> ## Documentation Index > Fetch the complete documentation index at: https://docs.praison.ai/llms.txt > Use this file to discover all available pages before exploring further. # Deep Research Agent > Automated research using OpenAI or Gemini Deep Research APIs with real-time streaming and citations. ```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} flowchart LR In[Research Query] --> Agent[Deep Research Agent] Agent --> Search[Web Search] Search --> Reason[Reasoning] Reason --> Report[Research Report] Report --> Out[Citations + Report] style In fill:#8B0000,color:#fff style Agent fill:#2E8B57,color:#fff style Search fill:#2E8B57,color:#fff style Reason fill:#2E8B57,color:#fff style Report fill:#2E8B57,color:#fff style Out fill:#8B0000,color:#fff ``` The Deep Research Agent automates comprehensive research using OpenAI or Gemini Deep Research APIs with real-time streaming, web search, and structured citations. **Agents: 1** — Specialized agent using provider deep research APIs. ## Workflow 1. Receive research query 2. Execute web searches via provider API 3. Perform multi-step reasoning 4. Generate comprehensive report with citations ## Setup ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} pip install praisonaiagents praisonai export OPENAI_API_KEY="your-key" # or GEMINI_API_KEY ``` ## Run — Python ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} from praisonaiagents import DeepResearchAgent agent = DeepResearchAgent( model="o4-mini-deep-research", ) result = agent.research("What are the latest AI trends in 2025?") print(result.report) print(f"Citations: {len(result.citations)}") ``` ## Run — CLI ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Deep research mode praisonai research "What are the latest AI trends?" # With save option praisonai research --save "Research quantum computing advances" ``` ## Run — agents.yaml ```yaml theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} framework: praisonai topic: Deep Research roles: researcher: role: Deep Research Specialist goal: Conduct comprehensive research with citations backstory: You are an expert researcher llm: o4-mini-deep-research tasks: research: description: Research the latest AI trends in 2025 expected_output: Comprehensive report with citations ``` ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai agents.yaml ``` ## Serve API ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} from praisonaiagents import DeepResearchAgent agent = DeepResearchAgent( model="o4-mini-deep-research", ) # Note: DeepResearchAgent uses .research() method # For API serving, wrap in standard agent ``` ## OpenAI Deep Research ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} from praisonaiagents import DeepResearchAgent agent = DeepResearchAgent( model="o4-mini-deep-research", # or "o3-deep-research" ) result = agent.research("What are the latest AI trends?") print(result.report) print(f"Citations: {len(result.citations)}") ``` ## Gemini Deep Research ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} from praisonaiagents import DeepResearchAgent agent = DeepResearchAgent( model="deep-research-pro", ) result = agent.research("Research quantum computing advances") print(result.report) ``` ## Features Supports OpenAI, Gemini, and LiteLLM providers. See reasoning summaries and web searches as they happen. Get citations with titles and URLs. Provider automatically detected from model name. ## Streaming Output Streaming is enabled by default. You will see: * 💭 Reasoning summaries * 🔎 Web search queries * Final report text ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Streaming is ON by default result = agent.research("Research topic") # Disable streaming result = agent.research("Research topic", stream=False) ``` ## Response Structure ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} 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) ``` ## Available Models | Provider | Models | | -------- | ------------------------------------------- | | OpenAI | `o3-deep-research`, `o4-mini-deep-research` | | Gemini | `deep-research-pro` | ## Configuration Options ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} agent = DeepResearchAgent( name="Researcher", model="o4-mini-deep-research", instructions="Focus on data-rich insights", poll_interval=5, # Gemini polling interval (seconds) max_wait_time=3600 # Max research time (seconds) ) ``` ## With Custom Instructions ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} 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 """, ) result = agent.research("Economic impact of AI on healthcare") ``` ## Accessing Citations ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} 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("---") ``` *** ## Monitor / Verify ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai research "test query" --verbose ``` ## Cleanup ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # No cleanup needed - uses provider APIs ``` ## Features Demonstrated | Feature | Implementation | | ----------------- | -------------------------------------- | | Workflow | Multi-step reasoning with web search | | Observability | `--verbose` flag, streaming output | | Tools | Built-in web search via provider API | | Resumability | `interaction_id` for Gemini follow-ups | | Structured Output | Citations with titles and URLs | ## Next Steps * [Research Agent](/agents/research) for custom research workflows * [RAG](/features/rag) for document-based research * [Memory](/features/advanced-memory) for persistent research context