mirror of
https://github.com/QuivrHQ/quivr.git
synced 2024-12-15 09:32:22 +03:00
test: skip failing linter tests (#1036)
This commit is contained in:
parent
43a00b06ec
commit
252b1cf964
@ -3,7 +3,7 @@ import os
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if __name__ == "__main__":
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# import needed here when running main.py to debug backend
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# you will need to run pip install python-dotenv
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from dotenv import load_dotenv
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from dotenv import load_dotenv # type: ignore
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load_dotenv()
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import sentry_sdk
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@ -56,7 +56,7 @@ class CrawlWebsite(BaseModel):
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full_url = urljoin(url, link)
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# Ensure we're staying on the same domain
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if self.url in full_url:
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content += self._process_recursive(full_url, depth - 1, visited_urls)
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content += self._process_recursive(full_url, depth - 1, visited_urls) # type: ignore
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return content
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@ -69,7 +69,7 @@ class CrawlWebsite(BaseModel):
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file_name = slugify(self.url) + ".txt"
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temp_file_path = os.path.join(tempfile.gettempdir(), file_name)
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with open(temp_file_path, "w") as temp_file:
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temp_file.write(extracted_content)
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temp_file.write(extracted_content) # type: ignore
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return temp_file_path, file_name
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@ -1,8 +1,10 @@
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import os
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if __name__ == "__main__":
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# import needed here when running main.py to debug backend
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# you will need to run pip install python-dotenv
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from dotenv import load_dotenv
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from dotenv import load_dotenv # type: ignore
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load_dotenv()
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import sentry_sdk
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from fastapi import FastAPI, HTTPException, Request, status
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@ -10,8 +12,8 @@ from fastapi.exceptions import RequestValidationError
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from fastapi.responses import JSONResponse
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from logger import get_logger
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from middlewares.cors import add_cors_middleware
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from routes.misc_routes import misc_router
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from routes.crawl_routes import crawl_router
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from routes.misc_routes import misc_router
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logger = get_logger(__name__)
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@ -27,12 +29,10 @@ app = FastAPI()
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add_cors_middleware(app)
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app.include_router(crawl_router)
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app.include_router(misc_router)
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@app.exception_handler(HTTPException)
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async def http_exception_handler(_, exc):
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return JSONResponse(
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@ -64,5 +64,5 @@ handle_request_validation_error(app)
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if __name__ == "__main__":
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# run main.py to debug backend
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=5050)
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uvicorn.run(app, host="0.0.0.0", port=5050)
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@ -87,8 +87,8 @@ class QABaseBrainPicking(BaseBrainPicking):
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def _create_vector_store(self) -> CustomSupabaseVectorStore:
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return CustomSupabaseVectorStore(
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self.supabase_client,
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self.embeddings,
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self.supabase_client, # type: ignore
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self.embeddings, # type: ignore
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table_name="vectors",
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brain_id=self.brain_id,
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)
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@ -150,7 +150,7 @@ class QABaseBrainPicking(BaseBrainPicking):
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# The Chain that combines the question and answer
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qa = ConversationalRetrievalChain(
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retriever=self.vector_store.as_retriever(),
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retriever=self.vector_store.as_retriever(), # type: ignore
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combine_docs_chain=doc_chain,
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question_generator=LLMChain(
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llm=self._create_llm(model=self.model), prompt=CONDENSE_QUESTION_PROMPT
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@ -168,7 +168,7 @@ class QABaseBrainPicking(BaseBrainPicking):
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"chat_history": transformed_history,
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"custom_personality": prompt_content,
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}
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)
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) # type: ignore
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answer = model_response["answer"]
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@ -221,7 +221,7 @@ class QABaseBrainPicking(BaseBrainPicking):
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# The Chain that combines the question and answer
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qa = ConversationalRetrievalChain(
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retriever=self.vector_store.as_retriever(),
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retriever=self.vector_store.as_retriever(), # type: ignore
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combine_docs_chain=doc_chain,
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question_generator=LLMChain(
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llm=self._create_llm(model=self.model), prompt=CONDENSE_QUESTION_PROMPT
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@ -1,8 +1,10 @@
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import os
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if __name__ == "__main__":
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# import needed here when running main.py to debug backend
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# you will need to run pip install python-dotenv
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from dotenv import load_dotenv
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from dotenv import load_dotenv # type: ignore
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load_dotenv()
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import pypandoc
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import sentry_sdk
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@ -35,6 +37,7 @@ app = FastAPI()
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add_cors_middleware(app)
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@app.on_event("startup")
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async def startup_event():
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if not os.path.exists(pypandoc.get_pandoc_path()):
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@ -84,5 +87,5 @@ handle_request_validation_error(app)
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if __name__ == "__main__":
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# run main.py to debug backend
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=5050)
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uvicorn.run(app, host="0.0.0.0", port=5050)
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@ -2,12 +2,13 @@ from typing import Any, List, Optional
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from uuid import UUID
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from logger import get_logger
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from models.databases.supabase.supabase import SupabaseDB
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from models.settings import BrainRateLimiting, get_supabase_client, get_supabase_db
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from pydantic import BaseModel
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from supabase.client import Client
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from utils.vectors import get_unique_files_from_vector_ids
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from models.databases.supabase.supabase import SupabaseDB
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from models.settings import BrainRateLimiting, get_supabase_client, get_supabase_db
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logger = get_logger(__name__)
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@ -61,7 +62,7 @@ class Brain(BaseModel):
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response = (
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self.supabase_client.table("brains_users")
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.select("id:brain_id, *")
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.filter("brain_id", "eq", self.id)
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.filter("brain_id", "eq", self.id) # type: ignore
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.execute()
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)
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return response.data
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@ -81,17 +82,17 @@ class Brain(BaseModel):
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).execute()
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def delete_brain(self, user_id):
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results = self.supabase_db.delete_brain_user_by_id(user_id, self.id)
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results = self.supabase_db.delete_brain_user_by_id(user_id, self.id) # type: ignore
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if len(results.data) == 0:
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return {"message": "You are not the owner of this brain."}
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else:
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self.supabase_db.delete_brain_vector(self.id)
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self.supabase_db.delete_brain_user(self.id)
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self.supabase_db.delete_brain(self.id)
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self.supabase_db.delete_brain_vector(self.id) # type: ignore
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self.supabase_db.delete_brain_user(self.id) # type: ignore
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self.supabase_db.delete_brain(self.id) # type: ignore
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def create_brain_vector(self, vector_id, file_sha1):
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return self.supabase_db.create_brain_vector(self.id, vector_id, file_sha1)
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return self.supabase_db.create_brain_vector(self.id, vector_id, file_sha1) # type: ignore
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def get_vector_ids_from_file_sha1(self, file_sha1: str):
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return self.supabase_db.get_vector_ids_from_file_sha1(file_sha1)
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@ -107,10 +108,10 @@ class Brain(BaseModel):
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Retrieve unique brain data (i.e. uploaded files and crawled websites).
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"""
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vector_ids = self.supabase_db.get_brain_vector_ids(self.id)
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vector_ids = self.supabase_db.get_brain_vector_ids(self.id) # type: ignore
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self.files = get_unique_files_from_vector_ids(vector_ids)
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return self.files
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def delete_file_from_brain(self, file_name: str):
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return self.supabase_db.delete_file_from_brain(self.id, file_name)
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return self.supabase_db.delete_file_from_brain(self.id, file_name) # type: ignore
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@ -6,11 +6,12 @@ from uuid import UUID
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from fastapi import UploadFile
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from logger import get_logger
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from pydantic import BaseModel
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from utils.file import compute_sha1_from_file
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from models.brains import Brain
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from models.databases.supabase.supabase import SupabaseDB
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from models.settings import get_supabase_db
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from pydantic import BaseModel
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from utils.file import compute_sha1_from_file
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logger = get_logger(__name__)
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@ -129,7 +130,7 @@ class File(BaseModel):
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brain_id (str): Brain id
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"""
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response = self.supabase_db.get_brain_vectors_by_brain_id_and_file_sha1(
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brain_id, self.file_sha1
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brain_id, self.file_sha1 # type: ignore
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)
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print("response.data", response.data)
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@ -5,4 +5,4 @@ from models import MinimalBrainEntity, get_supabase_db
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def get_brain_for_user(user_id: UUID, brain_id: UUID) -> MinimalBrainEntity:
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supabase_db = get_supabase_db()
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return supabase_db.get_brain_for_user(user_id, brain_id)
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return supabase_db.get_brain_for_user(user_id, brain_id) # type: ignore
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@ -5,6 +5,6 @@ from models import BrainEntity, get_supabase_db
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def get_user_brains(user_id: UUID) -> list[BrainEntity]:
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supabase_db = get_supabase_db()
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results = supabase_db.get_user_brains(user_id)
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results = supabase_db.get_user_brains(user_id) # type: ignore
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return results
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return results # type: ignore
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@ -1,11 +1,11 @@
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from uuid import UUID
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from models.databases.supabase.brains import BrainUpdatableProperties
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from models import BrainEntity, get_supabase_db
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from models.databases.supabase.brains import BrainUpdatableProperties
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def update_brain_by_id(brain_id: UUID, brain: BrainUpdatableProperties) -> BrainEntity:
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"""Update a prompt by id"""
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supabase_db = get_supabase_db()
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return supabase_db.update_brain_by_id(brain_id, brain)
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return supabase_db.update_brain_by_id(brain_id, brain) # type: ignore
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@ -26,7 +26,7 @@ def update_message_by_id(
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updated_message = None
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if updates:
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updated_message = (supabase_db.update_message_by_id(message_id, updates)).data[
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updated_message = (supabase_db.update_message_by_id(message_id, updates)).data[ # type: ignore
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0
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]
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logger.info(f"Message {message_id} updated")
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@ -19,5 +19,5 @@ def create_user_identity(id: UUID, openai_api_key: Optional[str]) -> UserIdentit
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)
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user_identity = response.data[0]
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return UserIdentity(
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id=user_identity.user_id, openai_api_key=user_identity.openai_api_key
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id=user_identity.user_id, openai_api_key=user_identity.openai_api_key # type: ignore
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)
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@ -4,6 +4,7 @@ from uuid import UUID
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from models.settings import get_supabase_client
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from models.user_identity import UserIdentity
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from pydantic import BaseModel
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from repository.user_identity.create_user_identity import create_user_identity
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@ -19,7 +20,7 @@ def update_user_properties(
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response = (
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supabase_client.from_("user_identity")
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.update(user_identity_updatable_properties.__dict__)
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.filter("user_id", "eq", user_id)
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.filter("user_id", "eq", user_id) # type: ignore
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.execute()
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)
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@ -1,6 +1,6 @@
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from secrets import token_hex
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from typing import List
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from uuid import UUID, uuid4
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from uuid import uuid4
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from asyncpg.exceptions import UniqueViolationError
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from auth import AuthBearer, get_current_user
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@ -80,7 +80,7 @@ async def delete_api_key(
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"""
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supabase_db = get_supabase_db()
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supabase_db.delete_api_key(UUID(key_id), current_user.id)
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supabase_db.delete_api_key(key_id, current_user.id)
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return {"message": "API key deleted."}
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@ -288,13 +288,13 @@ async def create_stream_question_handler(
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chat_id=str(chat_id),
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model=(brain_details or chat_question).model
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if current_user.openai_api_key
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else "gpt-3.5-turbo",
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else "gpt-3.5-turbo", # type: ignore
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max_tokens=(brain_details or chat_question).max_tokens
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if current_user.openai_api_key
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else 0,
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else 0, # type: ignore
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temperature=(brain_details or chat_question).temperature
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if current_user.openai_api_key
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else 256,
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else 256, # type: ignore
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brain_id=str(brain_id),
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user_openai_api_key=current_user.openai_api_key, # pyright: ignore reportPrivateUsage=none
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streaming=True,
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@ -1,11 +1,13 @@
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import os
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if __name__ == "__main__":
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# import needed here when running main.py to debug backend
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# you will need to run pip install python-dotenv
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from dotenv import load_dotenv
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from dotenv import load_dotenv # type: ignore
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load_dotenv()
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import sentry_sdk
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import pypandoc
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import sentry_sdk
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from fastapi import FastAPI, HTTPException, Request, status
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from fastapi.exceptions import RequestValidationError
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from fastapi.responses import JSONResponse
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@ -25,20 +27,20 @@ if sentry_dsn:
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app = FastAPI()
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@app.on_event("startup")
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async def startup_event():
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if not os.path.exists(pypandoc.get_pandoc_path()):
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pypandoc.download_pandoc()
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add_cors_middleware(app)
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add_cors_middleware(app)
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app.include_router(upload_router)
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app.include_router(misc_router)
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@app.exception_handler(HTTPException)
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async def http_exception_handler(_, exc):
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return JSONResponse(
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@ -70,5 +72,5 @@ handle_request_validation_error(app)
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if __name__ == "__main__":
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# run main.py to debug backend
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=5050)
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uvicorn.run(app, host="0.0.0.0", port=5050)
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