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Refactor UI state management (#1191) 

* Added logs at generation of the UI, and generate the UI in an object
* Make ingest script more verbose in case of an error at ingestion time
* Removed the explicit state in the UI containing ingested files
* Make script of ingestion a bit more verbose by displaying stack traces
* Change the browser tab title of privateGPT ui to `My Private GPT`
This commit is contained in:
lopagela 2023-11-10 10:42:43 +01:00 committed by GitHub
parent 55e626eac7
commit a666fd5b73
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 170 additions and 137 deletions
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8
private_gpt/main.py
View File

@ -1,4 +1,5 @@
"""FastAPI app creation, logger configuration and main API routes."""
import logging
from typing import Any
import llama_index
@ -14,6 +15,8 @@ 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__)
# Add LlamaIndex simple observability
llama_index.set_global_handler("simple")
@ -103,6 +106,7 @@ app.include_router(health_router)
if settings.ui.enabled:
from private_gpt.ui.ui import mount_in_app
logger.debug("Importing the UI module")
from private_gpt.ui.ui import PrivateGptUi
mount_in_app(app)
PrivateGptUi().mount_in_app(app)

97
private_gpt/ui/ui.py
View File

@ -1,4 +1,6 @@
"""This file should be imported only and only if you want to run the UI locally."""
import itertools
import logging
from collections.abc import Iterable
from pathlib import Path
from typing import Any, TextIO
@ -15,12 +17,22 @@ from private_gpt.server.ingest.ingest_service import IngestService
from private_gpt.settings.settings import settings
from private_gpt.ui.images import logo_svg
ingest_service = root_injector.get(IngestService)
chat_service = root_injector.get(ChatService)
chunks_service = root_injector.get(ChunksService)
logger = logging.getLogger(__name__)
def _chat(message: str, history: list[list[str]], mode: str, *_: Any) -> Any:
UI_TAB_TITLE = "My Private GPT"
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)
# Cache the UI blocks
self._ui_block = None
def _chat(self, message: str, history: list[list[str]], mode: str, *_: Any) -> Any:
def yield_deltas(stream: Iterable[ChatResponse | str]) -> Iterable[str]:
full_response: str = ""
for delta in stream:
@ -36,7 +48,9 @@ def _chat(message: str, history: list[list[str]], mode: str, *_: Any) -> Any:
*[
[
ChatMessage(content=interaction[0], role=MessageRole.USER),
ChatMessage(content=interaction[1], role=MessageRole.ASSISTANT),
ChatMessage(
content=interaction[1], role=MessageRole.ASSISTANT
),
]
for interaction in history
]
@ -50,21 +64,21 @@ def _chat(message: str, history: list[list[str]], mode: str, *_: Any) -> Any:
all_messages = [*build_history(), new_message]
match mode:
case "Query Docs":
query_stream = chat_service.stream_chat(
query_stream = self._chat_service.stream_chat(
messages=all_messages,
use_context=True,
)
yield from yield_deltas(query_stream)
case "LLM Chat":
llm_stream = chat_service.stream_chat(
llm_stream = self._chat_service.stream_chat(
messages=all_messages,
use_context=False,
)
yield from yield_deltas(llm_stream)
case "Search in Docs":
response = chunks_service.retrieve_relevant(
response = self._chunks_service.retrieve_relevant(
text=message, limit=4, prev_next_chunks=0
)
@ -75,29 +89,26 @@ def _chat(message: str, history: list[list[str]], mode: str, *_: Any) -> Any:
for index, chunk in enumerate(response, start=1)
)
def _list_ingested_files() -> list[str]:
def _list_ingested_files(self) -> list[list[str]]:
files = set()
for ingested_document in ingest_service.list_ingested():
if ingested_document.doc_metadata is not None:
files.add(
ingested_document.doc_metadata.get("file_name") or "[FILE NAME MISSING]"
for ingested_document in self._ingest_service.list_ingested():
if ingested_document.doc_metadata is None:
# Skipping documents without metadata
continue
file_name = ingested_document.doc_metadata.get(
"file_name", "[FILE NAME MISSING]"
)
return list(files)
files.add(file_name)
return [[row] for row in files]
# Global state
_uploaded_file_list = [[row] for row in _list_ingested_files()]
def _upload_file(file: TextIO) -> list[list[str]]:
def _upload_file(self, file: TextIO) -> None:
path = Path(file.name)
ingest_service.ingest(file_name=path.name, file_data=path)
_uploaded_file_list.append([path.name])
return _uploaded_file_list
self._ingest_service.ingest(file_name=path.name, file_data=path)
with gr.Blocks(
def _build_ui_blocks(self) -> gr.Blocks:
logger.debug("Creating the UI blocks")
with gr.Blocks(
title=UI_TAB_TITLE,
theme=gr.themes.Soft(primary_hue=slate),
css=".logo { "
"display:flex;"
@ -109,7 +120,7 @@ with gr.Blocks(
"align-items: center;"
"}"
".logo img { height: 25% }",
) as blocks:
) as blocks:
with gr.Row():
gr.HTML(f"<div class='logo'/><img src={logo_svg} alt=PrivateGPT></div")
@ -127,19 +138,25 @@ with gr.Blocks(
size="sm",
)
ingested_dataset = gr.List(
_uploaded_file_list,
self._list_ingested_files,
headers=["File name"],
label="Ingested Files",
interactive=False,
render=False, # Rendered under the button
)
upload_button.upload(
_upload_file, inputs=upload_button, outputs=ingested_dataset
self._upload_file,
inputs=upload_button,
outputs=ingested_dataset,
)
ingested_dataset.change(
self._list_ingested_files,
outputs=ingested_dataset,
)
ingested_dataset.render()
with gr.Column(scale=7):
chatbot = gr.ChatInterface(
_chat,
_ = gr.ChatInterface(
self._chat,
chatbot=gr.Chatbot(
label=f"LLM: {settings.llm.mode}",
show_copy_button=True,
@ -153,13 +170,23 @@ with gr.Blocks(
),
additional_inputs=[mode, upload_button],
)
return blocks
def get_ui_blocks(self) -> gr.Blocks:
if self._ui_block is None:
self._ui_block = self._build_ui_blocks()
return self._ui_block
def mount_in_app(app: FastAPI) -> None:
def mount_in_app(self, app: FastAPI) -> None:
blocks = self.get_ui_blocks()
blocks.queue()
gr.mount_gradio_app(app, blocks, path=settings.ui.path)
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)
if __name__ == "__main__":
blocks.queue()
blocks.launch(debug=False, show_api=False)
ui = PrivateGptUi()
_blocks = ui.get_ui_blocks()
_blocks.queue()
_blocks.launch(debug=False, show_api=False)

6
scripts/ingest_folder.py
View File

@ -69,8 +69,10 @@ def _do_ingest(changed_path: Path) -> None:
logger.info(f"Started ingesting {changed_path}")
ingest_service.ingest(changed_path.name, changed_path)
logger.info(f"Completed ingesting {changed_path}")
except Exception as e:
logger.error(f"Failed to ingest document: {changed_path}. Error: {e}")
except Exception:
logger.exception(
f"Failed to ingest document: {changed_path}, find the exception attached"
)
path = Path(args.folder)