deep-probe 0.1.3

Research anything, deeply, in one line of code. A Python library wrapping Google Gemini Deep Research API.

Deep Probe

Research anything, deeply, in one line of code.

A Python library that wraps Google Gemini Deep Research API with automatic reconnection and structured output.

Features

• Simple API: One line of code to run deep research
• Auto-reconnection: Handles network failures with exponential backoff
• Structured output: Pydantic models for type-safe results
• Sync & Async: Both synchronous and asynchronous interfaces
• Streaming: Real-time output with thought summaries
• CLI tool: Rich-powered command-line interface
• Resume support: Resume interrupted research operations

Installation

pip install deep-probe

Quick Start

Python API

from deep_probe import DeepProbe

# Initialize (uses GEMINI_API_KEY environment variable)
probe = DeepProbe()

# Run research
result = probe.research("What is quantum computing?")

# Access the report
print(result.report)

# Save to file
result.save("report.md")

Async API

import asyncio
from deep_probe import DeepProbe

async def main():
    probe = DeepProbe()
    result = await probe.research_async("AI trends 2024")
    print(result.report)

asyncio.run(main())

Streaming API

from deep_probe import DeepProbe

probe = DeepProbe()

def on_text(text: str):
    print(text, end="", flush=True)

def on_thought(thought: str):
    print(f"\n💭 {thought}\n")

result = probe.research_stream(
    "What is the future of AI?",
    on_text=on_text,
    on_thought=on_thought,
)

CLI

The CLI uses a research subcommand. Examples:

# Basic usage
deep-probe research "What is quantum computing?"

# Save to file
deep-probe research "AI trends 2024" --save report.md

# Show thinking process
deep-probe research "Climate change effects" --verbose

# Stream output in real-time
deep-probe research "Research topic" --stream

# Quiet mode (only output report)
deep-probe research "Test topic" --quiet

# Resume previous research
deep-probe research --resume "interaction-id-here"

Configuration

Set your Google Gemini API key:

export GEMINI_API_KEY='your-api-key'

Or create a .env file:

GEMINI_API_KEY=your-api-key

Get your API key from Google AI Studio.

API Reference

DeepProbe

Main client for running deep research.

from deep_probe import DeepProbe, ResearchResult

# Initialize with optional settings
probe = DeepProbe(
    api_key="optional-api-key",  # Or use GEMINI_API_KEY env var
    thinking_summaries=True,      # Enable thinking summaries output
)

# Synchronous research
result: ResearchResult = probe.research("topic")

# Asynchronous research
result: ResearchResult = await probe.research_async("topic")

# Streaming research with callbacks
result: ResearchResult = probe.research_stream(
    "topic",
    on_text=lambda text: print(text, end=""),
    on_thought=lambda thought: print(f"💭 {thought}"),
)

# Resume previous research
result: ResearchResult = probe.resume("interaction-id")
result: ResearchResult = await probe.resume_async("interaction-id")

ResearchResult

result.report          # str - The research report in markdown
result.sources         # list[Citation] - Sources cited
result.thoughts        # list[Thought] - Research process/thinking summaries
result.cost_usage      # TokenUsage - Token statistics
result.interaction_id  # str - Unique identifier for resume
result.status          # ResearchStatus - Final status

result.save("file.md")  # Save to file

Exceptions

from deep_probe.exceptions import (
    DeepProbeError,      # Base exception
    ProbeAuthError,      # API key issues
    ProbeNetworkError,   # Connection failures (includes interaction_id)
    ProbeTimeoutError,   # Time limit exceeded
    ProbeAPIError,       # Server-side errors
    ProbeCancelledError, # User cancellation
)

Auto-Reconnection

DeepProbe handles network failures automatically:

Scenario	Action	Max Retries	Delay
Network disconnect	Auto-reconnect	3	2s → 4s → 8s
API rate limit	Wait and retry	3	60s
Auth error	No retry	0	N/A

All network errors include interaction_id for resuming interrupted research.

Google Gemini Deep Research

This library uses the deep-research-pro-preview-12-2025 agent from Google's Gemini API. Key characteristics:

• Max duration: 60 minutes per research task
• Sources: Uses Google Search and URL context tools
• Pricing: ~$2-5 per task (estimates from Google)
• Output: Markdown-formatted research reports

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run linting
ruff check .

# Run type checking
mypy src/

License

Apache License 2.0

Links

• GitHub: https://github.com/liu-kaining/DeepProbe
• Author: liukaining