We're excited to announce R2R v3.5.0, featuring our new Deep Research API and significant improvements to our RAG capabilities.
🚀 Highlights
* Deep Research API: Multi-step reasoning system that fetches data from your knowledge base and the internet to deliver comprehensive, context-aware answers
* Enhanced RAG Agent: More robust with new web search and scraping capabilities
* Real-time Streaming: Server-side event streaming for visibility into the agent's thinking process and tool usage
✨ Key Features
Research Capabilities
* Research Agent: Specialized mode with advanced reasoning and computational tools
* Extended Thinking: Toggle reasoning capabilities with optimized Claude model support
* Improved Citations: Real-time citation identification with precise source attribution
New Tools
* Web Tools: Search external APIs and scrape web pages for up-to-date information
* Research Tools: Reasoning, critique, and Python execution for complex analysis
* RAG Tool: Leverage underlying RAG capabilities within the research agent
💡 Usage Examples
Basic RAG Mode
python
response = client.retrieval.agent(
query="What does deepseek r1 imply for the future of AI?",
generation_config={
"model": "anthropic/claude-3-7-sonnet-20250219",
"extended_thinking": True,
"thinking_budget": 4096,
"temperature": 1,
"max_tokens_to_sample": 16000,
"stream": True
},
rag_tools=["search_file_descriptions", "search_file_knowledge", "get_file_content", "web_search", "web_scrape"],
mode="rag"
)
Process the streaming events
for event in response:
if isinstance(event, ThinkingEvent):
print(f"🧠Thinking: {event.data.delta.content[0].payload.value}")
elif isinstance(event, ToolCallEvent):
print(f"🔧 Tool call: {event.data.name}({event.data.arguments})")
elif isinstance(event, ToolResultEvent):
print(f"📊 Tool result: {event.data.content[:60]}...")
elif isinstance(event, CitationEvent):
print(f"📑 Citation: {event.data}")
elif isinstance(event, MessageEvent):
print(f"💬 Message: {event.data.delta.content[0].payload.value}")
elif isinstance(event, FinalAnswerEvent):
print(f"✅ Final answer: {event.data.generated_answer[:100]}...")
print(f" Citations: {len(event.data.citations)} sources referenced")
Research Mode
python
response = client.retrieval.agent(
query="Analyze the philosophical implications of DeepSeek R1",
generation_config={
"model": "anthropic/claude-3-opus-20240229",
"extended_thinking": True,
"thinking_budget": 8192,
"temperature": 0.2,
"max_tokens_to_sample": 32000,
"stream": True
},
research_tools=["rag", "reasoning", "critique", "python_executor"],
mode="research"
)
For more details, visit our [documentation site](https://r2r-docs.sciphi.ai/).