Migration Guide: LDR v0.x to v1.0

Migration Guide: LDR v0.x to v1.0

Overview

Local Deep Research v1.0 introduces significant security and architectural improvements:

• User Authentication: All access now requires authentication
• Per-User Encrypted Databases: Each user has their own encrypted SQLCipher database
• Settings Snapshots: Thread-safe settings management for concurrent operations
• New API Structure: Reorganized endpoints under blueprint prefixes

Breaking Changes

1. Authentication Required

v0.x: Open access, no authentication

# Direct API access
from local_deep_research.api import quick_summary
result = quick_summary("query")

v1.0: Authentication required

from local_deep_research.api import quick_summary
from local_deep_research.settings import CachedSettingsManager
from local_deep_research.database.session_context import get_user_db_session

# Must authenticate first
with get_user_db_session(username="user", password="pass") as session:
    settings_manager = CachedSettingsManager(session, "user")
    settings_snapshot = settings_manager.get_all_settings()

    result = quick_summary(
        "query",
        settings_snapshot=settings_snapshot  # Required parameter
    )

2. HTTP API Changes

Endpoint Structure

• v0.x: /api/v1/quick_summary
• v1.0: /api/start_research

Authentication Flow

import requests

# v1.0 requires session-based authentication
session = requests.Session()

# 1. Login
session.post(
    "http://localhost:5000/auth/login",
    json={"username": "user", "password": "pass"}
)

# 2. Get CSRF token for state-changing operations
csrf = session.get("http://localhost:5000/auth/csrf-token").json()["csrf_token"]

# 3. Make API requests with CSRF token
response = session.post(
    "http://localhost:5000/api/start_research",
    json={"query": "test"},
    headers={"X-CSRF-Token": csrf}
)

3. Database Changes

v0.x

• Single shared database: ldr.db
• No encryption
• Direct database access from any thread

v1.0

• Per-user databases: encrypted_databases/{username}.db
• SQLCipher encryption with user passwords
• Thread-local session management
• In-memory queue tracking (no more service_db)

4. Settings Management

v0.x

# Direct settings access
from local_deep_research.config import get_db_setting
value = get_db_setting("llm.provider")

v1.0

# Settings require context
from local_deep_research.settings import CachedSettingsManager

# Within authenticated session
settings_manager = CachedSettingsManager(session, username)
value = settings_manager.get_setting("llm.provider")

# Or use settings snapshot for thread safety
settings_snapshot = settings_manager.get_all_settings()

Migration Steps

1. Update Dependencies

pip install --upgrade local-deep-research

2. Create User Accounts

Users must create accounts through the web interface:

1. Start the server: python -m local_deep_research.web.app
2. Open http://localhost:5000
3. Click "Register" and create an account
4. Configure LLM providers and API keys in Settings

3. Update Programmatic Code

Before (v0.x):

from local_deep_research.api import (
    quick_summary,
    detailed_research,
    generate_report
)

# Direct usage
result = quick_summary("What is AI?")

After (v1.0):

from local_deep_research.api import quick_summary
from local_deep_research.settings import CachedSettingsManager
from local_deep_research.database.session_context import get_user_db_session

def run_research(username, password, query):
    with get_user_db_session(username, password) as session:
        settings_manager = CachedSettingsManager(session, username)
        settings_snapshot = settings_manager.get_all_settings()

        return quick_summary(
            query=query,
            settings_snapshot=settings_snapshot,
            # Other parameters remain the same
            iterations=2,
            questions_per_iteration=3
        )

4. Update HTTP API Calls

Create a wrapper for authenticated requests:

class LDRClient:
    def __init__(self, base_url="http://localhost:5000"):
        self.base_url = base_url
        self.session = requests.Session()
        self.csrf_token = None

    def login(self, username, password):
        response = self.session.post(
            f"{self.base_url}/auth/login",
            json={"username": username, "password": password}
        )
        if response.status_code == 200:
            self.csrf_token = self.session.get(
                f"{self.base_url}/auth/csrf-token"
            ).json()["csrf_token"]
        return response

    def start_research(self, query, **kwargs):
        return self.session.post(
            f"{self.base_url}/api/start_research",
            json={"query": query, **kwargs},
            headers={"X-CSRF-Token": self.csrf_token}
        )

# Usage
client = LDRClient()
client.login("user", "pass")
result = client.start_research("What is quantum computing?")

5. Update Configuration

API Keys

API keys are now stored encrypted in per-user databases. Users must:

1. Login to the web interface
2. Go to Settings
3. Re-enter API keys for LLM providers

Custom LLMs

Custom LLM registrations now require settings context:

# v1.0 custom LLM with settings support
def create_custom_llm(model_name=None, temperature=None, settings_snapshot=None):
    # Access settings from snapshot if needed
    api_key = settings_snapshot.get("llm.custom.api_key", {}).get("value")
    return CustomLLM(api_key=api_key, model=model_name, temperature=temperature)

Common Issues and Solutions

Issue: "No settings context available in thread"

Solution: Pass settings_snapshot parameter to all API calls

Issue: "Encrypted database requires password"

Solution: Ensure you're using get_user_db_session() with credentials

Issue: CSRF token errors

Solution: Get fresh CSRF token before state-changing requests

Issue: Old endpoints return 404

Solution: Update to new endpoint structure (see mapping above)

Issue: Rate limiting not working

Solution: Rate limits are now per-user; ensure proper authentication

Backward Compatibility

For temporary backward compatibility, you can:

1. Set environment variable: LDR_USE_SHARED_DB=1 (not recommended)
2. Create a compatibility wrapper for your existing code

# compatibility.py
import os
os.environ["LDR_USE_SHARED_DB"] = "1"  # Use at your own risk

def quick_summary_compat(query, **kwargs):
    # Minimal compatibility wrapper
    # Note: This bypasses security features!
    from local_deep_research.api import quick_summary
    return quick_summary(query, settings_snapshot={}, **kwargs)

⚠️ Warning: Compatibility mode bypasses security features and is not recommended for production use.

Benefits of v1.0

1. Security: Encrypted databases protect sensitive API keys and research data
2. Multi-User: Multiple users can work simultaneously without conflicts
3. Performance: Cached settings and thread-local sessions improve speed
4. Reliability: Thread-safe operations prevent race conditions
5. Privacy: User data is completely isolated

Getting Help

• Check the API Quick Start Guide
• See examples/api_usage for updated examples
• Join our Discord for migration support
• Report issues on GitHub