Add front-end Electron application for Khoj local file syncing (#473)

* Initial version - setup a file-push architecture for generating embeddings with Khoj
* Use state.host and state.port for configuring the URL for the indexer
* Fix parsing of PDF files
* Read markdown files from streamed data and update unit tests
* On application startup, load in embeddings from configurations files, rather than regenerating the corpus based on file system
* Init: refactor indexer/batch endpoint to support a generic file ingestion format
* Add features to better support indexing from files sent by the desktop client
* Initial commit with Electron application
- Adds electron app
* Add import for pymupdf, remove import for pypdf
* Allow user to configure khoj host URL
* Remove search type configuration from index.html
* Use v1 path for current indexer routes
This commit is contained in:
sabaimran
2023-09-06 12:04:18 -07:00
committed by GitHub
parent 205dc90746
commit 76562f4250
54 changed files with 20132 additions and 82 deletions

View File

@@ -66,7 +66,7 @@ def test_index_batch(client):
headers = {"x-api-key": "secret"}
# Act
response = client.post("/indexer/batch", json=request_body, headers=headers)
response = client.post("/v1/indexer/batch", json=request_body, headers=headers)
# Assert
assert response.status_code == 200
@@ -81,7 +81,7 @@ def test_regenerate_with_valid_content_type(client):
headers = {"x-api-key": "secret"}
# Act
response = client.post(f"/indexer/batch?search_type={content_type}", json=request_body, headers=headers)
response = client.post(f"/v1/indexer/batch?search_type={content_type}", json=request_body, headers=headers)
# Assert
assert response.status_code == 200, f"Returned status: {response.status_code} for content type: {content_type}"
@@ -97,7 +97,7 @@ def test_regenerate_with_github_fails_without_pat(client):
headers = {"x-api-key": "secret"}
# Act
response = client.post(f"/indexer/batch?search_type=github", json=request_body, headers=headers)
response = client.post(f"/v1/indexer/batch?search_type=github", json=request_body, headers=headers)
# Assert
assert response.status_code == 200, f"Returned status: {response.status_code} for content type: github"

View File

@@ -1,6 +1,7 @@
# Standard Packages
import json
import os
import base64
# Internal Packages
from khoj.processor.pdf.pdf_to_jsonl import PdfToJsonl
@@ -15,7 +16,7 @@ def test_single_page_pdf_to_jsonl():
# Extract Entries from specified Pdf files
# Read singlepage.pdf into memory as bytes
with open("tests/data/pdf/singlepage.pdf", "rb") as f:
pdf_bytes = f.read()
pdf_bytes = base64.b64encode(f.read()).decode("utf-8")
data = {"tests/data/pdf/singlepage.pdf": pdf_bytes}
entries, entry_to_file_map = PdfToJsonl.extract_pdf_entries(pdf_files=data)
@@ -35,7 +36,7 @@ def test_multi_page_pdf_to_jsonl():
# Act
# Extract Entries from specified Pdf files
with open("tests/data/pdf/multipage.pdf", "rb") as f:
pdf_bytes = f.read()
pdf_bytes = base64.b64encode(f.read()).decode("utf-8")
data = {"tests/data/pdf/multipage.pdf": pdf_bytes}
entries, entry_to_file_map = PdfToJsonl.extract_pdf_entries(pdf_files=data)

View File

@@ -6,18 +6,6 @@ from khoj.utils.rawconfig import TextContentConfig, ImageContentConfig
# Test
# ----------------------------------------------------------------------------------------------------
def test_input_file_or_filter_required_in_text_content_config():
# Act
with pytest.raises(ValueError):
TextContentConfig(
input_files=None,
input_filter=None,
compressed_jsonl="notes.jsonl",
embeddings_file="note_embeddings.pt",
)
# ----------------------------------------------------------------------------------------------------
def test_input_filter_or_directories_required_in_image_content_config():
# Act

View File

@@ -131,6 +131,65 @@ def test_entry_chunking_by_max_tokens(org_config_with_only_new_file: TextContent
assert len(initial_notes_model.corpus_embeddings) == 2
# ----------------------------------------------------------------------------------------------------
# @pytest.mark.skip(reason="Flaky due to compressed_jsonl file being rewritten by other tests")
def test_entry_chunking_by_max_tokens_not_full_corpus(
org_config_with_only_new_file: TextContentConfig, search_models: SearchModels
):
# Arrange
# Insert org-mode entry with size exceeding max token limit to new org file
data = {
"readme.org": """
* Khoj
/Allow natural language search on user content like notes, images using transformer based models/
All data is processed locally. User can interface with khoj app via [[./interface/emacs/khoj.el][Emacs]], API or Commandline
** Dependencies
- Python3
- [[https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links][Miniconda]]
** Install
#+begin_src shell
git clone https://github.com/khoj-ai/khoj && cd khoj
conda env create -f environment.yml
conda activate khoj
#+end_src"""
}
text_search.setup(
OrgToJsonl,
data,
org_config_with_only_new_file,
search_models.text_search.bi_encoder,
regenerate=False,
)
max_tokens = 256
new_file_to_index = Path(org_config_with_only_new_file.input_files[0])
with open(new_file_to_index, "w") as f:
f.write(f"* Entry more than {max_tokens} words\n")
for index in range(max_tokens + 1):
f.write(f"{index} ")
data = get_org_files(org_config_with_only_new_file)
# Act
# reload embeddings, entries, notes model after adding new org-mode file
initial_notes_model = text_search.setup(
OrgToJsonl,
data,
org_config_with_only_new_file,
search_models.text_search.bi_encoder,
regenerate=False,
full_corpus=False,
)
# Assert
# verify newly added org-mode entry is split by max tokens
assert len(initial_notes_model.entries) == 5
assert len(initial_notes_model.corpus_embeddings) == 5
# ----------------------------------------------------------------------------------------------------
def test_regenerate_index_with_new_entry(
content_config: ContentConfig, search_models: SearchModels, new_org_file: Path