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feat: org wide ai features check

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swve 2024-01-14 11:58:09 +01:00
parent de93d56945
commit 077c26ce15
24 changed files with 573 additions and 163 deletions
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18
apps/api/Dockerfile
View file

@ -7,13 +7,19 @@ RUN pip install poetry
#
WORKDIR /usr/learnhouse/apps/api
#
COPY ./requirements.txt /usr/learnhouse/requirements.txt
# Copy poetry.lock* in case it doesn't exist in the repo
COPY ./poetry.lock* /usr/learnhouse/
#
RUN poetry config virtualenvs.create false \
&& pip install --upgrade pip \
&& pip install -r /usr/learnhouse/requirements.txt
# Copy project requirement files here to ensure they will be cached.
COPY pyproject.toml /usr/learnhouse/
# Install poetry
RUN pip install --upgrade pip \
&& pip install poetry \
&& poetry config virtualenvs.create false
# Install project dependencies.
RUN poetry install --no-interaction --no-ansi
#
COPY ./ /usr/learnhouse

51
apps/api/poetry.lock generated
View file

@ -226,17 +226,17 @@ typecheck = ["mypy"]
[[package]]
name = "boto3"
version = "1.34.17"
version = "1.34.18"
description = "The AWS SDK for Python"
optional = false
python-versions = ">= 3.8"
files = [
{file = "boto3-1.34.17-py3-none-any.whl", hash = "sha256:1efc02be786884034d503d59c018cf7650d0cff9fcb37cd2eb49b802a6fe6111"},
{file = "boto3-1.34.17.tar.gz", hash = "sha256:8ca248cc84e7e859e4e276eb9c4309fa01a3e58473bf48d6c33448be870c2bb8"},
{file = "boto3-1.34.18-py3-none-any.whl", hash = "sha256:ae7cfdf45f4dfd33bd3e84e36afcfbf0517e64a32e647989a068f34d053572b8"},
{file = "boto3-1.34.18.tar.gz", hash = "sha256:5e38ca63007e903a7efe0a1751a0374d287b50d7bc148b9d3d495cdf74a0b712"},
]
[package.dependencies]
botocore = ">=1.34.17,<1.35.0"
botocore = ">=1.34.18,<1.35.0"
jmespath = ">=0.7.1,<2.0.0"
s3transfer = ">=0.10.0,<0.11.0"
@ -245,13 +245,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
[[package]]
name = "botocore"
version = "1.34.17"
version = "1.34.18"
description = "Low-level, data-driven core of boto 3."
optional = false
python-versions = ">= 3.8"
files = [
{file = "botocore-1.34.17-py3-none-any.whl", hash = "sha256:7272c39032c6f1d62781e4c8445d9a1d9140c2bf52ba7ee66bf6db559c4b2427"},
{file = "botocore-1.34.17.tar.gz", hash = "sha256:e48a662f3a6919219276b55085e8f73c3347966675f55e9d448be30cf79678ee"},
{file = "botocore-1.34.18-py3-none-any.whl", hash = "sha256:2067d8385c11b7cf2d336227d8fa5aea632fe61afbadb3168dc169dcc13d8c3e"},
{file = "botocore-1.34.18.tar.gz", hash = "sha256:85a77e72560a45b0dfdad94f92f5e114c82be07a51bb2d19dd310dab8be158cf"},
]
[package.dependencies]
@ -1362,13 +1362,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
[[package]]
name = "langchain-core"
version = "0.1.9"
version = "0.1.10"
description = "Building applications with LLMs through composability"
optional = false
python-versions = ">=3.8.1,<4.0"
files = [
{file = "langchain_core-0.1.9-py3-none-any.whl", hash = "sha256:1dd45aec185ce3afb1c19fb2e88cdbc19fafa7ae929d8107799a7c82ef69ea9f"},
{file = "langchain_core-0.1.9.tar.gz", hash = "sha256:4b51fdbdbc06027c26ea89a6da809cae2e404c9daa95dc6c10e3eae383d8ea6a"},
{file = "langchain_core-0.1.10-py3-none-any.whl", hash = "sha256:d89952f6d0766cfc88d9f1e25b84d56f8d7bd63a45ad8ec1a9a038c9b49df16d"},
{file = "langchain_core-0.1.10.tar.gz", hash = "sha256:3c9e1383264c102fcc6f865700dbb9416c4931a25d0ac2195f6311c6b867aa17"},
]
[package.dependencies]
@ -1384,15 +1384,32 @@ tenacity = ">=8.1.0,<9.0.0"
[package.extras]
extended-testing = ["jinja2 (>=3,<4)"]
[[package]]
name = "langchain-openai"
version = "0.0.2.post1"
description = "An integration package connecting OpenAI and LangChain"
optional = false
python-versions = ">=3.8.1,<4.0"
files = [
{file = "langchain_openai-0.0.2.post1-py3-none-any.whl", hash = "sha256:ba468b94c23da9d8ccefe5d5a3c1c65b4b9702292523e53acc689a9110022e26"},
{file = "langchain_openai-0.0.2.post1.tar.gz", hash = "sha256:f8e78db4a663feeac71d9f036b9422406c199ea3ef4c97d99ff392c93530e073"},
]
[package.dependencies]
langchain-core = ">=0.1.7,<0.2"
numpy = ">=1,<2"
openai = ">=1.6.1,<2.0.0"
tiktoken = ">=0.5.2,<0.6.0"
[[package]]
name = "langsmith"
version = "0.0.79"
version = "0.0.80"
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
optional = false
python-versions = ">=3.8.1,<4.0"
files = [
{file = "langsmith-0.0.79-py3-none-any.whl", hash = "sha256:be0374e913c36d9f6a13dd6b6e20a506066d5a0f3abfd476f9cf9e0b086ed744"},
{file = "langsmith-0.0.79.tar.gz", hash = "sha256:d32639ccd18a92533b302f6f482255619afc8eb007fff91e37ee699d947c5e29"},
{file = "langsmith-0.0.80-py3-none-any.whl", hash = "sha256:dee1c6ef9e8241b82a8851926624269954d0ff8e22d82e32e73455f387f4e245"},
{file = "langsmith-0.0.80.tar.gz", hash = "sha256:6d22ee07eb41c65b3f5166b20041a026714952497d9e80d5be6879d3a5c14d84"},
]
[package.dependencies]
@ -2013,13 +2030,13 @@ sympy = "*"
[[package]]
name = "openai"
version = "1.7.1"
version = "1.7.2"
description = "The official Python library for the openai API"
optional = false
python-versions = ">=3.7.1"
files = [
{file = "openai-1.7.1-py3-none-any.whl", hash = "sha256:e52ad7ea015331edc584e6e9c98741c819d7ffbbd2ecc50bf1f55c33f9cb3f77"},
{file = "openai-1.7.1.tar.gz", hash = "sha256:7556e6aa30e20254b1ad68de49bb5ef4d8106bfac5e8a78abdc1daa911fbb1fb"},
{file = "openai-1.7.2-py3-none-any.whl", hash = "sha256:8f41b90a762f5fd9d182b45851041386fed94c8ad240a70abefee61a68e0ef53"},
{file = "openai-1.7.2.tar.gz", hash = "sha256:c73c78878258b07f1b468b0602c6591f25a1478f49ecb90b9bd44b7cc80bce73"},
]
[package.dependencies]
@ -4424,4 +4441,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
[metadata]
lock-version = "2.0"
python-versions = "^3.11"
content-hash = "05aa4db63c592f8c68e48c3f9aa71e7d376852faaaef9a95c0d0ae74d848bae0"
content-hash = "76237f0e04218f9ca9a2593ccf952452bd6d45657066feec87373279fb7fe6a2"

2
apps/api/pyproject.toml
View file

@ -38,6 +38,8 @@ sentence-transformers = "^2.2.2"
python-dotenv = "^1.0.0"
redis = "^5.0.1"
langchain-community = "^0.0.11"
langchain-openai = "^0.0.2.post1"
[build-system]
requires = ["poetry-core"]

1
apps/api/requirements.txt
View file

@ -20,6 +20,7 @@ sentry-sdk[fastapi]
pydantic[email]>=1.8.0,<2.0.0
langchain==0.1.0
langchain-community
langchain-openai
tiktoken
openai
chromadb

4
apps/api/src/db/organization_config.py
View file

@ -1,7 +1,4 @@
from json import JSONEncoder
import json
from typing import Literal, Optional
from click import Option
from pydantic import BaseModel
from sqlalchemy import JSON, BigInteger, Column, ForeignKey
from sqlmodel import Field, SQLModel
@ -21,6 +18,7 @@ class AIEnabledFeatures(BaseModel):
class AIConfig(BaseModel):
enabled : bool = True
limits: AILimitsSettings = AILimitsSettings()
embeddings: Literal[
"text-embedding-ada-002", "all-MiniLM-L6-v2"

2
apps/api/src/db/organizations.py
View file

@ -29,6 +29,6 @@ class OrganizationCreate(OrganizationBase):
class OrganizationRead(OrganizationBase):
id: int
org_uuid: str
config: OrganizationConfig | dict
config: Optional[OrganizationConfig | dict]
creation_date: str
update_date: str

21
apps/api/src/routers/orgs.py
View file

@ -1,6 +1,7 @@
from typing import List
from fastapi import APIRouter, Depends, Request, UploadFile
from sqlmodel import Session
from src.db.organization_config import OrganizationConfigBase
from src.db.users import PublicUser
from src.db.organizations import (
Organization,
@ -12,6 +13,7 @@ from src.core.events.database import get_db_session
from src.security.auth import get_current_user
from src.services.orgs.orgs import (
create_org,
create_org_with_config,
delete_org,
get_organization,
get_organization_by_slug,
@ -37,6 +39,23 @@ async def api_create_org(
return await create_org(request, org_object, current_user, db_session)
# Temporary pre-alpha code
@router.post("/withconfig/")
async def api_create_org_withconfig(
request: Request,
org_object: OrganizationCreate,
config_object: OrganizationConfigBase,
current_user: PublicUser = Depends(get_current_user),
db_session: Session = Depends(get_db_session),
) -> OrganizationRead:
"""
Create new organization
"""
return await create_org_with_config(
request, org_object, current_user, db_session, config_object
)
@router.get("/{org_id}")
async def api_get_org(
request: Request,
@ -110,7 +129,7 @@ async def api_update_org(
"""
Update Org by ID
"""
return await update_org(request, org_object,org_id, current_user, db_session)
return await update_org(request, org_object, org_id, current_user, db_session)
@router.delete("/{org_id}")

101
apps/api/src/services/ai/ai.py
View file

@ -2,6 +2,9 @@ from uuid import uuid4
from fastapi import Depends, HTTPException, Request
from requests import session
from sqlmodel import Session, select
from src.db.organization_config import OrganizationConfig
from src.db.organizations import Organization
from src.services.ai.utils import check_limits_and_config, count_ai_ask
from src.db.courses import Course, CourseRead
from src.core.events.database import get_db_session
from src.db.users import PublicUser
@ -29,6 +32,7 @@ def ai_start_activity_chat_session(
"""
Start a new AI Chat session with a Course Activity
"""
# Get the Activity
statement = select(Activity).where(
Activity.activity_uuid == chat_session_object.activity_uuid
@ -46,6 +50,14 @@ def ai_start_activity_chat_session(
course = db_session.exec(statement).first()
course = CourseRead.from_orm(course)
# Get the Organization
statement = select(Organization).where(Organization.id == course.org_id)
org = db_session.exec(statement).first()
# Check limits and usage
check_limits_and_config(db_session, org) # type: ignore
count_ai_ask(org, "increment") # type: ignore
if not activity:
raise HTTPException(
status_code=404,
@ -61,28 +73,48 @@ def ai_start_activity_chat_session(
structured, course, activity
)
# Get Activity Organization
statement = select(Organization).where(Organization.id == course.org_id)
org = db_session.exec(statement).first()
# Get Organization Config
statement = select(OrganizationConfig).where(
OrganizationConfig.org_id == org.id # type: ignore
)
result = db_session.exec(statement)
org_config = result.first()
org_config = OrganizationConfig.from_orm(org_config)
embeddings = org_config.config["AIConfig"]["embeddings"]
ai_model = org_config.config["AIConfig"]["ai_model"]
chat_session = get_chat_session_history()
message = "You are a helpful Education Assistant, and you are helping a student with the associated Course. "
message += "Use the available tools to get context about this question even if the question is not specific enough."
message += "For context, this is the Course name :"
message += course.name
message += " and this is the Lecture name :"
message += activity.name
message += "."
message += "Use your knowledge to help the student if the context is not enough."
response = ask_ai(
chat_session_object.message,
chat_session['message_history'],
chat_session["message_history"],
ai_friendly_text,
"You are a helpful Education Assistant, and you are helping a student with the associated Course. "
"Use the available tools to get context about this question even if the question is not specific enough."
"For context, this is the Course name :"
+ course.name
+ " and this is the Lecture name :"
+ activity.name
+ "."
"Use your knowledge to help the student.",
message,
embeddings,
ai_model,
)
return ActivityAIChatSessionResponse(
aichat_uuid=chat_session['aichat_uuid'],
aichat_uuid=chat_session["aichat_uuid"],
activity_uuid=activity.activity_uuid,
message=response["output"],
)
def ai_send_activity_chat_message(
request: Request,
chat_session_object: SendActivityAIChatMessage,
@ -109,6 +141,14 @@ def ai_send_activity_chat_message(
course = db_session.exec(statement).first()
course = CourseRead.from_orm(course)
# Get the Organization
statement = select(Organization).where(Organization.id == course.org_id)
org = db_session.exec(statement).first()
# Check limits and usage
check_limits_and_config(db_session, org) # type: ignore
count_ai_ask(org, "increment") # type: ignore
if not activity:
raise HTTPException(
status_code=404,
@ -116,7 +156,7 @@ def ai_send_activity_chat_message(
)
# Get Activity Content Blocks
content = activity.content
content = activity.content
# Serialize Activity Content Blocks to a text comprehensible by the AI
structured = structure_activity_content_by_type(content)
@ -124,24 +164,43 @@ def ai_send_activity_chat_message(
structured, course, activity
)
# Get Activity Organization
statement = select(Organization).where(Organization.id == course.org_id)
org = db_session.exec(statement).first()
# Get Organization Config
statement = select(OrganizationConfig).where(
OrganizationConfig.org_id == org.id # type: ignore
)
result = db_session.exec(statement)
org_config = result.first()
org_config = OrganizationConfig.from_orm(org_config)
embeddings = org_config.config["AIConfig"]["embeddings"]
ai_model = org_config.config["AIConfig"]["ai_model"]
chat_session = get_chat_session_history(chat_session_object.aichat_uuid)
message = "You are a helpful Education Assistant, and you are helping a student with the associated Course. "
message += "Use the available tools to get context about this question even if the question is not specific enough."
message += "For context, this is the Course name :"
message += course.name
message += " and this is the Lecture name :"
message += activity.name
message += "."
message += "Use your knowledge to help the student if the context is not enough."
response = ask_ai(
chat_session_object.message,
chat_session['message_history'],
chat_session["message_history"],
ai_friendly_text,
"You are a helpful Education Assistant, and you are helping a student with the associated Course. "
"Use the available tools to get context about this question even if the question is not specific enough."
"For context, this is the Course name :"
+ course.name
+ " and this is the Lecture name :"
+ activity.name
+ "."
"Use your knowledge to help the student if the context is not enough.",
message,
embeddings,
ai_model,
)
return ActivityAIChatSessionResponse(
aichat_uuid=chat_session['aichat_uuid'],
aichat_uuid=chat_session["aichat_uuid"],
activity_uuid=activity.activity_uuid,
message=response["output"],
)

25
apps/api/src/services/ai/base.py
View file

@ -11,6 +11,7 @@ from langchain_core.messages import SystemMessage
from langchain.agents.openai_functions_agent.agent_token_buffer_memory import (
AgentTokenBufferMemory,
)
from langchain_openai import OpenAIEmbeddings
from langchain_community.chat_models import ChatOpenAI
from langchain.agents.agent_toolkits import (
create_retriever_tool,
@ -31,6 +32,8 @@ def ask_ai(
message_history,
text_reference: str,
message_for_the_prompt: str,
embedding_model_name: str,
openai_model_name: str,
):
# Get API Keys
LH_CONFIG = get_learnhouse_config()
@ -41,8 +44,20 @@ def ask_ai(
documents = text_splitter.create_documents([text_reference])
texts = text_splitter.split_documents(documents)
# create the open-source embedding function
embedding_function = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")
embedding_models = {
"all-MiniLM-L6-v2": SentenceTransformerEmbeddings,
"text-embedding-ada-002": OpenAIEmbeddings,
}
embedding_function = None
if embedding_model_name in embedding_models:
if embedding_model_name == "text-embedding-ada-002":
embedding_function = embedding_models[embedding_model_name](model=embedding_model_name, api_key=openai_api_key)
if embedding_model_name == "all-MiniLM-L6-v2":
embedding_function = embedding_models[embedding_model_name](model_name=embedding_model_name)
else:
embedding_function = embedding_models[embedding_model_name](model_name=embedding_model_name)
# load it into Chroma and use it as a retriever
db = Chroma.from_documents(texts, embedding_function)
@ -53,12 +68,14 @@ def ask_ai(
)
tools = [tool]
llm = ChatOpenAI(temperature=0, api_key=openai_api_key, model_name="gpt-3.5-turbo")
llm = ChatOpenAI(
temperature=0, api_key=openai_api_key, model_name=openai_model_name
)
memory_key = "history"
memory = AgentTokenBufferMemory(
memory_key=memory_key, llm=llm, chat_memory=message_history, max_tokens=1000
memory_key=memory_key, llm=llm, chat_memory=message_history, max_token_limit=1000
)
system_message = SystemMessage(content=(message_for_the_prompt))

114
apps/api/src/services/ai/utils.py Normal file
View file

@ -0,0 +1,114 @@
from typing import Literal
import redis
from fastapi import HTTPException
from sqlmodel import Session, select
from config.config import get_learnhouse_config
from src.db.organization_config import OrganizationConfig
from src.db.organizations import Organization
def count_ai_ask(
organization: Organization,
operation: Literal["increment", "decrement"],
):
"""
Count the number of AI asks
"""
LH_CONFIG = get_learnhouse_config()
redis_conn_string = LH_CONFIG.redis_config.redis_connection_string
if not redis_conn_string:
raise HTTPException(
status_code=500,
detail="Redis connection string not found",
)
# Connect to Redis
r = redis.Redis.from_url(redis_conn_string)
if not r:
raise HTTPException(
status_code=500,
detail="Could not connect to Redis",
)
# Get the number of AI asks
ai_asks = r.get(f"ai_asks:{organization.org_uuid}")
if ai_asks is None:
ai_asks = 0
# Increment or decrement the number of AI asks
if operation == "increment":
ai_asks = int(ai_asks) + 1
elif operation == "decrement":
ai_asks = int(ai_asks) - 1
# Update the number of AI asks
r.set(f"ai_asks:{organization.org_uuid}", ai_asks)
# Set the expiration time to 30 days
r.expire(f"ai_asks:{organization.org_uuid}", 2592000)
def check_limits_and_config(db_session: Session, organization: Organization):
"""
Check the limits and config of an Organization
"""
# Get the Organization Config
statement = select(OrganizationConfig).where(
OrganizationConfig.org_id == organization.id
)
result = db_session.exec(statement)
org_config = result.first()
if org_config is None:
raise HTTPException(
status_code=404,
detail="Organization has no config",
)
# Check if the Organizations has AI enabled
if org_config.config["AIConfig"]["enabled"] == False:
raise HTTPException(
status_code=403,
detail="Organization has AI disabled",
)
# Check if the Organization has Limits enabled and if the max_asks limit has been reached
if org_config.config["AIConfig"]["limits"]["limits_enabled"] == True:
LH_CONFIG = get_learnhouse_config()
redis_conn_string = LH_CONFIG.redis_config.redis_connection_string
if not redis_conn_string:
raise HTTPException(
status_code=500,
detail="Redis connection string not found",
)
# Connect to Redis
r = redis.Redis.from_url(redis_conn_string)
if not r:
raise HTTPException(
status_code=500,
detail="Could not connect to Redis",
)
# Get the number of AI asks
ai_asks = r.get(f"ai_asks:{organization.org_uuid}")
# Get a number of AI asks
if ai_asks is None:
ai_asks = 0
else:
ai_asks = int(ai_asks)
# Check if the Number of asks is less than the max_asks limit
if org_config.config["AIConfig"]["limits"]["max_asks"] <= ai_asks:
raise HTTPException(
status_code=403,
detail="Organization has reached the max number of AI asks",
)

4
apps/api/src/services/blocks/block_types/imageBlock/imageBlock.py
View file

@ -44,12 +44,12 @@ async def create_image_block(
image_file,
activity_uuid,
block_uuid,
["jpg", "jpeg", "png", "gif"],
["jpg", "jpeg", "png", "gif", "webp"],
block_type,
org.org_uuid,
str(course.course_uuid),
)
# create block
block = Block(
activity_id=activity.id if activity.id else 0,

47
apps/api/src/services/courses/activities/utils.py
View file

@ -1,30 +1,25 @@
from src.db.activities import ActivityRead
from src.db.courses import CourseRead
def structure_activity_content_by_type(activity):
### Get Headings, Texts, Callouts, Answers and Paragraphs from the activity as a big list of strings (text only) and return it
content = activity["content"]
# Get Headings
headings = []
for item in activity["content"]:
if item["type"] == "heading":
headings.append(item["content"][0]["text"])
# Get Callouts
callouts = []
for item in activity["content"]:
if item["type"] == "calloutInfo":
# Get every type of text in the callout
text = ""
for text_item in item["content"]:
text += text_item["text"]
callouts.append(text)
# Get Paragraphs
paragraphs = []
for item in activity["content"]:
if item["type"] == "paragraph":
paragraphs.append(item["content"][0]["text"])
for item in content:
if 'content' in item:
if item["type"] == "heading" and "text" in item["content"][0]:
headings.append(item["content"][0]["text"])
elif item["type"] in ["calloutInfo", "calloutWarning"] and all("text" in text_item for text_item in item["content"]):
callouts.append(
"".join([text_item["text"] for text_item in item["content"]])
)
elif item["type"] == "paragraph" and "text" in item["content"][0]:
paragraphs.append(item["content"][0]["text"])
# TODO: Get Questions and Answers (if any)
@ -39,10 +34,14 @@ def structure_activity_content_by_type(activity):
# Add Paragraphs
data_array.append({"Paragraphs": paragraphs})
print(data_array)
return data_array
def serialize_activity_text_to_ai_comprehensible_text(data_array, course: CourseRead, activity: ActivityRead):
def serialize_activity_text_to_ai_comprehensible_text(
data_array, course: CourseRead, activity: ActivityRead
):
### Serialize the text to a format that is comprehensible by the AI
# Serialize Headings
@ -63,9 +62,13 @@ def serialize_activity_text_to_ai_comprehensible_text(data_array, course: Course
# Get a text that is comprehensible by the AI
text = (
'Use this as a context ' +
'This is a course about "' + course.name + '". '
+ 'This is a lecture about "' + activity.name + '". '
"Use this as a context "
+ 'This is a course about "'
+ course.name
+ '". '
+ 'This is a lecture about "'
+ activity.name
+ '". '
'These are the headings: "'
+ serialized_headings
+ '" These are the callouts: "'

82
apps/api/src/services/orgs/orgs.py
View file

@ -165,6 +165,7 @@ async def create_org(
active=True,
),
AIConfig=AIConfig(
enabled=False,
limits=AILimitsSettings(
limits_enabled=False,
max_asks=0,
@ -210,6 +211,87 @@ async def create_org(
return org
# Temporary pre-alpha code
async def create_org_with_config(
request: Request,
org_object: OrganizationCreate,
current_user: PublicUser | AnonymousUser,
db_session: Session,
submitted_config: OrganizationConfigBase,
):
statement = select(Organization).where(Organization.slug == org_object.slug)
result = db_session.exec(statement)
org = result.first()
if org:
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail="Organization already exists",
)
org = Organization.from_orm(org_object)
if isinstance(current_user, AnonymousUser):
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail="You should be logged in to be able to achieve this action",
)
# Complete the org object
org.org_uuid = f"org_{uuid4()}"
org.creation_date = str(datetime.now())
org.update_date = str(datetime.now())
db_session.add(org)
db_session.commit()
db_session.refresh(org)
# Link user to org
user_org = UserOrganization(
user_id=int(current_user.id),
org_id=int(org.id if org.id else 0),
role_id=1,
creation_date=str(datetime.now()),
update_date=str(datetime.now()),
)
db_session.add(user_org)
db_session.commit()
db_session.refresh(user_org)
org_config = submitted_config
org_config = json.loads(org_config.json())
# OrgSettings
org_settings = OrganizationConfig(
org_id=int(org.id if org.id else 0),
config=org_config,
creation_date=str(datetime.now()),
update_date=str(datetime.now()),
)
db_session.add(org_settings)
db_session.commit()
db_session.refresh(org_settings)
# Get org config
statement = select(OrganizationConfig).where(OrganizationConfig.org_id == org.id)
result = db_session.exec(statement)
org_config = result.first()
if org_config is None:
logging.error(f"Organization {org.id} has no config")
config = OrganizationConfig.from_orm(org_config)
org = OrganizationRead(**org.dict(), config=config)
return org
async def update_org(
request: Request,
org_object: OrganizationUpdate,