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Add Ollama JSON schema for categorization

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Keannu Christian Bernasol 2024-12-18 17:05:44 +08:00
parent 844113d44f
commit b24646d42d
5 changed files with 88 additions and 40 deletions
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64
docmanager_backend/config/management/commands/start_watcher.py
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@ -1,4 +1,3 @@
from ollama import ChatResponse
import base64
import httpx
from django.core.management.base import BaseCommand
@ -18,6 +17,9 @@ from django.core.files import File
import logging
import time
from ollama import Client
from pydantic import BaseModel
from typing import Optional
import json
class PDFHandler(FileSystemEventHandler):
@ -83,55 +85,52 @@ class PDFHandler(FileSystemEventHandler):
# Perform OCR
text = pytesseract.image_to_string(img).strip()
# Get document category
# Try to pass image to the Ollama image recognition API first
try:
class DocumentCategory(BaseModel):
category: str = "other"
explanation: Optional[str] = None
client = Client(
host=get_secret("OLLAMA_URL"),
auth=httpx.BasicAuth(
username=get_secret("OLLAMA_USERNAME"), password=get_secret("OLLAMA_PASSWORD")) if get_secret("OLLAMA_USE_AUTH") else None
username=get_secret("OLLAMA_USERNAME"), password=get_secret("OLLAMA_PASSWORD")) if get_secret("OLLAMA_USE_AUTH") else None,
)
encoded_image = base64.b64encode(
img_buffer.getvalue()).decode()
attempts = 0
while True:
if attempts >= 3:
raise Exception(
"Unable to categorize using Ollama API")
attempts += 1
possible_categories = set((Document.objects.all().values_list(
"document_type", flat=True), "Documented Procedures Manual", "Form", "Special Order"))
prompt = f"""
Read the text from the image and provide a category. Return as JSON.
content = f"""
Read the text from the image and provide a category.
Possible categories are: Announcement, Manual, Form
Respond only with the category. No explanations are necessary.
Possible categories are: {possible_categories}
"""
response = client.chat(
model=get_secret("OLLAMA_MODEL"),
messages=[
{"role": "user",
"content": prompt,
"images": [encoded_image]},
],
format=DocumentCategory.model_json_schema(),
options={
"temperature": 0
},
response: ChatResponse = client.chat(
model=get_secret("OLLAMA_MODEL"),
messages=[
{"role": "user", "content": content,
"images": [encoded_image]},
],
)
)
document_type = response["message"]["content"].replace(
"*", "").replace(".", "")
# A few safety checks if the model does not follow through with output instructions
if len(document_type) > 16:
self.logger.warning(
f"Ollama API gave incorrect document category: {response['message']['content']}. Retrying...")
break
DocumentCategory.model_validate_json(
response.message.content)
result = json.loads(response.message.content)
document_type = result.get("category")
# If that fails, just use regular OCR read the title as a dirty fix/fallback
except Exception as e:
self.logger.warning(f"Error! {e}")
self.logger.warning(
"Ollama OCR offloading failed. Falling back to default OCR")
"Ollama OCR offload failed. Falling back to default OCR")
lines = text.split("\n")
for line in lines:
@ -158,7 +157,8 @@ class PDFHandler(FileSystemEventHandler):
DOCUMENT.file.save(
name=filename, content=File(open(file_path, "rb")))
self.logger.info(
f"Document '{filename}' created successfully with type '{document_type}'."
f"Document '{filename}' created successfully with type '{
document_type}'."
)
else: