinstance(exc, HTTPException) else str(exc)
|
||||
if "Could not validate credentials" in str(exc):
|
||||
await websocket.close(code=status.WS_1008_POLICY_VIOLATION, reason="Unauthorized")
|
||||
else:
|
||||
await websocket.close(code=status.WS_1011_INTERNAL_ERROR, reason=messsage)
|
||||
|
||||
|
||||
@router.post("/build/init/{flow_id}", response_model=InitResponse, status_code=201)
|
||||
async def init_build(
|
||||
graph_data: dict,
|
||||
flow_id: str,
|
||||
current_user=Depends(get_current_active_user),
|
||||
chat_service: "ChatService" = Depends(get_chat_service),
|
||||
cache_service: "BaseCacheService" = Depends(get_cache_service),
|
||||
):
|
||||
"""Initialize the build by storing graph data and returning a unique session ID."""
|
||||
try:
|
||||
if flow_id is None:
|
||||
raise ValueError("No ID provided")
|
||||
# Check if already building
|
||||
if (
|
||||
flow_id in cache_service
|
||||
and isinstance(cache_service[flow_id], dict)
|
||||
and cache_service[flow_id].get("status") == BuildStatus.IN_PROGRESS
|
||||
):
|
||||
return InitResponse(flowId=flow_id)
|
||||
|
||||
# Delete from cache if already exists
|
||||
if flow_id in chat_service.cache_service:
|
||||
chat_service.cache_service.delete(flow_id)
|
||||
logger.debug(f"Deleted flow {flow_id} from cache")
|
||||
cache_service[flow_id] = {
|
||||
"graph_data": graph_data,
|
||||
"status": BuildStatus.STARTED,
|
||||
"user_id": current_user.id,
|
||||
}
|
||||
|
||||
return InitResponse(flowId=flow_id)
|
||||
except Exception as exc:
|
||||
logger.error(f"Error initializing build: {exc}")
|
||||
return HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
@router.get("/build/{flow_id}/status", response_model=BuiltResponse)
|
||||
async def build_status(flow_id: str, cache_service: "BaseCacheService" = Depends(get_cache_service)):
|
||||
"""Check the flow_id is in the cache_service."""
|
||||
try:
|
||||
built = flow_id in cache_service and cache_service[flow_id]["status"] == BuildStatus.SUCCESS
|
||||
|
||||
return BuiltResponse(
|
||||
built=built,
|
||||
)
|
||||
|
||||
except Exception as exc:
|
||||
logger.error(f"Error checking build status: {exc}")
|
||||
return HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
@router.get("/build/stream/{flow_id}", response_class=StreamingResponse)
|
||||
async def stream_build(
|
||||
flow_id: str,
|
||||
chat_service: "ChatService" = Depends(get_chat_service),
|
||||
cache_service: "BaseCacheService" = Depends(get_cache_service),
|
||||
):
|
||||
"""Stream the build process based on stored flow data."""
|
||||
|
||||
async def event_stream(flow_id):
|
||||
final_response = {"end_of_stream": True}
|
||||
artifacts = {}
|
||||
flow_cache = cache_service[flow_id]
|
||||
flow_cache = flow_cache if isinstance(flow_cache, dict) else {}
|
||||
try:
|
||||
if flow_id not in cache_service:
|
||||
error_message = "Invalid session ID"
|
||||
yield str(StreamData(event="error", data={"error": error_message}))
|
||||
return
|
||||
|
||||
if flow_cache.get("status") == BuildStatus.IN_PROGRESS:
|
||||
error_message = "Already building"
|
||||
yield str(StreamData(event="error", data={"error": error_message}))
|
||||
return
|
||||
|
||||
graph_data = flow_cache.get("graph_data")
|
||||
|
||||
if not graph_data:
|
||||
error_message = "No data provided"
|
||||
yield str(StreamData(event="error", data={"error": error_message}))
|
||||
return
|
||||
|
||||
logger.debug("Building langchain object")
|
||||
|
||||
# Some error could happen when building the graph
|
||||
graph = Graph.from_payload(graph_data)
|
||||
|
||||
number_of_nodes = len(graph.vertices)
|
||||
update_build_status(cache_service, flow_id, BuildStatus.IN_PROGRESS)
|
||||
time_elapsed = ""
|
||||
try:
|
||||
user_id = flow_cache["user_id"]
|
||||
except KeyError:
|
||||
logger.debug("No user_id found in cache_service")
|
||||
user_id = None
|
||||
for i, vertex in enumerate(graph.generator_build(), 1):
|
||||
start_time = time.perf_counter()
|
||||
try:
|
||||
log_dict = {
|
||||
"log": f"Building node {vertex.vertex_type}",
|
||||
}
|
||||
yield str(StreamData(event="log", data=log_dict))
|
||||
if vertex.is_task:
|
||||
vertex = await try_running_celery_task(vertex, user_id)
|
||||
else:
|
||||
await vertex.build(user_id=user_id)
|
||||
time_elapsed = format_elapsed_time(time.perf_counter() - start_time)
|
||||
params = vertex._built_object_repr()
|
||||
valid = True
|
||||
|
||||
logger.debug(f"Building node {str(vertex.vertex_type)}")
|
||||
logger.debug(f"Output: {params[:100]}{'...' if len(params) > 100 else ''}")
|
||||
if vertex.artifacts:
|
||||
# The artifacts will be prompt variables
|
||||
# passed to build_input_keys_response
|
||||
# to set the input_keys values
|
||||
artifacts.update(vertex.artifacts)
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
params = str(exc)
|
||||
valid = False
|
||||
time_elapsed = format_elapsed_time(time.perf_counter() - start_time)
|
||||
update_build_status(cache_service, flow_id, BuildStatus.FAILURE)
|
||||
|
||||
vertex_id = vertex.parent_node_id if vertex.parent_is_top_level else vertex.id
|
||||
if vertex_id in graph.top_level_vertices:
|
||||
response = {
|
||||
"valid": valid,
|
||||
"params": params,
|
||||
"id": vertex_id,
|
||||
"progress": round(i / number_of_nodes, 2),
|
||||
"duration": time_elapsed,
|
||||
}
|
||||
|
||||
yield str(StreamData(event="message", data=response))
|
||||
|
||||
langchain_object = await graph.build()
|
||||
# Now we need to check the input_keys to send them to the client
|
||||
if hasattr(langchain_object, "input_keys"):
|
||||
input_keys_response = build_input_keys_response(langchain_object, artifacts)
|
||||
else:
|
||||
input_keys_response = {
|
||||
"input_keys": None,
|
||||
"memory_keys": [],
|
||||
"handle_keys": [],
|
||||
}
|
||||
yield str(StreamData(event="message", data=input_keys_response))
|
||||
chat_service.set_cache(flow_id, langchain_object)
|
||||
# We need to reset the chat history
|
||||
chat_service.chat_history.empty_history(flow_id)
|
||||
update_build_status(cache_service, flow_id, BuildStatus.SUCCESS)
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
logger.error("Error while building the flow: %s", exc)
|
||||
|
||||
update_build_status(cache_service, flow_id, BuildStatus.FAILURE)
|
||||
yield str(StreamData(event="error", data={"error": str(exc)}))
|
||||
finally:
|
||||
yield str(StreamData(event="message", data=final_response))
|
||||
|
||||
try:
|
||||
return StreamingResponse(event_stream(flow_id), media_type="text/event-stream")
|
||||
except Exception as exc:
|
||||
logger.error(f"Error streaming build: {exc}")
|
||||
raise HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
async def try_running_celery_task(vertex, user_id):
|
||||
# Try running the task in celery
|
||||
# and set the task_id to the local vertex
|
||||
|
|
@ -232,3 +44,219 @@ async def try_running_celery_task(vertex, user_id):
|
|||
vertex.task_id = None
|
||||
await vertex.build(user_id=user_id)
|
||||
return vertex
|
||||
|
||||
|
||||
@router.get("/build/{flow_id}/vertices", response_model=VerticesOrderResponse)
|
||||
async def get_vertices(
|
||||
flow_id: str,
|
||||
stop_component_id: Optional[str] = None,
|
||||
start_component_id: Optional[str] = None,
|
||||
chat_service: "ChatService" = Depends(get_chat_service),
|
||||
session=Depends(get_session),
|
||||
):
|
||||
"""Check the flow_id is in the flow_data_store."""
|
||||
try:
|
||||
# First, we need to check if the flow_id is in the cache
|
||||
graph = None
|
||||
if cache := await chat_service.get_cache(flow_id):
|
||||
graph = cache.get("result")
|
||||
graph = await build_and_cache_graph(flow_id, session, chat_service, graph)
|
||||
if stop_component_id or start_component_id:
|
||||
try:
|
||||
vertices = graph.sort_vertices(stop_component_id, start_component_id)
|
||||
except Exception as exc:
|
||||
logger.error(exc)
|
||||
vertices = graph.sort_vertices()
|
||||
else:
|
||||
vertices = graph.sort_vertices()
|
||||
|
||||
# Now vertices is a list of lists
|
||||
# We need to get the id of each vertex
|
||||
# and return the same structure but only with the ids
|
||||
run_id = uuid.uuid4()
|
||||
graph.set_run_id(run_id)
|
||||
return VerticesOrderResponse(ids=vertices, run_id=run_id)
|
||||
|
||||
except Exception as exc:
|
||||
logger.error(f"Error checking build status: {exc}")
|
||||
logger.exception(exc)
|
||||
raise HTTPException(status_code=500, detail=str(exc)) from exc
|
||||
|
||||
|
||||
@router.post("/build/{flow_id}/vertices/{vertex_id}")
|
||||
async def build_vertex(
|
||||
flow_id: str,
|
||||
vertex_id: str,
|
||||
background_tasks: BackgroundTasks,
|
||||
inputs: Annotated[Optional[InputValueRequest], Body(embed=True)] = None,
|
||||
chat_service: "ChatService" = Depends(get_chat_service),
|
||||
current_user=Depends(get_current_active_user),
|
||||
):
|
||||
"""Build a vertex instead of the entire graph."""
|
||||
|
||||
start_time = time.perf_counter()
|
||||
next_vertices_ids = []
|
||||
try:
|
||||
start_time = time.perf_counter()
|
||||
cache = await chat_service.get_cache(flow_id)
|
||||
if not cache:
|
||||
# If there's no cache
|
||||
logger.warning(f"No cache found for {flow_id}. Building graph starting at {vertex_id}")
|
||||
graph = await build_and_cache_graph(flow_id=flow_id, session=next(get_session()), chat_service=chat_service)
|
||||
else:
|
||||
graph = cache.get("result")
|
||||
result_data_response = ResultDataResponse(results={})
|
||||
duration = ""
|
||||
|
||||
vertex = graph.get_vertex(vertex_id)
|
||||
try:
|
||||
if not vertex.frozen or not vertex._built:
|
||||
inputs_dict = inputs.model_dump() if inputs else {}
|
||||
await vertex.build(user_id=current_user.id, inputs=inputs_dict)
|
||||
|
||||
if vertex.result is not None:
|
||||
params = vertex._built_object_repr()
|
||||
valid = True
|
||||
result_dict = vertex.result
|
||||
artifacts = vertex.artifacts
|
||||
else:
|
||||
raise ValueError(f"No result found for vertex {vertex_id}")
|
||||
async with chat_service._cache_locks[flow_id] as lock:
|
||||
graph.remove_from_predecessors(vertex_id)
|
||||
next_vertices_ids = vertex.successors_ids
|
||||
next_vertices_ids = [v for v in next_vertices_ids if graph.should_run_vertex(v)]
|
||||
await chat_service.set_cache(flow_id=flow_id, data=graph, lock=lock)
|
||||
|
||||
result_data_response = ResultDataResponse(**result_dict.model_dump())
|
||||
|
||||
except Exception as exc:
|
||||
logger.exception(f"Error building vertex: {exc}")
|
||||
params = format_exception_message(exc)
|
||||
valid = False
|
||||
result_data_response = ResultDataResponse(results={})
|
||||
artifacts = {}
|
||||
# If there's an error building the vertex
|
||||
# we need to clear the cache
|
||||
await chat_service.clear_cache(flow_id)
|
||||
|
||||
# Log the vertex build
|
||||
if not vertex.will_stream:
|
||||
background_tasks.add_task(
|
||||
log_vertex_build,
|
||||
flow_id=flow_id,
|
||||
vertex_id=vertex_id,
|
||||
valid=valid,
|
||||
params=params,
|
||||
data=result_data_response,
|
||||
artifacts=artifacts,
|
||||
)
|
||||
|
||||
timedelta = time.perf_counter() - start_time
|
||||
duration = format_elapsed_time(timedelta)
|
||||
result_data_response.duration = duration
|
||||
result_data_response.timedelta = timedelta
|
||||
vertex.add_build_time(timedelta)
|
||||
inactivated_vertices = None
|
||||
inactivated_vertices = list(graph.inactivated_vertices)
|
||||
graph.reset_inactivated_vertices()
|
||||
graph.reset_activated_vertices()
|
||||
await chat_service.set_cache(flow_id, graph)
|
||||
|
||||
# graph.stop_vertex tells us if the user asked
|
||||
# to stop the build of the graph at a certain vertex
|
||||
# if it is in next_vertices_ids, we need to remove other
|
||||
# vertices from next_vertices_ids
|
||||
if graph.stop_vertex and graph.stop_vertex in next_vertices_ids:
|
||||
next_vertices_ids = [graph.stop_vertex]
|
||||
|
||||
build_response = VertexBuildResponse(
|
||||
inactivated_vertices=inactivated_vertices,
|
||||
next_vertices_ids=next_vertices_ids,
|
||||
valid=valid,
|
||||
params=params,
|
||||
id=vertex.id,
|
||||
data=result_data_response,
|
||||
)
|
||||
return build_response
|
||||
except Exception as exc:
|
||||
logger.error(f"Error building vertex: {exc}")
|
||||
logger.exception(exc)
|
||||
raise HTTPException(status_code=500, detail=str(exc)) from exc
|
||||
|
||||
|
||||
# Now onto an endpoint that is an SSE endpoint
|
||||
# it will receive a component_id and a flow_id
|
||||
#
|
||||
@router.get("/build/{flow_id}/{vertex_id}/stream", response_class=StreamingResponse)
|
||||
async def build_vertex_stream(
|
||||
flow_id: str,
|
||||
vertex_id: str,
|
||||
session_id: Optional[str] = None,
|
||||
chat_service: "ChatService" = Depends(get_chat_service),
|
||||
session_service: "SessionService" = Depends(get_session_service),
|
||||
):
|
||||
"""Build a vertex instead of the entire graph."""
|
||||
try:
|
||||
|
||||
async def stream_vertex():
|
||||
try:
|
||||
if not session_id:
|
||||
cache = chat_service.get_cache(flow_id)
|
||||
if not cache:
|
||||
# If there's no cache
|
||||
raise ValueError(f"No cache found for {flow_id}.")
|
||||
else:
|
||||
graph = cache.get("result")
|
||||
else:
|
||||
session_data = await session_service.load_session(session_id, flow_id=flow_id)
|
||||
graph, artifacts = session_data if session_data else (None, None)
|
||||
if not graph:
|
||||
raise ValueError(f"No graph found for {flow_id}.")
|
||||
|
||||
vertex: "ChatVertex" = graph.get_vertex(vertex_id)
|
||||
if not hasattr(vertex, "stream"):
|
||||
raise ValueError(f"Vertex {vertex_id} does not support streaming")
|
||||
if isinstance(vertex._built_result, str) and vertex._built_result:
|
||||
stream_data = StreamData(
|
||||
event="message",
|
||||
data={"message": f"Streaming vertex {vertex_id}"},
|
||||
)
|
||||
yield str(stream_data)
|
||||
stream_data = StreamData(
|
||||
event="message",
|
||||
data={"chunk": vertex._built_result},
|
||||
)
|
||||
yield str(stream_data)
|
||||
|
||||
elif not vertex.frozen or not vertex._built:
|
||||
logger.debug(f"Streaming vertex {vertex_id}")
|
||||
stream_data = StreamData(
|
||||
event="message",
|
||||
data={"message": f"Streaming vertex {vertex_id}"},
|
||||
)
|
||||
yield str(stream_data)
|
||||
async for chunk in vertex.stream():
|
||||
stream_data = StreamData(
|
||||
event="message",
|
||||
data={"chunk": chunk},
|
||||
)
|
||||
yield str(stream_data)
|
||||
elif vertex.result is not None:
|
||||
stream_data = StreamData(
|
||||
event="message",
|
||||
data={"chunk": vertex._built_result},
|
||||
)
|
||||
yield str(stream_data)
|
||||
else:
|
||||
raise ValueError(f"No result found for vertex {vertex_id}")
|
||||
|
||||
except Exception as exc:
|
||||
logger.error(f"Error building vertex: {exc}")
|
||||
yield str(StreamData(event="error", data={"error": str(exc)}))
|
||||
finally:
|
||||
logger.debug("Closing stream")
|
||||
yield str(StreamData(event="close", data={"message": "Stream closed"}))
|
||||
|
||||
return StreamingResponse(stream_vertex(), media_type="text/event-stream")
|
||||
except Exception as exc:
|
||||
raise HTTPException(status_code=500, detail="Error building vertex") from exc
|
||||
|
|
|
|||
|
|
@ -2,6 +2,8 @@ from datetime import datetime
|
|||
from uuid import UUID
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from sqlmodel import Session, select
|
||||
|
||||
from langflow.services.auth import utils as auth_utils
|
||||
from langflow.services.auth.utils import get_current_active_user
|
||||
from langflow.services.database.models.credential import (
|
||||
|
|
@ -12,7 +14,6 @@ from langflow.services.database.models.credential import (
|
|||
)
|
||||
from langflow.services.database.models.user.model import User
|
||||
from langflow.services.deps import get_session, get_settings_service
|
||||
from sqlmodel import Session, select
|
||||
|
||||
router = APIRouter(prefix="/credentials", tags=["Credentials"])
|
||||
|
||||
|
|
|
|||
|
|
@ -1,114 +1,39 @@
|
|||
from http import HTTPStatus
|
||||
from typing import Annotated, Any, List, Optional, Union
|
||||
from typing import Annotated, List, Optional, Union
|
||||
|
||||
import sqlalchemy as sa
|
||||
from fastapi import APIRouter, Body, Depends, HTTPException, UploadFile, status
|
||||
from loguru import logger
|
||||
from sqlmodel import Session, select
|
||||
|
||||
from langflow.api.utils import update_frontend_node_with_template_values
|
||||
from langflow.api.v1.schemas import (
|
||||
CustomComponentCode,
|
||||
PreloadResponse,
|
||||
CustomComponentRequest,
|
||||
InputValueRequest,
|
||||
ProcessResponse,
|
||||
TaskResponse,
|
||||
RunResponse,
|
||||
TaskStatusResponse,
|
||||
Tweaks,
|
||||
UpdateCustomComponentRequest,
|
||||
UploadFileResponse,
|
||||
)
|
||||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from langflow.interface.custom.directory_reader import DirectoryReader
|
||||
from langflow.interface.custom.utils import build_custom_component_template
|
||||
from langflow.processing.process import build_graph_and_generate_result, process_graph_cached, process_tweaks
|
||||
from langflow.processing.process import process_tweaks, run_graph
|
||||
from langflow.services.auth.utils import api_key_security, get_current_active_user
|
||||
from langflow.services.cache.utils import save_uploaded_file
|
||||
from langflow.services.database.models.flow import Flow
|
||||
from langflow.services.database.models.user.model import User
|
||||
from langflow.services.deps import get_session, get_session_service, get_settings_service, get_task_service
|
||||
from langflow.services.session.service import SessionService
|
||||
from loguru import logger
|
||||
from sqlmodel import select
|
||||
|
||||
try:
|
||||
from langflow.worker import process_graph_cached_task
|
||||
except ImportError:
|
||||
|
||||
def process_graph_cached_task(*args, **kwargs):
|
||||
raise NotImplementedError("Celery is not installed")
|
||||
|
||||
|
||||
from langflow.services.task.service import TaskService
|
||||
from sqlmodel import Session
|
||||
|
||||
# build router
|
||||
router = APIRouter(tags=["Base"])
|
||||
|
||||
|
||||
async def process_graph_data(
|
||||
graph_data: dict,
|
||||
inputs: Optional[Union[List[dict], dict]] = None,
|
||||
tweaks: Optional[dict] = None,
|
||||
clear_cache: bool = False,
|
||||
session_id: Optional[str] = None,
|
||||
task_service: "TaskService" = Depends(get_task_service),
|
||||
sync: bool = True,
|
||||
):
|
||||
task_result: Any = None
|
||||
task_status = None
|
||||
if tweaks:
|
||||
try:
|
||||
graph_data = process_tweaks(graph_data, tweaks)
|
||||
except Exception as exc:
|
||||
logger.error(f"Error processing tweaks: {exc}")
|
||||
if sync:
|
||||
result = await process_graph_cached(
|
||||
graph_data,
|
||||
inputs,
|
||||
clear_cache,
|
||||
session_id,
|
||||
)
|
||||
task_id = str(id(result))
|
||||
if isinstance(result, dict) and "result" in result:
|
||||
task_result = result["result"]
|
||||
session_id = result["session_id"]
|
||||
elif hasattr(result, "result") and hasattr(result, "session_id"):
|
||||
task_result = result.result
|
||||
|
||||
session_id = result.session_id
|
||||
else:
|
||||
task_result = result
|
||||
else:
|
||||
logger.warning(
|
||||
"This is an experimental feature and may not work as expected."
|
||||
"Please report any issues to our GitHub repository."
|
||||
)
|
||||
if session_id is None:
|
||||
# Generate a session ID
|
||||
session_id = get_session_service().generate_key(session_id=session_id, data_graph=graph_data)
|
||||
task_id, task = await task_service.launch_task(
|
||||
process_graph_cached_task if task_service.use_celery else process_graph_cached,
|
||||
graph_data,
|
||||
inputs,
|
||||
clear_cache,
|
||||
session_id,
|
||||
)
|
||||
task_status = task.status
|
||||
if task.status == "FAILURE":
|
||||
logger.error(f"Task {task_id} failed: {task.traceback}")
|
||||
task_result = str(task._exception)
|
||||
else:
|
||||
task_result = task.result
|
||||
|
||||
if task_id:
|
||||
task_response = TaskResponse(id=task_id, href=f"api/v1/task/{task_id}")
|
||||
else:
|
||||
task_response = None
|
||||
|
||||
return ProcessResponse(
|
||||
result=task_result,
|
||||
status=task_status,
|
||||
task=task_response,
|
||||
session_id=session_id,
|
||||
backend=task_service.backend_name,
|
||||
)
|
||||
|
||||
|
||||
@router.get("/all", dependencies=[Depends(get_current_active_user)])
|
||||
def get_all(
|
||||
settings_service=Depends(get_settings_service),
|
||||
|
|
@ -117,65 +42,86 @@ def get_all(
|
|||
|
||||
logger.debug("Building langchain types dict")
|
||||
try:
|
||||
return get_all_types_dict(settings_service)
|
||||
except Exception as exc:
|
||||
raise HTTPException(status_code=500, detail=str(exc)) from exc
|
||||
|
||||
|
||||
@router.post("/process/json", response_model=ProcessResponse)
|
||||
async def process_json(
|
||||
session: Annotated[Session, Depends(get_session)],
|
||||
data: dict,
|
||||
inputs: Optional[dict] = None,
|
||||
tweaks: Optional[dict] = None,
|
||||
clear_cache: Annotated[bool, Body(embed=True)] = False, # noqa: F821
|
||||
session_id: Annotated[Union[None, str], Body(embed=True)] = None, # noqa: F821
|
||||
task_service: "TaskService" = Depends(get_task_service),
|
||||
sync: Annotated[bool, Body(embed=True)] = True, # noqa: F821
|
||||
):
|
||||
try:
|
||||
return await process_graph_data(
|
||||
graph_data=data,
|
||||
inputs=inputs,
|
||||
tweaks=tweaks,
|
||||
clear_cache=clear_cache,
|
||||
session_id=session_id,
|
||||
task_service=task_service,
|
||||
sync=sync,
|
||||
)
|
||||
all_types_dict = get_all_types_dict(settings_service.settings.COMPONENTS_PATH)
|
||||
return all_types_dict
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
raise HTTPException(status_code=500, detail=str(exc)) from exc
|
||||
|
||||
|
||||
# Endpoint to preload a graph
|
||||
@router.post("/process/preload/{flow_id}", response_model=PreloadResponse)
|
||||
async def preload_flow(
|
||||
@router.post("/run/{flow_id}", response_model=RunResponse, response_model_exclude_none=True)
|
||||
async def run_flow_with_caching(
|
||||
session: Annotated[Session, Depends(get_session)],
|
||||
flow_id: str,
|
||||
session_id: Optional[str] = None,
|
||||
session_service: SessionService = Depends(get_session_service),
|
||||
inputs: Optional[List[InputValueRequest]] = [],
|
||||
outputs: Optional[List[str]] = [],
|
||||
tweaks: Annotated[Optional[Tweaks], Body(embed=True)] = None, # noqa: F821
|
||||
stream: Annotated[bool, Body(embed=True)] = False, # noqa: F821
|
||||
session_id: Annotated[Union[None, str], Body(embed=True)] = None, # noqa: F821
|
||||
api_key_user: User = Depends(api_key_security),
|
||||
clear_session: Annotated[bool, Body(embed=True)] = False, # noqa: F821
|
||||
session_service: SessionService = Depends(get_session_service),
|
||||
):
|
||||
"""
|
||||
Executes a specified flow by ID with optional input values, output selection, tweaks, and streaming capability.
|
||||
This endpoint supports running flows with caching to enhance performance and efficiency.
|
||||
|
||||
### Parameters:
|
||||
- `flow_id` (str): The unique identifier of the flow to be executed.
|
||||
- `inputs` (List[InputValueRequest], optional): A list of inputs specifying the input values and components for the flow. Each input can target specific components and provide custom values.
|
||||
- `outputs` (List[str], optional): A list of output names to retrieve from the executed flow. If not provided, all outputs are returned.
|
||||
- `tweaks` (Optional[Tweaks], optional): A dictionary of tweaks to customize the flow execution. The tweaks can be used to modify the flow's parameters and components. Tweaks can be overridden by the input values.
|
||||
- `stream` (bool, optional): Specifies whether the results should be streamed. Defaults to False.
|
||||
- `session_id` (Union[None, str], optional): An optional session ID to utilize existing session data for the flow execution.
|
||||
- `api_key_user` (User): The user associated with the current API key. Automatically resolved from the API key.
|
||||
- `session_service` (SessionService): The session service object for managing flow sessions.
|
||||
|
||||
### Returns:
|
||||
A `RunResponse` object containing the selected outputs (or all if not specified) of the executed flow and the session ID. The structure of the response accommodates multiple inputs, providing a nested list of outputs for each input.
|
||||
|
||||
### Raises:
|
||||
HTTPException: Indicates issues with finding the specified flow, invalid input formats, or internal errors during flow execution.
|
||||
|
||||
### Example usage:
|
||||
```json
|
||||
POST /run/{flow_id}
|
||||
Payload:
|
||||
{
|
||||
"inputs": [
|
||||
{"components": ["component1"], "input_value": "value1"},
|
||||
{"components": ["component3"], "input_value": "value2"}
|
||||
],
|
||||
"outputs": ["Component Name", "component_id"],
|
||||
"tweaks": {"parameter_name": "value", "Component Name": {"parameter_name": "value"}, "component_id": {"parameter_name": "value"}}
|
||||
"stream": false
|
||||
}
|
||||
```
|
||||
|
||||
This endpoint facilitates complex flow executions with customized inputs, outputs, and configurations, catering to diverse application requirements.
|
||||
"""
|
||||
try:
|
||||
# Get the flow that matches the flow_id and belongs to the user
|
||||
# flow = session.query(Flow).filter(Flow.id == flow_id).filter(Flow.user_id == api_key_user.id).first()
|
||||
if clear_session:
|
||||
session_service.clear_session(session_id)
|
||||
# Check if the session exists
|
||||
session_data = await session_service.load_session(session_id)
|
||||
# Session data is a tuple of (graph, artifacts)
|
||||
# or (None, None) if the session is empty
|
||||
if isinstance(session_data, tuple):
|
||||
graph, artifacts = session_data
|
||||
is_clear = graph is None and artifacts is None
|
||||
else:
|
||||
is_clear = session_data is None
|
||||
return PreloadResponse(session_id=session_id, is_clear=is_clear)
|
||||
if outputs is None:
|
||||
outputs = []
|
||||
|
||||
if session_id:
|
||||
session_data = await session_service.load_session(session_id, flow_id=flow_id)
|
||||
graph, artifacts = session_data if session_data else (None, None)
|
||||
task_result: List[RunOutputs] = []
|
||||
if not graph:
|
||||
raise ValueError("Graph not found in the session")
|
||||
task_result, session_id = await run_graph(
|
||||
graph=graph,
|
||||
flow_id=flow_id,
|
||||
session_id=session_id,
|
||||
inputs=inputs,
|
||||
outputs=outputs,
|
||||
artifacts=artifacts,
|
||||
session_service=session_service,
|
||||
stream=stream,
|
||||
)
|
||||
|
||||
else:
|
||||
if session_id is None:
|
||||
session_id = flow_id
|
||||
# Get the flow that matches the flow_id and belongs to the user
|
||||
# flow = session.query(Flow).filter(Flow.id == flow_id).filter(Flow.user_id == api_key_user.id).first()
|
||||
flow = session.exec(select(Flow).where(Flow.id == flow_id).where(Flow.user_id == api_key_user.id)).first()
|
||||
if flow is None:
|
||||
raise ValueError(f"Flow {flow_id} not found")
|
||||
|
|
@ -183,18 +129,29 @@ async def preload_flow(
|
|||
if flow.data is None:
|
||||
raise ValueError(f"Flow {flow_id} has no data")
|
||||
graph_data = flow.data
|
||||
session_service.clear_session(session_id)
|
||||
# Load the graph using SessionService
|
||||
session_data = await session_service.load_session(session_id, graph_data)
|
||||
graph, artifacts = session_data if session_data else (None, None)
|
||||
if not graph:
|
||||
raise ValueError("Graph not found in the session")
|
||||
_ = await graph.build()
|
||||
session_service.update_session(session_id, (graph, artifacts))
|
||||
return PreloadResponse(session_id=session_id)
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
raise HTTPException(status_code=500, detail=str(exc)) from exc
|
||||
graph_data = process_tweaks(graph_data, tweaks or {})
|
||||
task_result, session_id = await run_graph(
|
||||
graph=graph_data,
|
||||
flow_id=flow_id,
|
||||
session_id=session_id,
|
||||
inputs=inputs,
|
||||
outputs=outputs,
|
||||
artifacts={},
|
||||
session_service=session_service,
|
||||
stream=stream,
|
||||
)
|
||||
|
||||
return RunResponse(outputs=task_result, session_id=session_id)
|
||||
except sa.exc.StatementError as exc:
|
||||
# StatementError('(builtins.ValueError) badly formed hexadecimal UUID string')
|
||||
if "badly formed hexadecimal UUID string" in str(exc):
|
||||
# This means the Flow ID is not a valid UUID which means it can't find the flow
|
||||
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
|
||||
except ValueError as exc:
|
||||
if f"Flow {flow_id} not found" in str(exc):
|
||||
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
|
||||
else:
|
||||
raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(exc)) from exc
|
||||
|
||||
|
||||
@router.post(
|
||||
|
|
@ -221,84 +178,15 @@ async def process(
|
|||
"""
|
||||
Endpoint to process an input with a given flow_id.
|
||||
"""
|
||||
|
||||
try:
|
||||
if session_id:
|
||||
session_data = await session_service.load_session(session_id)
|
||||
graph, artifacts = session_data if session_data else (None, None)
|
||||
task_result: Any = None
|
||||
task_status = None
|
||||
task_id = None
|
||||
if not graph:
|
||||
raise ValueError("Graph not found in the session")
|
||||
result = await build_graph_and_generate_result(
|
||||
graph=graph,
|
||||
inputs=inputs,
|
||||
artifacts=artifacts,
|
||||
session_id=session_id,
|
||||
session_service=session_service,
|
||||
)
|
||||
task_id = str(id(result))
|
||||
if isinstance(result, dict) and "result" in result:
|
||||
task_result = result["result"]
|
||||
session_id = result["session_id"]
|
||||
elif hasattr(result, "result") and hasattr(result, "session_id"):
|
||||
task_result = result.result
|
||||
|
||||
session_id = result.session_id
|
||||
else:
|
||||
task_result = result
|
||||
if task_id:
|
||||
task_response = TaskResponse(id=task_id, href=f"api/v1/task/{task_id}")
|
||||
else:
|
||||
task_response = None
|
||||
return ProcessResponse(
|
||||
result=task_result,
|
||||
status=task_status,
|
||||
task=task_response,
|
||||
session_id=session_id,
|
||||
backend=task_service.backend_name,
|
||||
)
|
||||
|
||||
else:
|
||||
if api_key_user is None:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||||
detail="Invalid API Key",
|
||||
)
|
||||
|
||||
# Get the flow that matches the flow_id and belongs to the user
|
||||
# flow = session.query(Flow).filter(Flow.id == flow_id).filter(Flow.user_id == api_key_user.id).first()
|
||||
flow = session.exec(select(Flow).where(Flow.id == flow_id).where(Flow.user_id == api_key_user.id)).first()
|
||||
if flow is None:
|
||||
raise ValueError(f"Flow {flow_id} not found")
|
||||
|
||||
if flow.data is None:
|
||||
raise ValueError(f"Flow {flow_id} has no data")
|
||||
graph_data = flow.data
|
||||
return await process_graph_data(
|
||||
graph_data=graph_data,
|
||||
inputs=inputs,
|
||||
tweaks=tweaks,
|
||||
clear_cache=clear_cache,
|
||||
session_id=session_id,
|
||||
task_service=task_service,
|
||||
sync=sync,
|
||||
)
|
||||
except sa.exc.StatementError as exc:
|
||||
# StatementError('(builtins.ValueError) badly formed hexadecimal UUID string')
|
||||
if "badly formed hexadecimal UUID string" in str(exc):
|
||||
# This means the Flow ID is not a valid UUID which means it can't find the flow
|
||||
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
|
||||
except ValueError as exc:
|
||||
if f"Flow {flow_id} not found" in str(exc):
|
||||
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
|
||||
else:
|
||||
raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(exc)) from exc
|
||||
except Exception as e:
|
||||
# Log stack trace
|
||||
logger.exception(e)
|
||||
raise HTTPException(status_code=500, detail=str(e)) from e
|
||||
# Raise a depreciation warning
|
||||
logger.warning(
|
||||
"The /process endpoint is deprecated and will be removed in a future version. " "Please use /run instead."
|
||||
)
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_400_BAD_REQUEST,
|
||||
detail="The /process endpoint is deprecated and will be removed in a future version. "
|
||||
"Please use /run instead.",
|
||||
)
|
||||
|
||||
|
||||
@router.get("/task/{task_id}", response_model=TaskStatusResponse)
|
||||
|
|
@ -331,8 +219,10 @@ async def get_task_status(task_id: str):
|
|||
response_model=UploadFileResponse,
|
||||
status_code=HTTPStatus.CREATED,
|
||||
)
|
||||
async def create_upload_file(file: UploadFile, flow_id: str):
|
||||
# Cache file
|
||||
async def create_upload_file(
|
||||
file: UploadFile,
|
||||
flow_id: str,
|
||||
):
|
||||
try:
|
||||
file_path = save_uploaded_file(file, folder_name=flow_id)
|
||||
|
||||
|
|
@ -355,12 +245,12 @@ def get_version():
|
|||
|
||||
@router.post("/custom_component", status_code=HTTPStatus.OK)
|
||||
async def custom_component(
|
||||
raw_code: CustomComponentCode,
|
||||
raw_code: CustomComponentRequest,
|
||||
user: User = Depends(get_current_active_user),
|
||||
):
|
||||
component = CustomComponent(code=raw_code.code)
|
||||
|
||||
built_frontend_node = build_custom_component_template(component, user_id=user.id)
|
||||
built_frontend_node, _ = build_custom_component_template(component, user_id=user.id)
|
||||
|
||||
built_frontend_node = update_frontend_node_with_template_values(built_frontend_node, raw_code.frontend_node)
|
||||
return built_frontend_node
|
||||
|
|
@ -377,18 +267,46 @@ async def reload_custom_component(path: str, user: User = Depends(get_current_ac
|
|||
raise ValueError(content)
|
||||
|
||||
extractor = CustomComponent(code=content)
|
||||
return build_custom_component_template(extractor, user_id=user.id)
|
||||
frontend_node, _ = build_custom_component_template(extractor, user_id=user.id)
|
||||
return frontend_node
|
||||
except Exception as exc:
|
||||
raise HTTPException(status_code=400, detail=str(exc))
|
||||
|
||||
|
||||
@router.post("/custom_component/update", status_code=HTTPStatus.OK)
|
||||
async def custom_component_update(
|
||||
raw_code: CustomComponentCode,
|
||||
code_request: UpdateCustomComponentRequest,
|
||||
user: User = Depends(get_current_active_user),
|
||||
):
|
||||
component = CustomComponent(code=raw_code.code)
|
||||
"""
|
||||
Update a custom component with the provided code request.
|
||||
|
||||
component_node = build_custom_component_template(component, user_id=user.id, update_field=raw_code.field)
|
||||
# Update the field
|
||||
return component_node
|
||||
This endpoint generates the CustomComponentFrontendNode normally but then runs the `update_build_config` method
|
||||
on the latest version of the template. This ensures that every time it runs, it has the latest version of the template.
|
||||
|
||||
Args:
|
||||
code_request (CustomComponentRequest): The code request containing the updated code for the custom component.
|
||||
user (User, optional): The user making the request. Defaults to the current active user.
|
||||
|
||||
Returns:
|
||||
dict: The updated custom component node.
|
||||
|
||||
"""
|
||||
try:
|
||||
component = CustomComponent(code=code_request.code)
|
||||
|
||||
component_node, cc_instance = build_custom_component_template(
|
||||
component,
|
||||
user_id=user.id,
|
||||
)
|
||||
|
||||
updated_build_config = cc_instance.update_build_config(
|
||||
build_config=code_request.get_template(),
|
||||
field_value=code_request.field_value,
|
||||
field_name=code_request.field,
|
||||
)
|
||||
component_node["template"] = updated_build_config
|
||||
|
||||
return component_node
|
||||
except Exception as exc:
|
||||
raise HTTPException(status_code=400, detail=str(exc)) from exc
|
||||
|
|
|
|||
114
src/backend/langflow/api/v1/files.py
Normal file
114
src/backend/langflow/api/v1/files.py
Normal file
|
|
@ -0,0 +1,114 @@
|
|||
import hashlib
|
||||
from http import HTTPStatus
|
||||
from io import BytesIO
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, UploadFile
|
||||
from fastapi.responses import StreamingResponse
|
||||
from langflow.api.v1.schemas import UploadFileResponse
|
||||
from langflow.services.auth.utils import get_current_active_user
|
||||
from langflow.services.database.models.flow import Flow
|
||||
from langflow.services.deps import get_session, get_storage_service
|
||||
from langflow.services.storage.service import StorageService
|
||||
from langflow.services.storage.utils import build_content_type_from_extension
|
||||
|
||||
router = APIRouter(tags=["Files"], prefix="/files")
|
||||
|
||||
|
||||
# Create dep that gets the flow_id from the request
|
||||
# then finds it in the database and returns it while
|
||||
# using the current user as the owner
|
||||
def get_flow_id(
|
||||
flow_id: str,
|
||||
current_user=Depends(get_current_active_user),
|
||||
session=Depends(get_session),
|
||||
):
|
||||
# AttributeError: 'SelectOfScalar' object has no attribute 'first'
|
||||
flow = session.get(Flow, flow_id)
|
||||
if not flow:
|
||||
raise HTTPException(status_code=404, detail="Flow not found")
|
||||
if flow.user_id != current_user.id:
|
||||
raise HTTPException(status_code=403, detail="You don't have access to this flow")
|
||||
return flow_id
|
||||
|
||||
|
||||
@router.post("/upload/{flow_id}", status_code=HTTPStatus.CREATED)
|
||||
async def upload_file(
|
||||
file: UploadFile,
|
||||
flow_id: str = Depends(get_flow_id),
|
||||
storage_service: StorageService = Depends(get_storage_service),
|
||||
):
|
||||
try:
|
||||
file_content = await file.read()
|
||||
file_name = file.filename or hashlib.sha256(file_content).hexdigest()
|
||||
folder = flow_id
|
||||
await storage_service.save_file(flow_id=folder, file_name=file_name, data=file_content)
|
||||
return UploadFileResponse(flowId=flow_id, file_path=f"{folder}/{file_name}")
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.get("/download/{flow_id}/{file_name}")
|
||||
async def download_file(file_name: str, flow_id: str, storage_service: StorageService = Depends(get_storage_service)):
|
||||
try:
|
||||
extension = file_name.split(".")[-1]
|
||||
|
||||
if not extension:
|
||||
raise HTTPException(status_code=500, detail=f"Extension not found for file {file_name}")
|
||||
|
||||
content_type = build_content_type_from_extension(extension)
|
||||
|
||||
if not content_type:
|
||||
raise HTTPException(status_code=500, detail=f"Content type not found for extension {extension}")
|
||||
|
||||
file_content = await storage_service.get_file(flow_id=flow_id, file_name=file_name)
|
||||
headers = {
|
||||
"Content-Disposition": f"attachment; filename={file_name} filename*=UTF-8''{file_name}",
|
||||
"Content-Type": "application/octet-stream",
|
||||
"Content-Length": str(len(file_content)),
|
||||
}
|
||||
return StreamingResponse(BytesIO(file_content), media_type=content_type, headers=headers)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.get("/images/{flow_id}/{file_name}")
|
||||
async def download_image(file_name: str, flow_id: str, storage_service: StorageService = Depends(get_storage_service)):
|
||||
try:
|
||||
extension = file_name.split(".")[-1]
|
||||
|
||||
if not extension:
|
||||
raise HTTPException(status_code=500, detail=f"Extension not found for file {file_name}")
|
||||
|
||||
content_type = build_content_type_from_extension(extension)
|
||||
|
||||
if not content_type:
|
||||
raise HTTPException(status_code=500, detail=f"Content type not found for extension {extension}")
|
||||
elif not content_type.startswith("image"):
|
||||
raise HTTPException(status_code=500, detail=f"Content type {content_type} is not an image")
|
||||
|
||||
file_content = await storage_service.get_file(flow_id=flow_id, file_name=file_name)
|
||||
return StreamingResponse(BytesIO(file_content), media_type=content_type)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.get("/list/{flow_id}")
|
||||
async def list_files(
|
||||
flow_id: str = Depends(get_flow_id), storage_service: StorageService = Depends(get_storage_service)
|
||||
):
|
||||
try:
|
||||
files = await storage_service.list_files(flow_id=flow_id)
|
||||
return {"files": files}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.delete("/delete/{flow_id}/{file_name}")
|
||||
async def delete_file(
|
||||
file_name: str, flow_id: str = Depends(get_flow_id), storage_service: StorageService = Depends(get_storage_service)
|
||||
):
|
||||
try:
|
||||
await storage_service.delete_file(flow_id=flow_id, file_name=file_name)
|
||||
return {"message": f"File {file_name} deleted successfully"}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
|
@ -5,14 +5,22 @@ from uuid import UUID
|
|||
import orjson
|
||||
from fastapi import APIRouter, Depends, File, HTTPException, UploadFile
|
||||
from fastapi.encoders import jsonable_encoder
|
||||
from loguru import logger
|
||||
from sqlmodel import Session, select
|
||||
|
||||
from langflow.api.utils import remove_api_keys, validate_is_component
|
||||
from langflow.api.v1.schemas import FlowListCreate, FlowListRead
|
||||
from langflow.initial_setup.setup import STARTER_FOLDER_NAME
|
||||
from langflow.services.auth.utils import get_current_active_user
|
||||
from langflow.services.database.models.flow import Flow, FlowCreate, FlowRead, FlowUpdate
|
||||
from langflow.services.database.models.flow import (
|
||||
Flow,
|
||||
FlowCreate,
|
||||
FlowRead,
|
||||
FlowUpdate,
|
||||
)
|
||||
from langflow.services.database.models.user.model import User
|
||||
from langflow.services.deps import get_session, get_settings_service
|
||||
from langflow.services.settings.service import SettingsService
|
||||
|
||||
# build router
|
||||
router = APIRouter(prefix="/flows", tags=["Flows"])
|
||||
|
|
@ -42,11 +50,36 @@ def create_flow(
|
|||
def read_flows(
|
||||
*,
|
||||
current_user: User = Depends(get_current_active_user),
|
||||
session: Session = Depends(get_session),
|
||||
settings_service: "SettingsService" = Depends(get_settings_service),
|
||||
):
|
||||
"""Read all flows."""
|
||||
try:
|
||||
flows = current_user.flows
|
||||
flows = validate_is_component(flows)
|
||||
auth_settings = settings_service.auth_settings
|
||||
if auth_settings.AUTO_LOGIN:
|
||||
flows = session.exec(
|
||||
select(Flow).where(
|
||||
(Flow.user_id == None) | (Flow.user_id == current_user.id) # noqa
|
||||
)
|
||||
).all()
|
||||
else:
|
||||
flows = current_user.flows
|
||||
|
||||
flows = validate_is_component(flows) # type: ignore
|
||||
flow_ids = [flow.id for flow in flows]
|
||||
# with the session get the flows that DO NOT have a user_id
|
||||
try:
|
||||
example_flows = session.exec(
|
||||
select(Flow).where(
|
||||
Flow.user_id == None, # noqa
|
||||
Flow.folder == STARTER_FOLDER_NAME,
|
||||
)
|
||||
).all()
|
||||
for example_flow in example_flows:
|
||||
if example_flow.id not in flow_ids:
|
||||
flows.append(example_flow) # type: ignore
|
||||
except Exception as e:
|
||||
logger.error(e)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e)) from e
|
||||
return [jsonable_encoder(flow) for flow in flows]
|
||||
|
|
@ -58,9 +91,18 @@ def read_flow(
|
|||
session: Session = Depends(get_session),
|
||||
flow_id: UUID,
|
||||
current_user: User = Depends(get_current_active_user),
|
||||
settings_service: "SettingsService" = Depends(get_settings_service),
|
||||
):
|
||||
"""Read a flow."""
|
||||
if user_flow := (session.exec(select(Flow).where(Flow.id == flow_id, Flow.user_id == current_user.id)).first()):
|
||||
auth_settings = settings_service.auth_settings
|
||||
stmt = select(Flow).where(Flow.id == flow_id)
|
||||
if auth_settings.AUTO_LOGIN:
|
||||
# If auto login is enable user_id can be current_user.id or None
|
||||
# so write an OR
|
||||
stmt = stmt.where(
|
||||
(Flow.user_id == current_user.id) | (Flow.user_id == None) # noqa
|
||||
) # noqa
|
||||
if user_flow := session.exec(stmt).first():
|
||||
return user_flow
|
||||
else:
|
||||
raise HTTPException(status_code=404, detail="Flow not found")
|
||||
|
|
@ -77,7 +119,12 @@ def update_flow(
|
|||
):
|
||||
"""Update a flow."""
|
||||
|
||||
db_flow = read_flow(session=session, flow_id=flow_id, current_user=current_user)
|
||||
db_flow = read_flow(
|
||||
session=session,
|
||||
flow_id=flow_id,
|
||||
current_user=current_user,
|
||||
settings_service=settings_service,
|
||||
)
|
||||
if not db_flow:
|
||||
raise HTTPException(status_code=404, detail="Flow not found")
|
||||
flow_data = flow.model_dump(exclude_unset=True)
|
||||
|
|
@ -99,9 +146,15 @@ def delete_flow(
|
|||
session: Session = Depends(get_session),
|
||||
flow_id: UUID,
|
||||
current_user: User = Depends(get_current_active_user),
|
||||
settings_service=Depends(get_settings_service),
|
||||
):
|
||||
"""Delete a flow."""
|
||||
flow = read_flow(session=session, flow_id=flow_id, current_user=current_user)
|
||||
flow = read_flow(
|
||||
session=session,
|
||||
flow_id=flow_id,
|
||||
current_user=current_user,
|
||||
settings_service=settings_service,
|
||||
)
|
||||
if not flow:
|
||||
raise HTTPException(status_code=404, detail="Flow not found")
|
||||
session.delete(flow)
|
||||
|
|
@ -109,9 +162,6 @@ def delete_flow(
|
|||
return {"message": "Flow deleted successfully"}
|
||||
|
||||
|
||||
# Define a new model to handle multiple flows
|
||||
|
||||
|
||||
@router.post("/batch/", response_model=List[FlowRead], status_code=201)
|
||||
def create_flows(
|
||||
*,
|
||||
|
|
@ -157,8 +207,9 @@ async def upload_file(
|
|||
async def download_file(
|
||||
*,
|
||||
session: Session = Depends(get_session),
|
||||
settings_service: "SettingsService" = Depends(get_settings_service),
|
||||
current_user: User = Depends(get_current_active_user),
|
||||
):
|
||||
"""Download all flows as a file."""
|
||||
flows = read_flows(current_user=current_user)
|
||||
flows = read_flows(current_user=current_user, session=session, settings_service=settings_service)
|
||||
return FlowListRead(flows=flows)
|
||||
|
|
|
|||
|
|
@ -20,7 +20,9 @@ async def login_to_get_access_token(
|
|||
form_data: OAuth2PasswordRequestForm = Depends(),
|
||||
db: Session = Depends(get_session),
|
||||
# _: Session = Depends(get_current_active_user)
|
||||
settings_service=Depends(get_settings_service),
|
||||
):
|
||||
auth_settings = settings_service.auth_settings
|
||||
try:
|
||||
user = authenticate_user(form_data.username, form_data.password, db)
|
||||
except Exception as exc:
|
||||
|
|
@ -33,8 +35,22 @@ async def login_to_get_access_token(
|
|||
|
||||
if user:
|
||||
tokens = create_user_tokens(user_id=user.id, db=db, update_last_login=True)
|
||||
response.set_cookie("refresh_token_lf", tokens["refresh_token"], httponly=True)
|
||||
response.set_cookie("access_token_lf", tokens["access_token"], httponly=False)
|
||||
response.set_cookie(
|
||||
"refresh_token_lf",
|
||||
tokens["refresh_token"],
|
||||
httponly=auth_settings.REFRESH_HTTPONLY,
|
||||
samesite=auth_settings.REFRESH_SAME_SITE,
|
||||
secure=auth_settings.REFRESH_SECURE,
|
||||
expires=auth_settings.REFRESH_TOKEN_EXPIRE_MINUTES * 60,
|
||||
)
|
||||
response.set_cookie(
|
||||
"access_token_lf",
|
||||
tokens["access_token"],
|
||||
httponly=auth_settings.ACCESS_HTTPONLY,
|
||||
samesite=auth_settings.ACCESS_SAME_SITE,
|
||||
secure=auth_settings.ACCESS_SECURE,
|
||||
expires=auth_settings.ACCESS_TOKEN_EXPIRE_MINUTES * 60,
|
||||
)
|
||||
return tokens
|
||||
else:
|
||||
raise HTTPException(
|
||||
|
|
@ -46,11 +62,21 @@ async def login_to_get_access_token(
|
|||
|
||||
@router.get("/auto_login")
|
||||
async def auto_login(
|
||||
response: Response, db: Session = Depends(get_session), settings_service=Depends(get_settings_service)
|
||||
response: Response,
|
||||
db: Session = Depends(get_session),
|
||||
settings_service=Depends(get_settings_service),
|
||||
):
|
||||
auth_settings = settings_service.auth_settings
|
||||
if settings_service.auth_settings.AUTO_LOGIN:
|
||||
tokens = create_user_longterm_token(db)
|
||||
response.set_cookie("access_token_lf", tokens["access_token"], httponly=False)
|
||||
response.set_cookie(
|
||||
"access_token_lf",
|
||||
tokens["access_token"],
|
||||
httponly=auth_settings.ACCESS_HTTPONLY,
|
||||
samesite=auth_settings.ACCESS_SAME_SITE,
|
||||
secure=auth_settings.ACCESS_SECURE,
|
||||
expires=auth_settings.ACCESS_TOKEN_EXPIRE_MINUTES * 60,
|
||||
)
|
||||
return tokens
|
||||
|
||||
raise HTTPException(
|
||||
|
|
@ -63,12 +89,29 @@ async def auto_login(
|
|||
|
||||
|
||||
@router.post("/refresh")
|
||||
async def refresh_token(request: Request, response: Response):
|
||||
async def refresh_token(request: Request, response: Response, settings_service=Depends(get_settings_service)):
|
||||
auth_settings = settings_service.auth_settings
|
||||
|
||||
token = request.cookies.get("refresh_token_lf")
|
||||
|
||||
if token:
|
||||
tokens = create_refresh_token(token)
|
||||
response.set_cookie("refresh_token_lf", tokens["refresh_token"], httponly=True)
|
||||
response.set_cookie("access_token_lf", tokens["access_token"], httponly=False)
|
||||
response.set_cookie(
|
||||
"refresh_token_lf",
|
||||
tokens["refresh_token"],
|
||||
httponly=auth_settings.REFRESH_HTTPONLY,
|
||||
samesite=auth_settings.REFRESH_SAME_SITE,
|
||||
secure=auth_settings.REFRESH_SECURE,
|
||||
expires=auth_settings.REFRESH_TOKEN_EXPIRE_MINUTES * 60,
|
||||
)
|
||||
response.set_cookie(
|
||||
"access_token_lf",
|
||||
tokens["access_token"],
|
||||
httponly=auth_settings.ACCESS_HTTPONLY,
|
||||
samesite=auth_settings.ACCESS_SAME_SITE,
|
||||
secure=auth_settings.ACCESS_SECURE,
|
||||
expires=auth_settings.ACCESS_TOKEN_EXPIRE_MINUTES * 60,
|
||||
)
|
||||
return tokens
|
||||
else:
|
||||
raise HTTPException(
|
||||
|
|
|
|||
71
src/backend/langflow/api/v1/monitor.py
Normal file
71
src/backend/langflow/api/v1/monitor.py
Normal file
|
|
@ -0,0 +1,71 @@
|
|||
from typing import Optional
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query
|
||||
from langflow.services.deps import get_monitor_service
|
||||
from langflow.services.monitor.schema import VertexBuildMapModel
|
||||
from langflow.services.monitor.service import MonitorService
|
||||
|
||||
router = APIRouter(prefix="/monitor", tags=["Monitor"])
|
||||
|
||||
|
||||
# Get vertex_builds data from the monitor service
|
||||
@router.get("/builds", response_model=VertexBuildMapModel)
|
||||
async def get_vertex_builds(
|
||||
flow_id: Optional[str] = Query(None),
|
||||
vertex_id: Optional[str] = Query(None),
|
||||
valid: Optional[bool] = Query(None),
|
||||
order_by: Optional[str] = Query("timestamp"),
|
||||
monitor_service: MonitorService = Depends(get_monitor_service),
|
||||
):
|
||||
try:
|
||||
vertex_build_dicts = monitor_service.get_vertex_builds(
|
||||
flow_id=flow_id, vertex_id=vertex_id, valid=valid, order_by=order_by
|
||||
)
|
||||
vertex_build_map = VertexBuildMapModel.from_list_of_dicts(vertex_build_dicts)
|
||||
return vertex_build_map
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.delete("/builds", status_code=204)
|
||||
async def delete_vertex_builds(
|
||||
flow_id: Optional[str] = Query(None),
|
||||
monitor_service: MonitorService = Depends(get_monitor_service),
|
||||
):
|
||||
try:
|
||||
monitor_service.delete_vertex_builds(flow_id=flow_id)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.get("/messages")
|
||||
async def get_messages(
|
||||
session_id: Optional[str] = Query(None),
|
||||
sender: Optional[str] = Query(None),
|
||||
sender_name: Optional[str] = Query(None),
|
||||
order_by: Optional[str] = Query("timestamp"),
|
||||
monitor_service: MonitorService = Depends(get_monitor_service),
|
||||
):
|
||||
try:
|
||||
return monitor_service.get_messages(
|
||||
sender=sender,
|
||||
sender_name=sender_name,
|
||||
session_id=session_id,
|
||||
order_by=order_by,
|
||||
)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.get("/transactions")
|
||||
async def get_transactions(
|
||||
source: Optional[str] = Query(None),
|
||||
target: Optional[str] = Query(None),
|
||||
status: Optional[str] = Query(None),
|
||||
order_by: Optional[str] = Query("timestamp"),
|
||||
monitor_service: MonitorService = Depends(get_monitor_service),
|
||||
):
|
||||
try:
|
||||
return monitor_service.get_transactions(source=source, target=target, status=status, order_by=order_by)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
|
@ -1,13 +1,24 @@
|
|||
from datetime import datetime
|
||||
from enum import Enum
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional, Union
|
||||
from uuid import UUID
|
||||
|
||||
from pydantic import (
|
||||
BaseModel,
|
||||
ConfigDict,
|
||||
Field,
|
||||
RootModel,
|
||||
field_validator,
|
||||
model_serializer,
|
||||
)
|
||||
|
||||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.schema import dotdict
|
||||
from langflow.services.database.models.api_key.model import ApiKeyRead
|
||||
from langflow.services.database.models.base import orjson_dumps
|
||||
from langflow.services.database.models.flow import FlowCreate, FlowRead
|
||||
from langflow.services.database.models.user import UserRead
|
||||
from pydantic import BaseModel, Field, field_validator
|
||||
|
||||
|
||||
class BuildStatus(Enum):
|
||||
|
|
@ -19,26 +30,6 @@ class BuildStatus(Enum):
|
|||
IN_PROGRESS = "in_progress"
|
||||
|
||||
|
||||
class GraphData(BaseModel):
|
||||
"""Data inside the exported flow."""
|
||||
|
||||
nodes: List[Dict[str, Any]]
|
||||
edges: List[Dict[str, Any]]
|
||||
|
||||
|
||||
class ExportedFlow(BaseModel):
|
||||
"""Exported flow from Langflow."""
|
||||
|
||||
description: str
|
||||
name: str
|
||||
id: str
|
||||
data: GraphData
|
||||
|
||||
|
||||
class InputRequest(BaseModel):
|
||||
input: dict
|
||||
|
||||
|
||||
class TweaksRequest(BaseModel):
|
||||
tweaks: Optional[Dict[str, Dict[str, str]]] = Field(default_factory=dict)
|
||||
|
||||
|
|
@ -64,6 +55,26 @@ class ProcessResponse(BaseModel):
|
|||
backend: Optional[str] = None
|
||||
|
||||
|
||||
class RunResponse(BaseModel):
|
||||
"""Run response schema."""
|
||||
|
||||
outputs: Optional[List[RunOutputs]] = []
|
||||
session_id: Optional[str] = None
|
||||
|
||||
@model_serializer(mode="wrap")
|
||||
def serialize(self, handler):
|
||||
# Serialize all the outputs if they are base models
|
||||
if self.outputs:
|
||||
serialized_outputs = []
|
||||
for output in self.outputs:
|
||||
if isinstance(output, BaseModel):
|
||||
serialized_outputs.append(output.model_dump(exclude_none=True))
|
||||
else:
|
||||
serialized_outputs.append(output)
|
||||
self.outputs = serialized_outputs
|
||||
return handler(self)
|
||||
|
||||
|
||||
class PreloadResponse(BaseModel):
|
||||
"""Preload response schema."""
|
||||
|
||||
|
|
@ -71,9 +82,6 @@ class PreloadResponse(BaseModel):
|
|||
is_clear: Optional[bool] = None
|
||||
|
||||
|
||||
# TaskStatusResponse(
|
||||
# status=task.status, result=task.result if task.ready() else None
|
||||
# )
|
||||
class TaskStatusResponse(BaseModel):
|
||||
"""Task status response schema."""
|
||||
|
||||
|
|
@ -162,12 +170,21 @@ class StreamData(BaseModel):
|
|||
return f"event: {self.event}\ndata: {orjson_dumps(self.data, indent_2=False)}\n\n"
|
||||
|
||||
|
||||
class CustomComponentCode(BaseModel):
|
||||
class CustomComponentRequest(BaseModel):
|
||||
model_config = ConfigDict(arbitrary_types_allowed=True)
|
||||
code: str
|
||||
field: Optional[str] = None
|
||||
frontend_node: Optional[dict] = None
|
||||
|
||||
|
||||
class UpdateCustomComponentRequest(CustomComponentRequest):
|
||||
field: str
|
||||
field_value: Optional[Union[str, int, float, bool, dict, list]] = None
|
||||
template: dict
|
||||
|
||||
def get_template(self):
|
||||
return dotdict(self.template)
|
||||
|
||||
|
||||
class CustomComponentResponseError(BaseModel):
|
||||
detail: str
|
||||
traceback: str
|
||||
|
|
@ -212,3 +229,81 @@ class Token(BaseModel):
|
|||
|
||||
class ApiKeyCreateRequest(BaseModel):
|
||||
api_key: str
|
||||
|
||||
|
||||
class VerticesOrderResponse(BaseModel):
|
||||
ids: List[str]
|
||||
run_id: UUID
|
||||
|
||||
|
||||
class ResultDataResponse(BaseModel):
|
||||
results: Optional[Any] = Field(default_factory=dict)
|
||||
artifacts: Optional[Any] = Field(default_factory=dict)
|
||||
timedelta: Optional[float] = None
|
||||
duration: Optional[str] = None
|
||||
|
||||
|
||||
class VertexBuildResponse(BaseModel):
|
||||
id: Optional[str] = None
|
||||
inactivated_vertices: Optional[List[str]] = None
|
||||
next_vertices_ids: Optional[List[str]] = None
|
||||
valid: bool
|
||||
params: Optional[Any] = Field(default_factory=dict)
|
||||
"""JSON string of the params."""
|
||||
data: ResultDataResponse
|
||||
"""Mapping of vertex ids to result dict containing the param name and result value."""
|
||||
timestamp: Optional[datetime] = Field(default_factory=datetime.utcnow)
|
||||
"""Timestamp of the build."""
|
||||
|
||||
|
||||
class VerticesBuiltResponse(BaseModel):
|
||||
vertices: List[VertexBuildResponse]
|
||||
|
||||
|
||||
class InputValueRequest(BaseModel):
|
||||
components: Optional[List[str]] = []
|
||||
input_value: Optional[str] = None
|
||||
|
||||
# add an example
|
||||
model_config = {
|
||||
"json_schema_extra": {
|
||||
"examples": [
|
||||
{
|
||||
"components": ["components_id", "Component Name"],
|
||||
"input_value": "input_value",
|
||||
},
|
||||
{"components": ["Component Name"], "input_value": "input_value"},
|
||||
{"input_value": "input_value"},
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
class Tweaks(RootModel):
|
||||
root: dict[str, Union[str, dict[str, str]]] = Field(
|
||||
description="A dictionary of tweaks to adjust the flow's execution. Allows customizing flow behavior dynamically. All tweaks are overridden by the input values.",
|
||||
)
|
||||
model_config = {
|
||||
"json_schema_extra": {
|
||||
"examples": [
|
||||
{
|
||||
"parameter_name": "value",
|
||||
"Component Name": {"parameter_name": "value"},
|
||||
"component_id": {"parameter_name": "value"},
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
# This should behave like a dict
|
||||
def __getitem__(self, key):
|
||||
return self.root[key]
|
||||
|
||||
def __setitem__(self, key, value):
|
||||
self.root[key] = value
|
||||
|
||||
def __delitem__(self, key):
|
||||
del self.root[key]
|
||||
|
||||
def items(self):
|
||||
return self.root.items()
|
||||
|
|
|
|||
|
|
@ -1,14 +1,22 @@
|
|||
from collections import defaultdict
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from loguru import logger
|
||||
|
||||
from langflow.api.v1.base import (
|
||||
Code,
|
||||
CodeValidationResponse,
|
||||
PromptValidationResponse,
|
||||
ValidatePromptRequest,
|
||||
)
|
||||
from langflow.base.prompts.utils import (
|
||||
add_new_variables_to_template,
|
||||
get_old_custom_fields,
|
||||
remove_old_variables_from_template,
|
||||
update_input_variables_field,
|
||||
validate_prompt,
|
||||
)
|
||||
from langflow.template.field.base import TemplateField
|
||||
from langflow.utils.validate import validate_code
|
||||
from loguru import logger
|
||||
|
||||
# build router
|
||||
router = APIRouter(prefix="/validate", tags=["Validate"])
|
||||
|
|
@ -36,13 +44,26 @@ def post_validate_prompt(prompt_request: ValidatePromptRequest):
|
|||
input_variables=input_variables,
|
||||
frontend_node=None,
|
||||
)
|
||||
old_custom_fields = get_old_custom_fields(prompt_request)
|
||||
if not prompt_request.custom_fields:
|
||||
prompt_request.custom_fields = defaultdict(list)
|
||||
old_custom_fields = get_old_custom_fields(prompt_request.custom_fields, prompt_request.name)
|
||||
|
||||
add_new_variables_to_template(input_variables, prompt_request)
|
||||
add_new_variables_to_template(
|
||||
input_variables,
|
||||
prompt_request.custom_fields,
|
||||
prompt_request.frontend_node.template,
|
||||
prompt_request.name,
|
||||
)
|
||||
|
||||
remove_old_variables_from_template(old_custom_fields, input_variables, prompt_request)
|
||||
remove_old_variables_from_template(
|
||||
old_custom_fields,
|
||||
input_variables,
|
||||
prompt_request.custom_fields,
|
||||
prompt_request.frontend_node.template,
|
||||
prompt_request.name,
|
||||
)
|
||||
|
||||
update_input_variables_field(input_variables, prompt_request)
|
||||
update_input_variables_field(input_variables, prompt_request.frontend_node.template)
|
||||
|
||||
return PromptValidationResponse(
|
||||
input_variables=input_variables,
|
||||
|
|
@ -51,70 +72,3 @@ def post_validate_prompt(prompt_request: ValidatePromptRequest):
|
|||
except Exception as e:
|
||||
logger.exception(e)
|
||||
raise HTTPException(status_code=500, detail=str(e)) from e
|
||||
|
||||
|
||||
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]
|
||||
if old_custom_fields is None:
|
||||
old_custom_fields = []
|
||||
|
||||
old_custom_fields = old_custom_fields.copy()
|
||||
except KeyError:
|
||||
old_custom_fields = []
|
||||
prompt_request.frontend_node.custom_fields[prompt_request.name] = []
|
||||
return old_custom_fields
|
||||
|
||||
|
||||
def add_new_variables_to_template(input_variables, prompt_request):
|
||||
for variable in input_variables:
|
||||
try:
|
||||
template_field = TemplateField(
|
||||
name=variable,
|
||||
display_name=variable,
|
||||
field_type="str",
|
||||
show=True,
|
||||
advanced=False,
|
||||
multiline=True,
|
||||
input_types=["Document", "BaseOutputParser"],
|
||||
value="", # Set the value to empty string
|
||||
)
|
||||
if variable in prompt_request.frontend_node.template:
|
||||
# Set the new field with the old value
|
||||
template_field.value = prompt_request.frontend_node.template[variable]["value"]
|
||||
|
||||
prompt_request.frontend_node.template[variable] = template_field.to_dict()
|
||||
|
||||
# Check if variable is not already in the list before appending
|
||||
if variable not in prompt_request.frontend_node.custom_fields[prompt_request.name]:
|
||||
prompt_request.frontend_node.custom_fields[prompt_request.name].append(variable)
|
||||
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
raise HTTPException(status_code=500, detail=str(exc)) from exc
|
||||
|
||||
|
||||
def remove_old_variables_from_template(old_custom_fields, input_variables, prompt_request):
|
||||
for variable in old_custom_fields:
|
||||
if variable not in input_variables:
|
||||
try:
|
||||
# Remove the variable from custom_fields associated with the given name
|
||||
if variable in prompt_request.frontend_node.custom_fields[prompt_request.name]:
|
||||
prompt_request.frontend_node.custom_fields[prompt_request.name].remove(variable)
|
||||
|
||||
# Remove the variable from the template
|
||||
prompt_request.frontend_node.template.pop(variable, None)
|
||||
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
raise HTTPException(status_code=500, detail=str(exc)) from exc
|
||||
|
||||
|
||||
def update_input_variables_field(input_variables, prompt_request):
|
||||
if "input_variables" in prompt_request.frontend_node.template:
|
||||
prompt_request.frontend_node.template["input_variables"]["value"] = input_variables
|
||||
|
|
|
|||
0
src/backend/langflow/base/__init__.py
Normal file
0
src/backend/langflow/base/__init__.py
Normal file
Some files were not shown because too many files have changed in this diff Show more
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Add table
Add a link
Reference in a new issue