Merge branch 'dev' into modalRefactor
This commit is contained in:
Lucas Oliveira
commit
202d80e7b5
102 changed files with 20508 additions and 290 deletions
39
.github/workflows/deploy_gh-pages.yml
vendored
Normal file
39
.github/workflows/deploy_gh-pages.yml
vendored
Normal file
|
|
@ -0,0 +1,39 @@
|
|||
name: Deploy to GitHub Pages
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
# Review gh actions docs if you want to further define triggers, paths, etc
|
||||
# https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#on
|
||||
|
||||
jobs:
|
||||
deploy:
|
||||
name: Deploy to GitHub Pages
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 18
|
||||
cache: npm
|
||||
cache-dependency-path: ./docs/package-lock.json
|
||||
|
||||
- name: Install dependencies
|
||||
run: cd docs && npm install
|
||||
- name: Build website
|
||||
run: cd docs && npm run build
|
||||
|
||||
# Popular action to deploy to GitHub Pages:
|
||||
# Docs: https://github.com/peaceiris/actions-gh-pages#%EF%B8%8F-docusaurus
|
||||
- name: Deploy to GitHub Pages
|
||||
uses: peaceiris/actions-gh-pages@v3
|
||||
with:
|
||||
github_token: ${{ secrets.GITHUB_TOKEN }}
|
||||
# Build output to publish to the `gh-pages` branch:
|
||||
publish_dir: ./docs/build
|
||||
# The following lines assign commit authorship to the official
|
||||
# GH-Actions bot for deploys to `gh-pages` branch:
|
||||
# https://github.com/actions/checkout/issues/13#issuecomment-724415212
|
||||
# The GH actions bot is used by default if you didn't specify the two fields.
|
||||
# You can swap them out with your own user credentials.
|
||||
7
.gitignore
vendored
7
.gitignore
vendored
|
|
@ -244,5 +244,10 @@ dmypy.json
|
|||
# Poetry
|
||||
.testenv/*
|
||||
langflow.db
|
||||
|
||||
|
||||
.githooks/prepare-commit-msg
|
||||
langchain.db
|
||||
.langchain.db
|
||||
|
||||
# docusaurus
|
||||
.docusaurus/
|
||||
|
|
|
|||
31
.readthedocs.yaml
Normal file
31
.readthedocs.yaml
Normal file
|
|
@ -0,0 +1,31 @@
|
|||
# Read the Docs configuration file for Sphinx projects
|
||||
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
|
||||
|
||||
# Required
|
||||
version: 2
|
||||
|
||||
# Set the OS, Python version and other tools you might need
|
||||
build:
|
||||
os: ubuntu-22.04
|
||||
tools:
|
||||
python: "3.11"
|
||||
# You can also specify other tool versions:
|
||||
# nodejs: "19"
|
||||
# rust: "1.64"
|
||||
# golang: "1.19"
|
||||
|
||||
# Build documentation in the "docs/" directory with Sphinx
|
||||
sphinx:
|
||||
configuration: docs/conf.py
|
||||
|
||||
# Optionally build your docs in additional formats such as PDF and ePub
|
||||
# formats:
|
||||
# - pdf
|
||||
# - epub
|
||||
|
||||
# Optional but recommended, declare the Python requirements required
|
||||
# to build your documentation
|
||||
# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
|
||||
# python:
|
||||
# install:
|
||||
# - requirements: docs/requirements.txt
|
||||
41
docs/README.md
Normal file
41
docs/README.md
Normal file
|
|
@ -0,0 +1,41 @@
|
|||
# Website
|
||||
|
||||
This website is built using [Docusaurus 2](https://docusaurus.io/), a modern static website generator.
|
||||
|
||||
### Installation
|
||||
|
||||
```
|
||||
$ yarn
|
||||
```
|
||||
|
||||
### Local Development
|
||||
|
||||
```
|
||||
$ yarn start
|
||||
```
|
||||
|
||||
This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.
|
||||
|
||||
### Build
|
||||
|
||||
```
|
||||
$ yarn build
|
||||
```
|
||||
|
||||
This command generates static content into the `build` directory and can be served using any static contents hosting service.
|
||||
|
||||
### Deployment
|
||||
|
||||
Using SSH:
|
||||
|
||||
```
|
||||
$ USE_SSH=true yarn deploy
|
||||
```
|
||||
|
||||
Not using SSH:
|
||||
|
||||
```
|
||||
$ GIT_USER=<Your GitHub username> yarn deploy
|
||||
```
|
||||
|
||||
If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the `gh-pages` branch.
|
||||
3
docs/babel.config.js
Normal file
3
docs/babel.config.js
Normal file
|
|
@ -0,0 +1,3 @@
|
|||
module.exports = {
|
||||
presets: [require.resolve('@docusaurus/core/lib/babel/preset')],
|
||||
};
|
||||
2
docs/docs/components/agents.mdx
Normal file
2
docs/docs/components/agents.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Agents
|
||||
(coming soon)
|
||||
2
docs/docs/components/chains.mdx
Normal file
2
docs/docs/components/chains.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Chains
|
||||
(coming soon)
|
||||
2
docs/docs/components/embeddings.mdx
Normal file
2
docs/docs/components/embeddings.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Embeddings
|
||||
(coming soon)
|
||||
2
docs/docs/components/llms.mdx
Normal file
2
docs/docs/components/llms.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# LLMs
|
||||
(coming soon)
|
||||
2
docs/docs/components/loaders.mdx
Normal file
2
docs/docs/components/loaders.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Loaders
|
||||
(coming soon)
|
||||
2
docs/docs/components/memories.mdx
Normal file
2
docs/docs/components/memories.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Memories
|
||||
(coming soon)
|
||||
2
docs/docs/components/prompts.mdx
Normal file
2
docs/docs/components/prompts.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Prompts
|
||||
(coming soon)
|
||||
2
docs/docs/components/text-splitters.mdx
Normal file
2
docs/docs/components/text-splitters.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Text Splitters
|
||||
(coming soon)
|
||||
2
docs/docs/components/toolkits.mdx
Normal file
2
docs/docs/components/toolkits.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Toolkits
|
||||
(coming soon)
|
||||
2
docs/docs/components/tools.mdx
Normal file
2
docs/docs/components/tools.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Tools
|
||||
(coming soon)
|
||||
2
docs/docs/components/utilities.mdx
Normal file
2
docs/docs/components/utilities.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Utilities
|
||||
(coming soon)
|
||||
2
docs/docs/components/vector-stores.mdx
Normal file
2
docs/docs/components/vector-stores.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Vector Stores
|
||||
(coming soon)
|
||||
2
docs/docs/components/wrappers.mdx
Normal file
2
docs/docs/components/wrappers.mdx
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
# Wrappers
|
||||
(coming soon)
|
||||
38
docs/docs/contributing/community.md
Normal file
38
docs/docs/contributing/community.md
Normal file
|
|
@ -0,0 +1,38 @@
|
|||
# Community
|
||||
|
||||
## 🤖 Join **Langflow** Discord server
|
||||
|
||||
Join us to ask questions and showcase your projects.
|
||||
|
||||
Let's bring together the building blocks of AI integration!
|
||||
|
||||
Langflow [Discord](https://discord.gg/EqksyE2EX9) server.
|
||||
|
||||
---
|
||||
|
||||
## 🐦 Stay tunned for **Langflow** on Twitter
|
||||
|
||||
Follow [@logspace_ai](https://twitter.com/logspace_ai) on **Twitter** to get the latest news about **Langflow**.
|
||||
|
||||
---
|
||||
## ⭐️ Star **Langflow** on GitHub
|
||||
|
||||
You can "star" **Langflow** in [GitHub](https://github.com/logspace-ai/langflow).
|
||||
|
||||
By adding a star, other users will be able to find it more easily and see that it has been already useful for others.
|
||||
|
||||
---
|
||||
|
||||
## 👀 Watch the GitHub repository for releases
|
||||
|
||||
You can "watch" **Langflow** in [GitHub](https://github.com/logspace-ai/langflow).
|
||||
|
||||
|
||||
If you select "Watching" instead of "Releases only" you will receive notifications when someone creates a new issue or question. You can also specify that you only want to be notified about new issues, discussions, PRs, etc.
|
||||
|
||||
|
||||
Then you can try and help them solve those questions.
|
||||
|
||||
---
|
||||
|
||||
Thanks! 🚀
|
||||
27
docs/docs/contributing/github-issues.md
Normal file
27
docs/docs/contributing/github-issues.md
Normal file
|
|
@ -0,0 +1,27 @@
|
|||
# GitHub Issues
|
||||
|
||||
Our [issues](https://github.com/logspace-ai/langflow/issues) page is kept up to date
|
||||
with bugs, improvements, and feature requests. There is a taxonomy of labels to help
|
||||
with sorting and discovery of issues of interest.
|
||||
|
||||
If you're looking for help with your code, consider posting a question on the
|
||||
[GitHub Discussions board](https://github.com/logspace-ai/langflow/discussions). Please
|
||||
understand that we won't be able to provide individual support via email. We
|
||||
also believe that help is much more valuable if it's **shared publicly**,
|
||||
so that more people can benefit from it.
|
||||
|
||||
- **Describing your issue:** Try to provide as many details as possible. What
|
||||
exactly goes wrong? _How_ is it failing? Is there an error?
|
||||
"XY doesn't work" usually isn't that helpful for tracking down problems. Always
|
||||
remember to include the code you ran and if possible, extract only the relevant
|
||||
parts and don't just dump your entire script. This will make it easier for us to
|
||||
reproduce the error.
|
||||
|
||||
- **Sharing long blocks of code or logs:** If you need to include long code,
|
||||
logs or tracebacks, you can wrap them in `<details>` and `</details>`. This
|
||||
[collapses the content](https://developer.mozilla.org/en/docs/Web/HTML/Element/details) so it only becomes visible on click, making the issue easier to read and follow.
|
||||
|
||||
|
||||
## Issue labels
|
||||
|
||||
[See this page](https://github.com/logspace-ai/langflow/labels) for an overview of the system we use to tag our issues and pull requests.
|
||||
62
docs/docs/contributing/how-contribute.md
Normal file
62
docs/docs/contributing/how-contribute.md
Normal file
|
|
@ -0,0 +1,62 @@
|
|||
# How to contribute?
|
||||
|
||||
👋 Hello there! We welcome contributions from developers of all levels to our open-source project on [GitHub](https://github.com/logspace-ai/langflow). If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.
|
||||
|
||||
As an open-source project in a rapidly developing field, we are extremely open
|
||||
to contributions, whether in the form of a new feature, improved infra, or better documentation.
|
||||
|
||||
To contribute to this project, please follow a ["fork and pull request"](https://docs.github.com/en/get-started/quickstart/contributing-to-projects) workflow.
|
||||
|
||||
Please do not try to push directly to this repo unless you are a maintainer.
|
||||
|
||||
---
|
||||
## Local development
|
||||
|
||||
You can develop Langflow using docker compose, or locally.
|
||||
|
||||
We provide a .vscode/launch.json file for debugging the backend in VSCode, which is a lot faster than using docker compose.
|
||||
|
||||
Setting up hooks:
|
||||
```bash
|
||||
make init
|
||||
```
|
||||
|
||||
This will install the pre-commit hooks, which will run `make format` on every commit.
|
||||
|
||||
It is advised to run `make lint` before pushing to the repository.
|
||||
|
||||
---
|
||||
|
||||
## Run locally
|
||||
|
||||
Langflow can run locally by cloning the repository and installing the dependencies. We recommend using a virtual environment to isolate the dependencies from your system.
|
||||
|
||||
Before you start, make sure you have the following installed:
|
||||
|
||||
- Poetry (>=1.4)
|
||||
- Node.js
|
||||
|
||||
Then install the dependencies and start the development server for the backend:
|
||||
|
||||
```bash
|
||||
make install_backend
|
||||
make backend
|
||||
```
|
||||
|
||||
And the frontend:
|
||||
|
||||
```bash
|
||||
make frontend
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Docker compose
|
||||
|
||||
The following snippet will run the backend and frontend in separate containers. The frontend will be available at `localhost:3000` and the backend at `localhost:7860`.
|
||||
|
||||
```bash
|
||||
docker compose up --build
|
||||
# or
|
||||
make dev build=1
|
||||
```
|
||||
35
docs/docs/deployment/gcp-deployment.md
Normal file
35
docs/docs/deployment/gcp-deployment.md
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
# Deploy on Google Cloud Platform
|
||||
|
||||
## Run Langflow from a New Google Cloud Project
|
||||
|
||||
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.
|
||||
:::
|
||||
|
||||
|
||||
## Standard VM
|
||||
[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/logspace-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md)
|
||||
|
||||
This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment.
|
||||
|
||||
---
|
||||
|
||||
## Spot/Preemptible Instance
|
||||
|
||||
[](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
|
||||
|
||||
When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts.
|
||||
|
||||
---
|
||||
|
||||
## Pricing (approximate)
|
||||
> For a more accurate breakdown of costs, please use the [**GCP Pricing Calculator**](https://cloud.google.com/products/calculator)
|
||||
|
||||
|
||||
| Component | Regular Cost (Hourly) | Regular Cost (Monthly) | Spot/Preemptible Cost (Hourly) | Spot/Preemptible Cost (Monthly) | Notes |
|
||||
| -------------- | --------------------- | ---------------------- | ------------------------------ | ------------------------------- | ----- |
|
||||
| 100 GB Disk | - | $10/month | - | $10/month | Disk cost remains the same for both regular and Spot/Preemptible VMs |
|
||||
| VM (n1-standard-4) | $0.15/hr | ~$108/month | ~$0.04/hr | ~$29/month | The VM cost can be significantly reduced using a Spot/Preemptible instance |
|
||||
| **Total** | **$0.15/hr** | **~$118/month** | **~$0.04/hr** | **~$39/month** | Total costs for running the VM and disk 24/7 for an entire month |
|
||||
101
docs/docs/deployment/jina-deployment.md
Normal file
101
docs/docs/deployment/jina-deployment.md
Normal file
|
|
@ -0,0 +1,101 @@
|
|||
# Deploy on Jina AI Cloud
|
||||
|
||||
Langflow integrates with langchain-serve to provide a one-command deployment to [Jina AI Cloud](https://github.com/jina-ai/langchain-serve).
|
||||
|
||||
Start by installing `langchain-serve` with
|
||||
|
||||
```bash
|
||||
pip install -U langchain-serve
|
||||
```
|
||||
|
||||
Then, run:
|
||||
|
||||
```bash
|
||||
langflow --jcloud
|
||||
```
|
||||
|
||||
```text
|
||||
🎉 Langflow server successfully deployed on Jina AI Cloud 🎉
|
||||
🔗 Click on the link to open the server (please allow ~1-2 minutes for the server to startup): https://<your-app>.wolf.jina.ai/
|
||||
📖 Read more about managing the server: https://github.com/jina-ai/langchain-serve
|
||||
```
|
||||
|
||||
**Complete (example) output:**
|
||||
|
||||
```text
|
||||
🚀 Deploying Langflow server on Jina AI Cloud
|
||||
╭───────────────────────── 🎉 Flow is available! ──────────────────────────╮
|
||||
│ │
|
||||
│ ID langflow-e3dd8820ec │
|
||||
│ Gateway (Websocket) wss://langflow-e3dd8820ec.wolf.jina.ai │
|
||||
│ Dashboard https://dashboard.wolf.jina.ai/flow/e3dd8820ec │
|
||||
│ │
|
||||
╰──────────────────────────────────────────────────────────────────────────╯
|
||||
╭──────────────┬──────────────────────────────────────────────────────────────────────────────╮
|
||||
│ App ID │ langflow-e3dd8820ec │
|
||||
├──────────────┼──────────────────────────────────────────────────────────────────────────────┤
|
||||
│ Phase │ Serving │
|
||||
├──────────────┼──────────────────────────────────────────────────────────────────────────────┤
|
||||
│ Endpoint │ wss://langflow-e3dd8820ec.wolf.jina.ai │
|
||||
├──────────────┼──────────────────────────────────────────────────────────────────────────────┤
|
||||
│ App logs │ dashboards.wolf.jina.ai │
|
||||
├──────────────┼──────────────────────────────────────────────────────────────────────────────┤
|
||||
│ Swagger UI │ https://langflow-e3dd8820ec.wolf.jina.ai/docs │
|
||||
├──────────────┼──────────────────────────────────────────────────────────────────────────────┤
|
||||
│ OpenAPI JSON │ https://langflow-e3dd8820ec.wolf.jina.ai/openapi.json │
|
||||
╰──────────────┴──────────────────────────────────────────────────────────────────────────────╯
|
||||
|
||||
🎉 Langflow server successfully deployed on Jina AI Cloud 🎉
|
||||
🔗 Click on the link to open the server (please allow ~1-2 minutes for the server to startup): https://langflow-e3dd8820ec.wolf.jina.ai/
|
||||
📖 Read more about managing the server: https://github.com/jina-ai/langchain-serve
|
||||
```
|
||||
## API Usage (with python)
|
||||
|
||||
You can use Langflow directly on your browser or the API endpoints on Jina AI Cloud to interact with the server.
|
||||
|
||||
```python
|
||||
import requests
|
||||
|
||||
BASE_API_URL = "https://langflow-e3dd8820ec.wolf.jina.ai/api/v1/predict"
|
||||
FLOW_ID = "864c4f98-2e59-468b-8e13-79cd8da07468"
|
||||
# You can tweak the flow by adding a tweaks dictionary
|
||||
# e.g {"OpenAI-XXXXX": {"model_name": "gpt-4"}}
|
||||
TWEAKS = {
|
||||
"ChatOpenAI-g4jEr": {},
|
||||
"ConversationChain-UidfJ": {}
|
||||
}
|
||||
|
||||
def run_flow(message: str, flow_id: str, tweaks: dict = None) -> dict:
|
||||
"""
|
||||
Run a flow with a given message and optional tweaks.
|
||||
|
||||
:param message: The message to send to the flow
|
||||
:param flow_id: The ID of the flow to run
|
||||
:param tweaks: Optional tweaks to customize the flow
|
||||
:return: The JSON response from the flow
|
||||
"""
|
||||
api_url = f"{BASE_API_URL}/{flow_id}"
|
||||
|
||||
payload = {"message": message}
|
||||
|
||||
if tweaks:
|
||||
payload["tweaks"] = tweaks
|
||||
|
||||
response = requests.post(api_url, json=payload)
|
||||
return response.json()
|
||||
|
||||
# Setup any tweaks you want to apply to the flow
|
||||
print(run_flow("Your message", flow_id=FLOW_ID, tweaks=TWEAKS))
|
||||
```
|
||||
|
||||
```json
|
||||
{
|
||||
"result": "Great choice! Bangalore in the 1920s was a vibrant city with a rich cultural and political scene. Here are some suggestions for things to see and do:\n\n1. Visit the Bangalore Palace - built in 1887, this stunning palace is a perfect example of Tudor-style architecture. It was home to the Maharaja of Mysore and is now open to the public.\n\n2. Attend a performance at the Ravindra Kalakshetra - this cultural center was built in the 1920s and is still a popular venue for music and dance performances.\n\n3. Explore the neighborhoods of Basavanagudi and Malleswaram - both of these areas have retained much of their old-world charm and are great places to walk around and soak up the atmosphere.\n\n4. Check out the Bangalore Club - founded in 1868, this exclusive social club was a favorite haunt of the British expat community in the 1920s.\n\n5. Attend a meeting of the Indian National Congress - founded in 1885, the INC was a major force in the Indian independence movement and held many meetings and rallies in Bangalore in the 1920s.\n\nHope you enjoy your trip to 1920s Bangalore!"
|
||||
}
|
||||
```
|
||||
|
||||
:::info
|
||||
|
||||
Read more about resource customization, cost, and management of Langflow apps on Jina AI Cloud in the **[langchain-serve](https://github.com/jina-ai/langchain-serve)** repository.
|
||||
|
||||
:::
|
||||
25
docs/docs/examples/buffer-memory.mdx
Normal file
25
docs/docs/examples/buffer-memory.mdx
Normal file
|
|
@ -0,0 +1,25 @@
|
|||
# Buffer Memory
|
||||
|
||||
For certain applications, retaining past interactions is crucial. For that, chains and agents may accept a memory component as one of their input parameters. The `ConversationBufferMemory` component is one of them. It stores messages and extracts them into variables.
|
||||
|
||||
## ⛓️ 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/buffer-memory.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/Buffer_Memory.json" download>Download Flow</a>
|
||||
|
||||
:::note LangChain Components 🦜🔗
|
||||
|
||||
- [`ConversationBufferMemory`](https://python.langchain.com/docs/modules/memory/how_to/buffer)
|
||||
- [`ConversationChain`](https://python.langchain.com/docs/modules/chains/)
|
||||
- [`ChatOpenAI`](https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai)
|
||||
:::
|
||||
28
docs/docs/examples/conversation-chain.mdx
Normal file
28
docs/docs/examples/conversation-chain.mdx
Normal file
|
|
@ -0,0 +1,28 @@
|
|||
# Conversation Chain
|
||||
|
||||
This example shows how to instantiate a simple `ConversationChain` component using a Language Model (LLM). Once the Node Status turns green 🟢, the chat will be ready to take in user messages. Here, we used `ChatOpenAI` to act as the required LLM input, but you can use any LLM for this purpose.
|
||||
|
||||
:::info
|
||||
Make sure to always get the API key from the provider.
|
||||
:::
|
||||
|
||||
## ⛓️ 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/basic-chat.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/Basic_Chat.json" download>Download Flow</a>
|
||||
|
||||
:::note LangChain Components 🦜🔗
|
||||
|
||||
- [`ConversationChain`](https://python.langchain.com/docs/modules/chains/)
|
||||
- [`ChatOpenAI`](https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai)
|
||||
:::
|
||||
42
docs/docs/examples/csv-loader.mdx
Normal file
42
docs/docs/examples/csv-loader.mdx
Normal file
|
|
@ -0,0 +1,42 @@
|
|||
# CSV Loader
|
||||
|
||||
The `VectoStoreAgent` component retrieves information from one or more vector stores. This example shows a `VectoStoreAgent` connected to a CSV file through the `Chroma` vector store. Process description:
|
||||
|
||||
- The `CSVLoader` loads a CSV file into a list of documents.
|
||||
- The extracted data is then processed by the `CharacterTextSplitter`, which splits the text into small, meaningful chunks (usually sentences).
|
||||
- These chunks feed the `Chroma` vector store, which converts them into vectors and stores them for fast indexing.
|
||||
- Finally, the agent accesses the information of the vector store through the `VectorStoreInfo` tool.
|
||||
|
||||
:::info
|
||||
The vector store is used for efficient semantic search, while `VectorStoreInfo` carries information about it, such as its name and description. Embeddings are a way to represent words, phrases, or any entities in a vector space. Learn more about them [here](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings).
|
||||
:::
|
||||
|
||||
:::tip
|
||||
Once you build this flow, ask questions about the data in the chat interface (e.g., number of rows or columns).
|
||||
:::
|
||||
|
||||
## ⛓️ 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/csv-loader.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/CSV_Loader.json" download>Download Flow</a>
|
||||
|
||||
:::note LangChain Components 🦜🔗
|
||||
|
||||
- [`CSVLoader`](https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/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)
|
||||
- [`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)
|
||||
:::
|
||||
29
docs/docs/examples/how-upload-examples.mdx
Normal file
29
docs/docs/examples/how-upload-examples.mdx
Normal file
|
|
@ -0,0 +1,29 @@
|
|||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
|
||||
# 📚 How to Upload Examples?
|
||||
|
||||
We welcome all examples that can help our community learn and explore Langflow's capabilities.
|
||||
Langflow Examples is a repository on [GitHub](https://github.com/logspace-ai/langflow_examples) that contains examples of flows that people can use for inspiration and learning.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/community-examples.png",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
|
||||
To upload examples, please follow these steps:
|
||||
|
||||
1. **Create a Flow:** First, create a flow using Langflow. You can use any of the available templates or create a new flow from scratch.
|
||||
|
||||
2. **Export the Flow:** Once you have created a flow, export it as a JSON file. Make sure to give your file a descriptive name and include a brief description of what it does.
|
||||
|
||||
3. **Submit a Pull Request:** Finally, submit a pull request (PR) to the examples repo. Make sure to include your JSON file in the PR.
|
||||
|
||||
If your example uses any third-party libraries or packages, please include them in your PR and make sure that your example follows the [**⛓️ Langflow Code Of Conduct**](https://github.com/logspace-ai/langflow/blob/dev/CODE_OF_CONDUCT.md).
|
||||
40
docs/docs/examples/midjourney-prompt-chain.mdx
Normal file
40
docs/docs/examples/midjourney-prompt-chain.mdx
Normal file
|
|
@ -0,0 +1,40 @@
|
|||
# MidJourney Prompt Chain
|
||||
|
||||
The `MidJourneyPromptChain` can be used to generate imaginative and detailed MidJourney prompts.
|
||||
|
||||
For example, type something like:
|
||||
|
||||
```bash
|
||||
Dragon
|
||||
```
|
||||
|
||||
And get a response such as:
|
||||
|
||||
```text
|
||||
Imagine a mysterious forest, the trees are tall and ancient, their branches reaching up to the sky. Through the darkness, a dragon emerges from the shadows, its scales shimmering in the moonlight. Its wingspan is immense, and its eyes glow with a fierce intensity. It is a majestic and powerful creature, one that commands both respect and fear.
|
||||
```
|
||||
|
||||
:::tip
|
||||
Notice that the `ConversationSummaryMemory` stores a summary of the conversation over time. Try using it to create better prompts as the conversation goes on.
|
||||
:::
|
||||
|
||||
## ⛓️ 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/midjourney-prompt-chain.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/MidJourney_Prompt_Chain.json" download>Download Flow</a>
|
||||
|
||||
:::note 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)
|
||||
:::
|
||||
52
docs/docs/examples/multiple-vectorstores.mdx
Normal file
52
docs/docs/examples/multiple-vectorstores.mdx
Normal file
|
|
@ -0,0 +1,52 @@
|
|||
# Multiple Vector Stores
|
||||
|
||||
The example below shows an agent operating with two vector stores built upon different data sources.
|
||||
|
||||
The `TextLoader` loads a TXT file, while the `WebBaseLoader` pulls text from webpages into a document format to accessed downstream. The `Chroma` vector stores are created analogous to what we have demonstrated in our [CSV Loader](/examples/csv-loader.mdx) example. Finally, the `VectorStoreRouterAgent` constructs an agent that routes between the vector stores.
|
||||
|
||||
:::info
|
||||
Get the TXT file used [here](https://github.com/hwchase17/chat-your-data/blob/master/state_of_the_union.txt).
|
||||
:::
|
||||
|
||||
URL used by the `WebBaseLoader`:
|
||||
|
||||
```txt
|
||||
https://pt.wikipedia.org/wiki/Harry_Potter
|
||||
```
|
||||
|
||||
:::tip
|
||||
When you build the flow, request information about one of the sources. The agent should be able to use the correct source to generate a response.
|
||||
:::
|
||||
|
||||
:::info
|
||||
Learn more about Multiple Vector Stores [here](https://python.langchain.com/docs/modules/agents/toolkits/vectorstore?highlight=Multiple%20Vector%20Stores#multiple-vectorstores).
|
||||
:::
|
||||
|
||||
## ⛓️ 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/multiple-vectorstores.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/Multiple_Vector_Stores.json" download>Download Flow</a>
|
||||
|
||||
:::note 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)
|
||||
- [`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)
|
||||
- [`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)
|
||||
|
||||
:::
|
||||
48
docs/docs/examples/python-function.mdx
Normal file
48
docs/docs/examples/python-function.mdx
Normal file
|
|
@ -0,0 +1,48 @@
|
|||
# Python Function
|
||||
|
||||
Langflow allows you to create a customized tool using the `PythonFunction` connected to a `Tool` component. In this example, Regex is used in Python to validate a pattern.
|
||||
|
||||
```python
|
||||
import re
|
||||
|
||||
def is_brazilian_zipcode(zipcode: str) -> bool:
|
||||
pattern = r"\d{5}-?\d{3}"
|
||||
|
||||
# Check if the zip code matches the pattern
|
||||
if re.match(pattern, zipcode):
|
||||
return True
|
||||
|
||||
return False
|
||||
```
|
||||
|
||||
:::tip
|
||||
When a tool is called, it is often desirable to have its output returned directly to the user. You can do this by setting the **return_direct** flag for a tool to be True.
|
||||
:::
|
||||
|
||||
The `AgentInitializer` component is a quick way to construct an agent from the model and tools.
|
||||
|
||||
:::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).
|
||||
:::
|
||||
|
||||
## ⛓️ 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/python-function.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/Python_Function.json" download>Download Flow</a>
|
||||
|
||||
:::note LangChain Components 🦜🔗
|
||||
|
||||
- [`PythonFunctionTool`](https://python.langchain.com/docs/modules/agents/tools/how_to/custom_tools)
|
||||
- [`ChatOpenAI`](https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai)
|
||||
- [`AgentInitializer`](https://python.langchain.com/docs/modules/agents/)
|
||||
:::
|
||||
45
docs/docs/examples/serp-api-tool.mdx
Normal file
45
docs/docs/examples/serp-api-tool.mdx
Normal file
|
|
@ -0,0 +1,45 @@
|
|||
# Serp API Tool
|
||||
|
||||
The [Serp API](https://serpapi.com/) (Search Engine Results Page) allows developers to scrape results from search engines such as Google, Bing and Yahoo, and can be used as in Langflow through the `Search` component.
|
||||
|
||||
:::info
|
||||
To use the Serp API, you first need to sign up [Serp API](https://serpapi.com/) for an API key on the provider's website.
|
||||
:::
|
||||
|
||||
Here, the `ZeroShotPrompt` component specifies a prompt template for the `ZeroShotAgent`. Set a _Prefix_ and _Suffix_ with rules for the agent to obey. In the example, we used default templates.
|
||||
|
||||
The `LLMChain` is a simple chain that takes in a prompt template, formats it with the user input, and returns the response from an LLM.
|
||||
|
||||
:::tip
|
||||
In this example, we used [`ChatOpenAI`](https://platform.openai.com/) as the LLM, but feel free to experiment with other Language Models!
|
||||
:::
|
||||
|
||||
The `ZeroShotAgent` takes the `LLMChain` and the `Search` tool as inputs, using the tool to find information when necessary.
|
||||
|
||||
:::info
|
||||
Learn more about the Serp API [here](https://python.langchain.com/docs/modules/agents/tools/integrations/serpapi).
|
||||
:::
|
||||
|
||||
## ⛓️ 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/serp-api-tool.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
#### <a target="\_blank" href="json_files/SerpAPI_Tool.json" download>Download Flow</a>
|
||||
|
||||
:::note LangChain Components 🦜🔗
|
||||
|
||||
- [`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)
|
||||
- [`ZeroShotAgent`](https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent)
|
||||
:::
|
||||
37
docs/docs/getting-started/creating-flows.mdx
Normal file
37
docs/docs/getting-started/creating-flows.mdx
Normal file
|
|
@ -0,0 +1,37 @@
|
|||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import ReactPlayer from "react-player";
|
||||
|
||||
# 🎨 Creating Flows
|
||||
|
||||
## 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.
|
||||
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/langflow_canvas.png",
|
||||
}}
|
||||
/>
|
||||
|
||||
## Fork
|
||||
|
||||
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.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_fork.mp4" />
|
||||
</div>
|
||||
|
||||
## Build
|
||||
|
||||
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" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_build.mp4" />
|
||||
</div>
|
||||
20
docs/docs/getting-started/hugging-face-spaces.mdx
Normal file
20
docs/docs/getting-started/hugging-face-spaces.mdx
Normal file
|
|
@ -0,0 +1,20 @@
|
|||
# 🤗 HuggingFace Spaces
|
||||
|
||||
A fully featured version of Langflow can be accessed via HuggingFace spaces with no installation required.
|
||||
|
||||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/hugging-face.png",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
|
||||
Check out Langflow on [HuggingFace Spaces](https://huggingface.co/spaces/Logspace/Langflow).
|
||||
15
docs/docs/getting-started/installation.md
Normal file
15
docs/docs/getting-started/installation.md
Normal file
|
|
@ -0,0 +1,15 @@
|
|||
# 📦 How to install?
|
||||
|
||||
## Installation
|
||||
|
||||
You can install Langflow from pip:
|
||||
|
||||
```bash
|
||||
pip install langflow
|
||||
```
|
||||
|
||||
Next, run:
|
||||
|
||||
```bash
|
||||
langflow
|
||||
```
|
||||
13
docs/docs/guidelines/collection.mdx
Normal file
13
docs/docs/guidelines/collection.mdx
Normal file
|
|
@ -0,0 +1,13 @@
|
|||
import ThemedImage from '@theme/ThemedImage';
|
||||
import useBaseUrl from '@docusaurus/useBaseUrl';
|
||||
import ZoomableImage from '/src/theme/ZoomableImage.js';
|
||||
import ReactPlayer from 'react-player';
|
||||
|
||||
# Collection
|
||||
|
||||
A collection is a snapshot of the flows available in the database. You can download your entire collection for local storage and upload it anytime for future use.
|
||||
|
||||
<div style={{ marginBottom: '20px', display: 'flex', justifyContent: 'center' }}>
|
||||
<ReactPlayer playing controls url='/videos/langflow_collection.mp4'
|
||||
/>
|
||||
</div>
|
||||
59
docs/docs/guidelines/components.mdx
Normal file
59
docs/docs/guidelines/components.mdx
Normal file
|
|
@ -0,0 +1,59 @@
|
|||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import ReactPlayer from "react-player";
|
||||
|
||||
# Component
|
||||
|
||||
Components are the building blocks of the flows. They are made of inputs, outputs, and parameters that define their functionality, providing a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the LangChain [documentation](https://docs.langchain.com/docs/category/components) section.
|
||||
|
||||
### Component's Features
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
During the flow creation process, you will notice handles (colored circles)
|
||||
attached to one or both sides of a component. These handles represent the
|
||||
availability to connect to other components, while their colors are type hints
|
||||
(hover over a handle to see connection details).
|
||||
</div>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
For example, if you select a <code>ConversationChain</code> component, you
|
||||
will see orange <span style={{ color: "orange" }}>o</span> and purple{" "}
|
||||
<span style={{ color: "purple" }}>o</span> input handles. They indicate that
|
||||
this component accepts an LLM and a Memory component as inputs. The red
|
||||
asterisk <span style={{ color: "red" }}>*</span> means that at least one input
|
||||
of that type is required.
|
||||
</div>
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/single-compenent.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
On the top right corner, you will find the component status icon 🔴. Make the
|
||||
necessary connections, build the flow (⚡ zap icon on the bottom right of the
|
||||
canvas) and once the validation is completed, the status of each validated
|
||||
component should light green 🟢. Hover over the component status to reveal the
|
||||
outputs going through it in case of success, or the detected error in case of
|
||||
failure.
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
### Component's Parameters
|
||||
|
||||
Langflow components can be edited in the component settings button. Hide parameters to reduce complexity and keep the canvas clean and intuitive for experimentation.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_parameters.mp4" />
|
||||
</div>
|
||||
69
docs/docs/guidelines/features.mdx
Normal file
69
docs/docs/guidelines/features.mdx
Normal file
|
|
@ -0,0 +1,69 @@
|
|||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
import ReactPlayer from "react-player";
|
||||
|
||||
# Features
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
When you click for New Project, you will see on the top left corner of the
|
||||
screen, some options such as <strong>Import</strong>, <strong>Export</strong>,{" "}
|
||||
<strong>Code</strong> and <strong>Save</strong>, as displayed in the image
|
||||
below:
|
||||
</div>
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: useBaseUrl("img/features.png"),
|
||||
}}
|
||||
style={{ width: "100%", maxWidth: "800px", margin: "0 auto" }}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div style={{ marginBottom: "20px" }}>
|
||||
Further down, we will explain each of these options.
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
### Import and Export
|
||||
|
||||
Flows can be exported and imported as JSON files.
|
||||
|
||||
:::caution
|
||||
Watch out for API keys being stored in local files.
|
||||
:::
|
||||
|
||||
---
|
||||
|
||||
### Code
|
||||
|
||||
The Code button shows snippets to use your flow as a Python object or an API.
|
||||
|
||||
**Python Code**
|
||||
|
||||
Through the Langflow package, you can load a flow from a JSON file and use it as a LangChain object.
|
||||
|
||||
```py
|
||||
from langflow import load_flow_from_json
|
||||
|
||||
flow = load_flow_from_json("path/to/flow.json")
|
||||
# Now you can use it like any chain
|
||||
flow("Hey, have you heard of Langflow?")
|
||||
```
|
||||
|
||||
**API**
|
||||
|
||||
Once you save a flow, the API endpoint is created with your latest changes. Click the "code" button to use that flow as an API. You can post-adjust component parameters using the global variable TWEAKS.
|
||||
|
||||
The example below shows a Python script making a POST request to a local API endpoint, which gets a prediction based on the message input.
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ReactPlayer playing controls url="/videos/langflow_api.mp4" />
|
||||
</div>
|
||||
18
docs/docs/index.mdx
Normal file
18
docs/docs/index.mdx
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
# 👋 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.
|
||||
|
||||
import ThemedImage from "@theme/ThemedImage";
|
||||
import useBaseUrl from "@docusaurus/useBaseUrl";
|
||||
import ZoomableImage from "/src/theme/ZoomableImage.js";
|
||||
|
||||
<div
|
||||
style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }}
|
||||
>
|
||||
<ZoomableImage
|
||||
alt="Docusaurus themed image"
|
||||
sources={{
|
||||
light: "img/new_langflow2.gif",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
127
docs/docusaurus.config.js
Normal file
127
docs/docusaurus.config.js
Normal file
|
|
@ -0,0 +1,127 @@
|
|||
const lightCodeTheme = require("prism-react-renderer/themes/github");
|
||||
|
||||
// With JSDoc @type annotations, IDEs can provide config autocompletion
|
||||
/** @type {import('@docusaurus/types').DocusaurusConfig} */
|
||||
(
|
||||
module.exports = {
|
||||
title: "Langflow Documentation",
|
||||
tagline: "Langflow is a GUI for LangChain, designed with react-flow",
|
||||
favicon: "img/favicon.ico",
|
||||
url: "https://logspace-ai.github.io",
|
||||
baseUrl: "/",
|
||||
onBrokenLinks: "throw",
|
||||
onBrokenMarkdownLinks: "warn",
|
||||
organizationName: "logspace-ai",
|
||||
projectName: "langflow",
|
||||
trailingSlash: false,
|
||||
customFields: {
|
||||
mendableAnonKey: process.env.MENDABLE_ANON_KEY,
|
||||
},
|
||||
i18n: {
|
||||
defaultLocale: "en",
|
||||
locales: ["en"],
|
||||
},
|
||||
presets: [
|
||||
[
|
||||
"@docusaurus/preset-classic",
|
||||
/** @type {import('@docusaurus/preset-classic').Options} */
|
||||
({
|
||||
docs: {
|
||||
routeBasePath: "/",
|
||||
sidebarPath: require.resolve("./sidebars.js"),
|
||||
path: "docs",
|
||||
// sidebarPath: 'sidebars.js',
|
||||
},
|
||||
theme: {
|
||||
customCss: require.resolve("./src/css/custom.css"),
|
||||
},
|
||||
}),
|
||||
],
|
||||
],
|
||||
plugins: [
|
||||
["docusaurus-node-polyfills", { excludeAliases: ["console"] }],
|
||||
"docusaurus-plugin-image-zoom",
|
||||
// ....
|
||||
async function myPlugin(context, options) {
|
||||
return {
|
||||
name: "docusaurus-tailwindcss",
|
||||
configurePostCss(postcssOptions) {
|
||||
// Appends TailwindCSS and AutoPrefixer.
|
||||
postcssOptions.plugins.push(require("tailwindcss"));
|
||||
postcssOptions.plugins.push(require("autoprefixer"));
|
||||
return postcssOptions;
|
||||
},
|
||||
};
|
||||
},
|
||||
],
|
||||
themeConfig:
|
||||
/** @type {import('@docusaurus/preset-classic').ThemeConfig} */
|
||||
({
|
||||
navbar: {
|
||||
hideOnScroll: true,
|
||||
title: "Langflow",
|
||||
logo: {
|
||||
alt: "Langflow",
|
||||
src: "img/chain.png",
|
||||
},
|
||||
items: [
|
||||
// right
|
||||
{
|
||||
position: "right",
|
||||
href: "https://github.com/logspace-ai/langflow",
|
||||
position: "right",
|
||||
className: "header-github-link",
|
||||
target: "_blank",
|
||||
rel: null,
|
||||
},
|
||||
{
|
||||
position: "right",
|
||||
href: "https://twitter.com/logspace_ai",
|
||||
position: "right",
|
||||
className: "header-twitter-link",
|
||||
target: "_blank",
|
||||
rel: null,
|
||||
},
|
||||
{
|
||||
position: "right",
|
||||
href: "https://discord.gg/EqksyE2EX9",
|
||||
position: "right",
|
||||
className: "header-discord-link",
|
||||
target: "_blank",
|
||||
rel: null,
|
||||
},
|
||||
],
|
||||
},
|
||||
tableOfContents: {
|
||||
minHeadingLevel: 2,
|
||||
maxHeadingLevel: 5,
|
||||
},
|
||||
colorMode: {
|
||||
defaultMode: "light",
|
||||
disableSwitch: true,
|
||||
respectPrefersColorScheme: false,
|
||||
},
|
||||
announcementBar: {
|
||||
content:
|
||||
'⭐️ If you like ⛓️Langflow, star it on <a target="_blank" rel="noopener noreferrer" href="https://github.com/logspace-ai/langflow">GitHub</a>! ⭐️',
|
||||
backgroundColor: "#B53D38", //Mustard Yellow #D19900 #D4B20B - Salmon #E9967A
|
||||
textColor: "#fff",
|
||||
isCloseable: false,
|
||||
},
|
||||
footer: {
|
||||
links: [],
|
||||
copyright: `Copyright © ${new Date().getFullYear()} Logspace.`,
|
||||
},
|
||||
zoom: {
|
||||
selector: ".markdown :not(a) > img:not(.no-zoom)",
|
||||
background: {
|
||||
light: "rgba(240, 240, 240, 0.9)",
|
||||
},
|
||||
config: {},
|
||||
},
|
||||
prism: {
|
||||
theme: lightCodeTheme,
|
||||
},
|
||||
}),
|
||||
}
|
||||
);
|
||||
10
docs/index.d.ts
vendored
Normal file
10
docs/index.d.ts
vendored
Normal file
|
|
@ -0,0 +1,10 @@
|
|||
declare module '*.module.scss' {
|
||||
const classes: { readonly [key: string]: string };
|
||||
export default classes;
|
||||
}
|
||||
|
||||
declare module '@theme/*';
|
||||
|
||||
declare module '@components/*';
|
||||
|
||||
declare module '@docusaurus/*';
|
||||
17954
docs/package-lock.json
generated
Normal file
17954
docs/package-lock.json
generated
Normal file
File diff suppressed because it is too large
Load diff
70
docs/package.json
Normal file
70
docs/package.json
Normal file
|
|
@ -0,0 +1,70 @@
|
|||
{
|
||||
"name": "docusaurus",
|
||||
"version": "0.0.0",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"docusaurus": "docusaurus",
|
||||
"start": "docusaurus start",
|
||||
"build": "docusaurus build",
|
||||
"swizzle": "docusaurus swizzle",
|
||||
"deploy": "docusaurus deploy",
|
||||
"clear": "docusaurus clear",
|
||||
"serve": "docusaurus serve",
|
||||
"write-translations": "docusaurus write-translations",
|
||||
"write-heading-ids": "docusaurus write-heading-ids"
|
||||
},
|
||||
"dependencies": {
|
||||
"@babel/preset-react": "^7.22.3",
|
||||
"@docusaurus/core": "2.4.1",
|
||||
"@docusaurus/plugin-ideal-image": "^2.4.1",
|
||||
"@docusaurus/preset-classic": "2.4.1",
|
||||
"@docusaurus/theme-classic": "^2.4.1",
|
||||
"@docusaurus/theme-search-algolia": "^2.4.1",
|
||||
"@mdx-js/react": "^1.6.22",
|
||||
"@mendable/search": "^0.0.114",
|
||||
"@pbe/react-yandex-maps": "^1.2.4",
|
||||
"@prismicio/client": "^7.0.1",
|
||||
"@uiball/loaders": "^1.2.6",
|
||||
"autoprefixer": "^10.4.14",
|
||||
"clsx": "^1.2.1",
|
||||
"docusaurus-plugin-image-zoom": "^0.1.4",
|
||||
"jquery": "^3.7.0",
|
||||
"medium-zoom": "^1.0.8",
|
||||
"node-fetch": "^3.3.1",
|
||||
"path-browserify": "^1.0.1",
|
||||
"postcss": "^8.4.24",
|
||||
"prism-react-renderer": "^1.3.5",
|
||||
"react": "^17.0.2",
|
||||
"react-dom": "^17.0.2",
|
||||
"react-images": "^0.6.7",
|
||||
"react-medium-image-zoom": "^5.1.6",
|
||||
"react-player": "^2.12.0",
|
||||
"react-transition-group": "^4.4.5",
|
||||
"remark-parse": "^10.0.2",
|
||||
"swizzle": "^1.1.0",
|
||||
"tailwindcss": "^3.3.2"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@docusaurus/module-type-aliases": "2.4.1",
|
||||
"css-loader": "^6.8.1",
|
||||
"docusaurus-node-polyfills": "^1.0.0",
|
||||
"node-sass": "^9.0.0",
|
||||
"sass": "^1.62.1",
|
||||
"ts-loader": "^9.4.3"
|
||||
},
|
||||
"browserslist": {
|
||||
"production": [
|
||||
">0.5%",
|
||||
"not dead",
|
||||
"not op_mini all"
|
||||
],
|
||||
"development": [
|
||||
"last 1 chrome version",
|
||||
"last 1 firefox version",
|
||||
"last 1 safari version"
|
||||
]
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=16.14"
|
||||
}
|
||||
}
|
||||
18
docs/plugins/index.js
Normal file
18
docs/plugins/index.js
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
module.exports = function(context, options) {
|
||||
return {
|
||||
name: 'loaders',
|
||||
configureWebpack(config, isServer) {
|
||||
return {
|
||||
module: {
|
||||
rules: [
|
||||
{
|
||||
test: /\.(gif|png|jpe?g|svg)$/i,
|
||||
exclude: /\.(mdx?)$/i,
|
||||
use: ['file-loader', { loader: 'image-webpack-loader' }],
|
||||
},
|
||||
],
|
||||
},
|
||||
};
|
||||
},
|
||||
};
|
||||
};
|
||||
66
docs/sidebars.js
Normal file
66
docs/sidebars.js
Normal file
|
|
@ -0,0 +1,66 @@
|
|||
module.exports = {
|
||||
docs: [
|
||||
{
|
||||
type: "category",
|
||||
label: "Getting Started",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"index",
|
||||
"getting-started/installation",
|
||||
"getting-started/hugging-face-spaces",
|
||||
"getting-started/creating-flows",
|
||||
],
|
||||
},
|
||||
{
|
||||
type: "category",
|
||||
label: "Guidelines",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"guidelines/components",
|
||||
"guidelines/features",
|
||||
"guidelines/collection",
|
||||
],
|
||||
},
|
||||
// {
|
||||
// type: 'category',
|
||||
// label: 'Components',
|
||||
// collapsed: false,
|
||||
// items: [
|
||||
// 'components/agents', 'components/chains', 'components/loaders', 'components/embeddings', 'components/llms',
|
||||
// 'components/memories', 'components/prompts','components/text-splitters', 'components/toolkits', 'components/tools',
|
||||
// 'components/utilities', 'components/vector-stores', 'components/wrappers',
|
||||
// ],
|
||||
// },
|
||||
{
|
||||
type: "category",
|
||||
label: "Examples",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"examples/conversation-chain",
|
||||
"examples/buffer-memory",
|
||||
"examples/midjourney-prompt-chain",
|
||||
"examples/csv-loader",
|
||||
"examples/serp-api-tool",
|
||||
"examples/multiple-vectorstores",
|
||||
"examples/python-function",
|
||||
"examples/how-upload-examples",
|
||||
],
|
||||
},
|
||||
{
|
||||
type: "category",
|
||||
label: "Deployment",
|
||||
collapsed: false,
|
||||
items: ["deployment/gcp-deployment", "deployment/jina-deployment"],
|
||||
},
|
||||
{
|
||||
type: "category",
|
||||
label: "Contributing",
|
||||
collapsed: false,
|
||||
items: [
|
||||
"contributing/how-contribute",
|
||||
"contributing/github-issues",
|
||||
"contributing/community",
|
||||
],
|
||||
},
|
||||
],
|
||||
};
|
||||
4
docs/spell_add.sh
Normal file
4
docs/spell_add.sh
Normal file
|
|
@ -0,0 +1,4 @@
|
|||
for line in $(cat spell_check_results.txt); do
|
||||
echo "Adding $line to cspell.config.yaml"
|
||||
echo " - $line" >> cspell.config.yaml
|
||||
done
|
||||
26
docs/spell_check.sh
Normal file
26
docs/spell_check.sh
Normal file
|
|
@ -0,0 +1,26 @@
|
|||
# Using cspell, we'll loop over each subdirectory inside ./docs and check every mdx file for spelling errors.
|
||||
# If there is an error, we'll write the word to an output file
|
||||
|
||||
# prep
|
||||
if [ -f spell_check_results.txt ]; then
|
||||
rm spell_check_results.txt
|
||||
fi
|
||||
cd docs
|
||||
|
||||
# first check, over the mdx files in the root directory
|
||||
find . -maxdepth 1 -type f -name "*.mdx" -exec cspell --words-only {} \; >> ../output.txt
|
||||
|
||||
# loop over each subdirectory and any directories inside
|
||||
for dir in */; do
|
||||
find $dir -type d -exec cspell --words-only {}/*.mdx \; >> ../output.txt
|
||||
done
|
||||
|
||||
# loop over each line in the output file and prune duplications
|
||||
cd ../
|
||||
awk '!a[$0]++' output.txt > spell_check_results.txt
|
||||
rm output.txt
|
||||
|
||||
# check the number of lines in spell_check_results.txt
|
||||
lines=$(wc -l < spell_check_results.txt)
|
||||
|
||||
echo "There are $lines spelling errors or unknown words."
|
||||
191
docs/src/css/custom.css
Normal file
191
docs/src/css/custom.css
Normal file
|
|
@ -0,0 +1,191 @@
|
|||
/**
|
||||
* Any CSS included here will be global. The classic template
|
||||
* bundles Infima by default. Infima is a CSS framework designed to
|
||||
* work well for content-centric websites.
|
||||
*/
|
||||
:root {
|
||||
--ifm-background-color: var(--token-primary-bg-c);
|
||||
--ifm-navbar-link-hover-color: initial;
|
||||
--ifm-navbar-padding-vertical: 0;
|
||||
--ifm-navbar-item-padding-vertical: 0;
|
||||
--ifm-font-family-base: -apple-system, BlinkMacSystemFont, Inter, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI emoji';
|
||||
--ifm-font-family-monospace: 'SFMono-Regular', 'Roboto Mono', Consolas, 'Liberation Mono', Menlo, Courier, monospace;
|
||||
}
|
||||
|
||||
.theme-doc-sidebar-item-category.menu__list-item:not(:first-child) {
|
||||
margin-top: 1.5rem!important;
|
||||
}
|
||||
|
||||
.docusaurus-highlight-code-line {
|
||||
background-color: rgba(0, 0, 0, 0.1);
|
||||
display: block;
|
||||
margin: 0 calc(-1 * var(--ifm-pre-padding));
|
||||
padding: 0 var(--ifm-pre-padding);
|
||||
}
|
||||
|
||||
.diagonal-box {
|
||||
transform: skewY(-6deg);
|
||||
}
|
||||
|
||||
.diagonal-content {
|
||||
transform: skewY(6deg);
|
||||
}
|
||||
|
||||
[class^='announcementBar'] {
|
||||
z-index: 10;
|
||||
}
|
||||
|
||||
.showcase {
|
||||
background-color: #fff;
|
||||
}
|
||||
|
||||
.showcase-border {
|
||||
border-color: rgba(243, 244, 246, 1);
|
||||
}
|
||||
|
||||
.text-description {
|
||||
color: rgba(107, 114, 128, 1);
|
||||
}
|
||||
|
||||
p {
|
||||
text-align: justify;
|
||||
}
|
||||
|
||||
/* apply */
|
||||
#hero-apply {
|
||||
z-index: -1;
|
||||
background-image: linear-gradient(
|
||||
var(--ifm-footer-background-color),
|
||||
var(--ifm-navbar-background-color)
|
||||
);
|
||||
}
|
||||
|
||||
.apply-form {
|
||||
background-image: linear-gradient(#fff, #f5f5fa);
|
||||
max-width: 600px;
|
||||
}
|
||||
|
||||
.apply-text {
|
||||
color: #36395a;
|
||||
}
|
||||
|
||||
/* index */
|
||||
#hero {
|
||||
background-image: linear-gradient(
|
||||
var(--ifm-footer-background-color),
|
||||
var(--ifm-navbar-background-color)
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Hero component title overrides to match other heading styles
|
||||
*/
|
||||
.hero-title {
|
||||
color: rgb(28, 30, 33);
|
||||
font-family: var(--ifm-heading-font-family);
|
||||
}
|
||||
h1 {
|
||||
font-size: 26px;
|
||||
}
|
||||
h2 {
|
||||
font-size: 22px;
|
||||
}
|
||||
h3 {
|
||||
font-size: 18px;
|
||||
}
|
||||
|
||||
body {
|
||||
font-size: 16px;
|
||||
}
|
||||
|
||||
.docsearch-logo {
|
||||
color: #21243d;
|
||||
}
|
||||
|
||||
.apply-button:hover {
|
||||
color: #fff;
|
||||
}
|
||||
|
||||
/* GitHub */
|
||||
.header-github-link:hover {
|
||||
opacity: 0.6;
|
||||
}
|
||||
|
||||
.header-github-link:before {
|
||||
content: '';
|
||||
width: 24px;
|
||||
height: 24px;
|
||||
display: flex;
|
||||
background: url("data:image/svg+xml,%3Csvg viewBox='0 0 24 24' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M12 .297c-6.63 0-12 5.373-12 12 0 5.303 3.438 9.8 8.205 11.385.6.113.82-.258.82-.577 0-.285-.01-1.04-.015-2.04-3.338.724-4.042-1.61-4.042-1.61C4.422 18.07 3.633 17.7 3.633 17.7c-1.087-.744.084-.729.084-.729 1.205.084 1.838 1.236 1.838 1.236 1.07 1.835 2.809 1.305 3.495.998.108-.776.417-1.305.76-1.605-2.665-.3-5.466-1.332-5.466-5.93 0-1.31.465-2.38 1.235-3.22-.135-.303-.54-1.523.105-3.176 0 0 1.005-.322 3.3 1.23.96-.267 1.98-.399 3-.405 1.02.006 2.04.138 3 .405 2.28-1.552 3.285-1.23 3.285-1.23.645 1.653.24 2.873.12 3.176.765.84 1.23 1.91 1.23 3.22 0 4.61-2.805 5.625-5.475 5.92.42.36.81 1.096.81 2.22 0 1.606-.015 2.896-.015 3.286 0 .315.21.69.825.57C20.565 22.092 24 17.592 24 12.297c0-6.627-5.373-12-12-12'/%3E%3C/svg%3E")
|
||||
no-repeat;
|
||||
}
|
||||
|
||||
/* Twitter */
|
||||
.header-twitter-link:hover {
|
||||
opacity: 0.6;
|
||||
}
|
||||
|
||||
.header-twitter-link::before {
|
||||
content: '';
|
||||
width: 24px;
|
||||
height: 24px;
|
||||
display: flex;
|
||||
background: url("/logos/twitter.svg");
|
||||
background-size: contain;
|
||||
}
|
||||
|
||||
/* Discord */
|
||||
.header-discord-link:hover {
|
||||
opacity: 0.6;
|
||||
}
|
||||
|
||||
.header-discord-link::before {
|
||||
content: '';
|
||||
width: 24px;
|
||||
height: 24px;
|
||||
display: flex;
|
||||
background: url("/logos/discord.svg");
|
||||
background-size: contain;
|
||||
}
|
||||
|
||||
|
||||
/* Images */
|
||||
.image-rendering-crisp {
|
||||
image-rendering: crisp-edges;
|
||||
|
||||
/* alias for google chrome */
|
||||
image-rendering: -webkit-optimize-contrast;
|
||||
}
|
||||
|
||||
.image-rendering-pixel {
|
||||
image-rendering: pixelated;
|
||||
}
|
||||
|
||||
.img-center {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
width: 100%,
|
||||
}
|
||||
|
||||
.resized-image {
|
||||
width: 400px;
|
||||
}
|
||||
|
||||
/* Reduce width on mobile for Mendable Search */
|
||||
@media (max-width: 767px) {
|
||||
.mendable-search {
|
||||
width: 200px;
|
||||
}
|
||||
}
|
||||
|
||||
@media (max-width: 500px) {
|
||||
.mendable-search {
|
||||
width: 150px;
|
||||
}
|
||||
}
|
||||
|
||||
@media (max-width: 380px) {
|
||||
.mendable-search {
|
||||
width: 140px;
|
||||
}
|
||||
}
|
||||
23
docs/src/pages/index.module.css
Normal file
23
docs/src/pages/index.module.css
Normal file
|
|
@ -0,0 +1,23 @@
|
|||
/**
|
||||
* CSS files with the .module.css suffix will be treated as CSS modules
|
||||
* and scoped locally.
|
||||
*/
|
||||
|
||||
.heroBanner {
|
||||
padding: 4rem 0;
|
||||
text-align: center;
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
@media screen and (max-width: 996px) {
|
||||
.heroBanner {
|
||||
padding: 2rem;
|
||||
}
|
||||
}
|
||||
|
||||
.buttons {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
}
|
||||
7
docs/src/pages/markdown-page.md
Normal file
7
docs/src/pages/markdown-page.md
Normal file
|
|
@ -0,0 +1,7 @@
|
|||
---
|
||||
title: Markdown page example
|
||||
---
|
||||
|
||||
# Markdown page example
|
||||
|
||||
You don't need React to write simple standalone pages.
|
||||
50
docs/src/theme/Footer.js
Normal file
50
docs/src/theme/Footer.js
Normal file
|
|
@ -0,0 +1,50 @@
|
|||
import React from "react";
|
||||
import Footer from "@theme-original/Footer";
|
||||
import { MendableFloatingButton } from "@mendable/search";
|
||||
|
||||
export default function FooterWrapper(props) {
|
||||
const iconSpan1 = React.createElement(
|
||||
"img",
|
||||
{
|
||||
src: "/img/chain.png",
|
||||
style: { width: "40px" },
|
||||
},
|
||||
null
|
||||
);
|
||||
|
||||
const icon = React.createElement(
|
||||
"div",
|
||||
{
|
||||
style: {
|
||||
color: "#000000",
|
||||
fontSize: "22px",
|
||||
width: "48px",
|
||||
height: "48px",
|
||||
margin: "0px",
|
||||
padding: "0px",
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
textAlign: "center",
|
||||
},
|
||||
},
|
||||
[iconSpan1]
|
||||
);
|
||||
const {
|
||||
siteConfig: { customFields },
|
||||
} = useDocusaurusContext();
|
||||
|
||||
const mendableFloatingButton = React.createElement(MendableFloatingButton, {
|
||||
floatingButtonStyle: { color: "#000000", backgroundColor: "#f6f6f6" },
|
||||
anon_key: customFields.mendableAnonKey, // Mendable Search Public ANON key, ok to be public
|
||||
showSimpleSearch: true,
|
||||
icon: icon,
|
||||
});
|
||||
|
||||
return (
|
||||
<>
|
||||
<Footer />
|
||||
{mendableFloatingButton}
|
||||
</>
|
||||
);
|
||||
}
|
||||
5
docs/src/theme/SearchBar.js
Normal file
5
docs/src/theme/SearchBar.js
Normal file
|
|
@ -0,0 +1,5 @@
|
|||
// By default, the classic theme does not provide any SearchBar implementation
|
||||
// If you swizzled this, it is your responsibility to provide an implementation
|
||||
// Tip: swizzle the SearchBar from the Algolia theme for inspiration:
|
||||
// npm run swizzle @docusaurus/theme-search-algolia SearchBar
|
||||
export {default} from '@docusaurus/Noop';
|
||||
47
docs/src/theme/ZoomableImage.js
Normal file
47
docs/src/theme/ZoomableImage.js
Normal file
|
|
@ -0,0 +1,47 @@
|
|||
import React, { useState, useEffect } from 'react';
|
||||
import ThemedImage from '@theme/ThemedImage';
|
||||
import useBaseUrl from '@docusaurus/useBaseUrl';
|
||||
|
||||
const ZoomableImage = ({ alt, sources }) => {
|
||||
const [isFullscreen, setIsFullscreen] = useState(false);
|
||||
|
||||
const toggleFullscreen = () => {
|
||||
setIsFullscreen(!isFullscreen);
|
||||
};
|
||||
|
||||
const handleKeyPress = (event) => {
|
||||
if (event.key === 'Escape') {
|
||||
setIsFullscreen(false);
|
||||
}
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
if (isFullscreen) {
|
||||
document.addEventListener('keydown', handleKeyPress);
|
||||
} else {
|
||||
document.removeEventListener('keydown', handleKeyPress);
|
||||
}
|
||||
|
||||
return () => {
|
||||
document.removeEventListener('keydown', handleKeyPress);
|
||||
};
|
||||
}, [isFullscreen]);
|
||||
|
||||
return (
|
||||
<div
|
||||
className={`zoomable-image ${isFullscreen ? 'fullscreen' : ''}`}
|
||||
onClick={toggleFullscreen}
|
||||
>
|
||||
<ThemedImage
|
||||
className="zoomable-image-inner"
|
||||
alt={alt}
|
||||
sources={{
|
||||
light: useBaseUrl(sources.light),
|
||||
dark: useBaseUrl(sources.dark),
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default ZoomableImage;
|
||||
0
docs/static/.nojekyll
vendored
Normal file
0
docs/static/.nojekyll
vendored
Normal file
1
docs/static/CNAME
vendored
Normal file
1
docs/static/CNAME
vendored
Normal file
|
|
@ -0,0 +1 @@
|
|||
langflow.org
|
||||
101
docs/static/data/organizations-100.csv
vendored
Normal file
101
docs/static/data/organizations-100.csv
vendored
Normal file
|
|
@ -0,0 +1,101 @@
|
|||
Index,Organization Id,Name,Website,Country,Description,Founded,Industry,Number of employees
|
||||
1,FAB0d41d5b5d22c,Ferrell LLC,https://price.net/,Papua New Guinea,Horizontal empowering knowledgebase,1990,Plastics,3498
|
||||
2,6A7EdDEA9FaDC52,"Mckinney, Riley and Day",http://www.hall-buchanan.info/,Finland,User-centric system-worthy leverage,2015,Glass / Ceramics / Concrete,4952
|
||||
3,0bFED1ADAE4bcC1,Hester Ltd,http://sullivan-reed.com/,China,Switchable scalable moratorium,1971,Public Safety,5287
|
||||
4,2bFC1Be8a4ce42f,Holder-Sellers,https://becker.com/,Turkmenistan,De-engineered systemic artificial intelligence,2004,Automotive,921
|
||||
5,9eE8A6a4Eb96C24,Mayer Group,http://www.brewer.com/,Mauritius,Synchronized needs-based challenge,1991,Transportation,7870
|
||||
6,cC757116fe1C085,Henry-Thompson,http://morse.net/,Bahamas,Face-to-face well-modulated customer loyalty,1992,Primary / Secondary Education,4914
|
||||
7,219233e8aFF1BC3,Hansen-Everett,https://www.kidd.org/,Pakistan,Seamless disintermediate collaboration,2018,Publishing Industry,7832
|
||||
8,ccc93DCF81a31CD,Mcintosh-Mora,https://www.brooks.com/,Heard Island and McDonald Islands,Centralized attitude-oriented capability,1970,Import / Export,4389
|
||||
9,0B4F93aA06ED03e,Carr Inc,http://ross.com/,Kuwait,Distributed impactful customer loyalty,1996,Plastics,8167
|
||||
10,738b5aDe6B1C6A5,Gaines Inc,http://sandoval-hooper.com/,Uzbekistan,Multi-lateral scalable protocol,1997,Outsourcing / Offshoring,9698
|
||||
11,AE61b8Ffebbc476,Kidd Group,http://www.lyons.com/,Bouvet Island (Bouvetoya),Proactive foreground paradigm,2001,Primary / Secondary Education,7473
|
||||
12,eb3B7D06cCdD609,Crane-Clarke,https://www.sandoval.com/,Denmark,Front-line clear-thinking encryption,2014,Food / Beverages,9011
|
||||
13,8D0c29189C9798B,"Keller, Campos and Black",https://www.garner.info/,Liberia,Ameliorated directional emulation,2020,Museums / Institutions,2862
|
||||
14,D2c91cc03CA394c,Glover-Pope,http://www.silva.biz/,United Arab Emirates,Persevering contextually-based approach,2013,Medical Practice,9079
|
||||
15,C8AC1eaf9C036F4,Pacheco-Spears,https://aguilar.com/,Sweden,Secured logistical synergy,1984,Maritime,769
|
||||
16,b5D10A14f7a8AfE,Hodge-Ayers,http://www.archer-elliott.com/,Honduras,Future-proofed radical implementation,1990,Facilities Services,8508
|
||||
17,68139b5C4De03B4,"Bowers, Guerra and Krause",http://www.carrillo-nicholson.com/,Uganda,De-engineered transitional strategy,1972,Primary / Secondary Education,6986
|
||||
18,5c2EffEfdba2BdF,Mckenzie-Melton,http://montoya-thompson.com/,Hong Kong,Reverse-engineered heuristic alliance,1998,Investment Management / Hedge Fund / Private Equity,4589
|
||||
19,ba179F19F7925f5,Branch-Mann,http://www.lozano.com/,Botswana,Adaptive intangible frame,1999,Architecture / Planning,7961
|
||||
20,c1Ce9B350BAc66b,Weiss and Sons,https://barrett.com/,Korea,Sharable optimal functionalities,2011,Plastics,5984
|
||||
21,8de40AC4e6EaCa4,"Velez, Payne and Coffey",http://burton.com/,Luxembourg,Mandatory coherent synergy,1986,Wholesale,5010
|
||||
22,Aad86a4F0385F2d,Harrell LLC,http://www.frey-rosario.com/,Guadeloupe,Reverse-engineered mission-critical moratorium,2018,Construction,2185
|
||||
23,22aC3FFd64fD703,"Eaton, Reynolds and Vargas",http://www.freeman.biz/,Monaco,Self-enabling multi-tasking process improvement,2014,Luxury Goods / Jewelry,8987
|
||||
24,5Ec4C272bCf085c,Robbins-Cummings,http://donaldson-wilkins.com/,Belgium,Organic non-volatile hierarchy,1991,Pharmaceuticals,5038
|
||||
25,5fDBeA8BB91a000,Jenkins Inc,http://www.kirk.biz/,South Africa,Front-line systematic help-desk,2002,Insurance,1215
|
||||
26,dFfD6a6F9AC2d9C,"Greene, Benjamin and Novak",http://www.kent.net/,Romania,Centralized leadingedge moratorium,2012,Museums / Institutions,4941
|
||||
27,4B217cC5a0674C5,"Dickson, Richmond and Clay",http://everett.com/,Czech Republic,Team-oriented tangible complexity,1980,Real Estate / Mortgage,3122
|
||||
28,88b1f1cDcf59a37,Prince-David,http://thompson.com/,Christmas Island,Virtual holistic methodology,1970,Banking / Mortgage,1046
|
||||
29,f9F7bBCAEeC360F,Ayala LLC,http://www.zhang.com/,Philippines,Open-source zero administration hierarchy,2021,Legal Services,7664
|
||||
30,7Cb3AeFcE4Ba31e,Rivas Group,https://hebert.org/,Australia,Open-architected well-modulated capacity,1998,Logistics / Procurement,4155
|
||||
31,ccBcC32adcbc530,"Sloan, Mays and Whitehead",http://lawson.com/,Chad,Face-to-face high-level conglomeration,1997,Civil Engineering,365
|
||||
32,f5afd686b3d05F5,"Durham, Allen and Barnes",http://chan-stafford.org/,Zimbabwe,Synergistic web-enabled framework,1993,Mechanical or Industrial Engineering,6135
|
||||
33,38C6cfC5074Fa5e,Fritz-Franklin,http://www.lambert.com/,Nepal,Automated 4thgeneration website,1972,Hospitality,4516
|
||||
34,5Cd7efccCcba38f,Burch-Ewing,http://cline.net/,Taiwan,User-centric 4thgeneration system engine,1981,Venture Capital / VC,7443
|
||||
35,9E6Acb51e3F9d6F,"Glass, Barrera and Turner",https://dunlap.com/,Kyrgyz Republic,Multi-channeled 3rdgeneration open system,2020,Utilities,2610
|
||||
36,4D4d7E18321eaeC,Pineda-Cox,http://aguilar.org/,Bolivia,Fundamental asynchronous capability,2010,Human Resources / HR,1312
|
||||
37,485f5d06B938F2b,"Baker, Mccann and Macdonald",http://www.anderson-barker.com/,Kenya,Cross-group user-facing focus group,2013,Legislative Office,1638
|
||||
38,19E3a5Bf6dBDc4F,Cuevas-Moss,https://dodson-castaneda.net/,Guatemala,Extended human-resource intranet,1994,Music,9995
|
||||
39,6883A965c7b68F7,Hahn PLC,http://newman.com/,Belarus,Organic logistical leverage,2012,Electrical / Electronic Manufacturing,3715
|
||||
40,AC5B7AA74Aa4A2E,"Valentine, Ferguson and Kramer",http://stuart.net/,Jersey,Centralized secondary time-frame,1997,Non - Profit / Volunteering,3585
|
||||
41,decab0D5027CA6a,Arroyo Inc,https://www.turner.com/,Grenada,Managed demand-driven website,2006,Writing / Editing,9067
|
||||
42,dF084FbBb613eea,Walls LLC,http://www.reese-vasquez.biz/,Cape Verde,Self-enabling fresh-thinking installation,1989,Investment Management / Hedge Fund / Private Equity,1678
|
||||
43,A2D89Ab9bCcAd4e,"Mitchell, Warren and Schneider",https://fox.biz/,Trinidad and Tobago,Enhanced intangible time-frame,2021,Capital Markets / Hedge Fund / Private Equity,3816
|
||||
44,77aDc905434a49f,Prince PLC,https://www.watts.com/,Sweden,Profit-focused coherent installation,2016,Individual / Family Services,7645
|
||||
45,235fdEFE2cfDa5F,Brock-Blackwell,http://www.small.com/,Benin,Secured foreground emulation,1986,Online Publishing,7034
|
||||
46,1eD64cFe986BBbE,Walton-Barnett,https://ashley-schaefer.com/,Western Sahara,Right-sized clear-thinking flexibility,2001,Luxury Goods / Jewelry,1746
|
||||
47,CbBbFcdd0eaE2cF,Bartlett-Arroyo,https://cruz.com/,Northern Mariana Islands,Realigned didactic function,1976,Civic / Social Organization,3987
|
||||
48,49aECbDaE6aBD53,"Wallace, Madden and Morris",http://www.blevins-fernandez.biz/,Germany,Persistent real-time customer loyalty,2016,Pharmaceuticals,9443
|
||||
49,7b3fe6e7E72bFa4,Berg-Sparks,https://cisneros-love.com/,Canada,Stand-alone static implementation,1974,Arts / Crafts,2073
|
||||
50,c6DedA82A8aef7E,Gonzales Ltd,http://bird.com/,Tonga,Managed human-resource policy,1988,Consumer Goods,9069
|
||||
51,7D9FBF85cdC3871,Lawson and Sons,https://www.wong.com/,French Southern Territories,Compatible analyzing intranet,2021,Arts / Crafts,3527
|
||||
52,7dd18Fb7cB07b65,"Mcguire, Mcconnell and Olsen",https://melton-briggs.com/,Korea,Profound client-server frame,1988,Printing,8445
|
||||
53,EF5B55FadccB8Fe,Charles-Phillips,https://bowman.com/,Cote d'Ivoire,Monitored client-server implementation,2012,Mental Health Care,3450
|
||||
54,f8D4B99e11fAF5D,Odom Ltd,https://www.humphrey-hess.com/,Cote d'Ivoire,Advanced static process improvement,2012,Management Consulting,1825
|
||||
55,e24D21BFd3bF1E5,Richard PLC,https://holden-coleman.net/,Mayotte,Object-based optimizing model,1971,Broadcast Media,4942
|
||||
56,B9BdfEB6D3Ca44E,Sampson Ltd,https://blevins.com/,Cayman Islands,Intuitive local adapter,2005,Farming,1418
|
||||
57,2a74D6f3D3B268e,"Cherry, Le and Callahan",https://waller-delacruz.biz/,Nigeria,Universal human-resource collaboration,2017,Entertainment / Movie Production,7202
|
||||
58,Bf3F3f62c8aBC33,Cherry PLC,https://www.avila.info/,Marshall Islands,Persistent tertiary website,1980,Plastics,8245
|
||||
59,aeBe26B80a7a23c,Melton-Nichols,https://kennedy.com/,Palau,User-friendly clear-thinking productivity,2021,Legislative Office,8741
|
||||
60,aAeb29ad43886C6,Potter-Walsh,http://thomas-french.org/,Turkey,Optional non-volatile open system,2008,Human Resources / HR,6923
|
||||
61,bD1bc6bB6d1FeD3,Freeman-Chen,https://mathis.com/,Timor-Leste,Phased next generation adapter,1973,International Trade / Development,346
|
||||
62,EB9f456e8b7022a,Soto Group,https://norris.info/,Vietnam,Enterprise-wide executive installation,1988,Business Supplies / Equipment,9097
|
||||
63,Dfef38C51D8DAe3,"Poole, Cruz and Whitney",https://reed.info/,Reunion,Balanced analyzing groupware,1978,Marketing / Advertising / Sales,2992
|
||||
64,055ffEfB2Dd95B0,Riley Ltd,http://wiley.com/,Brazil,Optional exuding superstructure,1986,Textiles,9315
|
||||
65,cBfe4dbAE1699da,"Erickson, Andrews and Bailey",https://www.hobbs-grant.com/,Eritrea,Vision-oriented secondary project,2014,Consumer Electronics,7829
|
||||
66,fdFbecbadcdCdf1,"Wilkinson, Charles and Arroyo",http://hunter-mcfarland.com/,United States Virgin Islands,Assimilated 24/7 archive,1996,Building Materials,602
|
||||
67,5DCb8A5a5ca03c0,Floyd Ltd,http://www.whitney.com/,Falkland Islands (Malvinas),Function-based fault-tolerant concept,2017,Public Relations / PR,2911
|
||||
68,ce57DCbcFD6d618,Newman-Galloway,https://www.scott.com/,Luxembourg,Enhanced foreground collaboration,1987,Information Technology / IT,3934
|
||||
69,5aaD187dc929371,Frazier-Butler,https://www.daugherty-farley.info/,Northern Mariana Islands,Persistent interactive circuit,1972,Outsourcing / Offshoring,5130
|
||||
70,902D7Ac8b6d476b,Newton Inc,https://www.richmond-manning.info/,Netherlands Antilles,Fundamental stable info-mediaries,1976,Military Industry,563
|
||||
71,32BB9Ff4d939788,Duffy-Levy,https://www.potter.com/,Guernsey,Diverse exuding installation,1982,Wireless,6146
|
||||
72,adcB0afbE58bAe3,Wagner LLC,https://decker-esparza.com/,Uruguay,Reactive attitude-oriented toolset,1987,International Affairs,6874
|
||||
73,dfcA1c84AdB61Ac,Mccall-Holmes,http://www.dean.com/,Benin,Object-based value-added database,2009,Legal Services,696
|
||||
74,208044AC2fe52F3,Massey LLC,https://frazier.biz/,Suriname,Configurable zero administration Graphical User Interface,1986,Accounting,5004
|
||||
75,f3C365f0c1A0623,Hicks LLC,http://alvarez.biz/,Pakistan,Quality-focused client-server Graphical User Interface,1970,Computer Software / Engineering,8480
|
||||
76,ec5Bdd3CBAfaB93,"Cole, Russell and Avery",http://www.blankenship.com/,Mongolia,De-engineered fault-tolerant challenge,2000,Law Enforcement,7012
|
||||
77,DDB19Be7eeB56B4,Cummings-Rojas,https://simon-pearson.com/,Svalbard & Jan Mayen Islands,User-centric modular customer loyalty,2012,Financial Services,7529
|
||||
78,dd6CA3d0bc3cAfc,"Beasley, Greene and Mahoney",http://www.petersen-lawrence.com/,Togo,Extended content-based methodology,1976,Religious Institutions,869
|
||||
79,A0B9d56e61070e3,"Beasley, Sims and Allison",http://burke.info/,Latvia,Secured zero tolerance hub,1972,Facilities Services,6182
|
||||
80,cBa7EFe5D05Adaf,Crawford-Rivera,https://black-ramirez.org/,Cuba,Persevering exuding budgetary management,1999,Online Publishing,7805
|
||||
81,Ea3f6D52Ec73563,Montes-Hensley,https://krueger.org/,Liechtenstein,Multi-tiered secondary productivity,2009,Printing,8433
|
||||
82,bC0CEd48A8000E0,Velazquez-Odom,https://stokes.com/,Djibouti,Streamlined 6thgeneration function,2002,Alternative Dispute Resolution,4044
|
||||
83,c89b9b59BC4baa1,Eaton-Morales,https://www.reeves-graham.com/,Micronesia,Customer-focused explicit frame,1990,Capital Markets / Hedge Fund / Private Equity,7013
|
||||
84,FEC51bce8421a7b,"Roberson, Pennington and Palmer",http://www.keith-fisher.com/,Cameroon,Adaptive bi-directional hierarchy,1993,Telecommunications,5571
|
||||
85,e0E8e27eAc9CAd5,"George, Russo and Guerra",https://drake.com/,Sweden,Centralized non-volatile capability,1989,Military Industry,2880
|
||||
86,B97a6CF9bf5983C,Davila Inc,https://mcconnell.info/,Cocos (Keeling) Islands,Profit-focused dedicated frame,2017,Consumer Electronics,2215
|
||||
87,a0a6f9b3DbcBEb5,Mays-Preston,http://www.browning-key.com/,Mali,User-centric heuristic focus group,2006,Military Industry,5786
|
||||
88,8cC1bDa330a5871,Pineda-Morton,https://www.carr.com/,United States Virgin Islands,Grass-roots methodical info-mediaries,1991,Printing,6168
|
||||
89,ED889CB2FE9cbd3,Huang and Sons,https://www.bolton.com/,Eritrea,Re-contextualized dynamic hierarchy,1981,Semiconductors,7484
|
||||
90,F4Dc1417BC6cb8f,Gilbert-Simon,https://www.bradford.biz/,Burundi,Grass-roots radical parallelism,1973,Newspapers / Journalism,1927
|
||||
91,7ABc3c7ecA03B34,Sampson-Griffith,http://hendricks.org/,Benin,Multi-layered composite paradigm,1972,Textiles,3881
|
||||
92,4e0719FBE38e0aB,Miles-Dominguez,http://www.turner.com/,Gibraltar,Organized empowering forecast,1996,Civic / Social Organization,897
|
||||
93,dEbDAAeDfaed00A,Rowe and Sons,https://www.simpson.org/,El Salvador,Balanced multimedia knowledgebase,1978,Facilities Services,8172
|
||||
94,61BDeCfeFD0cEF5,"Valenzuela, Holmes and Rowland",https://www.dorsey.net/,Taiwan,Persistent tertiary focus group,1999,Transportation,1483
|
||||
95,4e91eD25f486110,"Best, Wade and Shepard",https://zimmerman.com/,Zimbabwe,Innovative background definition,1991,Gambling / Casinos,4873
|
||||
96,0a0bfFbBbB8eC7c,Holmes Group,https://mcdowell.org/,Ethiopia,Right-sized zero tolerance focus group,1975,Photography,2988
|
||||
97,BA6Cd9Dae2Efd62,Good Ltd,http://duffy.com/,Anguilla,Reverse-engineered composite moratorium,1971,Consumer Services,4292
|
||||
98,E7df80C60Abd7f9,Clements-Espinoza,http://www.flowers.net/,Falkland Islands (Malvinas),Progressive modular hub,1991,Broadcast Media,236
|
||||
99,AFc285dbE2fEd24,Mendez Inc,https://www.burke.net/,Kyrgyz Republic,User-friendly exuding migration,1993,Education Management,339
|
||||
100,e9eB5A60Cef8354,Watkins-Kaiser,http://www.herring.com/,Togo,Synergistic background access,2009,Financial Services,2785
|
||||
|
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||||
</svg>
|
||||
|
After Width: | Height: | Size: 1.5 KiB |
3
docs/static/logos/twitter.svg
vendored
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3
docs/static/logos/twitter.svg
vendored
Normal file
|
|
@ -0,0 +1,3 @@
|
|||
<svg width="18" height="18" viewBox="0 0 24 20" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
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After Width: | Height: | Size: 1.1 KiB |
BIN
docs/static/videos/langflow_api.mp4
vendored
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BIN
docs/static/videos/langflow_api.mp4
vendored
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Binary file not shown.
BIN
docs/static/videos/langflow_build.mp4
vendored
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BIN
docs/static/videos/langflow_build.mp4
vendored
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Binary file not shown.
BIN
docs/static/videos/langflow_collection.mp4
vendored
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BIN
docs/static/videos/langflow_collection.mp4
vendored
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BIN
docs/static/videos/langflow_collection_example.mp4
vendored
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BIN
docs/static/videos/langflow_collection_example.mp4
vendored
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BIN
docs/static/videos/langflow_fork.mp4
vendored
Normal file
BIN
docs/static/videos/langflow_fork.mp4
vendored
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BIN
docs/static/videos/langflow_parameters.mp4
vendored
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docs/static/videos/langflow_parameters.mp4
vendored
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Binary file not shown.
12
docs/tailwind.config.js
Normal file
12
docs/tailwind.config.js
Normal file
|
|
@ -0,0 +1,12 @@
|
|||
module.exports = {
|
||||
content: ['./src/**/*.html', './src/**/*.js', './src/**/*.tsx'],
|
||||
corePlugins: { preflight: false, container: false },
|
||||
important: '#tailwind',
|
||||
theme: {
|
||||
extend: {
|
||||
maxWidth: {
|
||||
xxs: '18rem',
|
||||
},
|
||||
},
|
||||
},
|
||||
};
|
||||
510
poetry.lock
generated
510
poetry.lock
generated
|
|
@ -647,14 +647,14 @@ uvicorn = {version = ">=0.18.3", extras = ["standard"]}
|
|||
|
||||
[[package]]
|
||||
name = "click"
|
||||
version = "8.1.4"
|
||||
version = "8.1.5"
|
||||
description = "Composable command line interface toolkit"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "click-8.1.4-py3-none-any.whl", hash = "sha256:2739815aaa5d2c986a88f1e9230c55e17f0caad3d958a5e13ad0797c166db9e3"},
|
||||
{file = "click-8.1.4.tar.gz", hash = "sha256:b97d0c74955da062a7d4ef92fadb583806a585b2ea81958a81bd72726cbb8e37"},
|
||||
{file = "click-8.1.5-py3-none-any.whl", hash = "sha256:e576aa487d679441d7d30abb87e1b43d24fc53bffb8758443b1a9e1cee504548"},
|
||||
{file = "click-8.1.5.tar.gz", hash = "sha256:4be4b1af8d665c6d942909916d31a213a106800c47d0eeba73d34da3cbc11367"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -767,14 +767,14 @@ sqlalchemy = ["sqlalchemy (>1.3.21,<2.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "cohere"
|
||||
version = "4.12.1"
|
||||
version = "4.13.0"
|
||||
description = ""
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7,<4.0"
|
||||
files = [
|
||||
{file = "cohere-4.12.1-py3-none-any.whl", hash = "sha256:80d17ae928873cdf63883a338618e477de5c71b3d510d7891af7dfdabc25186e"},
|
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{file = "cohere-4.12.1.tar.gz", hash = "sha256:2e93a094757576d6c8d42e76363aa7841eb4166c5b0de8e5ed7272783982d2a4"},
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{file = "cohere-4.13.0-py3-none-any.whl", hash = "sha256:ac8faf352c9e8794dfd05002ce52b7d4f6da8f47a20172c8640ed58e8dfd3f10"},
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{file = "cohere-4.13.0.tar.gz", hash = "sha256:7c8e65aa4fc50fe6a9e8fe19d64e18b77d4250ec70845d480c68644d5a903253"},
|
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]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1448,86 +1448,73 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "frozenlist"
|
||||
version = "1.3.3"
|
||||
version = "1.4.0"
|
||||
description = "A list-like structure which implements collections.abc.MutableSequence"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
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{file = "frozenlist-1.3.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff8bf625fe85e119553b5383ba0fb6aa3d0ec2ae980295aaefa552374926b3f4"},
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|
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]
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||||
|
||||
[[package]]
|
||||
|
|
@ -1623,14 +1610,14 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
|
|||
|
||||
[[package]]
|
||||
name = "google-api-python-client"
|
||||
version = "2.92.0"
|
||||
version = "2.93.0"
|
||||
description = "Google API Client Library for Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "google-api-python-client-2.92.0.tar.gz", hash = "sha256:f38a6e106a7417719715506d36f0a233ec253335e422bda311352866a86c4187"},
|
||||
{file = "google_api_python_client-2.92.0-py2.py3-none-any.whl", hash = "sha256:e0b74ed5fa9bdb07a66fb030d3f4cae550ed1c07e23600d86450d3c3c5efae51"},
|
||||
{file = "google-api-python-client-2.93.0.tar.gz", hash = "sha256:62ee28e96031a10a1c341f226a75ac6a4f16bdb1d888dc8222b2cdca133d0031"},
|
||||
{file = "google_api_python_client-2.93.0-py2.py3-none-any.whl", hash = "sha256:f34abb671afd488bd19d30721ea20fb30d3796ddd825d6f91f26d8c718a9f07d"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1642,14 +1629,14 @@ uritemplate = ">=3.0.1,<5"
|
|||
|
||||
[[package]]
|
||||
name = "google-auth"
|
||||
version = "2.21.0"
|
||||
version = "2.22.0"
|
||||
description = "Google Authentication Library"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "google-auth-2.21.0.tar.gz", hash = "sha256:b28e8048e57727e7cf0e5bd8e7276b212aef476654a09511354aa82753b45c66"},
|
||||
{file = "google_auth-2.21.0-py2.py3-none-any.whl", hash = "sha256:da3f18d074fa0f5a7061d99b9af8cee3aa6189c987af7c1b07d94566b6b11268"},
|
||||
{file = "google-auth-2.22.0.tar.gz", hash = "sha256:164cba9af4e6e4e40c3a4f90a1a6c12ee56f14c0b4868d1ca91b32826ab334ce"},
|
||||
{file = "google_auth-2.22.0-py2.py3-none-any.whl", hash = "sha256:d61d1b40897407b574da67da1a833bdc10d5a11642566e506565d1b1a46ba873"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2483,14 +2470,14 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "importlib-metadata"
|
||||
version = "6.0.1"
|
||||
version = "6.8.0"
|
||||
description = "Read metadata from Python packages"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "importlib_metadata-6.0.1-py3-none-any.whl", hash = "sha256:1543daade821c89b1c4a55986c326f36e54f2e6ca3bad96be4563d0acb74dcd4"},
|
||||
{file = "importlib_metadata-6.0.1.tar.gz", hash = "sha256:950127d57e35a806d520817d3e92eec3f19fdae9f0cd99da77a407c5aabefba3"},
|
||||
{file = "importlib_metadata-6.8.0-py3-none-any.whl", hash = "sha256:3ebb78df84a805d7698245025b975d9d67053cd94c79245ba4b3eb694abe68bb"},
|
||||
{file = "importlib_metadata-6.8.0.tar.gz", hash = "sha256:dbace7892d8c0c4ac1ad096662232f831d4e64f4c4545bd53016a3e9d4654743"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2499,7 +2486,7 @@ zipp = ">=0.5"
|
|||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
perf = ["ipython"]
|
||||
testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
|
||||
testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
|
||||
|
||||
[[package]]
|
||||
name = "importlib-resources"
|
||||
|
|
@ -2941,21 +2928,21 @@ testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)",
|
|||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "0.0.229"
|
||||
version = "0.0.232"
|
||||
description = "Building applications with LLMs through composability"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
files = [
|
||||
{file = "langchain-0.0.229-py3-none-any.whl", hash = "sha256:a7ca79e4ab892756ede95d212bd42243303f91b172535cefd02b0b8965e4e7b7"},
|
||||
{file = "langchain-0.0.229.tar.gz", hash = "sha256:ab1beac7f3fc1f06ab1a0b545ef0d47a3d5efef3b2b4c646aafaefc2eb3151d3"},
|
||||
{file = "langchain-0.0.232-py3-none-any.whl", hash = "sha256:33d8d498115f9af8d1851ba7fa326348848fabd314497629ac55b3b9b61e3ec1"},
|
||||
{file = "langchain-0.0.232.tar.gz", hash = "sha256:afcd5ed45adf8ec1434151f881ac9ff73d958fe3ea8d7725d7b6b603feb48c8d"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
aiohttp = ">=3.8.3,<4.0.0"
|
||||
async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
|
||||
dataclasses-json = ">=0.5.7,<0.6.0"
|
||||
langchainplus-sdk = ">=0.0.20,<0.0.21"
|
||||
langsmith = ">=0.0.5,<0.0.6"
|
||||
numexpr = ">=2.8.4,<3.0.0"
|
||||
numpy = ">=1,<2"
|
||||
openapi-schema-pydantic = ">=1.2,<2.0"
|
||||
|
|
@ -2966,13 +2953,13 @@ SQLAlchemy = ">=1.4,<3"
|
|||
tenacity = ">=8.1.0,<9.0.0"
|
||||
|
||||
[package.extras]
|
||||
all = ["O365 (>=2.0.26,<3.0.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3,<0.4)", "arxiv (>=1.4,<2.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "awadb (>=0.3.3,<0.4.0)", "azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-vision (>=0.11.1b1,<0.12.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "beautifulsoup4 (>=4,<5)", "clarifai (>=9.1.0)", "clickhouse-connect (>=0.5.14,<0.6.0)", "cohere (>=3,<4)", "deeplake (>=3.6.2,<4.0.0)", "docarray[hnswlib] (>=0.32.0,<0.33.0)", "duckduckgo-search (>=3.8.3,<4.0.0)", "elasticsearch (>=8,<9)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-auth (>=2.18.1,<3.0.0)", "google-search-results (>=2,<3)", "gptcache (>=0.1.7)", "html2text (>=2020.1.16,<2021.0.0)", "huggingface_hub (>=0,<1)", "jina (>=3.14,<4.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "lancedb (>=0.1,<0.2)", "langkit (>=0.0.1.dev3,<0.1.0)", "lark (>=1.1.5,<2.0.0)", "lxml (>=4.9.2,<5.0.0)", "manifest-ml (>=0.0.1,<0.0.2)", "marqo (>=0.11.0,<0.12.0)", "momento (>=1.5.0,<2.0.0)", "nebula3-python (>=3.4.0,<4.0.0)", "neo4j (>=5.8.1,<6.0.0)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "octoai-sdk (>=0.1.1,<0.2.0)", "openai (>=0,<1)", "openlm (>=0.0.5,<0.0.6)", "opensearch-py (>=2.0.0,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pexpect (>=4.8.0,<5.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "pinecone-text (>=0.4.2,<0.5.0)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pymongo (>=4.3.3,<5.0.0)", "pyowm (>=3.3.0,<4.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pytesseract (>=0.3.10,<0.4.0)", "pyvespa (>=0.33.0,<0.34.0)", "qdrant-client (>=1.1.2,<2.0.0)", "rdflib (>=6.3.2,<7.0.0)", "redis (>=4,<5)", "requests-toolbelt (>=1.0.0,<2.0.0)", "sentence-transformers (>=2,<3)", "singlestoredb (>=0.7.1,<0.8.0)", "spacy (>=3,<4)", "steamship (>=2.16.9,<3.0.0)", "tensorflow-text (>=2.11.0,<3.0.0)", "tigrisdb (>=1.0.0b6,<2.0.0)", "tiktoken (>=0.3.2,<0.4.0)", "torch (>=1,<3)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"]
|
||||
all = ["O365 (>=2.0.26,<3.0.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3,<0.4)", "arxiv (>=1.4,<2.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "awadb (>=0.3.3,<0.4.0)", "azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-vision (>=0.11.1b1,<0.12.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "beautifulsoup4 (>=4,<5)", "clarifai (>=9.1.0)", "clickhouse-connect (>=0.5.14,<0.6.0)", "cohere (>=3,<4)", "deeplake (>=3.6.8,<4.0.0)", "docarray[hnswlib] (>=0.32.0,<0.33.0)", "duckduckgo-search (>=3.8.3,<4.0.0)", "elasticsearch (>=8,<9)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-auth (>=2.18.1,<3.0.0)", "google-search-results (>=2,<3)", "gptcache (>=0.1.7)", "html2text (>=2020.1.16,<2021.0.0)", "huggingface_hub (>=0,<1)", "jina (>=3.14,<4.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "lancedb (>=0.1,<0.2)", "langkit (>=0.0.6,<0.1.0)", "lark (>=1.1.5,<2.0.0)", "libdeeplake (>=0.0.60,<0.0.61)", "lxml (>=4.9.2,<5.0.0)", "manifest-ml (>=0.0.1,<0.0.2)", "marqo (>=0.11.0,<0.12.0)", "momento (>=1.5.0,<2.0.0)", "nebula3-python (>=3.4.0,<4.0.0)", "neo4j (>=5.8.1,<6.0.0)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "octoai-sdk (>=0.1.1,<0.2.0)", "openai (>=0,<1)", "openlm (>=0.0.5,<0.0.6)", "opensearch-py (>=2.0.0,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pexpect (>=4.8.0,<5.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "pinecone-text (>=0.4.2,<0.5.0)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pymongo (>=4.3.3,<5.0.0)", "pyowm (>=3.3.0,<4.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pytesseract (>=0.3.10,<0.4.0)", "pyvespa (>=0.33.0,<0.34.0)", "qdrant-client (>=1.1.2,<2.0.0)", "rdflib (>=6.3.2,<7.0.0)", "redis (>=4,<5)", "requests-toolbelt (>=1.0.0,<2.0.0)", "sentence-transformers (>=2,<3)", "singlestoredb (>=0.7.1,<0.8.0)", "spacy (>=3,<4)", "steamship (>=2.16.9,<3.0.0)", "tensorflow-text (>=2.11.0,<3.0.0)", "tigrisdb (>=1.0.0b6,<2.0.0)", "tiktoken (>=0.3.2,<0.4.0)", "torch (>=1,<3)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"]
|
||||
azure = ["azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-vision (>=0.11.1b1,<0.12.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-core (>=1.26.4,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "azure-search-documents (==11.4.0a20230509004)", "openai (>=0,<1)"]
|
||||
clarifai = ["clarifai (>=9.1.0)"]
|
||||
cohere = ["cohere (>=3,<4)"]
|
||||
docarray = ["docarray[hnswlib] (>=0.32.0,<0.33.0)"]
|
||||
embeddings = ["sentence-transformers (>=2,<3)"]
|
||||
extended-testing = ["atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.0.7,<0.0.8)", "chardet (>=5.1.0,<6.0.0)", "esprima (>=4.0.1,<5.0.0)", "gql (>=3.4.1,<4.0.0)", "html2text (>=2020.1.16,<2021.0.0)", "jq (>=1.4.1,<2.0.0)", "lxml (>=4.9.2,<5.0.0)", "openai (>=0,<1)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "streamlit (>=1.18.0,<2.0.0)", "telethon (>=1.28.5,<2.0.0)", "tqdm (>=4.48.0)", "zep-python (>=0.32)"]
|
||||
extended-testing = ["atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.0.7,<0.0.8)", "chardet (>=5.1.0,<6.0.0)", "esprima (>=4.0.1,<5.0.0)", "gql (>=3.4.1,<4.0.0)", "html2text (>=2020.1.16,<2021.0.0)", "jq (>=1.4.1,<2.0.0)", "lxml (>=4.9.2,<5.0.0)", "openai (>=0,<1)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tqdm (>=4.48.0)", "zep-python (>=0.32)"]
|
||||
javascript = ["esprima (>=4.0.1,<5.0.0)"]
|
||||
llms = ["anthropic (>=0.3,<0.4)", "clarifai (>=9.1.0)", "cohere (>=3,<4)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (>=0,<1)", "openllm (>=0.1.19)", "openlm (>=0.0.5,<0.0.6)", "torch (>=1,<3)", "transformers (>=4,<5)"]
|
||||
openai = ["openai (>=0,<1)", "tiktoken (>=0.3.2,<0.4.0)"]
|
||||
|
|
@ -2981,13 +2968,13 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "langchain-serve"
|
||||
version = "0.0.54"
|
||||
version = "0.0.56"
|
||||
description = "Langchain Serve - serve your langchain apps on Jina AI Cloud."
|
||||
category = "main"
|
||||
optional = true
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "langchain-serve-0.0.54.tar.gz", hash = "sha256:5cbc980886c81f3bac7ed3337adeb0b94fc9f3645e4501dd7f0702f90766bbaa"},
|
||||
{file = "langchain-serve-0.0.56.tar.gz", hash = "sha256:47c1e0290aec07c7e6366bb1b6b866d7d3f5446fb296160ca1bf2ef522c33fac"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -3006,21 +2993,20 @@ toml = "*"
|
|||
test = ["psutil", "pytest", "pytest-asyncio"]
|
||||
|
||||
[[package]]
|
||||
name = "langchainplus-sdk"
|
||||
version = "0.0.20"
|
||||
name = "langsmith"
|
||||
version = "0.0.5"
|
||||
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
files = [
|
||||
{file = "langchainplus_sdk-0.0.20-py3-none-any.whl", hash = "sha256:07a869d476755803aa04c4986ce78d00c2fe4ff584c0eaa57d7570c9664188db"},
|
||||
{file = "langchainplus_sdk-0.0.20.tar.gz", hash = "sha256:3d300e2e3290f68cc9d842c059f9458deba60e776c9e790309688cad1bfbb219"},
|
||||
{file = "langsmith-0.0.5-py3-none-any.whl", hash = "sha256:c9ce19cf7a45d4b9ef74b3133ace4d0583bc992383296d03c05065e8f871e01f"},
|
||||
{file = "langsmith-0.0.5.tar.gz", hash = "sha256:ffad2fc638cfee8c9d27c9eae2fa3c3f9ec423bf443b1dc44cc8184fa34cd6b2"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
pydantic = ">=1,<2"
|
||||
requests = ">=2,<3"
|
||||
tenacity = ">=8.1.0,<9.0.0"
|
||||
|
||||
[[package]]
|
||||
name = "linkify-it-py"
|
||||
|
|
@ -3889,62 +3875,61 @@ et-xmlfile = "*"
|
|||
|
||||
[[package]]
|
||||
name = "opentelemetry-api"
|
||||
version = "1.18.0"
|
||||
version = "1.19.0"
|
||||
description = "OpenTelemetry Python API"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_api-1.18.0-py3-none-any.whl", hash = "sha256:d05bcc94ec239fd76fd90d784c5e3ad081a8a1ac2ffc8a2c83a49ace052d1492"},
|
||||
{file = "opentelemetry_api-1.18.0.tar.gz", hash = "sha256:2bbf29739fcef268c419e3bf1735566c2e7f81026c14bcc78b62a0b97f8ecf2f"},
|
||||
{file = "opentelemetry_api-1.19.0-py3-none-any.whl", hash = "sha256:dcd2a0ad34b691964947e1d50f9e8c415c32827a1d87f0459a72deb9afdf5597"},
|
||||
{file = "opentelemetry_api-1.19.0.tar.gz", hash = "sha256:db374fb5bea00f3c7aa290f5d94cea50b659e6ea9343384c5f6c2bb5d5e8db65"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
deprecated = ">=1.2.6"
|
||||
importlib-metadata = ">=6.0.0,<6.1.0"
|
||||
setuptools = ">=16.0"
|
||||
importlib-metadata = ">=6.0,<7.0"
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp"
|
||||
version = "1.18.0"
|
||||
version = "1.19.0"
|
||||
description = "OpenTelemetry Collector Exporters"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_exporter_otlp-1.18.0-py3-none-any.whl", hash = "sha256:2b8d18aa3f8fa360df2fe6c274132cf38939a02f8aa621d6ed060a920aa9e4c6"},
|
||||
{file = "opentelemetry_exporter_otlp-1.18.0.tar.gz", hash = "sha256:cafcf7f28debbcc22e06d52cdc4f65a118f17b730dabe8f9d4b87587e95b1481"},
|
||||
{file = "opentelemetry_exporter_otlp-1.19.0-py3-none-any.whl", hash = "sha256:5316ffc754d5a4fb4faaa811a837593edd680bed429fd7c10d898e45f4946903"},
|
||||
{file = "opentelemetry_exporter_otlp-1.19.0.tar.gz", hash = "sha256:2d4b066180452b8e74a0a598d98901769148a0fe17900c70aca37d3c7c4e8aaa"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
opentelemetry-exporter-otlp-proto-grpc = "1.18.0"
|
||||
opentelemetry-exporter-otlp-proto-http = "1.18.0"
|
||||
opentelemetry-exporter-otlp-proto-grpc = "1.19.0"
|
||||
opentelemetry-exporter-otlp-proto-http = "1.19.0"
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp-proto-common"
|
||||
version = "1.18.0"
|
||||
version = "1.19.0"
|
||||
description = "OpenTelemetry Protobuf encoding"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_exporter_otlp_proto_common-1.18.0-py3-none-any.whl", hash = "sha256:276073ccc8c6e6570fe05ca8ca0de77d662bc89bc614ec8bfbc855112f7e25e3"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_common-1.18.0.tar.gz", hash = "sha256:4d9883d6929aabe75e485950bbe8b149a14d95e50b1570426832daa6913b0871"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_common-1.19.0-py3-none-any.whl", hash = "sha256:792d5496ecfebaf4f56b2c434c5e2823f88ffaeb5dcd272ea423b249fd52bded"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_common-1.19.0.tar.gz", hash = "sha256:c13d02a31dec161f8910d96db6b58309af17d92b827c64284bf85eec3f2d7297"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
opentelemetry-proto = "1.18.0"
|
||||
opentelemetry-proto = "1.19.0"
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp-proto-grpc"
|
||||
version = "1.18.0"
|
||||
version = "1.19.0"
|
||||
description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_exporter_otlp_proto_grpc-1.18.0-py3-none-any.whl", hash = "sha256:c773bc9df2c9d6464f0d5936963399b2fc440f0616c1277f29512d540ad7e0a2"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_grpc-1.18.0.tar.gz", hash = "sha256:8eddfde4267da876871e62f1b58369986bdb7e47e43032c498f1ea807d7191c4"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_grpc-1.19.0-py3-none-any.whl", hash = "sha256:ae2a6484d12ba4d0f1096c4565193c1c27a951a9d2b10a9a84da3e1f866e84d6"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_grpc-1.19.0.tar.gz", hash = "sha256:e69261b4da8cbaa42d9b5f1cff4fcebbf8a3c02f85d69a8aea698312084f4180"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -3953,23 +3938,23 @@ deprecated = ">=1.2.6"
|
|||
googleapis-common-protos = ">=1.52,<2.0"
|
||||
grpcio = ">=1.0.0,<2.0.0"
|
||||
opentelemetry-api = ">=1.15,<2.0"
|
||||
opentelemetry-exporter-otlp-proto-common = "1.18.0"
|
||||
opentelemetry-proto = "1.18.0"
|
||||
opentelemetry-sdk = ">=1.18.0,<1.19.0"
|
||||
opentelemetry-exporter-otlp-proto-common = "1.19.0"
|
||||
opentelemetry-proto = "1.19.0"
|
||||
opentelemetry-sdk = ">=1.19.0,<1.20.0"
|
||||
|
||||
[package.extras]
|
||||
test = ["pytest-grpc"]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-exporter-otlp-proto-http"
|
||||
version = "1.18.0"
|
||||
version = "1.19.0"
|
||||
description = "OpenTelemetry Collector Protobuf over HTTP Exporter"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_exporter_otlp_proto_http-1.18.0-py3-none-any.whl", hash = "sha256:c22110705473f1c61bd4d74ded3b8bd3fac66ffbe7d9ba376267d8539919ed90"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_http-1.18.0.tar.gz", hash = "sha256:d9a2118558decf9e9a2d6573ad9d33876f3a44d7dc43f10d38a900d5a6f867d6"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_http-1.19.0-py3-none-any.whl", hash = "sha256:4e050ca57819519a3cb8a6b17feac0d3b4b115796674b6a26295036ae941e11a"},
|
||||
{file = "opentelemetry_exporter_otlp_proto_http-1.19.0.tar.gz", hash = "sha256:7c8d2c1268cef4d9c1b13a1399f510e3c3dbb88c52f54597d487a128a23b681e"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -3977,9 +3962,9 @@ backoff = {version = ">=1.10.0,<3.0.0", markers = "python_version >= \"3.7\""}
|
|||
deprecated = ">=1.2.6"
|
||||
googleapis-common-protos = ">=1.52,<2.0"
|
||||
opentelemetry-api = ">=1.15,<2.0"
|
||||
opentelemetry-exporter-otlp-proto-common = "1.18.0"
|
||||
opentelemetry-proto = "1.18.0"
|
||||
opentelemetry-sdk = ">=1.18.0,<1.19.0"
|
||||
opentelemetry-exporter-otlp-proto-common = "1.19.0"
|
||||
opentelemetry-proto = "1.19.0"
|
||||
opentelemetry-sdk = ">=1.19.0,<1.20.0"
|
||||
requests = ">=2.7,<3.0"
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -4004,14 +3989,14 @@ prometheus-client = ">=0.5.0,<1.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "opentelemetry-instrumentation"
|
||||
version = "0.39b0"
|
||||
version = "0.40b0"
|
||||
description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_instrumentation-0.39b0-py3-none-any.whl", hash = "sha256:fcfd74413159fe797e343104f7e85a3f8146713634debcac10a057ac7f1eb011"},
|
||||
{file = "opentelemetry_instrumentation-0.39b0.tar.gz", hash = "sha256:2a6d1f386aa769dc763e6f2c6b483f50c4024f1bc76a78b57f05ae05970ce5f4"},
|
||||
{file = "opentelemetry_instrumentation-0.40b0-py3-none-any.whl", hash = "sha256:789d3726e698aa9526dd247b461b9172f99a4345571546c4aecf40279679fc8e"},
|
||||
{file = "opentelemetry_instrumentation-0.40b0.tar.gz", hash = "sha256:08bebe6a752514ed61e901e9fee5ccf06ae7533074442e707d75bb65f3e0aa17"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4021,106 +4006,106 @@ wrapt = ">=1.0.0,<2.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "opentelemetry-instrumentation-aiohttp-client"
|
||||
version = "0.39b0"
|
||||
version = "0.40b0"
|
||||
description = "OpenTelemetry aiohttp client instrumentation"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_instrumentation_aiohttp_client-0.39b0-py3-none-any.whl", hash = "sha256:315adf314f35532677b7ae2abd9a663ec86df7183594605592f0e89e599d86ca"},
|
||||
{file = "opentelemetry_instrumentation_aiohttp_client-0.39b0.tar.gz", hash = "sha256:20fd66f4aa757728e48efae1351d9eed98d6e352595933f47ca042df9d83fc78"},
|
||||
{file = "opentelemetry_instrumentation_aiohttp_client-0.40b0-py3-none-any.whl", hash = "sha256:195c7089636c7639463fbc588b79bc0cf41dd2971f7da1e99a9d4433249d058d"},
|
||||
{file = "opentelemetry_instrumentation_aiohttp_client-0.40b0.tar.gz", hash = "sha256:4de0a72b922d391183d00e2a1cc32e52b88dd2a6c77311b166e566b125b19943"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
opentelemetry-api = ">=1.12,<2.0"
|
||||
opentelemetry-instrumentation = "0.39b0"
|
||||
opentelemetry-semantic-conventions = "0.39b0"
|
||||
opentelemetry-util-http = "0.39b0"
|
||||
opentelemetry-instrumentation = "0.40b0"
|
||||
opentelemetry-semantic-conventions = "0.40b0"
|
||||
opentelemetry-util-http = "0.40b0"
|
||||
wrapt = ">=1.0.0,<2.0.0"
|
||||
|
||||
[package.extras]
|
||||
instruments = ["aiohttp (>=3.0,<4.0)"]
|
||||
test = ["opentelemetry-instrumentation-aiohttp-client[instruments]"]
|
||||
test = ["http-server-mock", "opentelemetry-instrumentation-aiohttp-client[instruments]"]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-instrumentation-asgi"
|
||||
version = "0.39b0"
|
||||
version = "0.40b0"
|
||||
description = "ASGI instrumentation for OpenTelemetry"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_instrumentation_asgi-0.39b0-py3-none-any.whl", hash = "sha256:cb9cbf56e32be12b0e5e70c21cf27999f10920afc73110457f4e4b0ec4078c5f"},
|
||||
{file = "opentelemetry_instrumentation_asgi-0.39b0.tar.gz", hash = "sha256:28b76aa6b9fe41fcfa52214c2e554a79cc371927d13c40b22e7a02aff35760eb"},
|
||||
{file = "opentelemetry_instrumentation_asgi-0.40b0-py3-none-any.whl", hash = "sha256:3fc6940bacaccf2d96c24bd937a46dade28b930df8ec4e1231f612f2a66e4496"},
|
||||
{file = "opentelemetry_instrumentation_asgi-0.40b0.tar.gz", hash = "sha256:98678ef9e3856746dd52b11b8c6ce258acc70ecb910c9053ad7aaabab8fa71f2"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
asgiref = ">=3.0,<4.0"
|
||||
opentelemetry-api = ">=1.12,<2.0"
|
||||
opentelemetry-instrumentation = "0.39b0"
|
||||
opentelemetry-semantic-conventions = "0.39b0"
|
||||
opentelemetry-util-http = "0.39b0"
|
||||
opentelemetry-instrumentation = "0.40b0"
|
||||
opentelemetry-semantic-conventions = "0.40b0"
|
||||
opentelemetry-util-http = "0.40b0"
|
||||
|
||||
[package.extras]
|
||||
instruments = ["asgiref (>=3.0,<4.0)"]
|
||||
test = ["opentelemetry-instrumentation-asgi[instruments]", "opentelemetry-test-utils (==0.39b0)"]
|
||||
test = ["opentelemetry-instrumentation-asgi[instruments]", "opentelemetry-test-utils (==0.40b0)"]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-instrumentation-fastapi"
|
||||
version = "0.39b0"
|
||||
version = "0.40b0"
|
||||
description = "OpenTelemetry FastAPI Instrumentation"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_instrumentation_fastapi-0.39b0-py3-none-any.whl", hash = "sha256:33223b46393ef63229d35c4e0903e900674d3dfc65ada49fbfd51db8742295cb"},
|
||||
{file = "opentelemetry_instrumentation_fastapi-0.39b0.tar.gz", hash = "sha256:02d4d583a0a62efc9a94d489f1a736ca2905fb6f7d445ac686608de51d7e375b"},
|
||||
{file = "opentelemetry_instrumentation_fastapi-0.40b0-py3-none-any.whl", hash = "sha256:2d71b41b460ebadc347a87ef6c9595864965745a7752b1e08d064eea327e350e"},
|
||||
{file = "opentelemetry_instrumentation_fastapi-0.40b0.tar.gz", hash = "sha256:d97276a4bda9155de74b0761cdf52831d22fb93894b644ebba026501aa6f7a94"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
opentelemetry-api = ">=1.12,<2.0"
|
||||
opentelemetry-instrumentation = "0.39b0"
|
||||
opentelemetry-instrumentation-asgi = "0.39b0"
|
||||
opentelemetry-semantic-conventions = "0.39b0"
|
||||
opentelemetry-util-http = "0.39b0"
|
||||
opentelemetry-instrumentation = "0.40b0"
|
||||
opentelemetry-instrumentation-asgi = "0.40b0"
|
||||
opentelemetry-semantic-conventions = "0.40b0"
|
||||
opentelemetry-util-http = "0.40b0"
|
||||
|
||||
[package.extras]
|
||||
instruments = ["fastapi (>=0.58,<1.0)"]
|
||||
test = ["httpx (>=0.22,<1.0)", "opentelemetry-instrumentation-fastapi[instruments]", "opentelemetry-test-utils (==0.39b0)", "requests (>=2.23,<3.0)"]
|
||||
test = ["httpx (>=0.22,<1.0)", "opentelemetry-instrumentation-fastapi[instruments]", "opentelemetry-test-utils (==0.40b0)", "requests (>=2.23,<3.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-instrumentation-grpc"
|
||||
version = "0.39b0"
|
||||
version = "0.40b0"
|
||||
description = "OpenTelemetry gRPC instrumentation"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_instrumentation_grpc-0.39b0-py3-none-any.whl", hash = "sha256:1ab7a1e4a43efd8e827d1666065253fdc4dca76ca7bcf43417fe7523999e3145"},
|
||||
{file = "opentelemetry_instrumentation_grpc-0.39b0.tar.gz", hash = "sha256:766ea59ff2677301e5354d2113a635c20e462611ecd4b5fb764121759d945bb2"},
|
||||
{file = "opentelemetry_instrumentation_grpc-0.40b0-py3-none-any.whl", hash = "sha256:36904f1c25a29465efcb1cc3f90b5871b462f547cd6ab244c5ea6185872eb507"},
|
||||
{file = "opentelemetry_instrumentation_grpc-0.40b0.tar.gz", hash = "sha256:c8ac3a1db5553f17aa0d071ac0a3f520da0ef1e9c6f1d1625b211fa58b084a7f"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
opentelemetry-api = ">=1.12,<2.0"
|
||||
opentelemetry-instrumentation = "0.39b0"
|
||||
opentelemetry-instrumentation = "0.40b0"
|
||||
opentelemetry-sdk = ">=1.12,<2.0"
|
||||
opentelemetry-semantic-conventions = "0.39b0"
|
||||
opentelemetry-semantic-conventions = "0.40b0"
|
||||
wrapt = ">=1.0.0,<2.0.0"
|
||||
|
||||
[package.extras]
|
||||
instruments = ["grpcio (>=1.27,<2.0)"]
|
||||
test = ["opentelemetry-instrumentation-grpc[instruments]", "opentelemetry-sdk (>=1.12,<2.0)", "opentelemetry-test-utils (==0.39b0)", "protobuf (>=3.13,<4.0)"]
|
||||
test = ["opentelemetry-instrumentation-grpc[instruments]", "opentelemetry-sdk (>=1.12,<2.0)", "opentelemetry-test-utils (==0.40b0)", "protobuf (>=3.13,<4.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-proto"
|
||||
version = "1.18.0"
|
||||
version = "1.19.0"
|
||||
description = "OpenTelemetry Python Proto"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "opentelemetry_proto-1.18.0-py3-none-any.whl", hash = "sha256:34d1c49283f0246a58761d9322d5a79702a09afda0bb181bb6378ed26862e446"},
|
||||
{file = "opentelemetry_proto-1.18.0.tar.gz", hash = "sha256:4f38d01049c3926b9fd09833574bfb5e172d84c8ca85e2ab7f4b5a198d75aeef"},
|
||||
{file = "opentelemetry_proto-1.19.0-py3-none-any.whl", hash = "sha256:d06391cb5fa0fab111b42d3adf5f22683748745bd8f59ed4acfd93cfd252b960"},
|
||||
{file = "opentelemetry_proto-1.19.0.tar.gz", hash = "sha256:be53205622d85ecd37ebbf764aed907d87620a45eae638860cb5a778bf900c04"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -4128,44 +4113,43 @@ protobuf = ">=3.19,<5.0"
|
|||
|
||||
[[package]]
|
||||
name = "opentelemetry-sdk"
|
||||
version = "1.18.0"
|
||||
version = "1.19.0"
|
||||
description = "OpenTelemetry Python SDK"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
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||||
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||||
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||||
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
opentelemetry-api = "1.18.0"
|
||||
opentelemetry-semantic-conventions = "0.39b0"
|
||||
setuptools = ">=16.0"
|
||||
opentelemetry-api = "1.19.0"
|
||||
opentelemetry-semantic-conventions = "0.40b0"
|
||||
typing-extensions = ">=3.7.4"
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-semantic-conventions"
|
||||
version = "0.39b0"
|
||||
version = "0.40b0"
|
||||
description = "OpenTelemetry Semantic Conventions"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
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|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-util-http"
|
||||
version = "0.39b0"
|
||||
version = "0.40b0"
|
||||
description = "Web util for OpenTelemetry"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
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||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -5114,86 +5098,86 @@ plugins = ["importlib-metadata"]
|
|||
|
||||
[[package]]
|
||||
name = "pymongo"
|
||||
version = "4.4.0"
|
||||
version = "4.4.1"
|
||||
description = "Python driver for MongoDB <http://www.mongodb.org>"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
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||||
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{file = "pymongo-4.4.1-cp39-cp39-win32.whl", hash = "sha256:c409e5888a94a3ff99783fffd9477128ffab8416e3f8b2c633993eecdcd5c267"},
|
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{file = "pymongo-4.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:3681caf37edbe05f72f0d351e4a6cb5874ec7ab5eeb99df3a277dbf110093739"},
|
||||
{file = "pymongo-4.4.1.tar.gz", hash = "sha256:a4df87dbbd03ac6372d24f2a8054b4dc33de497d5227b50ec649f436ad574284"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -5201,8 +5185,8 @@ dnspython = ">=1.16.0,<3.0.0"
|
|||
|
||||
[package.extras]
|
||||
aws = ["pymongo-auth-aws (<2.0.0)"]
|
||||
encryption = ["pymongo[aws]", "pymongocrypt (>=1.6.0,<2.0.0)"]
|
||||
gssapi = ["pykerberos", "winkerberos (>=0.5.0)"]
|
||||
encryption = ["pymongo-auth-aws (<2.0.0)", "pymongocrypt (>=1.6.0,<2.0.0)"]
|
||||
gssapi = ["pykerberos"]
|
||||
ocsp = ["certifi", "pyopenssl (>=17.2.0)", "requests (<3.0.0)", "service-identity (>=18.1.0)"]
|
||||
snappy = ["python-snappy"]
|
||||
zstd = ["zstandard"]
|
||||
|
|
@ -6634,14 +6618,14 @@ typing-extensions = ">=4.4.0,<5.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "threadpoolctl"
|
||||
version = "3.1.0"
|
||||
version = "3.2.0"
|
||||
description = "threadpoolctl"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "threadpoolctl-3.1.0-py3-none-any.whl", hash = "sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b"},
|
||||
{file = "threadpoolctl-3.1.0.tar.gz", hash = "sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380"},
|
||||
{file = "threadpoolctl-3.2.0-py3-none-any.whl", hash = "sha256:2b7818516e423bdaebb97c723f86a7c6b0a83d3f3b0970328d66f4d9104dc032"},
|
||||
{file = "threadpoolctl-3.2.0.tar.gz", hash = "sha256:c96a0ba3bdddeaca37dc4cc7344aafad41cdb8c313f74fdfe387a867bba93355"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
@ -7766,14 +7750,14 @@ multidict = ">=4.0"
|
|||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.16.0"
|
||||
version = "3.16.1"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.16.0-py3-none-any.whl", hash = "sha256:5dadc3ad0a1f825fe42ce1bce0f2fc5a13af2e6b2d386af5b0ff295bc0a287d3"},
|
||||
{file = "zipp-3.16.0.tar.gz", hash = "sha256:1876cb065531855bbe83b6c489dcf69ecc28f1068d8e95959fe8bbc77774c941"},
|
||||
{file = "zipp-3.16.1-py3-none-any.whl", hash = "sha256:0b37c326d826d5ca35f2b9685cd750292740774ef16190008b00a0227c256fe0"},
|
||||
{file = "zipp-3.16.1.tar.gz", hash = "sha256:857b158da2cbf427b376da1c24fd11faecbac5a4ac7523c3607f8a01f94c2ec0"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -7845,4 +7829,4 @@ deploy = ["langchain-serve"]
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.9,<3.11"
|
||||
content-hash = "3ef18bc73e595f6aa8c3ee4b4c9666f3328c601933aef1bf225b865f39504e3c"
|
||||
content-hash = "c3af9ea35a1786197ab1325814e4e45755aa46dae0fd363243ab807081f8d45c"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow"
|
||||
version = "0.2.13"
|
||||
version = "0.3.0"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Logspace <contact@logspace.ai>"]
|
||||
maintainers = [
|
||||
|
|
@ -30,7 +30,7 @@ google-search-results = "^2.4.1"
|
|||
google-api-python-client = "^2.79.0"
|
||||
typer = "^0.9.0"
|
||||
gunicorn = "^20.1.0"
|
||||
langchain = "^0.0.229"
|
||||
langchain = "^0.0.232"
|
||||
openai = "^0.27.8"
|
||||
pandas = "^2.0.0"
|
||||
chromadb = "^0.3.21"
|
||||
|
|
|
|||
|
|
@ -60,7 +60,7 @@ class Graph:
|
|||
# the toolkit node
|
||||
self._build_node_params()
|
||||
# remove invalid nodes
|
||||
self._remove_invalid_nodes()
|
||||
self._validate_nodes()
|
||||
|
||||
def _build_node_params(self) -> None:
|
||||
"""Identifies and handles the LLM node within the graph."""
|
||||
|
|
@ -75,14 +75,13 @@ class Graph:
|
|||
if isinstance(node, ToolkitVertex):
|
||||
node.params["llm"] = llm_node
|
||||
|
||||
def _remove_invalid_nodes(self) -> None:
|
||||
"""Removes invalid nodes from the graph."""
|
||||
self.nodes = [
|
||||
node
|
||||
for node in self.nodes
|
||||
if self._validate_node(node)
|
||||
or (len(self.nodes) == 1 and len(self.edges) == 0)
|
||||
]
|
||||
def _validate_nodes(self) -> None:
|
||||
"""Check that all nodes have edges"""
|
||||
for node in self.nodes:
|
||||
if not self._validate_node(node):
|
||||
raise ValueError(
|
||||
f"{node.vertex_type} is not connected to any other components"
|
||||
)
|
||||
|
||||
def _validate_node(self, node: Vertex) -> bool:
|
||||
"""Validates a node."""
|
||||
|
|
|
|||
|
|
@ -11,6 +11,12 @@ import { buildInputs, buildTweaks } from "./utils";
|
|||
*/
|
||||
export const MAX_LENGTH_TO_SCROLL_TOOLTIP = 200;
|
||||
|
||||
/**
|
||||
* Number maximum of components to scroll on tooltips
|
||||
* @constant
|
||||
*/
|
||||
export const MAX_WORDS_HIGHLIGHT = 79;
|
||||
|
||||
/**
|
||||
* The base text for subtitle of Export Dialog (Toolbar)
|
||||
* @constant
|
||||
|
|
@ -236,13 +242,13 @@ export const DESCRIPTIONS: string[] = [
|
|||
"Your Hub for Text Generation.",
|
||||
"Promptly Ingenious!",
|
||||
"Building Linguistic Labyrinths.",
|
||||
"LangFlow: Create, Chain, Communicate.",
|
||||
"Langflow: Create, Chain, Communicate.",
|
||||
"Connect the Dots, Craft Language.",
|
||||
"Interactive Language Weaving.",
|
||||
"Generate, Innovate, Communicate.",
|
||||
"Conversation Catalyst Engine.",
|
||||
"Language Chainlink Master.",
|
||||
"Design Dialogues with LangFlow.",
|
||||
"Design Dialogues with Langflow.",
|
||||
"Nurture NLP Nodes Here.",
|
||||
"Conversational Cartography Unlocked.",
|
||||
"Design, Develop, Dialogize.",
|
||||
|
|
|
|||
|
|
@ -195,7 +195,7 @@ export function TabsProvider({ children }: { children: ReactNode }) {
|
|||
if (!flow.data || !flow.data.edges) return;
|
||||
flow.data.edges.forEach((edge) => {
|
||||
edge.className = "";
|
||||
edge.style = { stroke: "#555555" };
|
||||
edge.style = { stroke: "#555" };
|
||||
});
|
||||
}
|
||||
|
||||
|
|
@ -472,7 +472,7 @@ export function TabsProvider({ children }: { children: ReactNode }) {
|
|||
sourceHandle,
|
||||
targetHandle,
|
||||
id,
|
||||
style: { stroke: "inherit" },
|
||||
style: { stroke: "#555" },
|
||||
className:
|
||||
targetHandle.split("|")[0] === "Text"
|
||||
? "stroke-gray-800 "
|
||||
|
|
|
|||
|
|
@ -115,6 +115,9 @@
|
|||
--status-green: #4ade80;
|
||||
--status-blue: #2563eb;
|
||||
--connection: #555;
|
||||
|
||||
--chat-bot-icon: #235d70;
|
||||
--chat-user-icon: #4f3d6e;
|
||||
|
||||
}}
|
||||
|
||||
|
|
@ -209,11 +212,11 @@ The cursor: default; property value restores the browser's default cursor style
|
|||
@apply focus:placeholder-transparent focus:ring-ring focus:border-ring
|
||||
}
|
||||
.input-primary {
|
||||
@apply bg-background block border-ring form-input px-3 placeholder:text-muted-foreground rounded-md shadow-sm sm:text-sm truncate w-full;
|
||||
@apply bg-background block border-border form-input px-3 placeholder:text-muted-foreground rounded-md shadow-sm sm:text-sm truncate w-full;
|
||||
}
|
||||
|
||||
.input-edit-node{
|
||||
@apply input-primary placeholder:text-center pt-0.5 pb-0.5 text-center
|
||||
@apply input-primary border-border placeholder:text-center pt-0.5 pb-0.5 text-center
|
||||
}
|
||||
.input-search{
|
||||
@apply input-primary pr-7 mx-2
|
||||
|
|
@ -652,10 +655,10 @@ The cursor: default; property value restores the browser's default cursor style
|
|||
@apply flex items-center justify-between px-4 py-1.5
|
||||
}
|
||||
.code-block-modal-span {
|
||||
@apply text-xs lowercase text-background
|
||||
@apply text-xs lowercase text-muted-foreground
|
||||
}
|
||||
.code-block-modal-button {
|
||||
@apply flex items-center gap-1.5 rounded bg-none p-1 text-xs text-background
|
||||
@apply flex items-center gap-1.5 rounded bg-none p-1 text-xs text-muted-foreground
|
||||
}
|
||||
|
||||
.chat-message-modal {
|
||||
|
|
@ -930,7 +933,11 @@ The cursor: default; property value restores the browser's default cursor style
|
|||
@apply bg-white text-primary
|
||||
}
|
||||
.code-highlight{
|
||||
@apply block px-3 py-2 w-full h-full text-sm outline-0 border-0 break-all overflow-y-hidden
|
||||
@apply block px-3 py-2 w-full max-h-[64vh] text-sm outline-0 border-0 break-all overflow-y-hidden
|
||||
}
|
||||
|
||||
.code-nohighlight{
|
||||
@apply block px-3 py-2 w-full max-h-[70vh] text-sm outline-0 border-0 break-all overflow-y-hidden
|
||||
}
|
||||
.form-modal-lockchat {
|
||||
@apply form-input focus:ring-ring focus:border-ring block w-full rounded-md border-border p-4 pr-16 custom-scroll sm:text-sm
|
||||
|
|
|
|||
|
|
@ -81,7 +81,7 @@ export default function ChatMessage({
|
|||
remarkPlugins={[remarkGfm, remarkMath]}
|
||||
rehypePlugins={[rehypeMathjax]}
|
||||
className="markdown prose inline-block break-words text-primary
|
||||
dark:prose-invert sm:max-w-[30vw] lg:max-w-[40vw]"
|
||||
dark:prose-invert sm:max-w-[30vw] lg:max-w-[40vw] sm:w-[30vw] lg:w-[40vw]"
|
||||
components={{
|
||||
code: ({
|
||||
node,
|
||||
|
|
|
|||
Some files were not shown because too many files have changed in this diff Show more
Loading…
Add table
Add a link
Reference in a new issue