AI Agent Governance - Policy-Based Sandboxing
Policy-Based Sandboxing: Define what your AI agent can and cannot do using declarative policies - Action Interception: Catch and validate agent action…
- OpenAI
Advanced Agents ·Intermediate
A streamlined multi-phase research agent built with Google's Interactions API that demonstrates stateful conversations, model mixing, background execution, and automatic infographic generation.
License Apache-2.0 · content curated and maintained by Doutor AI.
A streamlined multi-phase research agent built with Google's Interactions API that demonstrates stateful conversations, model mixing, background execution, and automatic infographic generation.
previous_interaction_id for maintaining context across phasesUser Goal
↓
[Phase 1] Gemini 3 Flash → Research Plan
↓
[Phase 2] Select Tasks → Deep Research Agent → Research Results
↓
[Phase 3] Gemini 3 Pro → Executive Report
+ Gemini 3 Pro Image → TL;DR Infographic
Interaction for stateful continuationprevious_interaction_id| Component | Technology |
|---|---|
| Planning Model | gemini-3-flash-preview |
| Research Agent | deep-research-pro-preview-12-2025 |
| Synthesis Model | gemini-3-pro-preview |
| Infographic Model | gemini-3-pro-image-preview |
| UI Framework | Streamlit |
| Python SDK | google-genai |
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd advanced_ai_agents/single_agent_apps/research_agent_gemini_interaction_api
pip install -r requirements.txt
streamlit run research_planner_executor_agent.py
http://localhost:8501agent parameter, not modelgenerate_content APIPart of the Awesome LLM Apps collection.
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