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Merge branch 'features/include-full-file-in-convo-with-filter' of github.com:khoj-ai/khoj into features/include-full-file-in-convo-with-filter

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This commit is contained in:
sabaimran 2024-11-11 09:34:08 -08:00
commit 47937d5148
4 changed files with 53 additions and 74 deletions
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4
src/interface/web/app/components/chatInputArea/chatInputArea.tsx
View file

@ -257,9 +257,6 @@ export const ChatInputArea = forwardRef<HTMLTextAreaElement, ChatInputProps>((pr
setConvertedAttachedFiles(data);
});
const totalSize = Array.from(files).reduce((acc, file) => acc + file.size, 0);
const totalSizeInMB = totalSize / (1024 * 1024);
// Set focus to the input for user message after uploading files
chatInputRef?.current?.focus();
}
@ -612,6 +609,7 @@ export const ChatInputArea = forwardRef<HTMLTextAreaElement, ChatInputProps>((pr
>
<input
type="file"
accept=".pdf,.doc,.docx,.txt,.md,.org,.jpg,.jpeg,.png,.webp"
multiple={true}
ref={fileInputRef}
onChange={handleFileChange}

28
src/khoj/processor/content/docx/docx_to_entries.py
View file

@ -1,7 +1,5 @@
import logging
import os
from datetime import datetime
from random import randint
import tempfile
from typing import Dict, List, Tuple
from langchain_community.document_loaders import Docx2txtLoader
@ -94,26 +92,20 @@ class DocxToEntries(TextToEntries):
def extract_text(docx_file):
"""Extract text from specified DOCX file"""
try:
timestamp_now = datetime.utcnow().timestamp()
random_suffix = randint(0, 1000)
tmp_file = f"tmp_docx_file_{timestamp_now}_{random_suffix}.docx"
docx_entry_by_pages = []
with open(tmp_file, "wb") as f:
bytes_content = docx_file
f.write(bytes_content)
# Create temp file with .docx extension that gets auto-deleted
with tempfile.NamedTemporaryFile(suffix=".docx", delete=True) as tmp:
tmp.write(docx_file)
tmp.flush() # Ensure all data is written
# Load the content using Docx2txtLoader
loader = Docx2txtLoader(tmp_file)
docx_entries_per_file = loader.load()
# Convert the loaded entries into the desired format
docx_entry_by_pages = [page.page_content for page in docx_entries_per_file]
# Load the content using Docx2txtLoader
loader = Docx2txtLoader(tmp.name)
docx_entries_per_file = loader.load()
# Convert the loaded entries into the desired format
docx_entry_by_pages = [page.page_content for page in docx_entries_per_file]
except Exception as e:
logger.warning(f"Unable to extract text from file: {docx_file}")
logger.warning(e, exc_info=True)
finally:
if os.path.exists(f"{tmp_file}"):
os.remove(f"{tmp_file}")
return docx_entry_by_pages

37
src/khoj/processor/content/pdf/pdf_to_entries.py
View file

@ -1,14 +1,10 @@
import base64
import logging
import os
from datetime import datetime
from random import randint
import tempfile
from io import BytesIO
from typing import Dict, List, Tuple
from langchain_community.document_loaders import PyMuPDFLoader
# importing FileObjectAdapter so that we can add new files and debug file object db.
# from khoj.database.adapters import FileObjectAdapters
from khoj.database.models import Entry as DbEntry
from khoj.database.models import KhojUser
from khoj.processor.content.text_to_entries import TextToEntries
@ -97,26 +93,19 @@ class PdfToEntries(TextToEntries):
def extract_text(pdf_file):
"""Extract text from specified PDF files"""
try:
# Write the PDF file to a temporary file, as it is stored in byte format in the pdf_file object and the PDF Loader expects a file path
timestamp_now = datetime.utcnow().timestamp()
random_suffix = randint(0, 1000)
tmp_file = f"tmp_pdf_file_{timestamp_now}_{random_suffix}.pdf"
pdf_entry_by_pages = []
with open(f"{tmp_file}", "wb") as f:
f.write(pdf_file)
try:
loader = PyMuPDFLoader(f"{tmp_file}", extract_images=False)
pdf_entry_by_pages = [page.page_content for page in loader.load()]
except ImportError:
loader = PyMuPDFLoader(f"{tmp_file}")
pdf_entry_by_pages = [
page.page_content for page in loader.load()
] # page_content items list for a given pdf.
# Create temp file with .pdf extension that gets auto-deleted
with tempfile.NamedTemporaryFile(suffix=".pdf", delete=True) as tmpf:
tmpf.write(pdf_file)
tmpf.flush() # Ensure all data is written
# Load the content using PyMuPDFLoader
loader = PyMuPDFLoader(tmpf.name, extract_images=True)
pdf_entries_per_file = loader.load()
# Convert the loaded entries into the desired format
pdf_entry_by_pages = [page.page_content for page in pdf_entries_per_file]
except Exception as e:
logger.warning(f"Unable to process file: {pdf_file}. This file will not be indexed.")
logger.warning(e, exc_info=True)
finally:
if os.path.exists(f"{tmp_file}"):
os.remove(f"{tmp_file}")
return pdf_entry_by_pages

58
src/khoj/processor/conversation/utils.py
View file

@ -140,6 +140,35 @@ def construct_iteration_history(
return previous_iterations_history
def construct_chat_history(conversation_history: dict, n: int = 4, agent_name="AI") -> str:
chat_history = ""
for chat in conversation_history.get("chat", [])[-n:]:
if chat["by"] == "khoj" and chat["intent"].get("type") in ["remember", "reminder", "summarize"]:
chat_history += f"User: {chat['intent']['query']}\n"
if chat["intent"].get("inferred-queries"):
chat_history += f'{agent_name}: {{"queries": {chat["intent"].get("inferred-queries")}}}\n'
chat_history += f"{agent_name}: {chat['message']}\n\n"
elif chat["by"] == "khoj" and ("text-to-image" in chat["intent"].get("type")):
chat_history += f"User: {chat['intent']['query']}\n"
chat_history += f"{agent_name}: [generated image redacted for space]\n"
elif chat["by"] == "khoj" and ("excalidraw" in chat["intent"].get("type")):
chat_history += f"User: {chat['intent']['query']}\n"
chat_history += f"{agent_name}: {chat['intent']['inferred-queries'][0]}\n"
elif chat["by"] == "you":
raw_attached_files = chat.get("attachedFiles")
if raw_attached_files:
attached_files: Dict[str, str] = {}
for file in raw_attached_files:
attached_files[file["name"]] = file["content"]
attached_file_context = gather_raw_attached_files(attached_files)
chat_history += f"User: {attached_file_context}\n"
return chat_history
def construct_tool_chat_history(
previous_iterations: List[InformationCollectionIteration], tool: ConversationCommand = None
) -> Dict[str, list]:
@ -540,35 +569,6 @@ def get_image_from_url(image_url: str, type="pil"):
return ImageWithType(content=None, type=None)
def construct_chat_history(conversation_history: dict, n: int = 4, agent_name="AI") -> str:
chat_history = ""
for chat in conversation_history.get("chat", [])[-n:]:
if chat["by"] == "khoj" and chat["intent"].get("type") in ["remember", "reminder", "summarize"]:
chat_history += f"User: {chat['intent']['query']}\n"
if chat["intent"].get("inferred-queries"):
chat_history += f'{agent_name}: {{"queries": {chat["intent"].get("inferred-queries")}}}\n'
chat_history += f"{agent_name}: {chat['message']}\n\n"
elif chat["by"] == "khoj" and ("text-to-image" in chat["intent"].get("type")):
chat_history += f"User: {chat['intent']['query']}\n"
chat_history += f"{agent_name}: [generated image redacted for space]\n"
elif chat["by"] == "khoj" and ("excalidraw" in chat["intent"].get("type")):
chat_history += f"User: {chat['intent']['query']}\n"
chat_history += f"{agent_name}: {chat['intent']['inferred-queries'][0]}\n"
elif chat["by"] == "you":
raw_attached_files = chat.get("attachedFiles")
if raw_attached_files:
attached_files: Dict[str, str] = {}
for file in raw_attached_files:
attached_files[file["name"]] = file["content"]
attached_file_context = gather_raw_attached_files(attached_files)
chat_history += f"User: {attached_file_context}\n"
return chat_history
def commit_conversation_trace(
session: list[ChatMessage],
response: str | list[dict],