From 022bd718e3dfc197027b1e24fb97e5525b186db4 Mon Sep 17 00:00:00 2001
From: Pablo Orgaz <pabloogc@gmail.com>
Date: Sun, 12 Nov 2023 22:20:36 +0100
Subject: [PATCH] fix: Remove global state (#1216)
* Remove all global settings state
* chore: remove autogenerated class
* chore: cleanup
* chore: merge conflicts
---
private_gpt/__main__.py | 2 +-
.../embedding/embedding_component.py | 4 +-
private_gpt/components/llm/llm_component.py | 4 +-
private_gpt/di.py | 16 ++-
private_gpt/launcher.py | 128 ++++++++++++++++++
private_gpt/main.py | 119 +---------------
private_gpt/paths.py | 4 +-
private_gpt/server/chat/chat_router.py | 9 +-
private_gpt/server/chunks/chunks_router.py | 7 +-
.../server/completions/completions_router.py | 8 +-
.../server/embeddings/embeddings_router.py | 7 +-
private_gpt/server/ingest/ingest_router.py | 15 +-
private_gpt/server/utils/auth.py | 6 +-
private_gpt/settings/settings.py | 29 +++-
private_gpt/settings/settings_loader.py | 15 +-
private_gpt/ui/ui.py | 29 ++--
scripts/ingest_folder.py | 4 +-
scripts/setup | 8 +-
settings-test.yaml | 6 +-
tests/fixtures/fast_api_test_client.py | 15 +-
tests/fixtures/mock_injector.py | 9 ++
tests/server/utils/test_simple_auth.py | 11 +-
tests/settings/test_settings.py | 11 +-
tests/ui/test_ui.py | 10 ++
24 files changed, 286 insertions(+), 190 deletions(-)
create mode 100644 private_gpt/launcher.py
create mode 100644 tests/ui/test_ui.py
diff --git a/private_gpt/__main__.py b/private_gpt/__main__.py
index 6bf2f156..18b42fd7 100644
--- a/private_gpt/__main__.py
+++ b/private_gpt/__main__.py
@@ -8,4 +8,4 @@ from private_gpt.settings.settings import settings
# Set log_config=None to do not use the uvicorn logging configuration, and
# use ours instead. For reference, see below:
# https://github.com/tiangolo/fastapi/discussions/7457#discussioncomment-5141108
-uvicorn.run(app, host="0.0.0.0", port=settings.server.port, log_config=None)
+uvicorn.run(app, host="0.0.0.0", port=settings().server.port, log_config=None)
diff --git a/private_gpt/components/embedding/embedding_component.py b/private_gpt/components/embedding/embedding_component.py
index f71be0a6..53fc984e 100644
--- a/private_gpt/components/embedding/embedding_component.py
+++ b/private_gpt/components/embedding/embedding_component.py
@@ -3,7 +3,7 @@ from llama_index import MockEmbedding
from llama_index.embeddings.base import BaseEmbedding
from private_gpt.paths import models_cache_path
-from private_gpt.settings.settings import settings
+from private_gpt.settings.settings import Settings
@singleton
@@ -11,7 +11,7 @@ class EmbeddingComponent:
embedding_model: BaseEmbedding
@inject
- def __init__(self) -> None:
+ def __init__(self, settings: Settings) -> None:
match settings.llm.mode:
case "local":
from llama_index.embeddings import HuggingFaceEmbedding
diff --git a/private_gpt/components/llm/llm_component.py b/private_gpt/components/llm/llm_component.py
index cad6ed67..4f46f151 100644
--- a/private_gpt/components/llm/llm_component.py
+++ b/private_gpt/components/llm/llm_component.py
@@ -4,7 +4,7 @@ from llama_index.llms.base import LLM
from llama_index.llms.llama_utils import completion_to_prompt, messages_to_prompt
from private_gpt.paths import models_path
-from private_gpt.settings.settings import settings
+from private_gpt.settings.settings import Settings
@singleton
@@ -12,7 +12,7 @@ class LLMComponent:
llm: LLM
@inject
- def __init__(self) -> None:
+ def __init__(self, settings: Settings) -> None:
match settings.llm.mode:
case "local":
from llama_index.llms import LlamaCPP
diff --git a/private_gpt/di.py b/private_gpt/di.py
index 115c8892..05021b01 100644
--- a/private_gpt/di.py
+++ b/private_gpt/di.py
@@ -1,9 +1,19 @@
from injector import Injector
+from private_gpt.settings.settings import Settings, unsafe_typed_settings
+
def create_application_injector() -> Injector:
- injector = Injector(auto_bind=True)
- return injector
+ _injector = Injector(auto_bind=True)
+ _injector.binder.bind(Settings, to=unsafe_typed_settings)
+ return _injector
-root_injector: Injector = create_application_injector()
+"""
+Global injector for the application.
+
+Avoid using this reference, it will make your code harder to test.
+
+Instead, use the `request.state.injector` reference, which is bound to every request
+"""
+global_injector: Injector = create_application_injector()
diff --git a/private_gpt/launcher.py b/private_gpt/launcher.py
new file mode 100644
index 00000000..e65f0edc
--- /dev/null
+++ b/private_gpt/launcher.py
@@ -0,0 +1,128 @@
+"""FastAPI app creation, logger configuration and main API routes."""
+import logging
+from typing import Any
+
+from fastapi import Depends, FastAPI, Request
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.openapi.utils import get_openapi
+from injector import Injector
+
+from private_gpt.paths import docs_path
+from private_gpt.server.chat.chat_router import chat_router
+from private_gpt.server.chunks.chunks_router import chunks_router
+from private_gpt.server.completions.completions_router import completions_router
+from private_gpt.server.embeddings.embeddings_router import embeddings_router
+from private_gpt.server.health.health_router import health_router
+from private_gpt.server.ingest.ingest_router import ingest_router
+from private_gpt.settings.settings import Settings
+
+logger = logging.getLogger(__name__)
+
+
+def create_app(root_injector: Injector) -> FastAPI:
+
+ # Start the API
+ with open(docs_path / "description.md") as description_file:
+ description = description_file.read()
+
+ tags_metadata = [
+ {
+ "name": "Ingestion",
+ "description": "High-level APIs covering document ingestion -internally "
+ "managing document parsing, splitting,"
+ "metadata extraction, embedding generation and storage- and ingested "
+ "documents CRUD."
+ "Each ingested document is identified by an ID that can be used to filter the "
+ "context"
+ "used in *Contextual Completions* and *Context Chunks* APIs.",
+ },
+ {
+ "name": "Contextual Completions",
+ "description": "High-level APIs covering contextual Chat and Completions. They "
+ "follow OpenAI's format, extending it to "
+ "allow using the context coming from ingested documents to create the "
+ "response. Internally"
+ "manage context retrieval, prompt engineering and the response generation.",
+ },
+ {
+ "name": "Context Chunks",
+ "description": "Low-level API that given a query return relevant chunks of "
+ "text coming from the ingested"
+ "documents.",
+ },
+ {
+ "name": "Embeddings",
+ "description": "Low-level API to obtain the vector representation of a given "
+ "text, using an Embeddings model."
+ "Follows OpenAI's embeddings API format.",
+ },
+ {
+ "name": "Health",
+ "description": "Simple health API to make sure the server is up and running.",
+ },
+ ]
+
+ async def bind_injector_to_request(request: Request) -> None:
+ request.state.injector = root_injector
+
+ app = FastAPI(dependencies=[Depends(bind_injector_to_request)])
+
+ def custom_openapi() -> dict[str, Any]:
+ if app.openapi_schema:
+ return app.openapi_schema
+ openapi_schema = get_openapi(
+ title="PrivateGPT",
+ description=description,
+ version="0.1.0",
+ summary="PrivateGPT is a production-ready AI project that allows you to "
+ "ask questions to your documents using the power of Large Language "
+ "Models (LLMs), even in scenarios without Internet connection. "
+ "100% private, no data leaves your execution environment at any point.",
+ contact={
+ "url": "https://github.com/imartinez/privateGPT",
+ },
+ license_info={
+ "name": "Apache 2.0",
+ "url": "https://www.apache.org/licenses/LICENSE-2.0.html",
+ },
+ routes=app.routes,
+ tags=tags_metadata,
+ )
+ openapi_schema["info"]["x-logo"] = {
+ "url": "https://lh3.googleusercontent.com/drive-viewer"
+ "/AK7aPaD_iNlMoTquOBsw4boh4tIYxyEuhz6EtEs8nzq3yNkNAK00xGj"
+ "E1KUCmPJSk3TYOjcs6tReG6w_cLu1S7L_gPgT9z52iw=s2560"
+ }
+
+ app.openapi_schema = openapi_schema
+ return app.openapi_schema
+
+ app.openapi = custom_openapi # type: ignore[method-assign]
+
+ app.include_router(completions_router)
+ app.include_router(chat_router)
+ app.include_router(chunks_router)
+ app.include_router(ingest_router)
+ app.include_router(embeddings_router)
+ app.include_router(health_router)
+
+ settings = root_injector.get(Settings)
+ if settings.server.cors.enabled:
+ logger.debug("Setting up CORS middleware")
+ app.add_middleware(
+ CORSMiddleware,
+ allow_credentials=settings.server.cors.allow_credentials,
+ allow_origins=settings.server.cors.allow_origins,
+ allow_origin_regex=settings.server.cors.allow_origin_regex,
+ allow_methods=settings.server.cors.allow_methods,
+ allow_headers=settings.server.cors.allow_headers,
+ )
+
+ if settings.ui.enabled:
+ logger.debug("Importing the UI module")
+ from private_gpt.ui.ui import PrivateGptUi
+
+ ui = root_injector.get(PrivateGptUi)
+ ui.mount_in_app(app, settings.ui.path)
+
+ return app
diff --git a/private_gpt/main.py b/private_gpt/main.py
index 519f205d..d249fa6c 100644
--- a/private_gpt/main.py
+++ b/private_gpt/main.py
@@ -1,124 +1,11 @@
"""FastAPI app creation, logger configuration and main API routes."""
-import logging
-from typing import Any
import llama_index
-from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.openapi.utils import get_openapi
-from private_gpt.paths import docs_path
-from private_gpt.server.chat.chat_router import chat_router
-from private_gpt.server.chunks.chunks_router import chunks_router
-from private_gpt.server.completions.completions_router import completions_router
-from private_gpt.server.embeddings.embeddings_router import embeddings_router
-from private_gpt.server.health.health_router import health_router
-from private_gpt.server.ingest.ingest_router import ingest_router
-from private_gpt.settings.settings import settings
-
-logger = logging.getLogger(__name__)
+from private_gpt.di import global_injector
+from private_gpt.launcher import create_app
# Add LlamaIndex simple observability
llama_index.set_global_handler("simple")
-# Start the API
-with open(docs_path / "description.md") as description_file:
- description = description_file.read()
-
-tags_metadata = [
- {
- "name": "Ingestion",
- "description": "High-level APIs covering document ingestion -internally "
- "managing document parsing, splitting,"
- "metadata extraction, embedding generation and storage- and ingested "
- "documents CRUD."
- "Each ingested document is identified by an ID that can be used to filter the "
- "context"
- "used in *Contextual Completions* and *Context Chunks* APIs.",
- },
- {
- "name": "Contextual Completions",
- "description": "High-level APIs covering contextual Chat and Completions. They "
- "follow OpenAI's format, extending it to "
- "allow using the context coming from ingested documents to create the "
- "response. Internally"
- "manage context retrieval, prompt engineering and the response generation.",
- },
- {
- "name": "Context Chunks",
- "description": "Low-level API that given a query return relevant chunks of "
- "text coming from the ingested"
- "documents.",
- },
- {
- "name": "Embeddings",
- "description": "Low-level API to obtain the vector representation of a given "
- "text, using an Embeddings model."
- "Follows OpenAI's embeddings API format.",
- },
- {
- "name": "Health",
- "description": "Simple health API to make sure the server is up and running.",
- },
-]
-
-app = FastAPI()
-
-
-def custom_openapi() -> dict[str, Any]:
- if app.openapi_schema:
- return app.openapi_schema
- openapi_schema = get_openapi(
- title="PrivateGPT",
- description=description,
- version="0.1.0",
- summary="PrivateGPT is a production-ready AI project that allows you to "
- "ask questions to your documents using the power of Large Language "
- "Models (LLMs), even in scenarios without Internet connection. "
- "100% private, no data leaves your execution environment at any point.",
- contact={
- "url": "https://github.com/imartinez/privateGPT",
- },
- license_info={
- "name": "Apache 2.0",
- "url": "https://www.apache.org/licenses/LICENSE-2.0.html",
- },
- routes=app.routes,
- tags=tags_metadata,
- )
- openapi_schema["info"]["x-logo"] = {
- "url": "https://lh3.googleusercontent.com/drive-viewer"
- "/AK7aPaD_iNlMoTquOBsw4boh4tIYxyEuhz6EtEs8nzq3yNkNAK00xGj"
- "E1KUCmPJSk3TYOjcs6tReG6w_cLu1S7L_gPgT9z52iw=s2560"
- }
-
- app.openapi_schema = openapi_schema
- return app.openapi_schema
-
-
-app.openapi = custom_openapi # type: ignore[method-assign]
-
-app.include_router(completions_router)
-app.include_router(chat_router)
-app.include_router(chunks_router)
-app.include_router(ingest_router)
-app.include_router(embeddings_router)
-app.include_router(health_router)
-
-if settings.server.cors.enabled:
- logger.debug("Setting up CORS middleware")
- app.add_middleware(
- CORSMiddleware,
- allow_credentials=settings.server.cors.allow_credentials,
- allow_origins=settings.server.cors.allow_origins,
- allow_origin_regex=settings.server.cors.allow_origin_regex,
- allow_methods=settings.server.cors.allow_methods,
- allow_headers=settings.server.cors.allow_headers,
- )
-
-
-if settings.ui.enabled:
- logger.debug("Importing the UI module")
- from private_gpt.ui.ui import PrivateGptUi
-
- PrivateGptUi().mount_in_app(app)
+app = create_app(global_injector)
diff --git a/private_gpt/paths.py b/private_gpt/paths.py
index 88310519..59db3a49 100644
--- a/private_gpt/paths.py
+++ b/private_gpt/paths.py
@@ -13,4 +13,6 @@ def _absolute_or_from_project_root(path: str) -> Path:
models_path: Path = PROJECT_ROOT_PATH / "models"
models_cache_path: Path = models_path / "cache"
docs_path: Path = PROJECT_ROOT_PATH / "docs"
-local_data_path: Path = _absolute_or_from_project_root(settings.data.local_data_folder)
+local_data_path: Path = _absolute_or_from_project_root(
+ settings().data.local_data_folder
+)
diff --git a/private_gpt/server/chat/chat_router.py b/private_gpt/server/chat/chat_router.py
index bd7034b4..79558f7f 100644
--- a/private_gpt/server/chat/chat_router.py
+++ b/private_gpt/server/chat/chat_router.py
@@ -1,9 +1,8 @@
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter, Depends, Request
from llama_index.llms import ChatMessage, MessageRole
from pydantic import BaseModel
from starlette.responses import StreamingResponse
-from private_gpt.di import root_injector
from private_gpt.open_ai.extensions.context_filter import ContextFilter
from private_gpt.open_ai.openai_models import (
OpenAICompletion,
@@ -52,7 +51,9 @@ class ChatBody(BaseModel):
responses={200: {"model": OpenAICompletion}},
tags=["Contextual Completions"],
)
-def chat_completion(body: ChatBody) -> OpenAICompletion | StreamingResponse:
+def chat_completion(
+ request: Request, body: ChatBody
+) -> OpenAICompletion | StreamingResponse:
"""Given a list of messages comprising a conversation, return a response.
If `use_context` is set to `true`, the model will use context coming
@@ -72,7 +73,7 @@ def chat_completion(body: ChatBody) -> OpenAICompletion | StreamingResponse:
"finish_reason":null}]}
```
"""
- service = root_injector.get(ChatService)
+ service = request.state.injector.get(ChatService)
all_messages = [
ChatMessage(content=m.content, role=MessageRole(m.role)) for m in body.messages
]
diff --git a/private_gpt/server/chunks/chunks_router.py b/private_gpt/server/chunks/chunks_router.py
index d965d984..4da377ac 100644
--- a/private_gpt/server/chunks/chunks_router.py
+++ b/private_gpt/server/chunks/chunks_router.py
@@ -1,9 +1,8 @@
from typing import Literal
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter, Depends, Request
from pydantic import BaseModel, Field
-from private_gpt.di import root_injector
from private_gpt.open_ai.extensions.context_filter import ContextFilter
from private_gpt.server.chunks.chunks_service import Chunk, ChunksService
from private_gpt.server.utils.auth import authenticated
@@ -25,7 +24,7 @@ class ChunksResponse(BaseModel):
@chunks_router.post("/chunks", tags=["Context Chunks"])
-def chunks_retrieval(body: ChunksBody) -> ChunksResponse:
+def chunks_retrieval(request: Request, body: ChunksBody) -> ChunksResponse:
"""Given a `text`, returns the most relevant chunks from the ingested documents.
The returned information can be used to generate prompts that can be
@@ -45,7 +44,7 @@ def chunks_retrieval(body: ChunksBody) -> ChunksResponse:
`/ingest/list` endpoint. If you want all ingested documents to be used,
remove `context_filter` altogether.
"""
- service = root_injector.get(ChunksService)
+ service = request.state.injector.get(ChunksService)
results = service.retrieve_relevant(
body.text, body.context_filter, body.limit, body.prev_next_chunks
)
diff --git a/private_gpt/server/completions/completions_router.py b/private_gpt/server/completions/completions_router.py
index 4840047f..887923b4 100644
--- a/private_gpt/server/completions/completions_router.py
+++ b/private_gpt/server/completions/completions_router.py
@@ -1,4 +1,4 @@
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter, Depends, Request
from pydantic import BaseModel
from starlette.responses import StreamingResponse
@@ -41,7 +41,9 @@ class CompletionsBody(BaseModel):
responses={200: {"model": OpenAICompletion}},
tags=["Contextual Completions"],
)
-def prompt_completion(body: CompletionsBody) -> OpenAICompletion | StreamingResponse:
+def prompt_completion(
+ request: Request, body: CompletionsBody
+) -> OpenAICompletion | StreamingResponse:
"""We recommend most users use our Chat completions API.
Given a prompt, the model will return one predicted completion. If `use_context`
@@ -70,4 +72,4 @@ def prompt_completion(body: CompletionsBody) -> OpenAICompletion | StreamingResp
include_sources=body.include_sources,
context_filter=body.context_filter,
)
- return chat_completion(chat_body)
+ return chat_completion(request, chat_body)
diff --git a/private_gpt/server/embeddings/embeddings_router.py b/private_gpt/server/embeddings/embeddings_router.py
index f5236c6a..f698392d 100644
--- a/private_gpt/server/embeddings/embeddings_router.py
+++ b/private_gpt/server/embeddings/embeddings_router.py
@@ -1,9 +1,8 @@
from typing import Literal
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter, Depends, Request
from pydantic import BaseModel
-from private_gpt.di import root_injector
from private_gpt.server.embeddings.embeddings_service import (
Embedding,
EmbeddingsService,
@@ -24,13 +23,13 @@ class EmbeddingsResponse(BaseModel):
@embeddings_router.post("/embeddings", tags=["Embeddings"])
-def embeddings_generation(body: EmbeddingsBody) -> EmbeddingsResponse:
+def embeddings_generation(request: Request, body: EmbeddingsBody) -> EmbeddingsResponse:
"""Get a vector representation of a given input.
That vector representation can be easily consumed
by machine learning models and algorithms.
"""
- service = root_injector.get(EmbeddingsService)
+ service = request.state.injector.get(EmbeddingsService)
input_texts = body.input if isinstance(body.input, list) else [body.input]
embeddings = service.texts_embeddings(input_texts)
return EmbeddingsResponse(object="list", model="private-gpt", data=embeddings)
diff --git a/private_gpt/server/ingest/ingest_router.py b/private_gpt/server/ingest/ingest_router.py
index d682de7b..c06a4d41 100644
--- a/private_gpt/server/ingest/ingest_router.py
+++ b/private_gpt/server/ingest/ingest_router.py
@@ -1,9 +1,8 @@
from typing import Literal
-from fastapi import APIRouter, Depends, HTTPException, UploadFile
+from fastapi import APIRouter, Depends, HTTPException, Request, UploadFile
from pydantic import BaseModel
-from private_gpt.di import root_injector
from private_gpt.server.ingest.ingest_service import IngestedDoc, IngestService
from private_gpt.server.utils.auth import authenticated
@@ -17,7 +16,7 @@ class IngestResponse(BaseModel):
@ingest_router.post("/ingest", tags=["Ingestion"])
-def ingest(file: UploadFile) -> IngestResponse:
+def ingest(request: Request, file: UploadFile) -> IngestResponse:
"""Ingests and processes a file, storing its chunks to be used as context.
The context obtained from files is later used in
@@ -33,7 +32,7 @@ def ingest(file: UploadFile) -> IngestResponse:
can be used to filter the context used to create responses in
`/chat/completions`, `/completions`, and `/chunks` APIs.
"""
- service = root_injector.get(IngestService)
+ service = request.state.injector.get(IngestService)
if file.filename is None:
raise HTTPException(400, "No file name provided")
ingested_documents = service.ingest(file.filename, file.file.read())
@@ -41,23 +40,23 @@ def ingest(file: UploadFile) -> IngestResponse:
@ingest_router.get("/ingest/list", tags=["Ingestion"])
-def list_ingested() -> IngestResponse:
+def list_ingested(request: Request) -> IngestResponse:
"""Lists already ingested Documents including their Document ID and metadata.
Those IDs can be used to filter the context used to create responses
in `/chat/completions`, `/completions`, and `/chunks` APIs.
"""
- service = root_injector.get(IngestService)
+ service = request.state.injector.get(IngestService)
ingested_documents = service.list_ingested()
return IngestResponse(object="list", model="private-gpt", data=ingested_documents)
@ingest_router.delete("/ingest/{doc_id}", tags=["Ingestion"])
-def delete_ingested(doc_id: str) -> None:
+def delete_ingested(request: Request, doc_id: str) -> None:
"""Delete the specified ingested Document.
The `doc_id` can be obtained from the `GET /ingest/list` endpoint.
The document will be effectively deleted from your storage context.
"""
- service = root_injector.get(IngestService)
+ service = request.state.injector.get(IngestService)
service.delete(doc_id)
diff --git a/private_gpt/server/utils/auth.py b/private_gpt/server/utils/auth.py
index 371e794d..4fd57a7f 100644
--- a/private_gpt/server/utils/auth.py
+++ b/private_gpt/server/utils/auth.py
@@ -38,13 +38,13 @@ logger = logging.getLogger(__name__)
def _simple_authentication(authorization: Annotated[str, Header()] = "") -> bool:
"""Check if the request is authenticated."""
- if not secrets.compare_digest(authorization, settings.server.auth.secret):
+ if not secrets.compare_digest(authorization, settings().server.auth.secret):
# If the "Authorization" header is not the expected one, raise an exception.
raise NOT_AUTHENTICATED
return True
-if not settings.server.auth.enabled:
+if not settings().server.auth.enabled:
logger.debug(
"Defining a dummy authentication mechanism for fastapi, always authenticating requests"
)
@@ -62,7 +62,7 @@ else:
_simple_authentication: Annotated[bool, Depends(_simple_authentication)]
) -> bool:
"""Check if the request is authenticated."""
- assert settings.server.auth.enabled
+ assert settings().server.auth.enabled
if not _simple_authentication:
raise NOT_AUTHENTICATED
return True
diff --git a/private_gpt/settings/settings.py b/private_gpt/settings/settings.py
index 9529cac1..30443119 100644
--- a/private_gpt/settings/settings.py
+++ b/private_gpt/settings/settings.py
@@ -2,7 +2,7 @@ from typing import Literal
from pydantic import BaseModel, Field
-from private_gpt.settings.settings_loader import load_active_profiles
+from private_gpt.settings.settings_loader import load_active_settings
class CorsSettings(BaseModel):
@@ -114,4 +114,29 @@ class Settings(BaseModel):
openai: OpenAISettings
-settings = Settings(**load_active_profiles())
+"""
+This is visible just for DI or testing purposes.
+
+Use dependency injection or `settings()` method instead.
+"""
+unsafe_settings = load_active_settings()
+
+"""
+This is visible just for DI or testing purposes.
+
+Use dependency injection or `settings()` method instead.
+"""
+unsafe_typed_settings = Settings(**unsafe_settings)
+
+
+def settings() -> Settings:
+ """Get the current loaded settings from the DI container.
+
+ This method exists to keep compatibility with the existing code,
+ that require global access to the settings.
+
+ For regular components use dependency injection instead.
+ """
+ from private_gpt.di import global_injector
+
+ return global_injector.get(Settings)
diff --git a/private_gpt/settings/settings_loader.py b/private_gpt/settings/settings_loader.py
index 99c2ca40..b4052db2 100644
--- a/private_gpt/settings/settings_loader.py
+++ b/private_gpt/settings/settings_loader.py
@@ -2,6 +2,7 @@ import functools
import logging
import os
import sys
+from collections.abc import Iterable
from pathlib import Path
from typing import Any
@@ -28,7 +29,11 @@ active_profiles: list[str] = unique_list(
)
-def load_profile(profile: str) -> dict[str, Any]:
+def merge_settings(settings: Iterable[dict[str, Any]]) -> dict[str, Any]:
+ return functools.reduce(deep_update, settings, {})
+
+
+def load_settings_from_profile(profile: str) -> dict[str, Any]:
if profile == "default":
profile_file_name = "settings.yaml"
else:
@@ -42,9 +47,11 @@ def load_profile(profile: str) -> dict[str, Any]:
return config
-def load_active_profiles() -> dict[str, Any]:
+def load_active_settings() -> dict[str, Any]:
"""Load active profiles and merge them."""
logger.info("Starting application with profiles=%s", active_profiles)
- loaded_profiles = [load_profile(profile) for profile in active_profiles]
- merged: dict[str, Any] = functools.reduce(deep_update, loaded_profiles, {})
+ loaded_profiles = [
+ load_settings_from_profile(profile) for profile in active_profiles
+ ]
+ merged: dict[str, Any] = merge_settings(loaded_profiles)
return merged
diff --git a/private_gpt/ui/ui.py b/private_gpt/ui/ui.py
index f4a1431a..dea99f50 100644
--- a/private_gpt/ui/ui.py
+++ b/private_gpt/ui/ui.py
@@ -8,10 +8,11 @@ from typing import Any, TextIO
import gradio as gr # type: ignore
from fastapi import FastAPI
from gradio.themes.utils.colors import slate # type: ignore
+from injector import inject, singleton
from llama_index.llms import ChatMessage, ChatResponse, MessageRole
from pydantic import BaseModel
-from private_gpt.di import root_injector
+from private_gpt.di import global_injector
from private_gpt.server.chat.chat_service import ChatService, CompletionGen
from private_gpt.server.chunks.chunks_service import Chunk, ChunksService
from private_gpt.server.ingest.ingest_service import IngestService
@@ -48,11 +49,18 @@ class Source(BaseModel):
return curated_sources
+@singleton
class PrivateGptUi:
- def __init__(self) -> None:
- self._ingest_service = root_injector.get(IngestService)
- self._chat_service = root_injector.get(ChatService)
- self._chunks_service = root_injector.get(ChunksService)
+ @inject
+ def __init__(
+ self,
+ ingest_service: IngestService,
+ chat_service: ChatService,
+ chunks_service: ChunksService,
+ ) -> None:
+ self._ingest_service = ingest_service
+ self._chat_service = chat_service
+ self._chunks_service = chunks_service
# Cache the UI blocks
self._ui_block = None
@@ -198,7 +206,7 @@ class PrivateGptUi:
_ = gr.ChatInterface(
self._chat,
chatbot=gr.Chatbot(
- label=f"LLM: {settings.llm.mode}",
+ label=f"LLM: {settings().llm.mode}",
show_copy_button=True,
render=False,
avatar_images=(
@@ -217,16 +225,15 @@ class PrivateGptUi:
self._ui_block = self._build_ui_blocks()
return self._ui_block
- def mount_in_app(self, app: FastAPI) -> None:
+ def mount_in_app(self, app: FastAPI, path: str) -> None:
blocks = self.get_ui_blocks()
blocks.queue()
- base_path = settings.ui.path
- logger.info("Mounting the gradio UI, at path=%s", base_path)
- gr.mount_gradio_app(app, blocks, path=base_path)
+ logger.info("Mounting the gradio UI, at path=%s", path)
+ gr.mount_gradio_app(app, blocks, path=path)
if __name__ == "__main__":
- ui = PrivateGptUi()
+ ui = global_injector.get(PrivateGptUi)
_blocks = ui.get_ui_blocks()
_blocks.queue()
_blocks.launch(debug=False, show_api=False)
diff --git a/scripts/ingest_folder.py b/scripts/ingest_folder.py
index f2bc24c5..cdb164ef 100644
--- a/scripts/ingest_folder.py
+++ b/scripts/ingest_folder.py
@@ -2,13 +2,13 @@ import argparse
import logging
from pathlib import Path
-from private_gpt.di import root_injector
+from private_gpt.di import global_injector
from private_gpt.server.ingest.ingest_service import IngestService
from private_gpt.server.ingest.ingest_watcher import IngestWatcher
logger = logging.getLogger(__name__)
-ingest_service = root_injector.get(IngestService)
+ingest_service = global_injector.get(IngestService)
parser = argparse.ArgumentParser(prog="ingest_folder.py")
parser.add_argument("folder", help="Folder to ingest")
diff --git a/scripts/setup b/scripts/setup
index fc56d139..377bbe0b 100755
--- a/scripts/setup
+++ b/scripts/setup
@@ -9,9 +9,9 @@ from private_gpt.settings.settings import settings
os.makedirs(models_path, exist_ok=True)
embedding_path = models_path / "embedding"
-print(f"Downloading embedding {settings.local.embedding_hf_model_name}")
+print(f"Downloading embedding {settings().local.embedding_hf_model_name}")
snapshot_download(
- repo_id=settings.local.embedding_hf_model_name,
+ repo_id=settings().local.embedding_hf_model_name,
cache_dir=models_cache_path,
local_dir=embedding_path,
)
@@ -20,8 +20,8 @@ print("Downloading models for local execution...")
# Download LLM and create a symlink to the model file
hf_hub_download(
- repo_id=settings.local.llm_hf_repo_id,
- filename=settings.local.llm_hf_model_file,
+ repo_id=settings().local.llm_hf_repo_id,
+ filename=settings().local.llm_hf_model_file,
cache_dir=models_cache_path,
local_dir=models_path,
)
diff --git a/settings-test.yaml b/settings-test.yaml
index 965a0efe..5f7a190b 100644
--- a/settings-test.yaml
+++ b/settings-test.yaml
@@ -5,8 +5,12 @@ server:
# Dummy secrets used for tests
secret: "foo bar; dummy secret"
+
data:
local_data_folder: local_data/tests
llm:
- mode: mock
\ No newline at end of file
+ mode: mock
+
+ui:
+ enabled: false
\ No newline at end of file
diff --git a/tests/fixtures/fast_api_test_client.py b/tests/fixtures/fast_api_test_client.py
index b91dfec0..77d6037c 100644
--- a/tests/fixtures/fast_api_test_client.py
+++ b/tests/fixtures/fast_api_test_client.py
@@ -1,15 +1,14 @@
import pytest
-from fastapi import FastAPI
from fastapi.testclient import TestClient
-from private_gpt.main import app
+from private_gpt.launcher import create_app
+from tests.fixtures.mock_injector import MockInjector
@pytest.fixture()
-def current_test_app() -> FastAPI:
- return app
+def test_client(request: pytest.FixtureRequest, injector: MockInjector) -> TestClient:
+ if request is not None and hasattr(request, "param"):
+ injector.bind_settings(request.param or {})
-
-@pytest.fixture()
-def test_client() -> TestClient:
- return TestClient(app)
+ app_under_test = create_app(injector.test_injector)
+ return TestClient(app_under_test)
diff --git a/tests/fixtures/mock_injector.py b/tests/fixtures/mock_injector.py
index 5a74358f..5769b33d 100644
--- a/tests/fixtures/mock_injector.py
+++ b/tests/fixtures/mock_injector.py
@@ -1,10 +1,13 @@
from collections.abc import Callable
+from typing import Any
from unittest.mock import MagicMock
import pytest
from injector import Provider, ScopeDecorator, singleton
from private_gpt.di import create_application_injector
+from private_gpt.settings.settings import Settings, unsafe_settings
+from private_gpt.settings.settings_loader import merge_settings
from private_gpt.utils.typing import T
@@ -24,6 +27,12 @@ class MockInjector:
self.test_injector.binder.bind(interface, to=mock, scope=scope)
return mock # type: ignore
+ def bind_settings(self, settings: dict[str, Any]) -> Settings:
+ merged = merge_settings([unsafe_settings, settings])
+ new_settings = Settings(**merged)
+ self.test_injector.binder.bind(Settings, new_settings)
+ return new_settings
+
def get(self, interface: type[T]) -> T:
return self.test_injector.get(interface)
diff --git a/tests/server/utils/test_simple_auth.py b/tests/server/utils/test_simple_auth.py
index 6c304a57..0ef3614c 100644
--- a/tests/server/utils/test_simple_auth.py
+++ b/tests/server/utils/test_simple_auth.py
@@ -8,7 +8,7 @@ NOTE: We are not testing the switch based on the config in
from typing import Annotated
import pytest
-from fastapi import Depends, FastAPI
+from fastapi import Depends
from fastapi.testclient import TestClient
from private_gpt.server.utils.auth import (
@@ -29,15 +29,16 @@ def _copy_simple_authenticated(
@pytest.fixture(autouse=True)
-def _patch_authenticated_dependency(current_test_app: FastAPI):
+def _patch_authenticated_dependency(test_client: TestClient):
# Patch the server to use simple authentication
- current_test_app.dependency_overrides[authenticated] = _copy_simple_authenticated
+
+ test_client.app.dependency_overrides[authenticated] = _copy_simple_authenticated
# Call the actual test
yield
# Remove the patch for other tests
- current_test_app.dependency_overrides = {}
+ test_client.app.dependency_overrides = {}
def test_default_auth_working_when_enabled_401(test_client: TestClient) -> None:
@@ -50,6 +51,6 @@ def test_default_auth_working_when_enabled_200(test_client: TestClient) -> None:
assert response_fail.status_code == 401
response_success = test_client.get(
- "/v1/ingest/list", headers={"Authorization": settings.server.auth.secret}
+ "/v1/ingest/list", headers={"Authorization": settings().server.auth.secret}
)
assert response_success.status_code == 200
diff --git a/tests/settings/test_settings.py b/tests/settings/test_settings.py
index 3178967a..f10bdd81 100644
--- a/tests/settings/test_settings.py
+++ b/tests/settings/test_settings.py
@@ -1,5 +1,12 @@
-from private_gpt.settings.settings import settings
+from private_gpt.settings.settings import Settings, settings
+from tests.fixtures.mock_injector import MockInjector
def test_settings_are_loaded_and_merged() -> None:
- assert settings.server.env_name == "test"
+ assert settings().server.env_name == "test"
+
+
+def test_settings_can_be_overriden(injector: MockInjector) -> None:
+ injector.bind_settings({"server": {"env_name": "overriden"}})
+ mocked_settings = injector.get(Settings)
+ assert mocked_settings.server.env_name == "overriden"
diff --git a/tests/ui/test_ui.py b/tests/ui/test_ui.py
new file mode 100644
index 00000000..4f4361b0
--- /dev/null
+++ b/tests/ui/test_ui.py
@@ -0,0 +1,10 @@
+import pytest
+from fastapi.testclient import TestClient
+
+
+@pytest.mark.parametrize(
+ "test_client", [{"ui": {"enabled": True, "path": "/ui"}}], indirect=True
+)
+def test_ui_starts_in_the_given_endpoint(test_client: TestClient) -> None:
+ response = test_client.get("/ui")
+ assert response.status_code == 200