Rename embedchain to mem0 and open sourcing code for long term memory (#1474)
Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>
This commit is contained in:
Taranjeet Singh
32
embedchain/docs/examples/chat-with-PDF.mdx
Normal file
32
embedchain/docs/examples/chat-with-PDF.mdx
Normal file
@@ -0,0 +1,32 @@
|
||||
### Embedchain Chat with PDF App
|
||||
|
||||
You can easily create and deploy your own `chat-pdf` App using Embedchain.
|
||||
|
||||
Here are few simple steps for you to create and deploy your app:
|
||||
|
||||
1. Fork the embedchain repo from [Github](https://github.com/embedchain/embedchain).
|
||||
|
||||
<Note>
|
||||
If you run into problems with forking, please refer to [github docs](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo) for forking a repo.
|
||||
</Note>
|
||||
|
||||
2. Navigate to `chat-pdf` example app from your forked repo:
|
||||
|
||||
```bash
|
||||
cd <your_fork_repo>/examples/chat-pdf
|
||||
```
|
||||
|
||||
3. Run your app in development environment with simple commands
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
ec dev
|
||||
```
|
||||
|
||||
Feel free to improve our simple `chat-pdf` streamlit app and create pull request to showcase your app [here](https://docs.embedchain.ai/examples/showcase)
|
||||
|
||||
4. You can easily deploy your app using Streamlit interface
|
||||
|
||||
Connect your Github account with Streamlit and refer this [guide](https://docs.streamlit.io/streamlit-community-cloud/deploy-your-app) to deploy your app.
|
||||
|
||||
You can also use the deploy button from your streamlit website you see when running `ec dev` command.
|
||||
115
embedchain/docs/examples/community/showcase.mdx
Normal file
115
embedchain/docs/examples/community/showcase.mdx
Normal file
@@ -0,0 +1,115 @@
|
||||
---
|
||||
title: '🎪 Community showcase'
|
||||
---
|
||||
|
||||
Embedchain community has been super active in creating demos on top of Embedchain. On this page, we showcase all the apps, blogs, videos, and tutorials created by the community. ❤️
|
||||
|
||||
## Apps
|
||||
|
||||
### Open Source
|
||||
|
||||
- [My GSoC23 bot- Streamlit chat](https://github.com/lucifertrj/EmbedChain_GSoC23_BOT) by Tarun Jain
|
||||
- [Discord Bot for LLM chat](https://github.com/Reidond/discord_bots_playground/tree/c8b0c36541e4b393782ee506804c4b6962426dd6/python/chat-channel-bot) by Reidond
|
||||
- [EmbedChain-Streamlit-Docker App](https://github.com/amjadraza/embedchain-streamlit-app) by amjadraza
|
||||
- [Harry Potter Philosphers Stone Bot](https://github.com/vinayak-kempawad/Harry_Potter_Philosphers_Stone_Bot/) by Vinayak Kempawad, ([LinkedIn post](https://www.linkedin.com/feed/update/urn:li:activity:7080907532155686912/))
|
||||
- [LLM bot trained on own messages](https://github.com/Harin329/harinBot) by Hao Wu
|
||||
|
||||
### Closed Source
|
||||
|
||||
- [Taobot.io](https://taobot.io) - chatbot & knowledgebase hybrid by [cachho](https://github.com/cachho)
|
||||
- [Create Instant ChatBot 🤖 using embedchain](https://databutton.com/v/h3e680h9) by Avra, ([Tweet](https://twitter.com/Avra_b/status/1674704745154641920/))
|
||||
- [JOBO 🤖 — The AI-driven sidekick to craft your resume](https://try-jobo.com/) by Enrico Willemse, ([LinkedIn Post](https://www.linkedin.com/posts/enrico-willemse_jobai-gptfun-embedchain-activity-7090340080879374336-ueLB/))
|
||||
- [Explore Your Knowledge Base: Interactive chats over various forms of documents](https://chatdocs.dkedar.com/) by Kedar Dabhadkar, ([LinkedIn Post](https://www.linkedin.com/posts/dkedar7_machinelearning-llmops-activity-7092524836639424513-2O3L/))
|
||||
- [Chatbot trained on 1000+ videos of Ester hicks the co-author behind the famous book Secret](https://ask-abraham.thoughtseed.repl.co) by Mohan Kumar
|
||||
|
||||
|
||||
## Templates
|
||||
|
||||
### Replit
|
||||
- [Embedchain Chat Bot](https://replit.com/@taranjeet1/Embedchain-Chat-Bot) by taranjeetio
|
||||
- [Embedchain Memory Chat Bot Template](https://replit.com/@taranjeetio/Embedchain-Memory-Chat-Bot-Template) by taranjeetio
|
||||
- [Chatbot app to demonstrate question-answering using retrieved information](https://replit.com/@AllisonMorrell/EmbedChainlitPublic) by Allison Morrell, ([LinkedIn Post](https://www.linkedin.com/posts/allison-morrell-2889275a_retrievalbot-screenshots-activity-7080339991754649600-wihZ/))
|
||||
|
||||
## Posts
|
||||
|
||||
### Blogs
|
||||
|
||||
- [Customer Service LINE Bot](https://www.evanlin.com/langchain-embedchain/) by Evan Lin
|
||||
- [Chatbot in Under 5 mins using Embedchain](https://medium.com/@ayush.wattal/chatbot-in-under-5-mins-using-embedchain-a4f161fcf9c5) by Ayush Wattal
|
||||
- [Understanding what the LLM framework embedchain does](https://zenn.dev/hijikix/articles/4bc8d60156a436) by Daisuke Hashimoto
|
||||
- [In bed with GPT and Node.js](https://dev.to/worldlinetech/in-bed-with-gpt-and-nodejs-4kh2) by Raphaël Semeteys, ([LinkedIn Post](https://www.linkedin.com/posts/raphaelsemeteys_in-bed-with-gpt-and-nodejs-activity-7088113552326029313-nn87/))
|
||||
- [Using Embedchain — A powerful LangChain Python wrapper to build Chat Bots even faster!⚡](https://medium.com/@avra42/using-embedchain-a-powerful-langchain-python-wrapper-to-build-chat-bots-even-faster-35c12994a360) by Avra, ([Tweet](https://twitter.com/Avra_b/status/1686767751560310784/))
|
||||
- [What is the Embedchain library?](https://jahaniwww.com/%da%a9%d8%aa%d8%a7%d8%a8%d8%ae%d8%a7%d9%86%d9%87-embedchain/) by Ali Jahani, ([LinkedIn Post](https://www.linkedin.com/posts/ajahani_aepaetaeqaexaggahyaeu-aetaexaesabraeaaeqaepaeu-activity-7097605202135904256-ppU-/))
|
||||
- [LangChain is Nice, But Have You Tried EmbedChain ?](https://medium.com/thoughts-on-machine-learning/langchain-is-nice-but-have-you-tried-embedchain-215a34421cde) by FS Ndzomga, ([Tweet](https://twitter.com/ndzfs/status/1695583640372035951/))
|
||||
- [Simplest Method to Build a Custom Chatbot with GPT-3.5 (via Embedchain)](https://www.ainewsletter.today/p/simplest-method-to-build-a-custom) by Arjun, ([Tweet](https://twitter.com/aiguy_arjun/status/1696393808467091758/))
|
||||
|
||||
### LinkedIn
|
||||
|
||||
- [What is embedchain](https://www.linkedin.com/posts/activity-7079393104423698432-wRyi/) by Rithesh Sreenivasan
|
||||
- [Building a chatbot with EmbedChain](https://www.linkedin.com/posts/activity-7078434598984060928-Zdso/) by Lior Sinclair
|
||||
- [Making chatbot without vs with embedchain](https://www.linkedin.com/posts/kalyanksnlp_llms-chatbots-langchain-activity-7077453416221863936-7N1L/) by Kalyan KS
|
||||
- [EmbedChain - very intuitive, first you index your data and then query!](https://www.linkedin.com/posts/shubhamsaboo_embedchain-a-framework-to-easily-create-activity-7079535460699557888-ad1X/) by Shubham Saboo
|
||||
- [EmbedChain - Harnessing power of LLM](https://www.linkedin.com/posts/uditsaini_chatbotrevolution-llmpoweredbots-embedchainframework-activity-7077520356827181056-FjTK/) by Udit S.
|
||||
- [AI assistant for ABBYY Vantage](https://www.linkedin.com/posts/maximevermeir_llm-github-abbyy-activity-7081658972071424000-fXfZ/) by Maxime V.
|
||||
- [About embedchain](https://www.linkedin.com/feed/update/urn:li:activity:7080984218914189312/) by Morris Lee
|
||||
- [How to use Embedchain](https://www.linkedin.com/posts/nehaabansal_github-embedchainembedchain-framework-activity-7085830340136595456-kbW5/) by Neha Bansal
|
||||
- [Youtube/Webpage summary for Energy Study](https://www.linkedin.com/posts/bar%C4%B1%C5%9F-sanl%C4%B1-34b82715_enerji-python-activity-7082735341563977730-Js0U/) by Barış Sanlı, ([Tweet](https://twitter.com/barissanli/status/1676968784979193857/))
|
||||
- [Demo: How to use Embedchain? (Contains Collab Notebook link)](https://www.linkedin.com/posts/liorsinclair_embedchain-is-getting-a-lot-of-traction-because-activity-7103044695995424768-RckT/) by Lior Sinclair
|
||||
|
||||
### Twitter
|
||||
|
||||
- [What is embedchain](https://twitter.com/AlphaSignalAI/status/1672668574450847745) by Lior
|
||||
- [Building a chatbot with Embedchain](https://twitter.com/Saboo_Shubham_/status/1673537044419686401) by Shubham Saboo
|
||||
- [Chatbot docker image behind an API with yaml configs with Embedchain](https://twitter.com/tricalt/status/1678411430192730113/) by Vasilije
|
||||
- [Build AI powered PDF chatbot with just five lines of Python code with Embedchain!](https://twitter.com/Saboo_Shubham_/status/1676627104866156544/) by Shubham Saboo
|
||||
- [Chatbot against a youtube video using embedchain](https://twitter.com/smaameri/status/1675201443043704834/) by Sami Maameri
|
||||
- [Highlights of EmbedChain](https://twitter.com/carl_AIwarts/status/1673542204328120321/) by carl_AIwarts
|
||||
- [Build Llama-2 chatbot in less than 5 minutes](https://twitter.com/Saboo_Shubham_/status/1682168956918833152/) by Shubham Saboo
|
||||
- [All cool features of embedchain](https://twitter.com/DhravyaShah/status/1683497882438217728/) by Dhravya Shah, ([LinkedIn Post](https://www.linkedin.com/posts/dhravyashah_what-if-i-tell-you-that-you-can-make-an-ai-activity-7089459599287726080-ZIYm/))
|
||||
- [Read paid Medium articles for Free using embedchain](https://twitter.com/kumarkaushal_/status/1688952961622585344) by Kaushal Kumar
|
||||
|
||||
## Videos
|
||||
|
||||
- [Embedchain in one shot](https://www.youtube.com/watch?v=vIhDh7H73Ww&t=82s) by AI with Tarun
|
||||
- [embedChain Create LLM powered bots over any dataset Python Demo Tesla Neurallink Chatbot Example](https://www.youtube.com/watch?v=bJqAn22a6Gc) by Rithesh Sreenivasan
|
||||
- [Embedchain - NEW 🔥 Langchain BABY to build LLM Bots](https://www.youtube.com/watch?v=qj_GNQ06I8o) by 1littlecoder
|
||||
- [EmbedChain -- NEW!: Build LLM-Powered Bots with Any Dataset](https://www.youtube.com/watch?v=XmaBezzGHu4) by DataInsightEdge
|
||||
- [Chat With Your PDFs in less than 10 lines of code! EMBEDCHAIN tutorial](https://www.youtube.com/watch?v=1ugkcsAcw44) by Phani Reddy
|
||||
- [How To Create A Custom Knowledge AI Powered Bot | Install + How To Use](https://www.youtube.com/watch?v=VfCrIiAst-c) by The Ai Solopreneur
|
||||
- [Build Custom Chatbot in 6 min with this Framework [Beginner Friendly]](https://www.youtube.com/watch?v=-8HxOpaFySM) by Maya Akim
|
||||
- [embedchain-streamlit-app](https://www.youtube.com/watch?v=3-9GVd-3v74) by Amjad Raza
|
||||
- [🤖CHAT with ANY ONLINE RESOURCES using EMBEDCHAIN - a LangChain wrapper, in few lines of code !](https://www.youtube.com/watch?v=Mp7zJe4TIdM) by Avra
|
||||
- [Building resource-driven LLM-powered bots with Embedchain](https://www.youtube.com/watch?v=IVfcAgxTO4I) by BugBytes
|
||||
- [embedchain-streamlit-demo](https://www.youtube.com/watch?v=yJAWB13FhYQ) by Amjad Raza
|
||||
- [Embedchain - create your own AI chatbots using open source models](https://www.youtube.com/shorts/O3rJWKwSrWE) by Dhravya Shah
|
||||
- [AI ChatBot in 5 lines Python Code](https://www.youtube.com/watch?v=zjWvLJLksv8) by Data Engineering
|
||||
- [Interview with Karl Marx](https://www.youtube.com/watch?v=5Y4Tscwj1xk) by Alexander Ray Williams
|
||||
- [Vlog where we try to build a bot based on our content on the internet](https://www.youtube.com/watch?v=I2w8CWM3bx4) by DV, ([Tweet](https://twitter.com/dvcoolster/status/1688387017544261632))
|
||||
- [CHAT with ANY ONLINE RESOURCES using EMBEDCHAIN|STREAMLIT with MEMORY |All OPENSOURCE](https://www.youtube.com/watch?v=TqQIHWoWTDQ&pp=ygUKZW1iZWRjaGFpbg%3D%3D) by DataInsightEdge
|
||||
- [Build POWERFUL LLM Bots EASILY with Your Own Data - Embedchain - Langchain 2.0? (Tutorial)](https://www.youtube.com/watch?v=jE24Y_GasE8) by WorldofAI, ([Tweet](https://twitter.com/intheworldofai/status/1696229166922780737))
|
||||
- [Embedchain: An AI knowledge base assistant for customizing enterprise private data, which can be connected to discord, whatsapp, slack, tele and other terminals (with gradio to build a request interface) in Chinese](https://www.youtube.com/watch?v=5RZzCJRk-d0) by AIGC LINK
|
||||
- [Embedchain Introduction](https://www.youtube.com/watch?v=Jet9zAqyggI) by Fahd Mirza
|
||||
|
||||
## Mentions
|
||||
|
||||
### Github repos
|
||||
|
||||
- [Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM)
|
||||
- [awesome-chatgpt-api](https://github.com/reorx/awesome-chatgpt-api)
|
||||
- [awesome-langchain](https://github.com/kyrolabs/awesome-langchain)
|
||||
- [Awesome-Prompt-Engineering](https://github.com/promptslab/Awesome-Prompt-Engineering)
|
||||
- [awesome-chatgpt](https://github.com/eon01/awesome-chatgpt)
|
||||
- [Awesome-LLMOps](https://github.com/tensorchord/Awesome-LLMOps)
|
||||
- [awesome-generative-ai](https://github.com/filipecalegario/awesome-generative-ai)
|
||||
- [awesome-gpt](https://github.com/formulahendry/awesome-gpt)
|
||||
- [awesome-ChatGPT-repositories](https://github.com/taishi-i/awesome-ChatGPT-repositories)
|
||||
- [awesome-gpt-prompt-engineering](https://github.com/snwfdhmp/awesome-gpt-prompt-engineering)
|
||||
- [awesome-chatgpt](https://github.com/awesome-chatgpt/awesome-chatgpt)
|
||||
- [awesome-llm-and-aigc](https://github.com/sjinzh/awesome-llm-and-aigc)
|
||||
- [awesome-compbio-chatgpt](https://github.com/csbl-br/awesome-compbio-chatgpt)
|
||||
- [Awesome-LLM4Tool](https://github.com/OpenGVLab/Awesome-LLM4Tool)
|
||||
|
||||
## Meetups
|
||||
|
||||
- [Dash and ChatGPT: Future of AI-enabled apps 30/08/23](https://go.plotly.com/dash-chatgpt)
|
||||
- [Pie & AI: Bangalore - Build end-to-end LLM app using Embedchain 01/09/23](https://www.eventbrite.com/e/pie-ai-bangalore-build-end-to-end-llm-app-using-embedchain-tickets-698045722547)
|
||||
70
embedchain/docs/examples/discord_bot.mdx
Normal file
70
embedchain/docs/examples/discord_bot.mdx
Normal file
@@ -0,0 +1,70 @@
|
||||
---
|
||||
title: "🤖 Discord Bot"
|
||||
---
|
||||
|
||||
### 🔑 Keys Setup
|
||||
|
||||
- Set your `OPENAI_API_KEY` in your variables.env file.
|
||||
- Go to [https://discord.com/developers/applications/](https://discord.com/developers/applications/) and click on `New Application`.
|
||||
- Enter the name for your bot, accept the terms and click on `Create`. On the resulting page, enter the details of your bot as you like.
|
||||
- On the left sidebar, click on `Bot`. Under the heading `Privileged Gateway Intents`, toggle all 3 options to ON position. Save your changes.
|
||||
- Now click on `Reset Token` and copy the token value. Set it as `DISCORD_BOT_TOKEN` in .env file.
|
||||
- On the left sidebar, click on `OAuth2` and go to `General`.
|
||||
- Set `Authorization Method` to `In-app Authorization`. Under `Scopes` select `bot`.
|
||||
- Under `Bot Permissions` allow the following and then click on `Save Changes`.
|
||||
|
||||
```text
|
||||
Send Messages (under Text Permissions)
|
||||
```
|
||||
|
||||
- Now under `OAuth2` and go to `URL Generator`. Under `Scopes` select `bot`.
|
||||
- Under `Bot Permissions` set the same permissions as above.
|
||||
- Now scroll down and copy the `Generated URL`. Paste it in a browser window and select the Server where you want to add the bot.
|
||||
- Click on `Continue` and authorize the bot.
|
||||
- 🎉 The bot has been successfully added to your server. But it's still offline.
|
||||
|
||||
### Take the bot online
|
||||
|
||||
<Tabs>
|
||||
<Tab title="docker">
|
||||
```bash
|
||||
docker run --name discord-bot -e OPENAI_API_KEY=sk-xxx -e DISCORD_BOT_TOKEN=xxx -p 8080:8080 embedchain/discord-bot:latest
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="python">
|
||||
```bash
|
||||
pip install --upgrade "embedchain[discord]"
|
||||
|
||||
python -m embedchain.bots.discord
|
||||
|
||||
# or if you prefer to see the question and not only the answer, run it with
|
||||
python -m embedchain.bots.discord --include-question
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
### 🚀 Usage Instructions
|
||||
|
||||
- Go to the server where you have added your bot.
|
||||
|
||||
- You can add data sources to the bot using the slash command:
|
||||
|
||||
```text
|
||||
/ec add <data_type> <url_or_text>
|
||||
```
|
||||
|
||||
- You can ask your queries from the bot using the slash command:
|
||||
|
||||
```text
|
||||
/ec query <question>
|
||||
```
|
||||
|
||||
- You can chat with the bot using the slash command:
|
||||
|
||||
```text
|
||||
/ec chat <question>
|
||||
```
|
||||
|
||||
📝 Note: To use the bot privately, you can message the bot directly by right clicking the bot and selecting `Message`.
|
||||
|
||||
🎉 Happy Chatting! 🎉
|
||||
57
embedchain/docs/examples/full_stack.mdx
Normal file
57
embedchain/docs/examples/full_stack.mdx
Normal file
@@ -0,0 +1,57 @@
|
||||
---
|
||||
title: 'Full Stack'
|
||||
---
|
||||
|
||||
The Full Stack app example can be found [here](https://github.com/embedchain/embedchain/tree/main/examples/full_stack).
|
||||
|
||||
This guide will help you setup the full stack app on your local machine.
|
||||
|
||||
### 🐳 Docker Setup
|
||||
|
||||
- Create a `docker-compose.yml` file and paste the following code in it.
|
||||
|
||||
```yaml
|
||||
version: "3.9"
|
||||
|
||||
services:
|
||||
backend:
|
||||
container_name: embedchain-backend
|
||||
restart: unless-stopped
|
||||
build:
|
||||
context: backend
|
||||
dockerfile: Dockerfile
|
||||
image: embedchain/backend
|
||||
ports:
|
||||
- "8000:8000"
|
||||
|
||||
frontend:
|
||||
container_name: embedchain-frontend
|
||||
restart: unless-stopped
|
||||
build:
|
||||
context: frontend
|
||||
dockerfile: Dockerfile
|
||||
image: embedchain/frontend
|
||||
ports:
|
||||
- "3000:3000"
|
||||
depends_on:
|
||||
- "backend"
|
||||
```
|
||||
|
||||
- Run the following command,
|
||||
|
||||
```bash
|
||||
docker-compose up
|
||||
```
|
||||
|
||||
📝 Note: The build command might take a while to install all the packages depending on your system resources.
|
||||
|
||||
|
||||
|
||||
### 🚀 Usage Instructions
|
||||
|
||||
- Go to [http://localhost:3000/](http://localhost:3000/) in your browser to view the dashboard.
|
||||
- Add your `OpenAI API key` 🔑 in the Settings.
|
||||
- Create a new bot and you'll be navigated to its page.
|
||||
- Here you can add your data sources and then chat with the bot.
|
||||
|
||||
🎉 Happy Chatting! 🎉
|
||||
124
embedchain/docs/examples/nextjs-assistant.mdx
Normal file
124
embedchain/docs/examples/nextjs-assistant.mdx
Normal file
@@ -0,0 +1,124 @@
|
||||
Fork the Embedchain repo on [Github](https://github.com/embedchain/embedchain) to create your own NextJS discord and slack bot powered by Embedchain.
|
||||
|
||||
If you run into problems with forking, please refer to [github docs](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo) for forking a repo.
|
||||
|
||||
We will work from the `examples/nextjs` folder so change your current working directory by running the command - `cd <your_forked_repo>/examples/nextjs`
|
||||
|
||||
# Installation
|
||||
|
||||
First, lets start by install all the required packages and dependencies.
|
||||
|
||||
- Install all the required python packages by running ```pip install -r requirements.txt```
|
||||
|
||||
- We will use [Fly.io](https://fly.io/) to deploy our embedchain app, discord and slack bot. Follow the step one to install [Fly.io CLI](https://docs.embedchain.ai/deployment/fly_io#step-1-install-flyctl-command-line)
|
||||
|
||||
# Developement
|
||||
|
||||
## Embedchain App
|
||||
|
||||
First, we need an Embedchain app powered with the knowledge of NextJS. We have already created an embedchain app using FastAPI in `ec_app` folder for you. Feel free to ingest data of your choice to power the App.
|
||||
|
||||
<Note>
|
||||
Navigate to `ec_app` folder and create `.env` file in this folder and set your OpenAI API key as shown in `.env.example` file. If you want to use other open-source models, feel free to use the app config in `app.py`. More details for using custom configuration for Embedchain app is [available here](https://docs.embedchain.ai/api-reference/advanced/configuration).
|
||||
</Note>
|
||||
|
||||
Before running the ec commands to develope the app, open `fly.toml` file and update the `name` variable to something unique. This is important as `fly.io` requires users to provide a globally unique deployment app names.
|
||||
|
||||
Now, we need to launch this application with fly.io. You can see your app on [fly.io dashboard](https://fly.io/dashboard). Run the following command to launch your app on fly.io:
|
||||
```bash
|
||||
fly launch --no-deploy
|
||||
```
|
||||
|
||||
To run the app in development, run the following command:
|
||||
|
||||
```bash
|
||||
ec dev
|
||||
```
|
||||
|
||||
Run `ec deploy` to deploy your app on Fly.io. Once you deploy your app, save the endpoint on which our discord and slack bot will send requests.
|
||||
|
||||
|
||||
## Discord bot
|
||||
|
||||
For discord bot, you will need to create the bot on discord developer portal and get the discord bot token and your discord bot name.
|
||||
|
||||
While keeping in mind the following note, create the discord bot by following the instructions from our [discord bot docs](https://docs.embedchain.ai/examples/discord_bot) and get discord bot token.
|
||||
|
||||
<Note>
|
||||
You do not need to set `OPENAI_API_KEY` to run this discord bot. Follow the remaining instructions to create a discord bot app. We recommend you to give the following sets of bot permissions to run the discord bot without errors:
|
||||
|
||||
```
|
||||
(General Permissions)
|
||||
Read Message/View Channels
|
||||
|
||||
(Text Permissions)
|
||||
Send Messages
|
||||
Create Public Thread
|
||||
Create Private Thread
|
||||
Send Messages in Thread
|
||||
Manage Threads
|
||||
Embed Links
|
||||
Read Message History
|
||||
```
|
||||
</Note>
|
||||
|
||||
Once you have your discord bot token and discord app name. Navigate to `nextjs_discord` folder and create `.env` file and define your discord bot token, discord bot name and endpoint of your embedchain app as shown in `.env.example` file.
|
||||
|
||||
To run the app in development:
|
||||
|
||||
```bash
|
||||
python app.py
|
||||
```
|
||||
|
||||
Before deploying the app, open `fly.toml` file and update the `name` variable to something unique. This is important as `fly.io` requires users to provide a globally unique deployment app names.
|
||||
|
||||
Now, we need to launch this application with fly.io. You can see your app on [fly.io dashboard](https://fly.io/dashboard). Run the following command to launch your app on fly.io:
|
||||
```bash
|
||||
fly launch --no-deploy
|
||||
```
|
||||
|
||||
Run `ec deploy` to deploy your app on Fly.io. Once you deploy your app, your discord bot will be live!
|
||||
|
||||
|
||||
## Slack bot
|
||||
|
||||
For Slack bot, you will need to create the bot on slack developer portal and get the slack bot token and slack app token.
|
||||
|
||||
### Setup
|
||||
|
||||
- Create a workspace on Slack if you don't have one already by clicking [here](https://slack.com/intl/en-in/).
|
||||
- Create a new App on your Slack account by going [here](https://api.slack.com/apps).
|
||||
- Select `From Scratch`, then enter the Bot Name and select your workspace.
|
||||
- Go to `App Credentials` section on the `Basic Information` tab from the left sidebar, create your app token and save it in your `.env` file as `SLACK_APP_TOKEN`.
|
||||
- Go to `Socket Mode` tab from the left sidebar and enable the socket mode to listen to slack message from your workspace.
|
||||
- (Optional) Under the `App Home` tab you can change your App display name and default name.
|
||||
- Navigate to `Event Subscription` tab, and enable the event subscription so that we can listen to slack events.
|
||||
- Once you enable the event subscription, you will need to subscribe to bot events to authorize the bot to listen to app mention events of the bot. Do that by tapping on `Add Bot User Event` button and select `app_mention`.
|
||||
- On the left Sidebar, go to `OAuth and Permissions` and add the following scopes under `Bot Token Scopes`:
|
||||
```text
|
||||
app_mentions:read
|
||||
channels:history
|
||||
channels:read
|
||||
chat:write
|
||||
emoji:read
|
||||
reactions:write
|
||||
reactions:read
|
||||
```
|
||||
- Now select the option `Install to Workspace` and after it's done, copy the `Bot User OAuth Token` and set it in your `.env` file as `SLACK_BOT_TOKEN`.
|
||||
|
||||
Once you have your slack bot token and slack app token. Navigate to `nextjs_slack` folder and create `.env` file and define your slack bot token, slack app token and endpoint of your embedchain app as shown in `.env.example` file.
|
||||
|
||||
To run the app in development:
|
||||
|
||||
```bash
|
||||
python app.py
|
||||
```
|
||||
|
||||
Before deploying the app, open `fly.toml` file and update the `name` variable to something unique. This is important as `fly.io` requires users to provide a globally unique deployment app names.
|
||||
|
||||
Now, we need to launch this application with fly.io. You can see your app on [fly.io dashboard](https://fly.io/dashboard). Run the following command to launch your app on fly.io:
|
||||
```bash
|
||||
fly launch --no-deploy
|
||||
```
|
||||
|
||||
Run `ec deploy` to deploy your app on Fly.io. Once you deploy your app, your slack bot will be live!
|
||||
138
embedchain/docs/examples/notebooks-and-replits.mdx
Normal file
138
embedchain/docs/examples/notebooks-and-replits.mdx
Normal file
@@ -0,0 +1,138 @@
|
||||
---
|
||||
title: Notebooks & Replits
|
||||
---
|
||||
|
||||
# Explore awesome apps
|
||||
|
||||
Check out the remarkable work accomplished using [Embedchain](https://app.embedchain.ai/custom-gpts/).
|
||||
|
||||
## Collection of Google colab notebook and Replit links for users
|
||||
|
||||
Get started with Embedchain by trying out the examples below. You can run the examples in your browser using Google Colab or Replit.
|
||||
|
||||
<table>
|
||||
<thead>
|
||||
<tr>
|
||||
<th>LLM</th>
|
||||
<th>Google Colab</th>
|
||||
<th>Replit</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<td className="align-middle">OpenAI</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/openai.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/openai#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Anthropic</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/anthropic.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/anthropic#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Azure OpenAI</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/azure-openai.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/azureopenai#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">VertexAI</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/vertex_ai.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/vertexai#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Cohere</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/cohere.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/cohere#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Together</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/together.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Ollama</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/ollama.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Hugging Face</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/hugging_face_hub.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/huggingface#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">JinaChat</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/jina.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/jina#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">GPT4All</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/gpt4all.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/gpt4all#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Llama2</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/llama2.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/llama2#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<table>
|
||||
<thead>
|
||||
<tr>
|
||||
<th>Embedding model</th>
|
||||
<th>Google Colab</th>
|
||||
<th>Replit</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<td className="align-middle">OpenAI</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/openai.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/openai#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">VertexAI</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/vertex_ai.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/vertexai#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">GPT4All</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/gpt4all.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/gpt4all#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Hugging Face</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/hugging_face_hub.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/huggingface#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<table>
|
||||
<thead>
|
||||
<tr>
|
||||
<th>Vector DB</th>
|
||||
<th>Google Colab</th>
|
||||
<th>Replit</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
<tr>
|
||||
<td className="align-middle">ChromaDB</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/chromadb.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/chromadb#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Elasticsearch</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/elasticsearch.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/elasticsearchdb#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Opensearch</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/opensearch.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/opensearchdb#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td className="align-middle">Pinecone</td>
|
||||
<td className="align-middle"><a target="_blank" href="https://colab.research.google.com/github/embedchain/embedchain/blob/main/notebooks/pinecone.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" noZoom alt="Open In Colab"/></a></td>
|
||||
<td className="align-middle"><a target="_blank" href="https://replit.com/@taranjeetio/pineconedb#main.py"><img src="https://replit.com/badge?caption=Try%20with%20Replit&variant=small" noZoom alt="Try with Replit Badge"/></a></td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
60
embedchain/docs/examples/openai-assistant.mdx
Normal file
60
embedchain/docs/examples/openai-assistant.mdx
Normal file
@@ -0,0 +1,60 @@
|
||||
---
|
||||
title: 'OpenAI Assistant'
|
||||
---
|
||||
|
||||
<img src="https://blogs.swarthmore.edu/its/wp-content/uploads/2022/05/openai.jpg" align="center" width="500" alt="OpenAI Logo"/>
|
||||
|
||||
Embedchain now supports [OpenAI Assistants API](https://platform.openai.com/docs/assistants/overview) which allows you to build AI assistants within your own applications. An Assistant has instructions and can leverage models, tools, and knowledge to respond to user queries.
|
||||
|
||||
At a high level, an integration of the Assistants API has the following flow:
|
||||
|
||||
1. Create an Assistant in the API by defining custom instructions and picking a model
|
||||
2. Create a Thread when a user starts a conversation
|
||||
3. Add Messages to the Thread as the user ask questions
|
||||
4. Run the Assistant on the Thread to trigger responses. This automatically calls the relevant tools.
|
||||
|
||||
Creating an OpenAI Assistant using Embedchain is very simple 3 step process.
|
||||
|
||||
## Step 1: Create OpenAI Assistant
|
||||
|
||||
Make sure that you have `OPENAI_API_KEY` set in the environment variable.
|
||||
|
||||
```python Initialize
|
||||
from embedchain.store.assistants import OpenAIAssistant
|
||||
|
||||
assistant = OpenAIAssistant(
|
||||
name="OpenAI DevDay Assistant",
|
||||
instructions="You are an organizer of OpenAI DevDay",
|
||||
)
|
||||
```
|
||||
|
||||
If you want to use the existing assistant, you can do something like this:
|
||||
|
||||
```python Initialize
|
||||
# Load an assistant and create a new thread
|
||||
assistant = OpenAIAssistant(assistant_id="asst_xxx")
|
||||
|
||||
# Load a specific thread for an assistant
|
||||
assistant = OpenAIAssistant(assistant_id="asst_xxx", thread_id="thread_xxx")
|
||||
```
|
||||
|
||||
## Step-2: Add data to thread
|
||||
|
||||
You can add any custom data source that is supported by Embedchain. Else, you can directly pass the file path on your local system and Embedchain propagates it to OpenAI Assistant.
|
||||
```python Add data
|
||||
assistant.add("/path/to/file.pdf")
|
||||
assistant.add("https://www.youtube.com/watch?v=U9mJuUkhUzk")
|
||||
assistant.add("https://openai.com/blog/new-models-and-developer-products-announced-at-devday")
|
||||
```
|
||||
|
||||
## Step-3: Chat with your Assistant
|
||||
```python Chat
|
||||
assistant.chat("How much OpenAI credits were offered to attendees during OpenAI DevDay?")
|
||||
# Response: 'Every attendee of OpenAI DevDay 2023 was offered $500 in OpenAI credits.'
|
||||
```
|
||||
|
||||
You can try it out yourself using the following Google Colab notebook:
|
||||
|
||||
<a href="https://colab.research.google.com/drive/1BKlXZYSl6AFRgiHZ5XIzXrXC_24kDYHQ?usp=sharing">
|
||||
<img src="https://camo.githubusercontent.com/84f0493939e0c4de4e6dbe113251b4bfb5353e57134ffd9fcab6b8714514d4d1/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667" alt="Open in Colab" />
|
||||
</a>
|
||||
51
embedchain/docs/examples/opensource-assistant.mdx
Normal file
51
embedchain/docs/examples/opensource-assistant.mdx
Normal file
@@ -0,0 +1,51 @@
|
||||
---
|
||||
title: 'Open-Source AI Assistant'
|
||||
---
|
||||
|
||||
Embedchain also provides support for creating Open-Source AI Assistants (similar to [OpenAI Assistants API](https://platform.openai.com/docs/assistants/overview)) which allows you to build AI assistants within your own applications using any LLM (OpenAI or otherwise). An Assistant has instructions and can leverage models, tools, and knowledge to respond to user queries.
|
||||
|
||||
At a high level, the Open-Source AI Assistants API has the following flow:
|
||||
|
||||
1. Create an AI Assistant by picking a model
|
||||
2. Create a Thread when a user starts a conversation
|
||||
3. Add Messages to the Thread as the user ask questions
|
||||
4. Run the Assistant on the Thread to trigger responses. This automatically calls the relevant tools.
|
||||
|
||||
Creating an Open-Source AI Assistant is a simple 3 step process.
|
||||
|
||||
## Step 1: Instantiate AI Assistant
|
||||
|
||||
```python Initialize
|
||||
from embedchain.store.assistants import AIAssistant
|
||||
|
||||
assistant = AIAssistant(
|
||||
name="My Assistant",
|
||||
data_sources=[{"source": "https://www.youtube.com/watch?v=U9mJuUkhUzk"}])
|
||||
```
|
||||
|
||||
If you want to use the existing assistant, you can do something like this:
|
||||
|
||||
```python Initialize
|
||||
# Load an assistant and create a new thread
|
||||
assistant = AIAssistant(assistant_id="asst_xxx")
|
||||
|
||||
# Load a specific thread for an assistant
|
||||
assistant = AIAssistant(assistant_id="asst_xxx", thread_id="thread_xxx")
|
||||
```
|
||||
|
||||
## Step-2: Add data to thread
|
||||
|
||||
You can add any custom data source that is supported by Embedchain. Else, you can directly pass the file path on your local system and Embedchain propagates it to OpenAI Assistant.
|
||||
|
||||
```python Add data
|
||||
assistant.add("/path/to/file.pdf")
|
||||
assistant.add("https://www.youtube.com/watch?v=U9mJuUkhUzk")
|
||||
assistant.add("https://openai.com/blog/new-models-and-developer-products-announced-at-devday")
|
||||
```
|
||||
|
||||
## Step-3: Chat with your AI Assistant
|
||||
|
||||
```python Chat
|
||||
assistant.chat("How much OpenAI credits were offered to attendees during OpenAI DevDay?")
|
||||
# Response: 'Every attendee of OpenAI DevDay 2023 was offered $500 in OpenAI credits.'
|
||||
```
|
||||
59
embedchain/docs/examples/poe_bot.mdx
Normal file
59
embedchain/docs/examples/poe_bot.mdx
Normal file
@@ -0,0 +1,59 @@
|
||||
---
|
||||
title: '🔮 Poe Bot'
|
||||
---
|
||||
|
||||
### 🚀 Getting started
|
||||
|
||||
1. Install embedchain python package:
|
||||
|
||||
```bash
|
||||
pip install fastapi-poe==0.0.16
|
||||
```
|
||||
|
||||
2. Create a free account on [Poe](https://www.poe.com?utm_source=embedchain).
|
||||
3. Click "Create Bot" button on top left.
|
||||
4. Give it a handle and an optional description.
|
||||
5. Select `Use API`.
|
||||
6. Under `API URL` enter your server or ngrok address. You can use your machine's public IP or DNS. Otherwise, employ a proxy server like [ngrok](https://ngrok.com/) to make your local bot accessible.
|
||||
7. Copy your api key and paste it in `.env` as `POE_API_KEY`.
|
||||
8. You will need to set `OPENAI_API_KEY` for generating embeddings and using LLM. Copy your OpenAI API key from [here](https://platform.openai.com/account/api-keys) and paste it in `.env` as `OPENAI_API_KEY`.
|
||||
9. Now create your bot using the following code snippet.
|
||||
|
||||
```bash
|
||||
# make sure that you have set OPENAI_API_KEY and POE_API_KEY in .env file
|
||||
from embedchain.bots import PoeBot
|
||||
|
||||
poe_bot = PoeBot()
|
||||
|
||||
# add as many data sources as you want
|
||||
poe_bot.add("https://en.wikipedia.org/wiki/Adam_D%27Angelo")
|
||||
poe_bot.add("https://www.youtube.com/watch?v=pJQVAqmKua8")
|
||||
|
||||
# start the bot
|
||||
# this start the poe bot server on port 8080 by default
|
||||
poe_bot.start()
|
||||
```
|
||||
|
||||
10. You can paste the above in a file called `your_script.py` and then simply do
|
||||
|
||||
```bash
|
||||
python your_script.py
|
||||
```
|
||||
|
||||
Now your bot will start running at port `8080` by default.
|
||||
|
||||
11. You can refer the [Supported Data formats](https://docs.embedchain.ai/advanced/data_types) section to refer the supported data types in embedchain.
|
||||
|
||||
12. Click `Run check` to make sure your machine can be reached.
|
||||
13. Make sure your bot is private if that's what you want.
|
||||
14. Click `Create bot` at the bottom to finally create the bot
|
||||
15. Now your bot is created.
|
||||
|
||||
### 💬 How to use
|
||||
|
||||
- To ask the bot questions, just type your query in the Poe interface:
|
||||
```text
|
||||
<your-question-here>
|
||||
```
|
||||
|
||||
- If you wish to add more data source to the bot, simply update your script and add as many `.add` as you like. You need to restart the server.
|
||||
22
embedchain/docs/examples/rest-api/add-data.mdx
Normal file
22
embedchain/docs/examples/rest-api/add-data.mdx
Normal file
@@ -0,0 +1,22 @@
|
||||
---
|
||||
openapi: post /{app_id}/add
|
||||
---
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/{app_id}/add \
|
||||
-d "source=https://www.forbes.com/profile/elon-musk" \
|
||||
-d "data_type=web_page"
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{ "response": "fec7fe91e6b2d732938a2ec2e32bfe3f" }
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
3
embedchain/docs/examples/rest-api/chat.mdx
Normal file
3
embedchain/docs/examples/rest-api/chat.mdx
Normal file
@@ -0,0 +1,3 @@
|
||||
---
|
||||
openapi: post /{app_id}/chat
|
||||
---
|
||||
20
embedchain/docs/examples/rest-api/check-status.mdx
Normal file
20
embedchain/docs/examples/rest-api/check-status.mdx
Normal file
@@ -0,0 +1,20 @@
|
||||
---
|
||||
openapi: get /ping
|
||||
---
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request GET \
|
||||
--url http://localhost:8080/ping
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{ "ping": "pong" }
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
96
embedchain/docs/examples/rest-api/create.mdx
Normal file
96
embedchain/docs/examples/rest-api/create.mdx
Normal file
@@ -0,0 +1,96 @@
|
||||
---
|
||||
openapi: post /create
|
||||
---
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/create?app_id=app1 \
|
||||
-F "config=@/path/to/config.yaml"
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{ "response": "App created successfully. App ID: app1" }
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
|
||||
By default we will use the opensource **gpt4all** model to get started. You can also specify your own config by uploading a config YAML file.
|
||||
|
||||
For example, create a `config.yaml` file (adjust according to your requirements):
|
||||
|
||||
```yaml
|
||||
app:
|
||||
config:
|
||||
id: "default-app"
|
||||
|
||||
llm:
|
||||
provider: openai
|
||||
config:
|
||||
model: "gpt-3.5-turbo"
|
||||
temperature: 0.5
|
||||
max_tokens: 1000
|
||||
top_p: 1
|
||||
stream: false
|
||||
prompt: |
|
||||
Use the following pieces of context to answer the query at the end.
|
||||
If you don't know the answer, just say that you don't know, don't try to make up an answer.
|
||||
|
||||
$context
|
||||
|
||||
Query: $query
|
||||
|
||||
Helpful Answer:
|
||||
|
||||
vectordb:
|
||||
provider: chroma
|
||||
config:
|
||||
collection_name: "rest-api-app"
|
||||
dir: db
|
||||
allow_reset: true
|
||||
|
||||
embedder:
|
||||
provider: openai
|
||||
config:
|
||||
model: "text-embedding-ada-002"
|
||||
```
|
||||
|
||||
To learn more about custom configurations, check out the [custom configurations docs](https://docs.embedchain.ai/advanced/configuration). To explore more examples of config yamls for embedchain, visit [embedchain/configs](https://github.com/embedchain/embedchain/tree/main/configs).
|
||||
|
||||
Now, you can upload this config file in the request body.
|
||||
|
||||
For example,
|
||||
|
||||
```bash Request
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/create?app_id=my-app \
|
||||
-F "config=@/path/to/config.yaml"
|
||||
```
|
||||
|
||||
**Note:** To use custom models, an **API key** might be required. Refer to the table below to determine the necessary API key for your provider.
|
||||
|
||||
| Keys | Providers |
|
||||
| -------------------------- | ------------------------------ |
|
||||
| `OPENAI_API_KEY ` | OpenAI, Azure OpenAI, Jina etc |
|
||||
| `OPENAI_API_TYPE` | Azure OpenAI |
|
||||
| `OPENAI_API_BASE` | Azure OpenAI |
|
||||
| `OPENAI_API_VERSION` | Azure OpenAI |
|
||||
| `COHERE_API_KEY` | Cohere |
|
||||
| `TOGETHER_API_KEY` | Together |
|
||||
| `ANTHROPIC_API_KEY` | Anthropic |
|
||||
| `JINACHAT_API_KEY` | Jina |
|
||||
| `HUGGINGFACE_ACCESS_TOKEN` | Huggingface |
|
||||
| `REPLICATE_API_TOKEN` | LLAMA2 |
|
||||
|
||||
To add env variables, you can simply run the docker command with the `-e` flag.
|
||||
|
||||
For example,
|
||||
|
||||
```bash
|
||||
docker run --name embedchain -p 8080:8080 -e OPENAI_API_KEY=<YOUR_OPENAI_API_KEY> embedchain/rest-api:latest
|
||||
```
|
||||
21
embedchain/docs/examples/rest-api/delete.mdx
Normal file
21
embedchain/docs/examples/rest-api/delete.mdx
Normal file
@@ -0,0 +1,21 @@
|
||||
---
|
||||
openapi: delete /{app_id}/delete
|
||||
---
|
||||
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request DELETE \
|
||||
--url http://localhost:8080/{app_id}/delete
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{ "response": "App with id {app_id} deleted successfully." }
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
22
embedchain/docs/examples/rest-api/deploy.mdx
Normal file
22
embedchain/docs/examples/rest-api/deploy.mdx
Normal file
@@ -0,0 +1,22 @@
|
||||
---
|
||||
openapi: post /{app_id}/deploy
|
||||
---
|
||||
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/{app_id}/deploy \
|
||||
-d "api_key=ec-xxxx"
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{ "response": "App deployed successfully." }
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
33
embedchain/docs/examples/rest-api/get-all-apps.mdx
Normal file
33
embedchain/docs/examples/rest-api/get-all-apps.mdx
Normal file
@@ -0,0 +1,33 @@
|
||||
---
|
||||
openapi: get /apps
|
||||
---
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request GET \
|
||||
--url http://localhost:8080/apps
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{
|
||||
"results": [
|
||||
{
|
||||
"config": "config1.yaml",
|
||||
"id": 1,
|
||||
"app_id": "app1"
|
||||
},
|
||||
{
|
||||
"config": "config2.yaml",
|
||||
"id": 2,
|
||||
"app_id": "app2"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
28
embedchain/docs/examples/rest-api/get-data.mdx
Normal file
28
embedchain/docs/examples/rest-api/get-data.mdx
Normal file
@@ -0,0 +1,28 @@
|
||||
---
|
||||
openapi: get /{app_id}/data
|
||||
---
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request GET \
|
||||
--url http://localhost:8080/{app_id}/data
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{
|
||||
"results": [
|
||||
{
|
||||
"data_type": "web_page",
|
||||
"data_value": "https://www.forbes.com/profile/elon-musk/",
|
||||
"metadata": "null"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
294
embedchain/docs/examples/rest-api/getting-started.mdx
Normal file
294
embedchain/docs/examples/rest-api/getting-started.mdx
Normal file
@@ -0,0 +1,294 @@
|
||||
---
|
||||
title: "🌍 Getting Started"
|
||||
---
|
||||
|
||||
## Quickstart
|
||||
|
||||
To use Embedchain as a REST API service, run the following command:
|
||||
|
||||
```bash
|
||||
docker run --name embedchain -p 8080:8080 embedchain/rest-api:latest
|
||||
```
|
||||
|
||||
Navigate to [http://localhost:8080/docs](http://localhost:8080/docs) to interact with the API. There is a full-fledged Swagger docs playground with all the information about the API endpoints.
|
||||
|
||||
|
||||
|
||||
## ⚡ Steps to get started
|
||||
|
||||
<Steps>
|
||||
<Step title="⚙️ Create an app">
|
||||
<Tabs>
|
||||
<Tab title="cURL">
|
||||
```bash
|
||||
curl --request POST "http://localhost:8080/create?app_id=my-app" \
|
||||
-H "accept: application/json"
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="python">
|
||||
```python
|
||||
import requests
|
||||
|
||||
url = "http://localhost:8080/create?app_id=my-app"
|
||||
|
||||
payload={}
|
||||
|
||||
response = requests.request("POST", url, data=payload)
|
||||
|
||||
print(response)
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="javascript">
|
||||
```javascript
|
||||
const data = fetch("http://localhost:8080/create?app_id=my-app", {
|
||||
method: "POST",
|
||||
}).then((res) => res.json());
|
||||
|
||||
console.log(data);
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="go">
|
||||
```go
|
||||
package main
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"net/http"
|
||||
"io/ioutil"
|
||||
)
|
||||
|
||||
func main() {
|
||||
|
||||
url := "http://localhost:8080/create?app_id=my-app"
|
||||
|
||||
payload := strings.NewReader("")
|
||||
|
||||
req, _ := http.NewRequest("POST", url, payload)
|
||||
|
||||
req.Header.Add("Content-Type", "application/json")
|
||||
|
||||
res, _ := http.DefaultClient.Do(req)
|
||||
|
||||
defer res.Body.Close()
|
||||
body, _ := ioutil.ReadAll(res.Body)
|
||||
|
||||
fmt.Println(res)
|
||||
fmt.Println(string(body))
|
||||
|
||||
}
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
</Step>
|
||||
<Step title="🗃️ Add data sources">
|
||||
<Tabs>
|
||||
<Tab title="cURL">
|
||||
```bash
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/my-app/add \
|
||||
-d "source=https://www.forbes.com/profile/elon-musk" \
|
||||
-d "data_type=web_page"
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="python">
|
||||
```python
|
||||
import requests
|
||||
|
||||
url = "http://localhost:8080/my-app/add"
|
||||
|
||||
payload = "source=https://www.forbes.com/profile/elon-musk&data_type=web_page"
|
||||
headers = {}
|
||||
|
||||
response = requests.request("POST", url, headers=headers, data=payload)
|
||||
|
||||
print(response)
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="javascript">
|
||||
```javascript
|
||||
const data = fetch("http://localhost:8080/my-app/add", {
|
||||
method: "POST",
|
||||
body: "source=https://www.forbes.com/profile/elon-musk&data_type=web_page",
|
||||
}).then((res) => res.json());
|
||||
|
||||
console.log(data);
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="go">
|
||||
```go
|
||||
package main
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"strings"
|
||||
"net/http"
|
||||
"io/ioutil"
|
||||
)
|
||||
|
||||
func main() {
|
||||
|
||||
url := "http://localhost:8080/my-app/add"
|
||||
|
||||
payload := strings.NewReader("source=https://www.forbes.com/profile/elon-musk&data_type=web_page")
|
||||
|
||||
req, _ := http.NewRequest("POST", url, payload)
|
||||
|
||||
req.Header.Add("Content-Type", "application/x-www-form-urlencoded")
|
||||
|
||||
res, _ := http.DefaultClient.Do(req)
|
||||
|
||||
defer res.Body.Close()
|
||||
body, _ := ioutil.ReadAll(res.Body)
|
||||
|
||||
fmt.Println(res)
|
||||
fmt.Println(string(body))
|
||||
|
||||
}
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
</Step>
|
||||
<Step title="💬 Query on your data">
|
||||
<Tabs>
|
||||
<Tab title="cURL">
|
||||
```bash
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/my-app/query \
|
||||
-d "query=Who is Elon Musk?"
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="python">
|
||||
```python
|
||||
import requests
|
||||
|
||||
url = "http://localhost:8080/my-app/query"
|
||||
|
||||
payload = "query=Who is Elon Musk?"
|
||||
headers = {}
|
||||
|
||||
response = requests.request("POST", url, headers=headers, data=payload)
|
||||
|
||||
print(response)
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="javascript">
|
||||
```javascript
|
||||
const data = fetch("http://localhost:8080/my-app/query", {
|
||||
method: "POST",
|
||||
body: "query=Who is Elon Musk?",
|
||||
}).then((res) => res.json());
|
||||
|
||||
console.log(data);
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="go">
|
||||
```go
|
||||
package main
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"strings"
|
||||
"net/http"
|
||||
"io/ioutil"
|
||||
)
|
||||
|
||||
func main() {
|
||||
|
||||
url := "http://localhost:8080/my-app/query"
|
||||
|
||||
payload := strings.NewReader("query=Who is Elon Musk?")
|
||||
|
||||
req, _ := http.NewRequest("POST", url, payload)
|
||||
|
||||
req.Header.Add("Content-Type", "application/x-www-form-urlencoded")
|
||||
|
||||
res, _ := http.DefaultClient.Do(req)
|
||||
|
||||
defer res.Body.Close()
|
||||
body, _ := ioutil.ReadAll(res.Body)
|
||||
|
||||
fmt.Println(res)
|
||||
fmt.Println(string(body))
|
||||
|
||||
}
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
</Step>
|
||||
<Step title="🚀 (Optional) Deploy your app to Embedchain Platform">
|
||||
<Tabs>
|
||||
<Tab title="cURL">
|
||||
```bash
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/my-app/deploy \
|
||||
-d "api_key=ec-xxxx"
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="python">
|
||||
```python
|
||||
import requests
|
||||
|
||||
url = "http://localhost:8080/my-app/deploy"
|
||||
|
||||
payload = "api_key=ec-xxxx"
|
||||
|
||||
response = requests.request("POST", url, data=payload)
|
||||
|
||||
print(response)
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="javascript">
|
||||
```javascript
|
||||
const data = fetch("http://localhost:8080/my-app/deploy", {
|
||||
method: "POST",
|
||||
body: "api_key=ec-xxxx",
|
||||
}).then((res) => res.json());
|
||||
|
||||
console.log(data);
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="go">
|
||||
```go
|
||||
package main
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"strings"
|
||||
"net/http"
|
||||
"io/ioutil"
|
||||
)
|
||||
|
||||
func main() {
|
||||
|
||||
url := "http://localhost:8080/my-app/deploy"
|
||||
|
||||
payload := strings.NewReader("api_key=ec-xxxx")
|
||||
|
||||
req, _ := http.NewRequest("POST", url, payload)
|
||||
|
||||
req.Header.Add("Content-Type", "application/x-www-form-urlencoded")
|
||||
|
||||
res, _ := http.DefaultClient.Do(req)
|
||||
|
||||
defer res.Body.Close()
|
||||
body, _ := ioutil.ReadAll(res.Body)
|
||||
|
||||
fmt.Println(res)
|
||||
fmt.Println(string(body))
|
||||
|
||||
}
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
And you're ready! 🎉
|
||||
|
||||
If you run into issues, please feel free to contact us using below links:
|
||||
|
||||
<Snippet file="get-help.mdx" />
|
||||
21
embedchain/docs/examples/rest-api/query.mdx
Normal file
21
embedchain/docs/examples/rest-api/query.mdx
Normal file
@@ -0,0 +1,21 @@
|
||||
---
|
||||
openapi: post /{app_id}/query
|
||||
---
|
||||
|
||||
<RequestExample>
|
||||
|
||||
```bash Request
|
||||
curl --request POST \
|
||||
--url http://localhost:8080/{app_id}/query \
|
||||
-d "query=who is Elon Musk?"
|
||||
```
|
||||
|
||||
</RequestExample>
|
||||
|
||||
<ResponseExample>
|
||||
|
||||
```json Response
|
||||
{ "response": "Net worth of Elon Musk is $218 Billion." }
|
||||
```
|
||||
|
||||
</ResponseExample>
|
||||
115
embedchain/docs/examples/showcase.mdx
Normal file
115
embedchain/docs/examples/showcase.mdx
Normal file
@@ -0,0 +1,115 @@
|
||||
---
|
||||
title: '🎪 Community showcase'
|
||||
---
|
||||
|
||||
Embedchain community has been super active in creating demos on top of Embedchain. On this page, we showcase all the apps, blogs, videos, and tutorials created by the community. ❤️
|
||||
|
||||
## Apps
|
||||
|
||||
### Open Source
|
||||
|
||||
- [My GSoC23 bot- Streamlit chat](https://github.com/lucifertrj/EmbedChain_GSoC23_BOT) by Tarun Jain
|
||||
- [Discord Bot for LLM chat](https://github.com/Reidond/discord_bots_playground/tree/c8b0c36541e4b393782ee506804c4b6962426dd6/python/chat-channel-bot) by Reidond
|
||||
- [EmbedChain-Streamlit-Docker App](https://github.com/amjadraza/embedchain-streamlit-app) by amjadraza
|
||||
- [Harry Potter Philosphers Stone Bot](https://github.com/vinayak-kempawad/Harry_Potter_Philosphers_Stone_Bot/) by Vinayak Kempawad, ([LinkedIn post](https://www.linkedin.com/feed/update/urn:li:activity:7080907532155686912/))
|
||||
- [LLM bot trained on own messages](https://github.com/Harin329/harinBot) by Hao Wu
|
||||
|
||||
### Closed Source
|
||||
|
||||
- [Taobot.io](https://taobot.io) - chatbot & knowledgebase hybrid by [cachho](https://github.com/cachho)
|
||||
- [Create Instant ChatBot 🤖 using embedchain](https://databutton.com/v/h3e680h9) by Avra, ([Tweet](https://twitter.com/Avra_b/status/1674704745154641920/))
|
||||
- [JOBO 🤖 — The AI-driven sidekick to craft your resume](https://try-jobo.com/) by Enrico Willemse, ([LinkedIn Post](https://www.linkedin.com/posts/enrico-willemse_jobai-gptfun-embedchain-activity-7090340080879374336-ueLB/))
|
||||
- [Explore Your Knowledge Base: Interactive chats over various forms of documents](https://chatdocs.dkedar.com/) by Kedar Dabhadkar, ([LinkedIn Post](https://www.linkedin.com/posts/dkedar7_machinelearning-llmops-activity-7092524836639424513-2O3L/))
|
||||
- [Chatbot trained on 1000+ videos of Ester hicks the co-author behind the famous book Secret](https://askabraham.tokenofme.io/) by Mohan Kumar
|
||||
|
||||
|
||||
## Templates
|
||||
|
||||
### Replit
|
||||
- [Embedchain Chat Bot](https://replit.com/@taranjeet1/Embedchain-Chat-Bot) by taranjeetio
|
||||
- [Embedchain Memory Chat Bot Template](https://replit.com/@taranjeetio/Embedchain-Memory-Chat-Bot-Template) by taranjeetio
|
||||
- [Chatbot app to demonstrate question-answering using retrieved information](https://replit.com/@AllisonMorrell/EmbedChainlitPublic) by Allison Morrell, ([LinkedIn Post](https://www.linkedin.com/posts/allison-morrell-2889275a_retrievalbot-screenshots-activity-7080339991754649600-wihZ/))
|
||||
|
||||
## Posts
|
||||
|
||||
### Blogs
|
||||
|
||||
- [Customer Service LINE Bot](https://www.evanlin.com/langchain-embedchain/) by Evan Lin
|
||||
- [Chatbot in Under 5 mins using Embedchain](https://medium.com/@ayush.wattal/chatbot-in-under-5-mins-using-embedchain-a4f161fcf9c5) by Ayush Wattal
|
||||
- [Understanding what the LLM framework embedchain does](https://zenn.dev/hijikix/articles/4bc8d60156a436) by Daisuke Hashimoto
|
||||
- [In bed with GPT and Node.js](https://dev.to/worldlinetech/in-bed-with-gpt-and-nodejs-4kh2) by Raphaël Semeteys, ([LinkedIn Post](https://www.linkedin.com/posts/raphaelsemeteys_in-bed-with-gpt-and-nodejs-activity-7088113552326029313-nn87/))
|
||||
- [Using Embedchain — A powerful LangChain Python wrapper to build Chat Bots even faster!⚡](https://medium.com/@avra42/using-embedchain-a-powerful-langchain-python-wrapper-to-build-chat-bots-even-faster-35c12994a360) by Avra, ([Tweet](https://twitter.com/Avra_b/status/1686767751560310784/))
|
||||
- [What is the Embedchain library?](https://jahaniwww.com/%da%a9%d8%aa%d8%a7%d8%a8%d8%ae%d8%a7%d9%86%d9%87-embedchain/) by Ali Jahani, ([LinkedIn Post](https://www.linkedin.com/posts/ajahani_aepaetaeqaexaggahyaeu-aetaexaesabraeaaeqaepaeu-activity-7097605202135904256-ppU-/))
|
||||
- [LangChain is Nice, But Have You Tried EmbedChain ?](https://medium.com/thoughts-on-machine-learning/langchain-is-nice-but-have-you-tried-embedchain-215a34421cde) by FS Ndzomga, ([Tweet](https://twitter.com/ndzfs/status/1695583640372035951/))
|
||||
- [Simplest Method to Build a Custom Chatbot with GPT-3.5 (via Embedchain)](https://www.ainewsletter.today/p/simplest-method-to-build-a-custom) by Arjun, ([Tweet](https://twitter.com/aiguy_arjun/status/1696393808467091758/))
|
||||
|
||||
### LinkedIn
|
||||
|
||||
- [What is embedchain](https://www.linkedin.com/posts/activity-7079393104423698432-wRyi/) by Rithesh Sreenivasan
|
||||
- [Building a chatbot with EmbedChain](https://www.linkedin.com/posts/activity-7078434598984060928-Zdso/) by Lior Sinclair
|
||||
- [Making chatbot without vs with embedchain](https://www.linkedin.com/posts/kalyanksnlp_llms-chatbots-langchain-activity-7077453416221863936-7N1L/) by Kalyan KS
|
||||
- [EmbedChain - very intuitive, first you index your data and then query!](https://www.linkedin.com/posts/shubhamsaboo_embedchain-a-framework-to-easily-create-activity-7079535460699557888-ad1X/) by Shubham Saboo
|
||||
- [EmbedChain - Harnessing power of LLM](https://www.linkedin.com/posts/uditsaini_chatbotrevolution-llmpoweredbots-embedchainframework-activity-7077520356827181056-FjTK/) by Udit S.
|
||||
- [AI assistant for ABBYY Vantage](https://www.linkedin.com/posts/maximevermeir_llm-github-abbyy-activity-7081658972071424000-fXfZ/) by Maxime V.
|
||||
- [About embedchain](https://www.linkedin.com/feed/update/urn:li:activity:7080984218914189312/) by Morris Lee
|
||||
- [How to use Embedchain](https://www.linkedin.com/posts/nehaabansal_github-embedchainembedchain-framework-activity-7085830340136595456-kbW5/) by Neha Bansal
|
||||
- [Youtube/Webpage summary for Energy Study](https://www.linkedin.com/posts/bar%C4%B1%C5%9F-sanl%C4%B1-34b82715_enerji-python-activity-7082735341563977730-Js0U/) by Barış Sanlı, ([Tweet](https://twitter.com/barissanli/status/1676968784979193857/))
|
||||
- [Demo: How to use Embedchain? (Contains Collab Notebook link)](https://www.linkedin.com/posts/liorsinclair_embedchain-is-getting-a-lot-of-traction-because-activity-7103044695995424768-RckT/) by Lior Sinclair
|
||||
|
||||
### Twitter
|
||||
|
||||
- [What is embedchain](https://twitter.com/AlphaSignalAI/status/1672668574450847745) by Lior
|
||||
- [Building a chatbot with Embedchain](https://twitter.com/Saboo_Shubham_/status/1673537044419686401) by Shubham Saboo
|
||||
- [Chatbot docker image behind an API with yaml configs with Embedchain](https://twitter.com/tricalt/status/1678411430192730113/) by Vasilije
|
||||
- [Build AI powered PDF chatbot with just five lines of Python code with Embedchain!](https://twitter.com/Saboo_Shubham_/status/1676627104866156544/) by Shubham Saboo
|
||||
- [Chatbot against a youtube video using embedchain](https://twitter.com/smaameri/status/1675201443043704834/) by Sami Maameri
|
||||
- [Highlights of EmbedChain](https://twitter.com/carl_AIwarts/status/1673542204328120321/) by carl_AIwarts
|
||||
- [Build Llama-2 chatbot in less than 5 minutes](https://twitter.com/Saboo_Shubham_/status/1682168956918833152/) by Shubham Saboo
|
||||
- [All cool features of embedchain](https://twitter.com/DhravyaShah/status/1683497882438217728/) by Dhravya Shah, ([LinkedIn Post](https://www.linkedin.com/posts/dhravyashah_what-if-i-tell-you-that-you-can-make-an-ai-activity-7089459599287726080-ZIYm/))
|
||||
- [Read paid Medium articles for Free using embedchain](https://twitter.com/kumarkaushal_/status/1688952961622585344) by Kaushal Kumar
|
||||
|
||||
## Videos
|
||||
|
||||
- [Embedchain in one shot](https://www.youtube.com/watch?v=vIhDh7H73Ww&t=82s) by AI with Tarun
|
||||
- [embedChain Create LLM powered bots over any dataset Python Demo Tesla Neurallink Chatbot Example](https://www.youtube.com/watch?v=bJqAn22a6Gc) by Rithesh Sreenivasan
|
||||
- [Embedchain - NEW 🔥 Langchain BABY to build LLM Bots](https://www.youtube.com/watch?v=qj_GNQ06I8o) by 1littlecoder
|
||||
- [EmbedChain -- NEW!: Build LLM-Powered Bots with Any Dataset](https://www.youtube.com/watch?v=XmaBezzGHu4) by DataInsightEdge
|
||||
- [Chat With Your PDFs in less than 10 lines of code! EMBEDCHAIN tutorial](https://www.youtube.com/watch?v=1ugkcsAcw44) by Phani Reddy
|
||||
- [How To Create A Custom Knowledge AI Powered Bot | Install + How To Use](https://www.youtube.com/watch?v=VfCrIiAst-c) by The Ai Solopreneur
|
||||
- [Build Custom Chatbot in 6 min with this Framework [Beginner Friendly]](https://www.youtube.com/watch?v=-8HxOpaFySM) by Maya Akim
|
||||
- [embedchain-streamlit-app](https://www.youtube.com/watch?v=3-9GVd-3v74) by Amjad Raza
|
||||
- [🤖CHAT with ANY ONLINE RESOURCES using EMBEDCHAIN - a LangChain wrapper, in few lines of code !](https://www.youtube.com/watch?v=Mp7zJe4TIdM) by Avra
|
||||
- [Building resource-driven LLM-powered bots with Embedchain](https://www.youtube.com/watch?v=IVfcAgxTO4I) by BugBytes
|
||||
- [embedchain-streamlit-demo](https://www.youtube.com/watch?v=yJAWB13FhYQ) by Amjad Raza
|
||||
- [Embedchain - create your own AI chatbots using open source models](https://www.youtube.com/shorts/O3rJWKwSrWE) by Dhravya Shah
|
||||
- [AI ChatBot in 5 lines Python Code](https://www.youtube.com/watch?v=zjWvLJLksv8) by Data Engineering
|
||||
- [Interview with Karl Marx](https://www.youtube.com/watch?v=5Y4Tscwj1xk) by Alexander Ray Williams
|
||||
- [Vlog where we try to build a bot based on our content on the internet](https://www.youtube.com/watch?v=I2w8CWM3bx4) by DV, ([Tweet](https://twitter.com/dvcoolster/status/1688387017544261632))
|
||||
- [CHAT with ANY ONLINE RESOURCES using EMBEDCHAIN|STREAMLIT with MEMORY |All OPENSOURCE](https://www.youtube.com/watch?v=TqQIHWoWTDQ&pp=ygUKZW1iZWRjaGFpbg%3D%3D) by DataInsightEdge
|
||||
- [Build POWERFUL LLM Bots EASILY with Your Own Data - Embedchain - Langchain 2.0? (Tutorial)](https://www.youtube.com/watch?v=jE24Y_GasE8) by WorldofAI, ([Tweet](https://twitter.com/intheworldofai/status/1696229166922780737))
|
||||
- [Embedchain: An AI knowledge base assistant for customizing enterprise private data, which can be connected to discord, whatsapp, slack, tele and other terminals (with gradio to build a request interface) in Chinese](https://www.youtube.com/watch?v=5RZzCJRk-d0) by AIGC LINK
|
||||
- [Embedchain Introduction](https://www.youtube.com/watch?v=Jet9zAqyggI) by Fahd Mirza
|
||||
|
||||
## Mentions
|
||||
|
||||
### Github repos
|
||||
|
||||
- [Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM)
|
||||
- [awesome-chatgpt-api](https://github.com/reorx/awesome-chatgpt-api)
|
||||
- [awesome-langchain](https://github.com/kyrolabs/awesome-langchain)
|
||||
- [Awesome-Prompt-Engineering](https://github.com/promptslab/Awesome-Prompt-Engineering)
|
||||
- [awesome-chatgpt](https://github.com/eon01/awesome-chatgpt)
|
||||
- [Awesome-LLMOps](https://github.com/tensorchord/Awesome-LLMOps)
|
||||
- [awesome-generative-ai](https://github.com/filipecalegario/awesome-generative-ai)
|
||||
- [awesome-gpt](https://github.com/formulahendry/awesome-gpt)
|
||||
- [awesome-ChatGPT-repositories](https://github.com/taishi-i/awesome-ChatGPT-repositories)
|
||||
- [awesome-gpt-prompt-engineering](https://github.com/snwfdhmp/awesome-gpt-prompt-engineering)
|
||||
- [awesome-chatgpt](https://github.com/awesome-chatgpt/awesome-chatgpt)
|
||||
- [awesome-llm-and-aigc](https://github.com/sjinzh/awesome-llm-and-aigc)
|
||||
- [awesome-compbio-chatgpt](https://github.com/csbl-br/awesome-compbio-chatgpt)
|
||||
- [Awesome-LLM4Tool](https://github.com/OpenGVLab/Awesome-LLM4Tool)
|
||||
|
||||
## Meetups
|
||||
|
||||
- [Dash and ChatGPT: Future of AI-enabled apps 30/08/23](https://go.plotly.com/dash-chatgpt)
|
||||
- [Pie & AI: Bangalore - Build end-to-end LLM app using Embedchain 01/09/23](https://www.eventbrite.com/e/pie-ai-bangalore-build-end-to-end-llm-app-using-embedchain-tickets-698045722547)
|
||||
67
embedchain/docs/examples/slack-AI.mdx
Normal file
67
embedchain/docs/examples/slack-AI.mdx
Normal file
@@ -0,0 +1,67 @@
|
||||
[Embedchain Examples Repo](https://github.com/embedchain/examples) contains code on how to build your own Slack AI to chat with the unstructured data lying in your slack channels.
|
||||
|
||||
|
||||
|
||||
## Getting started
|
||||
|
||||
Create a Slack AI involves 3 steps
|
||||
|
||||
* Create slack user
|
||||
* Set environment variables
|
||||
* Run the app locally
|
||||
|
||||
### Step 1: Create Slack user token
|
||||
|
||||
Follow the steps given below to fetch your slack user token to get data through Slack APIs:
|
||||
|
||||
1. Create a workspace on Slack if you don’t have one already by clicking [here](https://slack.com/intl/en-in/).
|
||||
2. Create a new App on your Slack account by going [here](https://api.slack.com/apps).
|
||||
3. Select `From Scratch`, then enter the App Name and select your workspace.
|
||||
4. Navigate to `OAuth & Permissions` tab from the left sidebar and go to the `scopes` section. Add the following scopes under `User Token Scopes`:
|
||||
|
||||
```
|
||||
# Following scopes are needed for reading channel history
|
||||
channels:history
|
||||
channels:read
|
||||
|
||||
# Following scopes are needed to fetch list of channels from slack
|
||||
groups:read
|
||||
mpim:read
|
||||
im:read
|
||||
```
|
||||
|
||||
5. Click on the `Install to Workspace` button under `OAuth Tokens for Your Workspace` section in the same page and install the app in your slack workspace.
|
||||
6. After installing the app you will see the `User OAuth Token`, save that token as you will need to configure it as `SLACK_USER_TOKEN` for this demo.
|
||||
|
||||
### Step 2: Set environment variables
|
||||
|
||||
Navigate to `api` folder and set your `HUGGINGFACE_ACCESS_TOKEN` and `SLACK_USER_TOKEN` in `.env.example` file. Then rename the `.env.example` file to `.env`.
|
||||
|
||||
|
||||
<Note>
|
||||
By default, we use `Mixtral` model from Hugging Face. However, if you prefer to use OpenAI model, then set `OPENAI_API_KEY` instead of `HUGGINGFACE_ACCESS_TOKEN` along with `SLACK_USER_TOKEN` in `.env` file, and update the code in `api/utils/app.py` file to use OpenAI model instead of Hugging Face model.
|
||||
</Note>
|
||||
|
||||
### Step 3: Run app locally
|
||||
|
||||
Follow the instructions given below to run app locally based on your development setup (with docker or without docker):
|
||||
|
||||
#### With docker
|
||||
|
||||
```bash
|
||||
docker-compose build
|
||||
ec start --docker
|
||||
```
|
||||
|
||||
#### Without docker
|
||||
|
||||
```bash
|
||||
ec install-reqs
|
||||
ec start
|
||||
```
|
||||
|
||||
Finally, you will have the Slack AI frontend running on http://localhost:3000. You can also access the REST APIs on http://localhost:8000.
|
||||
|
||||
## Credits
|
||||
|
||||
This demo was built using the Embedchain's [full stack demo template](https://docs.embedchain.ai/get-started/full-stack). Follow the instructions [given here](https://docs.embedchain.ai/get-started/full-stack) to create your own full stack RAG application.
|
||||
50
embedchain/docs/examples/slack_bot.mdx
Normal file
50
embedchain/docs/examples/slack_bot.mdx
Normal file
@@ -0,0 +1,50 @@
|
||||
---
|
||||
title: '💼 Slack Bot'
|
||||
---
|
||||
|
||||
### 🖼️ Setup
|
||||
|
||||
1. Create a workspace on Slack if you don't have one already by clicking [here](https://slack.com/intl/en-in/).
|
||||
2. Create a new App on your Slack account by going [here](https://api.slack.com/apps).
|
||||
3. Select `From Scratch`, then enter the Bot Name and select your workspace.
|
||||
4. On the left Sidebar, go to `OAuth and Permissions` and add the following scopes under `Bot Token Scopes`:
|
||||
```text
|
||||
app_mentions:read
|
||||
channels:history
|
||||
channels:read
|
||||
chat:write
|
||||
```
|
||||
5. Now select the option `Install to Workspace` and after it's done, copy the `Bot User OAuth Token` and set it in your secrets as `SLACK_BOT_TOKEN`.
|
||||
6. Run your bot now,
|
||||
<Tabs>
|
||||
<Tab title="docker">
|
||||
```bash
|
||||
docker run --name slack-bot -e OPENAI_API_KEY=sk-xxx -e SLACK_BOT_TOKEN=xxx -p 8000:8000 embedchain/slack-bot
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="python">
|
||||
```bash
|
||||
pip install --upgrade "embedchain[slack]"
|
||||
python3 -m embedchain.bots.slack --port 8000
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
7. Expose your bot to the internet. You can use your machine's public IP or DNS. Otherwise, employ a proxy server like [ngrok](https://ngrok.com/) to make your local bot accessible.
|
||||
8. On the Slack API website go to `Event Subscriptions` on the left Sidebar and turn on `Enable Events`.
|
||||
9. In `Request URL`, enter your server or ngrok address.
|
||||
10. After it gets verified, click on `Subscribe to bot events`, add `message.channels` Bot User Event and click on `Save Changes`.
|
||||
11. Now go to your workspace, right click on the bot name in the sidebar, click `view app details`, then `add this app to a channel`.
|
||||
|
||||
### 🚀 Usage Instructions
|
||||
|
||||
- Go to the channel where you have added your bot.
|
||||
- To add data sources to the bot, use the command:
|
||||
```text
|
||||
add <data_type> <url_or_text>
|
||||
```
|
||||
- To ask queries from the bot, use the command:
|
||||
```text
|
||||
query <question>
|
||||
```
|
||||
|
||||
🎉 Happy Chatting! 🎉
|
||||
51
embedchain/docs/examples/telegram_bot.mdx
Normal file
51
embedchain/docs/examples/telegram_bot.mdx
Normal file
@@ -0,0 +1,51 @@
|
||||
---
|
||||
title: "📱 Telegram Bot"
|
||||
---
|
||||
|
||||
### 🖼️ Template Setup
|
||||
|
||||
- Open the Telegram app and search for the `BotFather` user.
|
||||
- Start a chat with BotFather and use the `/newbot` command to create a new bot.
|
||||
- Follow the instructions to choose a name and username for your bot.
|
||||
- Once the bot is created, BotFather will provide you with a unique token for your bot.
|
||||
|
||||
<Tabs>
|
||||
<Tab title="docker">
|
||||
```bash
|
||||
docker run --name telegram-bot -e OPENAI_API_KEY=sk-xxx -e TELEGRAM_BOT_TOKEN=xxx -p 8000:8000 embedchain/telegram-bot
|
||||
```
|
||||
|
||||
<Note>
|
||||
If you wish to use **Docker**, you would need to host your bot on a server.
|
||||
You can use [ngrok](https://ngrok.com/) to expose your localhost to the
|
||||
internet and then set the webhook using the ngrok URL.
|
||||
</Note>
|
||||
|
||||
</Tab>
|
||||
<Tab title="replit">
|
||||
<Card>
|
||||
Fork <ins>**[this](https://replit.com/@taranjeetio/EC-Telegram-Bot-Template?v=1#README.md)**</ins> replit template.
|
||||
</Card>
|
||||
|
||||
- Set your `OPENAI_API_KEY` in Secrets.
|
||||
- Set the unique token as `TELEGRAM_BOT_TOKEN` in Secrets.
|
||||
|
||||
</Tab>
|
||||
|
||||
</Tabs>
|
||||
|
||||
- Click on `Run` in the replit container and a URL will get generated for your bot.
|
||||
- Now set your webhook by running the following link in your browser:
|
||||
|
||||
```url
|
||||
https://api.telegram.org/bot<Your_Telegram_Bot_Token>/setWebhook?url=<Replit_Generated_URL>
|
||||
```
|
||||
|
||||
- When you get a successful response in your browser, your bot is ready to be used.
|
||||
|
||||
### 🚀 Usage Instructions
|
||||
|
||||
- Open your bot by searching for it using the bot name or bot username.
|
||||
- Click on `Start` or type `/start` and follow the on screen instructions.
|
||||
|
||||
🎉 Happy Chatting! 🎉
|
||||
55
embedchain/docs/examples/whatsapp_bot.mdx
Normal file
55
embedchain/docs/examples/whatsapp_bot.mdx
Normal file
@@ -0,0 +1,55 @@
|
||||
---
|
||||
title: '💬 WhatsApp Bot'
|
||||
---
|
||||
|
||||
### 🚀 Getting started
|
||||
|
||||
1. Install embedchain python package:
|
||||
|
||||
```bash
|
||||
pip install --upgrade embedchain
|
||||
```
|
||||
|
||||
2. Launch your WhatsApp bot:
|
||||
|
||||
<Tabs>
|
||||
<Tab title="docker">
|
||||
```bash
|
||||
docker run --name whatsapp-bot -e OPENAI_API_KEY=sk-xxx -p 8000:8000 embedchain/whatsapp-bot
|
||||
```
|
||||
</Tab>
|
||||
<Tab title="python">
|
||||
```bash
|
||||
python -m embedchain.bots.whatsapp --port 5000
|
||||
```
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
|
||||
If your bot needs to be accessible online, use your machine's public IP or DNS. Otherwise, employ a proxy server like [ngrok](https://ngrok.com/) to make your local bot accessible.
|
||||
|
||||
3. Create a free account on [Twilio](https://www.twilio.com/try-twilio)
|
||||
- Set up a WhatsApp Sandbox in your Twilio dashboard. Access it via the left sidebar: `Messaging > Try it out > Send a WhatsApp Message`.
|
||||
- Follow on-screen instructions to link a phone number for chatting with your bot
|
||||
- Copy your bot's public URL, add /chat at the end, and paste it in Twilio's WhatsApp Sandbox settings under "When a message comes in". Save the settings.
|
||||
|
||||
- Copy your bot's public url, append `/chat` at the end and paste it under `When a message comes in` under the `Sandbox settings` for Whatsapp in Twilio. Save your settings.
|
||||
|
||||
### 💬 How to use
|
||||
|
||||
- To connect a new number or reconnect an old one in the Sandbox, follow Twilio's instructions.
|
||||
- To include data sources, use this command:
|
||||
```text
|
||||
add <url_or_text>
|
||||
```
|
||||
|
||||
- To ask the bot questions, just type your query:
|
||||
```text
|
||||
<your-question-here>
|
||||
```
|
||||
|
||||
### Example
|
||||
|
||||
Here is an example of Elon Musk WhatsApp Bot that we created:
|
||||
|
||||
<img src="/images/whatsapp.jpg"/>
|
||||
Reference in New Issue
Block a user