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The Deep Research Agent automates comprehensive research using OpenAI or Gemini Deep Research APIs with real-time streaming, web search, and structured citations.

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Quick Start

1

Install Package

pip install praisonaiagents
2

Set API Key

# For OpenAI
export OPENAI_API_KEY=your_api_key_here

# For Gemini
export GEMINI_API_KEY=your_api_key_here
3

Create Script

from praisonaiagents import DeepResearchAgent

agent = DeepResearchAgent(
    model="o4-mini-deep-research",
    verbose=True
)

result = agent.research("What are the latest AI trends in 2025?")
print(result.report)

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OpenAI Deep Research

from praisonaiagents import DeepResearchAgent

agent = DeepResearchAgent(
    model="o4-mini-deep-research",  # or "o3-deep-research"
    verbose=True
)

result = agent.research("What are the latest AI trends?")
print(result.report)
print(f"Citations: {len(result.citations)}")

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Gemini Deep Research

from praisonaiagents import DeepResearchAgent

agent = DeepResearchAgent(
    model="deep-research-pro",
    verbose=True
)

result = agent.research("Research quantum computing advances")
print(result.report)

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Features

Multi-Provider

Supports OpenAI, Gemini, and LiteLLM providers.

Real-time Streaming

See reasoning summaries and web searches as they happen.

Structured Citations

Get citations with titles and URLs.

Auto Detection

Provider automatically detected from model name.

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Streaming Output

Streaming is enabled by default. You will see:
  • 💭 Reasoning summaries
  • 🔎 Web search queries
  • Final report text
# Streaming is ON by default
result = agent.research("Research topic")

# Disable streaming
result = agent.research("Research topic", stream=False)

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Response Structure

result.report           # Full research report
result.citations        # List of citations with URLs
result.web_searches     # Web searches performed
result.reasoning_steps  # Reasoning steps captured
result.interaction_id   # Session ID (for Gemini follow-ups)

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Available Models

ProviderModels
OpenAIo3-deep-research, o4-mini-deep-research
Geminideep-research-pro

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Configuration Options

agent = DeepResearchAgent(
    name="Researcher",
    model="o4-mini-deep-research",
    instructions="Focus on data-rich insights",
    verbose=True,
    poll_interval=5,      # Gemini polling interval (seconds)
    max_wait_time=3600    # Max research time (seconds)
)

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With Custom Instructions

from praisonaiagents import DeepResearchAgent

agent = DeepResearchAgent(
    model="o4-mini-deep-research",
    instructions="""
    You are a professional researcher. Focus on:
    - Data-rich insights with specific figures
    - Reliable sources and citations
    - Clear, structured responses
    """,
    verbose=True
)

result = agent.research("Economic impact of AI on healthcare")

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Accessing Citations

result = agent.research("Research topic")

for citation in result.citations:
    print(f"Title: {citation.title}")
    print(f"URL: {citation.url}")
    print(f"Snippet: {citation.snippet}")
    print("---")

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Next Steps

  • Learn about Research Agent for custom research workflows
  • Explore RAG for document-based research
  • Check out Memory for persistent research context