renamed to open assistant

This commit is contained in:
Yannic Kilcher
2022-12-17 23:56:05 +01:00
parent a6c957ccfd
commit 13551ae3e4
32 changed files with 22 additions and 757 deletions
+1 -1
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@@ -8,6 +8,6 @@ jobs:
build-backend:
uses: ./.github/workflows/docker-build.yaml
with:
image-name: ocgpt-backend
image-name: oasst-backend
folder: backend
build-args: ""
+4 -4
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@@ -1,8 +1,8 @@
# Open-Chat-GPT
# Open-Assistant
Open chat gpt is a project meant to give everyone access to a great chat based large language model.
Open Assistant is a project meant to give everyone access to a great chat based large language model.
We believe that by doing this we will create a revolution in innovation in language. In the same way that stable-diffusion helped the world make art and images in new ways we hope open chat gpt can help improve the world by improving language itself.
We believe that by doing this we will create a revolution in innovation in language. In the same way that stable-diffusion helped the world make art and images in new ways we hope Open Assistant can help improve the world by improving language itself.
## How can you help?
@@ -14,7 +14,7 @@ All open source projects begins with people like you. Open source is the belief
[Join the LAION Discord Server!](https://discord.gg/RQFtmAmk)
[Visit the Notion](https://ykilcher.com/open-chat-gpt)
[Visit the Notion](https://ykilcher.com/open-assistant)
## Developer Setup
+2 -2
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@@ -1,4 +1,4 @@
# Open-Chat-GPT REST Backend
# Open-Assistant REST Backend
## REST Server Configuration
@@ -8,7 +8,7 @@ Example contents of a `.env` file for the backend:
```
DATABASE_URI="postgresql://<username>:<password>@<host>/<database_name>"
BACKEND_CORS_ORIGINS=["http://localhost", "http://localhost:4200", "http://localhost:3000", "http://localhost:8080", "https://localhost", "https://localhost:4200", "https://localhost:3000", "https://localhost:8080", "http://dev.ocgpt.laion.ai", "https://stag.ocgpt.laion.ai", "https://ocgpt.laion.ai"]
BACKEND_CORS_ORIGINS=["http://localhost", "http://localhost:4200", "http://localhost:3000", "http://localhost:8080", "https://localhost", "https://localhost:4200", "https://localhost:3000", "https://localhost:8080", "http://dev.oasst.laion.ai", "https://stag.oasst.laion.ai", "https://oasst.laion.ai"]
```
@@ -5,7 +5,7 @@ from pydantic import AnyHttpUrl, BaseSettings, PostgresDsn, validator
class Settings(BaseSettings):
PROJECT_NAME: str = "open-chatGPT backend"
PROJECT_NAME: str = "open-assistant backend"
API_V1_STR: str = "/api/v1"
POSTGRES_HOST: str = "localhost"
-57
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@@ -1,57 +0,0 @@
# -*- coding: utf-8 -*-
from secrets import token_hex
from typing import Generator
from uuid import UUID
from fastapi import HTTPException, Security
from fastapi.security.api_key import APIKey, APIKeyHeader, APIKeyQuery
from loguru import logger
from ocgpt.config import settings
from ocgpt.database import engine
from ocgpt.models import ApiClient
from sqlmodel import Session
from starlette.status import HTTP_403_FORBIDDEN
def get_db() -> Generator:
with Session(engine) as db:
yield db
api_key_query = APIKeyQuery(name="api_key", auto_error=False)
api_key_header = APIKeyHeader(name="X-API-Key", auto_error=False)
async def get_api_key(
api_key_query: str = Security(api_key_query),
api_key_header: str = Security(api_key_header),
):
if api_key_query:
return api_key_query
else:
return api_key_header
def api_auth(
api_key: APIKey,
db: Session,
) -> ApiClient:
if api_key is not None:
if settings.ALLOW_ANY_API_KEY:
# make sure that a dummy api key exits in db (foreign key references)
ANY_API_KEY_ID = UUID("00000000-1111-2222-3333-444444444444")
api_client: ApiClient = db.query(ApiClient).filter(ApiClient.id == ANY_API_KEY_ID).first()
if api_client is None:
token = token_hex(32)
logger.info(f"ANY_API_KEY missing, inserting api_key: {token}")
api_client = ApiClient(id=ANY_API_KEY_ID, api_key=token, description="ANY_API_KEY, random token")
db.add(api_client)
db.commit()
return api_client
api_client = db.query(ApiClient).filter(ApiClient.api_key == api_key).first()
if api_client is not None and api_client.enabled:
return api_client
raise HTTPException(status_code=HTTP_403_FORBIDDEN, detail="Could not validate credentials")
-6
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@@ -1,6 +0,0 @@
# -*- coding: utf-8 -*-
from fastapi import APIRouter
from ocgpt.api.v1 import tasks
api_router = APIRouter()
api_router.include_router(tasks.router, prefix="/tasks", tags=["tasks"])
-259
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@@ -1,259 +0,0 @@
# -*- coding: utf-8 -*-
import random
from typing import Any
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException
from fastapi.security.api_key import APIKey
from loguru import logger
from ocgpt.api import deps
from ocgpt.models.db_payload import TaskPayload
from ocgpt.prompt_repository import PromptRepository
from ocgpt.schemas import protocol as protocol_schema
from sqlmodel import Session
from starlette.status import HTTP_400_BAD_REQUEST
router = APIRouter()
def generate_task(request: protocol_schema.TaskRequest) -> protocol_schema.Task:
match (request.type):
case protocol_schema.TaskRequestType.random:
logger.info("Frontend requested a random task.")
while request.type == protocol_schema.TaskRequestType.random:
request.type = random.choice(list(protocol_schema.TaskRequestType)).value
return generate_task(request)
case protocol_schema.TaskRequestType.summarize_story:
logger.info("Generating a SummarizeStoryTask.")
task = protocol_schema.SummarizeStoryTask(
story="This is a story. A very long story. So long, it needs to be summarized.",
)
case protocol_schema.TaskRequestType.rate_summary:
logger.info("Generating a RateSummaryTask.")
task = protocol_schema.RateSummaryTask(
full_text="This is a story. A very long story. So long, it needs to be summarized.",
summary="This is a summary.",
scale=protocol_schema.RatingScale(min=1, max=5),
)
case protocol_schema.TaskRequestType.initial_prompt:
logger.info("Generating an InitialPromptTask.")
task = protocol_schema.InitialPromptTask(
hint="Ask the assistant about a current event." # this is optional
)
case protocol_schema.TaskRequestType.user_reply:
logger.info("Generating a UserReplyTask.")
task = protocol_schema.UserReplyTask(
conversation=protocol_schema.Conversation(
messages=[
protocol_schema.ConversationMessage(
text="Hey, assistant, what's going on in the world?",
is_assistant=False,
),
protocol_schema.ConversationMessage(
text="I'm not sure I understood correctly, could you rephrase that?",
is_assistant=True,
),
],
)
)
case protocol_schema.TaskRequestType.assistant_reply:
logger.info("Generating a AssistantReplyTask.")
task = protocol_schema.AssistantReplyTask(
conversation=protocol_schema.Conversation(
messages=[
protocol_schema.ConversationMessage(
text="Hey, assistant, write me an English essay about water.",
is_assistant=False,
),
],
)
)
case protocol_schema.TaskRequestType.rank_initial_prompts:
logger.info("Generating a RankInitialPromptsTask.")
task = protocol_schema.RankInitialPromptsTask(
prompts=[
"Please write a story about a time you were happy.",
"Please write a story about a time you were sad.",
]
)
case protocol_schema.TaskRequestType.rank_user_replies:
logger.info("Generating a RankUserRepliesTask.")
task = protocol_schema.RankUserRepliesTask(
conversation=protocol_schema.Conversation(
messages=[
protocol_schema.ConversationMessage(
text="Hey, assistant, what's going on in the world?",
is_assistant=False,
),
protocol_schema.ConversationMessage(
text="I'm not sure I understood correctly, could you rephrase that?",
is_assistant=True,
),
],
),
replies=[
"Oh come oooooon!",
"What are the news?",
],
)
case protocol_schema.TaskRequestType.rank_assistant_replies:
logger.info("Generating a RankAssistantRepliesTask.")
task = protocol_schema.RankAssistantRepliesTask(
conversation=protocol_schema.Conversation(
messages=[
protocol_schema.ConversationMessage(
text="Hey, assistant, what's going on in the world?",
is_assistant=False,
),
],
),
replies=[
"I'm not sure I understood correctly, could you rephrase that?",
"The world is fine. All good.",
"Crap is hitting the fan. Start farming.",
],
)
case _:
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail="Invalid request type.",
)
logger.info(f"Generated {task=}.")
return task
@router.post("/", response_model=protocol_schema.AnyTask) # work with Union once more types are added
def request_task(
*,
db: Session = Depends(deps.get_db),
api_key: APIKey = Depends(deps.get_api_key),
request: protocol_schema.TaskRequest,
) -> Any:
"""
Create new task.
"""
api_client = deps.api_auth(api_key, db)
try:
task = generate_task(request)
pr = PromptRepository(db, api_client, request.user)
pr.store_task(task)
except Exception:
logger.exception("Failed to generate task.")
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
)
return task
@router.post("/{task_id}/ack")
def acknowledge_task(
*,
db: Session = Depends(deps.get_db),
api_key: APIKey = Depends(deps.get_api_key),
task_id: UUID,
ack_request: protocol_schema.TaskAck,
) -> Any:
"""
The frontend acknowledges a task.
"""
api_client = deps.api_auth(api_key, db)
try:
pr = PromptRepository(db, api_client, user=None)
# here we store the post id in the database for the task
pr.bind_frontend_post_id(task_id=task_id, post_id=ack_request.post_id)
logger.info(f"Frontend acknowledges task {task_id=}, {ack_request=}.")
except Exception:
logger.exception("Failed to acknowledge task.")
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
)
return {}
@router.post("/{task_id}/nack")
def acknowledge_task_failure(
*,
db: Session = Depends(deps.get_db),
api_key: APIKey = Depends(deps.get_api_key),
task_id: UUID,
nack_request: protocol_schema.TaskNAck,
) -> Any:
"""
The frontend reports failure to implement a task.
"""
deps.api_auth(api_key, db)
logger.info(f"Frontend reports failure to implement task {task_id=}, {nack_request=}.")
# here we would store the post id in the database for the task
return {}
@router.post("/interaction")
def post_interaction(
*,
db: Session = Depends(deps.get_db),
api_key: APIKey = Depends(deps.get_api_key),
interaction: protocol_schema.AnyInteraction,
) -> Any:
"""
The frontend reports an interaction.
"""
api_client = deps.api_auth(api_key, db)
try:
pr = PromptRepository(db, api_client, user=interaction.user)
match type(interaction):
case protocol_schema.TextReplyToPost:
logger.info(
f"Frontend reports text reply to {interaction.post_id=} with {interaction.text=} by {interaction.user=}."
)
work_package = pr.fetch_workpackage_by_postid(interaction.post_id)
work_payload: TaskPayload = work_package.payload.payload
logger.info(f"found task work package in db: {work_payload}")
# here we store the text reply in the database
# ToDo: role user or agent?
pr.store_text_reply(interaction, role="unknown")
return protocol_schema.TaskDone()
case protocol_schema.PostRating:
logger.info(
f"Frontend reports rating of {interaction.post_id=} with {interaction.rating=} by {interaction.user=}."
)
# here we store the rating in the database
pr.store_rating(interaction)
return protocol_schema.TaskDone()
case protocol_schema.PostRanking:
logger.info(
f"Frontend reports ranking of {interaction.post_id=} with {interaction.ranking=} by {interaction.user=}."
)
# TODO: check if the ranking is valid
pr.store_ranking(interaction)
# here we would store the ranking in the database
return protocol_schema.TaskDone()
case _:
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
detail="Invalid response type.",
)
except Exception:
logger.exception("Interaction request failed.")
raise HTTPException(
status_code=HTTP_400_BAD_REQUEST,
)
-8
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@@ -1,8 +0,0 @@
# -*- coding: utf-8 -*-
from ocgpt.config import settings
from sqlmodel import create_engine
if settings.DATABASE_URI is None:
raise ValueError("DATABASE_URI is not set")
engine = create_engine(settings.DATABASE_URI)
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@@ -1,94 +0,0 @@
# -*- coding: utf-8 -*-
from typing import Literal
from ocgpt.models.payload_column_type import payload_type
from ocgpt.schemas import protocol as protocol_schema
from pydantic import BaseModel
@payload_type
class TaskPayload(BaseModel):
type: str
@payload_type
class SummarizationStoryPayload(TaskPayload):
type: Literal["summarize_story"] = "summarize_story"
story: str
@payload_type
class RateSummaryPayload(TaskPayload):
type: Literal["rate_summary"] = "rate_summary"
full_text: str
summary: str
scale: protocol_schema.RatingScale
@payload_type
class InitialPromptPayload(TaskPayload):
type: Literal["initial_prompt"] = "initial_prompt"
hint: str
@payload_type
class UserReplyPayload(TaskPayload):
type: Literal["user_reply"] = "user_reply"
conversation: protocol_schema.Conversation
hint: str | None
@payload_type
class AssistantReplyPayload(TaskPayload):
type: Literal["assistant_reply"] = "assistant_reply"
conversation: protocol_schema.Conversation
@payload_type
class PostPayload(BaseModel):
text: str
@payload_type
class ReactionPayload(BaseModel):
type: str
@payload_type
class RatingReactionPayload(ReactionPayload):
type: Literal["post_rating"] = "post_rating"
rating: str
@payload_type
class RankingReactionPayload(ReactionPayload):
type: Literal["post_ranking"] = "post_ranking"
ranking: list[int]
@payload_type
class RankConversationRepliesPayload(TaskPayload):
conversation: protocol_schema.Conversation # the conversation so far
replies: list[str]
@payload_type
class RankInitialPromptsPayload(TaskPayload):
"""A task to rank a set of initial prompts."""
type: Literal["rank_initial_prompts"] = "rank_initial_prompts"
prompts: list[str]
@payload_type
class RankUserRepliesPayload(RankConversationRepliesPayload):
"""A task to rank a set of user replies to a conversation."""
type: Literal["rank_user_replies"] = "rank_user_replies"
@payload_type
class RankAssistantRepliesPayload(RankConversationRepliesPayload):
"""A task to rank a set of assistant replies to a conversation."""
type: Literal["rank_assistant_replies"] = "rank_assistant_replies"
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@@ -1,311 +0,0 @@
# -*- coding: utf-8 -*-
from datetime import datetime
from typing import Optional
from uuid import UUID, uuid4
import ocgpt.models.db_payload as db_payload
from loguru import logger
from ocgpt.models import ApiClient, Person, Post, PostReaction, WorkPackage
from ocgpt.models.payload_column_type import PayloadContainer
from ocgpt.schemas import protocol as protocol_schema
from sqlmodel import Session
class PromptRepository:
def __init__(self, db: Session, api_client: ApiClient, user: Optional[protocol_schema.User]):
self.db = db
self.api_client = api_client
self.person = self.lookup_person(user)
self.person_id = self.person.id if self.person else None
def lookup_person(self, user: protocol_schema.User) -> Person:
if not user:
return None
person: Person = (
self.db.query(Person)
.filter(
Person.api_client_id == self.api_client.id,
Person.username == user.id,
Person.auth_method == user.auth_method,
)
.first()
)
if person is None:
# user is unknown, create new record
person = Person(username=user.id, display_name=user.display_name, api_client_id=self.api_client.id)
self.db.add(person)
self.db.commit()
self.db.refresh(person)
elif user.display_name and user.display_name != person.display_name:
# we found the user but the display name changed
person.display_name = user.display_name
self.db.add(person)
self.db.commit()
return person
def validate_post_id(self, post_id: str) -> None:
if not isinstance(post_id, str):
raise TypeError(f"post_id must be string, not {type(post_id)}")
if not post_id:
raise ValueError("post_id must not be empty")
def bind_frontend_post_id(self, task_id: UUID, post_id: str):
self.validate_post_id(post_id)
# find work package
work_pack: WorkPackage = (
self.db.query(WorkPackage)
.filter(WorkPackage.id == task_id, WorkPackage.api_client_id == self.api_client.id)
.first()
)
if work_pack is None:
raise KeyError(f"WorkPackage for task {task_id} not found")
if work_pack.expiry_date is not None and datetime.utcnow() > work_pack.expiry_date:
raise RuntimeError("WorkPackage already expired.")
# ToDo: check race-condition, transaction
# check if task thread exits
thread_root = (
self.db.query(Post)
.filter(
Post.workpackage_id == work_pack.id,
Post.frontend_post_id == post_id,
Post.parent_id is None,
Post.api_client_id == self.api_client.id,
)
.one_or_none()
)
if thread_root is None:
thread_id = uuid4()
thread_root = self.insert_post(
post_id=thread_id,
thread_id=thread_id,
frontend_post_id=post_id,
parent_id=None,
role="system",
workpackage_id=work_pack.id,
payload=None,
payload_type="bind",
)
return thread_root
def fetch_post_by_frontend_post_id(self, frontend_post_id: str, fail_if_missing: bool = True) -> Post:
self.validate_post_id(frontend_post_id)
post: Post = (
self.db.query(Post)
.filter(Post.api_client_id == self.api_client.id, Post.frontend_post_id == frontend_post_id)
.one_or_none()
)
if fail_if_missing and post is None:
raise KeyError(f"Post with post_id {frontend_post_id} not found.")
return post
def fetch_workpackage_by_postid(self, post_id: str) -> WorkPackage:
self.validate_post_id(post_id)
post = self.fetch_post_by_frontend_post_id(post_id, fail_if_missing=True)
work_pack = self.db.query(WorkPackage).filter(WorkPackage.id == post.workpackage_id).one()
return work_pack
def store_text_reply(self, reply: protocol_schema.TextReplyToPost, role: str) -> Post:
self.validate_post_id(reply.post_id)
self.validate_post_id(reply.user_post_id)
# find post with post-id
parent_post: Post = (
self.db.query(Post)
.filter(
Post.api_client_id == self.api_client.id,
Post.frontend_post_id == reply.post_id,
# Post.person_id == self.person_id
)
.one_or_none()
)
if parent_post is None:
raise KeyError(f"Post for post_id {reply.post_id} not found.")
# create reply post
user_post_id = uuid4()
user_post = self.insert_post(
post_id=user_post_id,
frontend_post_id=reply.user_post_id,
parent_id=parent_post.id,
thread_id=parent_post.thread_id,
workpackage_id=parent_post.workpackage_id,
role=role,
payload=db_payload.PostPayload(text=reply.text),
)
return user_post
def store_rating(self, rating: protocol_schema.PostRating) -> PostReaction:
post = self.fetch_post_by_frontend_post_id(rating.post_id, fail_if_missing=True)
work_package = self.fetch_workpackage_by_postid(rating.post_id)
work_payload: db_payload.RateSummaryPayload = work_package.payload.payload
if type(work_payload) != db_payload.RateSummaryPayload:
raise ValueError(
f"work_package payload type mismatch: {type(work_payload)=} != {db_payload.RateSummaryPayload}"
)
if rating.rating < work_payload.scale.min or rating.rating > work_payload.scale.max:
raise ValueError(f"Invalid rating value: {rating.rating=} not in {work_payload.scale=}")
# store reaction to post
reaction_payload = db_payload.RatingReactionPayload(rating=rating.rating)
reaction = self.insert_reaction(post.id, reaction_payload)
logger.info(f"Ranking {rating.rating} stored for work_package {work_package.id}.")
return reaction
def store_ranking(self, ranking: protocol_schema.PostRanking) -> PostReaction:
post = self.fetch_post_by_frontend_post_id(ranking.post_id, fail_if_missing=True)
# fetch work_package
work_package = self.fetch_workpackage_by_postid(ranking.post_id)
work_payload: db_payload.RankConversationRepliesPayload | db_payload.RankInitialPromptsPayload = (
work_package.payload.payload
)
match type(work_payload):
case db_payload.RankUserRepliesPayload | db_payload.RankAssistantRepliesPayload:
# validate ranking
num_replies = len(work_payload.replies)
if sorted(ranking.ranking) != list(range(num_replies)):
raise ValueError(
f"Invalid ranking submitted. Each reply index must appear exactly once ({num_replies=})."
)
# store reaction to post
reaction_payload = db_payload.RankingReactionPayload(ranking=ranking.ranking)
reaction = self.insert_reaction(post.id, reaction_payload)
logger.info(f"Ranking {ranking.ranking} stored for work_package {work_package.id}.")
return reaction
case db_payload.RankInitialPromptsPayload:
# validate ranking
if sorted(ranking.ranking) != list(range(num_prompts := len(work_payload.prompts))):
raise ValueError(
f"Invalid ranking submitted. Each reply index must appear exactly once ({num_prompts=})."
)
# store reaction to post
reaction_payload = db_payload.RankingReactionPayload(ranking=ranking.ranking)
reaction = self.insert_reaction(post.id, reaction_payload)
logger.info(f"Ranking {ranking.ranking} stored for work_package {work_package.id}.")
return reaction
case _:
raise ValueError(
f"work_package payload type mismatch: {type(work_payload)=} != {db_payload.RankConversationRepliesPayload}"
)
def store_task(self, task: protocol_schema.Task) -> WorkPackage:
payload: db_payload.TaskPayload
match type(task):
case protocol_schema.SummarizeStoryTask:
payload = db_payload.SummarizationStoryPayload(story=task.story)
case protocol_schema.RateSummaryTask:
payload = db_payload.RateSummaryPayload(
full_text=task.full_text, summary=task.summary, scale=task.scale
)
case protocol_schema.InitialPromptTask:
payload = db_payload.InitialPromptPayload(hint=task.hint)
case protocol_schema.UserReplyTask:
payload = db_payload.UserReplyPayload(conversation=task.conversation, hint=task.hint)
case protocol_schema.AssistantReplyTask:
payload = db_payload.AssistantReplyPayload(type=task.type, conversation=task.conversation)
case protocol_schema.RankInitialPromptsTask:
payload = db_payload.RankInitialPromptsPayload(tpye=task.type, prompts=task.prompts)
case protocol_schema.RankUserRepliesTask:
payload = db_payload.RankUserRepliesPayload(
tpye=task.type, conversation=task.conversation, replies=task.replies
)
case protocol_schema.RankAssistantRepliesTask:
payload = db_payload.RankAssistantRepliesPayload(
tpye=task.type, conversation=task.conversation, replies=task.replies
)
case _:
raise ValueError(f"Invalid task type: {type(task)=}")
wp = self.insert_work_package(payload=payload, id=task.id)
assert wp.id == task.id
return wp
def insert_work_package(self, payload: db_payload.TaskPayload, id: UUID = None) -> WorkPackage:
c = PayloadContainer(payload=payload)
wp = WorkPackage(
id=id,
person_id=self.person_id,
payload_type=type(payload).__name__,
payload=c,
api_client_id=self.api_client.id,
)
self.db.add(wp)
self.db.commit()
self.db.refresh(wp)
return wp
def insert_post(
self,
*,
post_id: UUID,
frontend_post_id: str,
parent_id: UUID,
thread_id: UUID,
workpackage_id: UUID,
role: str,
payload: db_payload.PostPayload,
payload_type: str = None,
) -> Post:
if payload_type is None:
if payload is None:
payload_type = "null"
else:
payload_type = type(payload).__name__
post = Post(
id=post_id,
parent_id=parent_id,
thread_id=thread_id,
workpackage_id=workpackage_id,
person_id=self.person_id,
role=role,
frontend_post_id=frontend_post_id,
api_client_id=self.api_client.id,
payload_type=payload_type,
payload=PayloadContainer(payload=payload),
)
self.db.add(post)
self.db.commit()
self.db.refresh(post)
return post
def insert_reaction(self, post_id: UUID, payload: db_payload.ReactionPayload) -> PostReaction:
if self.person_id is None:
raise ValueError("User required")
container = PayloadContainer(payload=payload)
reaction = PostReaction(
post_id=post_id,
person_id=self.person_id,
payload=container,
api_client_id=self.api_client.id,
payload_type=type(payload).__name__,
)
self.db.add(reaction)
self.db.commit()
self.db.refresh(reaction)
return reaction
+2 -2
View File
@@ -1,6 +1,6 @@
# open-chat-gpt
# open-assistant
This is the github repo for the open-chat-gpt project.
This is the github repo for the open-assistant project.
We are currently building a discord bot in order to make everyone contribute with great prompts and answers.
Join us!
https://discord.gg/ZUfPw6jP
+2 -2
View File
@@ -33,7 +33,7 @@ guild_ids = [TEST_GUILD, TEST_GUILD_LAION]
# Initiate the client and command tree to create slash commands.
class OpenChatGPTClient(discord.Client):
class OpenAssistantClient(discord.Client):
def __init__(self, *, intents: discord.Intents):
super().__init__(intents=intents)
self.tree = app_commands.CommandTree(self)
@@ -59,7 +59,7 @@ class OpenChatGPTClient(discord.Client):
# List the set of intents needed for commands to operate properly.
intents = discord.Intents.default()
intents.message_content = True
client = OpenChatGPTClient(intents=intents)
client = OpenAssistantClient(intents=intents)
class LikeButton(discord.ui.Button):
+2 -2
View File
@@ -12,11 +12,11 @@ if __name__ == "__main__":
REQUIREMENTS = _read_reqs("requirements.txt")
setup(
name="open-chat-gpt",
name="open-assistant",
packages=find_packages(),
version="0.0.1",
license="Apache 2.0",
description="A Discord Bot for collecting and ranking prompts to train an Open ChatGPT",
description="A Discord Bot for collecting and ranking prompts to train an Open Assistant",
keywords=["machine learning", "natural language processing", "discord"],
install_requires=REQUIREMENTS,
classifiers=[
@@ -16,7 +16,7 @@ services:
service: adminer
backend:
build: ../../backend/.
image: ocgpt-backend
image: oasst-backend
environment:
- POSTGRES_HOST=db
- ALLOW_ANY_API_KEY=True
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "website",
"homepage": "http://projects.laion.ai.github.io/Open-Chat-GPT",
"homepage": "http://projects.laion.ai.github.io/Open-Assistant",
"version": "0.1.0",
"private": true,
"scripts": {
+4 -4
View File
@@ -20,9 +20,9 @@ export default function Home() {
<div className={styles.App}>
<header className={styles.AppHeader}>
{/* <img src={logo} className="App-logo" alt="logo" /> */}
<h2>Open Chat Gpt</h2>
<h2>Open Assistant</h2>
<p>
Open chat gpt is a project meant to give everyone access to a great
Open Assistant is a project meant to give everyone access to a great
chat based large language model.
</p>
@@ -30,7 +30,7 @@ export default function Home() {
<p>
We believe that by doing this we will create a revolution in
innovation in language. In the same way that stable-diffusion helped
the world make art and images in new ways we hope open chat gpt can
the world make art and images in new ways we hope Open Assistant can
help improve the world by improving language itself.
</p>
@@ -62,7 +62,7 @@ export default function Home() {
<header className={styles.AppHeader}>
{/* <img src={logo} className="App-logo" alt="logo" /> */}
<h2>Open Chat Gpt</h2>
<h2>Open Assistant</h2>
<p>You are logged in</p>
+2 -2
View File
@@ -5,7 +5,7 @@
<link rel="icon" href="%PUBLIC_URL%/favicon.ico" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<meta name="theme-color" content="#000000" />
<meta name="description" content="Open-Chat-GPT" />
<meta name="description" content="Open-Assistant" />
<link rel="apple-touch-icon" href="%PUBLIC_URL%/logo192.png" />
<!--
manifest.json provides metadata used when your web app is installed on a
@@ -21,7 +21,7 @@
work correctly both with client-side routing and a non-root public URL.
Learn how to configure a non-root public URL by running `npm run build`.
-->
<title>Open Chat GPT</title>
<title>Open Assistant</title>
</head>
<body>
<noscript>You need to enable JavaScript to run this app.</noscript>