Deep Research | NeuraAI Documentation

NeuraAI’s deep research capabilities enable comprehensive analysis and investigation of complex topics. These specialized models can conduct multi-source research, synthesize information, and provide detailed analytical reports.

Overview

Deep research models are designed for tasks that require:

Comprehensive information gathering from multiple sources
Critical analysis and synthesis of data
Detailed, evidence-based conclusions
Citation of sources and supporting evidence

Basic Usage

from openai import OpenAI
client = OpenAI(
    base_url="https://api.neura-ai.app/v1",
    timeout=3600  # Research tasks may take longer
)
input_text = """
Research the economic impact of semaglutide on global healthcare systems.
Do:
- Include specific figures, trends, statistics, and measurable outcomes.
- Prioritize reliable, up-to-date sources: peer-reviewed research, health
  organizations (e.g., WHO, CDC), regulatory agencies, or pharmaceutical
  earnings reports.
- Include inline citations and return all source metadata.
Be analytical, avoid generalities, and ensure that each section supports
data-backed reasoning that could inform healthcare policy or financial modeling.
"""
response = client.responses.create(
    model="sonar-deep-research",
    input=input_text,
    tools=[
        {"type": "web_search_preview"},
        {"type": "code_interpreter", "container": {"type": "auto"}},
    ],
)
print(response.output_text)

Available Tools

Web Search

Enables the model to search for current information online:

tools=[
    {"type": "web_search_preview"}
]

Code Interpreter

Allows the model to execute code for data analysis:

tools=[
    {"type": "code_interpreter", "container": {"type": "auto"}}
]

Combined Approach

Use multiple tools for comprehensive research:

tools=[
    {"type": "web_search_preview"},
    {"type": "code_interpreter", "container": {"type": "auto"}}
]

Example Use Cases

Market Research

response = client.responses.create(
    model="sonar-deep-research",
    input="""
    Analyze the current state of the electric vehicle market in Europe.
    Include:
    - Market size and growth projections for 2024-2026
    - Leading manufacturers and their market share
    - Government policies affecting adoption
    - Infrastructure development trends
    - Consumer sentiment data
    
    Provide specific figures and cite all sources.
    """,
    tools=[{"type": "web_search_preview"}]
)

Scientific Literature Review

response = client.responses.create(
    model="sonar-deep-research",
    input="""
    Conduct a comprehensive review of recent advances in CRISPR gene editing 
    technology (2023-2024). Focus on:
    - Clinical trial results
    - New applications and methodologies
    - Ethical considerations and regulations
    - Future research directions
    
    Reference peer-reviewed publications and clinical data.
    """,
    tools=[{"type": "web_search_preview"}]
)

Competitive Analysis

response = client.responses.create(
    model="sonar-deep-research",
    input="""
    Compare the business models, pricing strategies, and market positioning 
    of the top 5 cloud infrastructure providers.
    
    Analyze:
    - Service offerings and differentiation
    - Pricing structures and total cost of ownership
    - Target customer segments
    - Recent financial performance
    - Strategic partnerships and acquisitions
    """,
    tools=[
        {"type": "web_search_preview"},
        {"type": "code_interpreter", "container": {"type": "auto"}}
    ]
)

Data-Driven Analysis

response = client.responses.create(
    model="sonar-deep-research",
    input="""
    Investigate the correlation between remote work adoption and 
    commercial real estate values in major US cities (2020-2024).
    
    Use statistical analysis to:
    - Identify trends in office space vacancy rates
    - Correlate with property values
    - Compare across different cities
    - Project future implications
    
    Include data visualizations where appropriate.
    """,
    tools=[
        {"type": "web_search_preview"},
        {"type": "code_interpreter", "container": {"type": "auto"}}
    ]
)

Best Practices

Clear Research Objectives

Define what you want to learn and what constitutes a complete answer:

input_text = """
Research Question: How has AI impacted software development productivity?
Scope:
- Time period: 2022-2024
- Focus on: Code completion tools, automated testing, and bug detection
- Metrics: Developer productivity, code quality, time savings
Required:
- Quantitative data from studies or surveys
- Case studies from companies implementing these tools
- Expert opinions from industry leaders
"""

Specify Source Quality

Guide the model toward reliable sources:

input_text = """
Research renewable energy adoption in developing nations.
Source Requirements:
- Prefer: Academic journals, international organizations (UN, World Bank), 
  government reports
- Include: Industry reports from reputable firms
- Avoid: Blog posts, opinion pieces, unverified claims
"""

Request Structure

Ask for organized, actionable output:

input_text = """
Analyze smartphone market trends in Asia.
Output Structure:
1. Executive Summary (key findings)
2. Market Size and Growth
3. Competitive Landscape
4. Consumer Preferences
5. Future Outlook
6. Sources and References
"""

Timeout Considerations

Research tasks can take significant time. Set appropriate timeouts:

client = OpenAI(
    base_url="https://api.neura-ai.app/v1",
    timeout=3600  # 1 hour for complex research
)

Tips for Effective Research

Be specific about the scope and depth required
Request citations and source verification
Ask for data visualizations when analyzing numbers
Specify the format you need (report, summary, bullet points)
Set realistic timeouts for complex queries
Review and verify critical findings independently