Merge branch 'main' into main

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Mohit Dhote 2023-10-07 15:23:53 +05:30 committed by GitHub
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.github/labeler.yml vendored Normal file
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@ -0,0 +1,23 @@
repo:
- '*'
github:
- .github/**/*
application:
- application/**/*
docs:
- docs/**/*
extensions:
- extensions/**/*
frontend:
- frontend/**/*
scripts:
- scripts/**/*
tests:
- tests/**/*

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.github/workflows/labeler.yml vendored Normal file
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@ -0,0 +1,15 @@
# https://github.com/actions/labeler
name: Pull Request Labeler
on:
- pull_request_target
jobs:
triage:
permissions:
contents: read
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: actions/labeler@v4
with:
repo-token: "${{ secrets.GITHUB_TOKEN }}"
sync-labels: true

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@ -2,7 +2,7 @@
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
We as members, contributors, and leaders, pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
@ -10,20 +10,20 @@ nationality, personal appearance, race, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
diverse, inclusive, and a healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
Examples of behavior that contribute to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Demonstrating empathy and kindness towards other people
* Being respectful and open to differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Taking accountability and offering apologies to those who have been impacted by our errors,
while also gaining insights from the situation
* Focusing on what is best not just for us as individuals, but for the
overall community
community as a whole
Examples of unacceptable behavior include:
@ -31,7 +31,7 @@ Examples of unacceptable behavior include:
advances of any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email
* Publishing other's private information, such as a physical or email
address, without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
@ -74,7 +74,7 @@ the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
unprofessional or unwelcome in the community space.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
@ -107,7 +107,7 @@ Violating these terms may lead to a permanent ban.
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
individual, or aggression towards or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within
the community.

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@ -1,6 +1,6 @@
# Welcome to DocsGPT Contributing guideline
# Welcome to DocsGPT Contributing Guidelines
Thank you for choosing this project to contribute to, we are all very grateful!
Thank you for choosing this project to contribute to. We are all very grateful!
### [🎉 Join the Hacktoberfest with DocsGPT and Earn a Free T-shirt! 🎉](https://github.com/arc53/DocsGPT/blob/main/HACKTOBERFEST.md)
@ -17,30 +17,36 @@ Thank you for choosing this project to contribute to, we are all very grateful!
## 🐞 Issues and Pull requests
We value contributions to our issues in the form of discussion or suggestion, we recommend that you check out existing issues and our [Roadmap](https://github.com/orgs/arc53/projects/2)
We value contributions to our issues in the form of discussion or suggestions. We recommend that you check out existing issues and our [roadmap](https://github.com/orgs/arc53/projects/2).
If you want to contribute by writing code there are a few things that you should know before doing it:
We have frontend (React, Vite) and Backend (python)
If you want to contribute by writing code, there are a few things that you should know before doing it:
We have a frontend in React (Vite) and backend in Python.
### If you are looking to contribute to frontend (⚛React, Vite):
- The current frontend is being migrated from `/application` to `/frontend` with a new design, so please contribute to the new one.
- Check out this [milestone](https://github.com/arc53/DocsGPT/milestone/1) and its issues.
- The Figma design can be found [here](https://www.figma.com/file/OXLtrl1EAy885to6S69554/DocsGPT?node-id=0%3A1&t=hjWVuxRg9yi5YkJ9-1).
### If you are looking to contribute to Frontend (⚛React, Vite):
The current frontend is being migrated from /application to /frontend with a new design, so please contribute to the new one. Check out this [Milestone](https://github.com/arc53/DocsGPT/milestone/1) and its issues also [Figma](https://www.figma.com/file/OXLtrl1EAy885to6S69554/DocsGPT?node-id=0%3A1&t=hjWVuxRg9yi5YkJ9-1)
Please try to follow the guidelines.
### If you are looking to contribute to Backend (🐍Python):
* Check out our issues, and contribute to /application or /scripts (ignore old ingest_rst.py ingest_rst_sphinx.py files, they will be deprecated soon)
* All new code should be covered with unit tests ([pytest](https://github.com/pytest-dev/pytest)). Please find tests under [/tests](https://github.com/arc53/DocsGPT/tree/main/tests) folder.
* Before submitting your PR make sure that after you ingested some test data it is queryable.
### If you are looking to contribute to Backend (🐍 Python):
- Check out our issues and contribute to `/application` or `/scripts` (ignore old `ingest_rst.py` `ingest_rst_sphinx.py` files; they will be deprecated soon).
- All new code should be covered with unit tests ([pytest](https://github.com/pytest-dev/pytest)). Please find tests under [`/tests`](https://github.com/arc53/DocsGPT/tree/main/tests) folder.
- Before submitting your PR, ensure it is queryable after ingesting some test data.
### Testing
To run unit tests, from the root of the repository execute:
To run unit tests from the root of the repository, execute:
```
python -m pytest
```
### Workflow:
Create a fork, make changes on your forked repository, and submit changes in the form of a pull request.
Create a fork, make changes on your forked repository, and submit changes as a pull request.
## Questions/collaboration
Please join our [Discord](https://discord.gg/n5BX8dh8rU) don't hesitate, we are very friendly and welcoming to new contributors.
Please join our [Discord](https://discord.gg/n5BX8dh8rU). Don't hesitate; we are very friendly and welcoming to new contributors.
# Thank you so much for considering contributing to DocsGPT!🙏

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@ -2,13 +2,13 @@
Welcome, contributors! We're excited to announce that DocsGPT is participating in Hacktoberfest. Get involved by submitting a **meaningful** pull request, and earn a free shirt in return!
All contributors with accepted PR's will receive a cool holopin! 🤩 (Watchout for a reply in your PR to collect it)
All contributors with accepted PRs will receive a cool Holopin! 🤩 (Watch out for a reply in your PR to collect it).
📜 Here's How to Contribute:
🛠️ Code: This is the golden ticket! Make meaningful contributions through PRs.
📚 Wiki: Improve our documentation, Create a guide or change existing documentation.
🖥️ Design: Improve the UI/UX, or design a new feature.
🖥️ Design: Improve the UI/UX or design a new feature.
📝 Guidelines for Pull Requests:
@ -16,20 +16,20 @@ Familiarize yourself with the current contributions and our [Roadmap](https://gi
Deciding to contribute with code? Here are some insights based on the area of your interest:
Frontend (⚛React, Vite):
Most of the code is located in /frontend folder. You can also check out our React extension in /extensions/react-widget.
For design references, here's the [Figma](https://www.figma.com/file/OXLtrl1EAy885to6S69554/DocsGPT?node-id=0%3A1&t=hjWVuxRg9yi5YkJ9-1).
Ensure you adhere to the established guidelines.
- Frontend (⚛React, Vite):
- Most of the code is located in `/frontend` folder. You can also check out our React extension in /extensions/react-widget.
- For design references, here's the [Figma](https://www.figma.com/file/OXLtrl1EAy885to6S69554/DocsGPT?node-id=0%3A1&t=hjWVuxRg9yi5YkJ9-1).
- Ensure you adhere to the established guidelines.
Backend (🐍Python):
Focus on /application or /scripts. However, avoid the files ingest_rst.py and ingest_rst_sphinx.py as they are soon to be deprecated.
Newly added code should come with relevant unit tests (pytest).
Refer to the /tests folder for test suites.
- Backend (🐍Python):
- Focus on `/application` or `/scripts`. However, avoid the files ingest_rst.py and ingest_rst_sphinx.py, as they will soon be deprecated.
- Newly added code should come with relevant unit tests (pytest).
- Refer to the `/tests` folder for test suites.
Check out [Contributing Guidelines](https://github.com/arc53/DocsGPT/blob/main/CONTRIBUTING.md)
Check out our [Contributing Guidelines](https://github.com/arc53/DocsGPT/blob/main/CONTRIBUTING.md)
Once you have Created your PR and it was merged, please fill in this [form](https://airtable.com/appfkqFVjB0RpYCJh/shrXXM98xgRsbjO7s)
Once you have created your PR and our maintainers have merged it, please fill in this [form](https://airtable.com/appfkqFVjB0RpYCJh/shrXXM98xgRsbjO7s).
Don't be shy! Hop into our [Discord](https://discord.gg/n5BX8dh8rU) Server. We're a friendly bunch and eager to assist newcomers.
Feel free to join our Discord server. We're here to help newcomers, so don't hesitate to jump in! [Join us here](https://discord.gg/n5BX8dh8rU).
Big thanks for considering contributing to DocsGPT during Hacktoberfest! 🙏 Your effort can earn you a swanky new t-shirt. 🎁 Let's code together! 🚀
Thank you very much for considering contributing to DocsGPT during Hacktoberfest! 🙏 Your contributions could earn you a stylish new t-shirt as a token of our appreciation. 🎁 Join us, and let's code together! 🚀

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@ -18,15 +18,13 @@ Say goodbye to time-consuming manual searches, and let <strong>DocsGPT</strong>
<a href="https://github.com/arc53/DocsGPT">![example2](https://img.shields.io/github/forks/arc53/docsgpt?style=social)</a>
<a href="https://github.com/arc53/DocsGPT/blob/main/LICENSE">![example3](https://img.shields.io/github/license/arc53/docsgpt)</a>
<a href="https://discord.gg/n5BX8dh8rU">![example3](https://img.shields.io/discord/1070046503302877216)</a>
</div>
### Production Support/ Help for companies:
### Production Support / Help for companies:
When deploying your DocsGPT to a live environment, we're eager to provide personalized assistance.
- [Schedule Demo 👋](https://cal.com/arc53/docsgpt-demo-b2b?date=2023-10-04&month=2023-10)
We're eager to provide personalized assistance when deploying your DocsGPT to a live environment.
- [Get Support 👋](https://airtable.com/appdeaL0F1qV8Bl2C/shrrJF1Ll7btCJRbP)
- [Send Email ✉️](mailto:contact@arc53.com?subject=DocsGPT%20support%2Fsolutions)
### [🎉 Join the Hacktoberfest with DocsGPT and Earn a Free T-shirt! 🎉](https://github.com/arc53/DocsGPT/blob/main/HACKTOBERFEST.md)
@ -36,9 +34,9 @@ When deploying your DocsGPT to a live environment, we're eager to provide person
## Roadmap
You can find our [Roadmap](https://github.com/orgs/arc53/projects/2) here. Please don't hesitate to contribute or create issues, it helps us make DocsGPT better!
You can find our roadmap [here](https://github.com/orgs/arc53/projects/2). Please don't hesitate to contribute or create issues, it helps us improve DocsGPT!
## Our Open-Source models optimised for DocsGPT:
## Our Open-Source models optimized for DocsGPT:
| Name | Base Model | Requirements (or similar) |
|-------------------|------------|----------------------------------------------------------|
@ -47,7 +45,7 @@ You can find our [Roadmap](https://github.com/orgs/arc53/projects/2) here. Pleas
| [Docsgpt-40b-falcon](https://huggingface.co/Arc53/docsgpt-40b-falcon) | falcon-40b | 8xA10G gpu's |
If you don't have enough resources to run it you can use bitsnbytes to quantize
If you don't have enough resources to run it, you can use bitsnbytes to quantize.
## Features
@ -58,7 +56,7 @@ If you don't have enough resources to run it you can use bitsnbytes to quantize
## Useful links
[Live preview](https://docsgpt.arc53.com/)
[Join Our Discord](https://discord.gg/n5BX8dh8rU)
[Join our Discord](https://discord.gg/n5BX8dh8rU)
[Guides](https://docs.docsgpt.co.uk/)
@ -70,28 +68,28 @@ If you don't have enough resources to run it you can use bitsnbytes to quantize
## Project structure
- Application - Flask app (main application)
- Application - Flask app (main application).
- Extensions - Chrome extension
- Extensions - Chrome extension.
- Scripts - Script that creates similarity search index and store for other libraries.
- Scripts - Script that creates similarity search index and stores for other libraries.
- Frontend - Frontend uses Vite and React
- Frontend - Frontend uses Vite and React.
## QuickStart
Note: Make sure you have Docker installed
On Mac OS or Linux just write:
On Mac OS or Linux, write:
`./setup.sh`
It will install all the dependencies and give you an option to download local model or use OpenAI
It will install all the dependencies and allow you to download the local model or use OpenAI.
Otherwise refer to this Guide:
Otherwise, refer to this Guide:
1. Download and open this repository with `git clone https://github.com/arc53/DocsGPT.git`
2. Create a .env file in your root directory and set the env variable OPENAI_API_KEY with your OpenAI API key and VITE_API_STREAMING to true or false, depending on if you want streaming answers or not
2. Create a `.env` file in your root directory and set the env variable `OPENAI_API_KEY` with your OpenAI API key and `VITE_API_STREAMING` to true or false, depending on if you want streaming answers or not.
It should look like this inside:
```
@ -99,15 +97,15 @@ Otherwise refer to this Guide:
VITE_API_STREAMING=true
```
See optional environment variables in the `/.env-template` and `/application/.env_sample` files.
3. Run `./run-with-docker-compose.sh`
4. Navigate to http://localhost:5173/
3. Run `./run-with-docker-compose.sh`.
4. Navigate to http://localhost:5173/.
To stop just run Ctrl + C
To stop, just run `Ctrl + C`.
## Development environments
### Spin up mongo and redis
For development only 2 containers are used from docker-compose.yaml (by deleting all services except for Redis and Mongo).
For development, only two containers are used from `docker-compose.yaml` (by deleting all services except for Redis and Mongo).
See file [docker-compose-dev.yaml](./docker-compose-dev.yaml).
Run
@ -120,31 +118,31 @@ docker compose -f docker-compose-dev.yaml up -d
Make sure you have Python 3.10 or 3.11 installed.
1. Export required environment variables or prep .env file in application folder
Prepare .env file
Copy `.env_sample` and create `.env` with your OpenAI API token for the API_KEY and EMBEDDINGS_KEY fields
1. Export required environment variables or prepare a `.env` file in the `/application` folder:
- Copy `.env_sample` and create `.env` with your OpenAI API token for the `API_KEY` and `EMBEDDINGS_KEY` fields.
(check out application/core/settings.py if you want to see more config options)
3. (optional) Create a Python virtual environment
(check out [`application/core/settings.py`](application/core/settings.py) if you want to see more config options.)
2. (optional) Create a Python virtual environment:
```commandline
python -m venv venv
. venv/bin/activate
```
4. Change to `application/` subdir and install dependencies for the backend
3. Change to the `application/` subdir and install dependencies for the backend:
```commandline
pip install -r application/requirements.txt
```
5. Run the app `flask run --host=0.0.0.0 --port=7091`
6. Start worker with `celery -A application.app.celery worker -l INFO`
4. Run the app using `flask run --host=0.0.0.0 --port=7091`.
5. Start worker with `celery -A application.app.celery worker -l INFO`.
### Start frontend
Make sure you have Node version 16 or higher.
1. Navigate to `/frontend` folder
2. Install dependencies
`npm install`
3. Run the app
`npm run dev`
1. Navigate to the `/frontend` folder.
2. Install dependencies by running `npm install`.
3. Run the app using `npm run dev`.
## Contributing
Please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for information about how to get involved. We welcome issues, questions, and pull requests.
@ -152,7 +150,7 @@ Please refer to the [CONTRIBUTING.md](CONTRIBUTING.md) file for information abou
## Code Of Conduct
We as members, contributors, and leaders, pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation. Please refer to the [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) file for more information about contributing.
## All Thanks To Our Contributors
## Many Thanks To Our Contributors
<a href="[https://github.com/arc53/DocsGPT/graphs/contributors](https://docsgpt.arc53.com/)">
<img src="https://contrib.rocks/image?repo=arc53/DocsGPT" />
@ -162,4 +160,3 @@ We as members, contributors, and leaders, pledge to make participation in our co
The source code license is MIT, as described in the LICENSE file.
Built with [🦜️🔗 LangChain](https://github.com/hwchase17/langchain)

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@ -1,68 +1,44 @@
import platform
import dotenv
from application.celery import celery
from flask import Flask, request, redirect
from application.core.settings import settings
from application.api.user.routes import user
from application.api.answer.routes import answer
from application.api.internal.routes import internal
# Redirect PosixPath to WindowsPath on Windows
if platform.system() == "Windows":
import pathlib
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath
# loading the .env file
dotenv.load_dotenv()
app = Flask(__name__)
app.register_blueprint(user)
app.register_blueprint(answer)
app.register_blueprint(internal)
app.config["UPLOAD_FOLDER"] = UPLOAD_FOLDER = "inputs"
app.config["CELERY_BROKER_URL"] = settings.CELERY_BROKER_URL
app.config["CELERY_RESULT_BACKEND"] = settings.CELERY_RESULT_BACKEND
app.config["MONGO_URI"] = settings.MONGO_URI
app.config.update(
UPLOAD_FOLDER="inputs",
CELERY_BROKER_URL=settings.CELERY_BROKER_URL,
CELERY_RESULT_BACKEND=settings.CELERY_RESULT_BACKEND,
MONGO_URI=settings.MONGO_URI
)
celery.config_from_object("application.celeryconfig")
@app.route("/")
def home():
"""
The frontend source code lives in the /frontend directory of the repository.
"""
if request.remote_addr in ('0.0.0.0', '127.0.0.1', 'localhost', '172.18.0.1'):
# If users locally try to access DocsGPT running in Docker,
# they will be redirected to the Frontend application.
return redirect('http://localhost:5173')
else:
# Handle other cases or render the default page
return 'Welcome to DocsGPT Backend!'
# handling CORS
@app.after_request
def after_request(response):
response.headers.add("Access-Control-Allow-Origin", "*")
response.headers.add("Access-Control-Allow-Headers", "Content-Type,Authorization")
response.headers.add("Access-Control-Allow-Methods", "GET,PUT,POST,DELETE,OPTIONS")
# response.headers.add("Access-Control-Allow-Credentials", "true")
return response
if __name__ == "__main__":
app.run(debug=True, port=7091)

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@ -32,6 +32,12 @@ class Settings(BaseSettings):
ELASTIC_URL: str = None # url for elasticsearch
ELASTIC_INDEX: str = "docsgpt" # index name for elasticsearch
# SageMaker config
SAGEMAKER_ENDPOINT: str = None # SageMaker endpoint name
SAGEMAKER_REGION: str = None # SageMaker region name
SAGEMAKER_ACCESS_KEY: str = None # SageMaker access key
SAGEMAKER_SECRET_KEY: str = None # SageMaker secret key
path = Path(__file__).parent.parent.absolute()
settings = Settings(_env_file=path.joinpath(".env"), _env_file_encoding="utf-8")

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@ -1,27 +1,139 @@
from application.llm.base import BaseLLM
from application.core.settings import settings
import requests
import json
import io
class LineIterator:
"""
A helper class for parsing the byte stream input.
The output of the model will be in the following format:
```
b'{"outputs": [" a"]}\n'
b'{"outputs": [" challenging"]}\n'
b'{"outputs": [" problem"]}\n'
...
```
While usually each PayloadPart event from the event stream will contain a byte array
with a full json, this is not guaranteed and some of the json objects may be split across
PayloadPart events. For example:
```
{'PayloadPart': {'Bytes': b'{"outputs": '}}
{'PayloadPart': {'Bytes': b'[" problem"]}\n'}}
```
This class accounts for this by concatenating bytes written via the 'write' function
and then exposing a method which will return lines (ending with a '\n' character) within
the buffer via the 'scan_lines' function. It maintains the position of the last read
position to ensure that previous bytes are not exposed again.
"""
def __init__(self, stream):
self.byte_iterator = iter(stream)
self.buffer = io.BytesIO()
self.read_pos = 0
def __iter__(self):
return self
def __next__(self):
while True:
self.buffer.seek(self.read_pos)
line = self.buffer.readline()
if line and line[-1] == ord('\n'):
self.read_pos += len(line)
return line[:-1]
try:
chunk = next(self.byte_iterator)
except StopIteration:
if self.read_pos < self.buffer.getbuffer().nbytes:
continue
raise
if 'PayloadPart' not in chunk:
print('Unknown event type:' + chunk)
continue
self.buffer.seek(0, io.SEEK_END)
self.buffer.write(chunk['PayloadPart']['Bytes'])
class SagemakerAPILLM(BaseLLM):
def __init__(self, *args, **kwargs):
self.url = settings.SAGEMAKER_API_URL
import boto3
runtime = boto3.client(
'runtime.sagemaker',
aws_access_key_id='xxx',
aws_secret_access_key='xxx',
region_name='us-west-2'
)
self.endpoint = settings.SAGEMAKER_ENDPOINT
self.runtime = runtime
def gen(self, model, engine, messages, stream=False, **kwargs):
context = messages[0]['content']
user_question = messages[-1]['content']
prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
response = requests.post(
url=self.url,
headers={
"Content-Type": "application/json; charset=utf-8",
},
data=json.dumps({"input": prompt})
)
# Construct payload for endpoint
payload = {
"inputs": prompt,
"stream": False,
"parameters": {
"do_sample": True,
"temperature": 0.1,
"max_new_tokens": 30,
"repetition_penalty": 1.03,
"stop": ["</s>", "###"]
}
}
body_bytes = json.dumps(payload).encode('utf-8')
return response.json()['answer']
# Invoke the endpoint
response = self.runtime.invoke_endpoint(EndpointName=self.endpoint,
ContentType='application/json',
Body=body_bytes)
result = json.loads(response['Body'].read().decode())
import sys
print(result[0]['generated_text'], file=sys.stderr)
return result[0]['generated_text'][len(prompt):]
def gen_stream(self, model, engine, messages, stream=True, **kwargs):
raise NotImplementedError("Sagemaker does not support streaming")
context = messages[0]['content']
user_question = messages[-1]['content']
prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
# Construct payload for endpoint
payload = {
"inputs": prompt,
"stream": True,
"parameters": {
"do_sample": True,
"temperature": 0.1,
"max_new_tokens": 512,
"repetition_penalty": 1.03,
"stop": ["</s>", "###"]
}
}
body_bytes = json.dumps(payload).encode('utf-8')
# Invoke the endpoint
response = self.runtime.invoke_endpoint_with_response_stream(EndpointName=self.endpoint,
ContentType='application/json',
Body=body_bytes)
#result = json.loads(response['Body'].read().decode())
event_stream = response['Body']
start_json = b'{'
for line in LineIterator(event_stream):
if line != b'' and start_json in line:
#print(line)
data = json.loads(line[line.find(start_json):].decode('utf-8'))
if data['token']['text'] not in ["</s>", "###"]:
print(data['token']['text'],end='')
yield data['token']['text']

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@ -1,5 +1,5 @@
from application.vectorstore.base import BaseVectorStore
from langchain import FAISS
from langchain.vectorstores import FAISS
from application.core.settings import settings
class FaissStore(BaseVectorStore):

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@ -19,7 +19,6 @@ services:
- CELERY_BROKER_URL=redis://redis:6379/0
- CELERY_RESULT_BACKEND=redis://redis:6379/1
- MONGO_URI=mongodb://mongo:27017/docsgpt
- SELF_HOSTED_MODEL=$SELF_HOSTED_MODEL
ports:
- "7091:7091"
volumes:

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@ -10,7 +10,7 @@ It will install all the dependencies and give you an option to download the loca
Otherwise, refer to this Guide:
1. Open and download this repository with `git clone https://github.com/arc53/DocsGPT.git`.
2. Create a `.env` file in your root directory and set your `API_KEY` with your openai api key.
2. Create a `.env` file in your root directory and set your `API_KEY` with your [OpenAI api key](https://platform.openai.com/account/api-keys).
3. Run `docker-compose build && docker-compose up`.
4. Navigate to `http://localhost:5173/`.

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@ -133,7 +133,7 @@ There are two types of responses:
```
### /api/delete_old
Deletes old vecotstores:
Deletes old vectorstores:
```js
// Task status (GET http://127.0.0.1:5000/api/docs_check)
fetch("http://localhost:5001/api/task_status?task_id=b2d2a0f4-387c-44fd-a443-e4fe2e7454d1", {

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@ -1,4 +1,4 @@
## To customise a main prompt navigate to `/application/prompt/combine_prompt.txt`
## To customize a main prompt navigate to `/application/prompt/combine_prompt.txt`
You can try editing it to see how the model responses.

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@ -35,7 +35,7 @@ It will tell you how much it will cost
Once you run it will use new context that is relevant to your documentation
Make sure you select default in the dropdown in the UI
## Customisation
## Customization
You can learn more about options while running ingest.py by running:
`python ingest.py --help`

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@ -201,7 +201,9 @@ export default function Navigation() {
<div className="flex gap-4">
<img src={Message} className="ml-2 w-5"></img>
<p className="my-auto text-eerie-black">
{conversation.name}
{conversation.name.length > 45
? conversation.name.substring(0, 45) + '...'
: conversation.name}
</p>
</div>
@ -227,11 +229,11 @@ export default function Navigation() {
<div className="flex flex-col-reverse border-b-2">
<div className="relative my-4 flex gap-2 px-2">
<div
className="flex h-12 w-full cursor-pointer justify-between rounded-3xl rounded-md border-2 bg-white"
className="flex h-12 min-w-[85%] cursor-pointer justify-between rounded-3xl rounded-md border-2 bg-white"
onClick={() => setIsDocsListOpen(!isDocsListOpen)}
>
{selectedDocs && (
<p className="my-3 mx-4">
<p className="my-3 mx-4 overflow-hidden text-ellipsis whitespace-nowrap">
{selectedDocs.name} {selectedDocs.version}
</p>
)}

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@ -0,0 +1,96 @@
# FILEPATH: /path/to/test_sagemaker.py
import json
import unittest
from unittest.mock import MagicMock, patch
from application.llm.sagemaker import SagemakerAPILLM, LineIterator
class TestSagemakerAPILLM(unittest.TestCase):
def setUp(self):
self.sagemaker = SagemakerAPILLM()
self.context = "This is the context"
self.user_question = "What is the answer?"
self.messages = [
{"content": self.context},
{"content": "Some other message"},
{"content": self.user_question}
]
self.prompt = f"### Instruction \n {self.user_question} \n ### Context \n {self.context} \n ### Answer \n"
self.payload = {
"inputs": self.prompt,
"stream": False,
"parameters": {
"do_sample": True,
"temperature": 0.1,
"max_new_tokens": 30,
"repetition_penalty": 1.03,
"stop": ["</s>", "###"]
}
}
self.payload_stream = {
"inputs": self.prompt,
"stream": True,
"parameters": {
"do_sample": True,
"temperature": 0.1,
"max_new_tokens": 512,
"repetition_penalty": 1.03,
"stop": ["</s>", "###"]
}
}
self.body_bytes = json.dumps(self.payload).encode('utf-8')
self.body_bytes_stream = json.dumps(self.payload_stream).encode('utf-8')
self.response = {
"Body": MagicMock()
}
self.result = [
{
"generated_text": "This is the generated text"
}
]
self.response['Body'].read.return_value.decode.return_value = json.dumps(self.result)
def test_gen(self):
with patch.object(self.sagemaker.runtime, 'invoke_endpoint',
return_value=self.response) as mock_invoke_endpoint:
output = self.sagemaker.gen(None, None, self.messages)
mock_invoke_endpoint.assert_called_once_with(
EndpointName=self.sagemaker.endpoint,
ContentType='application/json',
Body=self.body_bytes
)
self.assertEqual(output,
self.result[0]['generated_text'][len(self.prompt):])
def test_gen_stream(self):
with patch.object(self.sagemaker.runtime, 'invoke_endpoint_with_response_stream',
return_value=self.response) as mock_invoke_endpoint:
output = list(self.sagemaker.gen_stream(None, None, self.messages))
mock_invoke_endpoint.assert_called_once_with(
EndpointName=self.sagemaker.endpoint,
ContentType='application/json',
Body=self.body_bytes_stream
)
self.assertEqual(output, [])
class TestLineIterator(unittest.TestCase):
def setUp(self):
self.stream = [
{'PayloadPart': {'Bytes': b'{"outputs": [" a"]}\n'}},
{'PayloadPart': {'Bytes': b'{"outputs": [" challenging"]}\n'}},
{'PayloadPart': {'Bytes': b'{"outputs": [" problem"]}\n'}}
]
self.line_iterator = LineIterator(self.stream)
def test_iter(self):
self.assertEqual(iter(self.line_iterator), self.line_iterator)
def test_next(self):
self.assertEqual(next(self.line_iterator), b'{"outputs": [" a"]}')
self.assertEqual(next(self.line_iterator), b'{"outputs": [" challenging"]}')
self.assertEqual(next(self.line_iterator), b'{"outputs": [" problem"]}')
if __name__ == '__main__':
unittest.main()