Skip to content

Commit 7778d74

Browse files
WSPlutaWSPluta
authored
Merge pull request #215 from oracle-devrel/feature/oamp-support-assistant-notebook
notebooks/agent_memory: add OAMP support assistant example
2 parents 462643d + 1d2a2e8 commit 7778d74

2 files changed

Lines changed: 1990 additions & 7 deletions

File tree

‎notebooks/agent_memory/README.md‎

Lines changed: 8 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -38,13 +38,14 @@ The notebooks in this folder use the [`oracleagentmemory`](https://www.oracle.co
3838

3939
## Notebooks
4040

41-
| # | Name | Description | Framework | Open Notebook | Open in Colab |
42-
| --- | -------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
43-
| 01 | Deep Research Agent | Build a deep research agent for human genome exploration that uses Tavily for live web search and stores running conversation + durable findings in Oracle AI Database. Demonstrates the OpenAI Agents SDK `Session` protocol implemented against an Oracle-backed memory store. | OpenAI Agents SDK · Tavily · OAMP | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./01_deep_research_openai_agents.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/01_deep_research_openai_agents.ipynb) |
44-
| 02 | Supply Chain Assistant | A supply chain assistant that tracks and updates shipment cargo through in-process tools and an MCP server. Uses Oracle AI Agent Memory to persist shipment records, operational notes, and conversation history across restarts. | Claude Agent SDK · MCP · OAMP | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./02_supply_chain_claude_agent_sdk.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/02_supply_chain_claude_agent_sdk.ipynb) |
45-
| 03 | Mortgage Approval Workflow | A deterministic mortgage approval workflow modeled as a `StateGraph` with prebuilt `create_agent` nodes. Uses Oracle AI Agent Memory so a workflow that fails mid-stage can resume from the last persisted state instead of restarting. | LangGraph · OAMP | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./03_mortgage_workflow_langgraph.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/03_mortgage_workflow_langgraph.ipynb) |
46-
| 04 | OAMP Benchmarks | Quantifies the practical benefits of Oracle AI Agent Memory over naive flat-history memory along three axes: token consumption per turn, wall-clock latency, and response quality (LLM-as-a-judge). Runs the same 80-turn scripted conversation through three agents. | OAMP · LiteLLM · OpenAI | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./oracle_agent_memory_benchmarks.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/oracle_agent_memory_benchmarks.ipynb) |
47-
| 05 | OAMP Developer Guide | A hands-on, step-by-step guide to the `oracleagentmemory` package. Builds an agent memory system from scratch — connection, the three primitives (users/agents, memories, threads), manual vs. automatic LLM-powered extraction, vector search, context cards, and scoping. | OAMP · LiteLLM | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./oracle_agent_memory_developer_guide.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/oracle_agent_memory_developer_guide.ipynb) |
41+
| # | Name | Description | Framework | Open Notebook | Open in Colab |
42+
| --- | -------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
43+
| 01 | Deep Research Agent | Build a deep research agent for human genome exploration that uses Tavily for live web search and stores running conversation + durable findings in Oracle AI Database. Demonstrates the OpenAI Agents SDK `Session` protocol implemented against an Oracle-backed memory store. | OpenAI Agents SDK · Tavily · OAMP | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./01_deep_research_openai_agents.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/01_deep_research_openai_agents.ipynb) |
44+
| 02 | Supply Chain Assistant | A supply chain assistant that tracks and updates shipment cargo through in-process tools and an MCP server. Uses Oracle AI Agent Memory to persist shipment records, operational notes, and conversation history across restarts. | Claude Agent SDK · MCP · OAMP | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./02_supply_chain_claude_agent_sdk.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/02_supply_chain_claude_agent_sdk.ipynb) |
45+
| 03 | Mortgage Approval Workflow | A deterministic mortgage approval workflow modeled as a `StateGraph` with prebuilt `create_agent` nodes. Uses Oracle AI Agent Memory so a workflow that fails mid-stage can resume from the last persisted state instead of restarting. | LangGraph · OAMP | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./03_mortgage_workflow_langgraph.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/03_mortgage_workflow_langgraph.ipynb) |
46+
| 04 | OAMP Benchmarks | Quantifies the practical benefits of Oracle AI Agent Memory over naive flat-history memory along three axes: token consumption per turn, wall-clock latency, and response quality (LLM-as-a-judge). Runs the same 80-turn scripted conversation through three agents. | OAMP · LiteLLM · OpenAI | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./oracle_agent_memory_benchmarks.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/oracle_agent_memory_benchmarks.ipynb) |
47+
| 05 | OAMP Developer Guide | A hands-on, step-by-step guide to the `oracleagentmemory` package. Builds an agent memory system from scratch — connection, the three primitives (users/agents, memories, threads), manual vs. automatic LLM-powered extraction, vector search, context cards, and scoping. | OAMP · LiteLLM | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./oracle_agent_memory_developer_guide.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/oracle_agent_memory_developer_guide.ipynb) |
48+
| 06 | Support Assistant Copilot | An end-to-end customer-support copilot that follows one damaged-delivery case from setup through knowledge ingestion, agent tool use, context-card compaction, preference correction, cross-user isolation, TTL/retention, and teardown. Demonstrates background extraction, hybrid search, metadata inheritance and filtering, in-database embeddings, and chunked semantic indexing. | OpenAI Agents SDK · OAMP | [![Open Notebook](https://img.shields.io/badge/Open%20Notebook-orange?style=flat-square)](./oamp_support_assistant_example.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/oracle-devrel/oracle-ai-developer-hub/blob/main/notebooks/agent_memory/oamp_support_assistant_example.ipynb) |
4849

4950
## Getting Started
5051

0 commit comments

Comments
 (0)