feat: add Smolagents memory integration example

[m1lestones]

Summary

• Adds examples/smolagents/python/ — a full Honcho memory integration for Smolagents (HuggingFace)
• Demonstrates persistent memory using a ToolCallingAgent with LiteLLMModel, a Tool subclass for memory recall, and Honcho context injected into the task string
• Follows the same pattern as the existing examples/openai-agents/ example

What's included

examples/smolagents/
├── README.md
└── python/
    ├── main.py
    ├── pyproject.toml
    └── tools/
        ├── client.py
        ├── save_memory.py
        ├── get_context.py
        └── query_memory.py  # QueryMemoryTool(Tool) subclass

How it works

1. Context injection — Honcho session history is prepended to the agent task string so the model always has recent context.
2. Tool subclass — QueryMemoryTool extends smolagents.Tool, implementing forward() to call Honcho's Dialectic API. The user_id is stored as an instance attribute.
3. Auto-save — chat() persists the user message before the agent runs and the assistant response after.

Test plan

• Set HONCHO_API_KEY and OPENAI_API_KEY in python/.env
• pip install "smolagents[litellm]" honcho-ai python-dotenv
• cd python && python main.py
• Tell the agent something about yourself, then ask "What do you remember about me?" in a new session

🤖 Generated with Claude Code

Summary by CodeRabbit

• Documentation

  • Added comprehensive integration guide explaining Smolagents setup with persistent memory, including required project structure, environment variables, dependencies, and step-by-step usage examples.

• New Features

  • Added a complete working example demonstrating conversational AI with persistent memory capabilities, enabling automatic conversation history retrieval and natural-language semantic memory recall across separate user sessions.

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ℹ️ Review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

Plan: Pro

Run ID: 7d3d9adc-067d-405e-a49b-e78c46f72771

📥 Commits

Reviewing files that changed from the base of the PR and between 31717c0 and 7a33df3.

📒 Files selected for processing (3)

• examples/smolagents/python/main.py
• examples/smolagents/python/tools/query_memory.py
• examples/smolagents/python/tools/save_memory.py

Walkthrough

This PR adds a complete Smolagents integration example with Honcho persistent memory, including documentation, project configuration, a conversational agent entrypoint, and modular tools for Honcho client setup, context retrieval, memory querying via Dialectic API, and memory persistence.

Changes

Cohort / File(s)	Summary
Documentation examples/smolagents/README.md	Introduces the integration pattern, expected project structure, required environment variables, installation steps, quick-start usage example with chat() function, control flow explanation, and concept mapping.
Project Configuration examples/smolagents/python/pyproject.toml	Defines Python package metadata, minimum Python 3.10+ requirement, and dependencies for smolagents[litellm], honcho-ai, and python-dotenv.
Honcho Integration Tools examples/smolagents/python/tools/client.py, examples/smolagents/python/tools/get_context.py, examples/smolagents/python/tools/query_memory.py, examples/smolagents/python/tools/save_memory.py	Implements modular tools: HonchoContext dataclass and get_client() for setup, get_context() for fetching session conversation history, QueryMemoryTool Smolagents tool exposing Dialectic API queries, and save_memory() for persisting messages.
Agent Entrypoint examples/smolagents/python/main.py	Implements chat(user_id, message, session_id) function orchestrating the agent flow: fetching recent context, injecting history, creating a ToolCallingAgent with QueryMemoryTool, running inference via gpt-4-mini, and persisting both user and assistant messages to Honcho.

Sequence Diagram

sequenceDiagram
    participant User
    participant Chat as chat()
    participant Honcho as Honcho Client
    participant Agent as ToolCallingAgent
    participant OpenAI as OpenAI API
    participant Dialectic as Dialectic API

    User->>Chat: (user_id, message, session_id)
    Chat->>Honcho: get_context(ctx, tokens=2000)
    Honcho-->>Chat: context_history
    Chat->>Agent: forward(context + message)
    Agent->>OpenAI: LLM call
    OpenAI-->>Agent: response
    alt Agent calls QueryMemoryTool
        Agent->>Honcho: peer.chat(query)
        Honcho->>Dialectic: semantic search
        Dialectic-->>Honcho: results
        Honcho-->>Agent: retrieved memory
    end
    Agent-->>Chat: assistant_response
    Chat->>Honcho: save_memory(user_message, "user")
    Chat->>Honcho: save_memory(assistant_response, "assistant")
    Chat-->>User: assistant_response

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Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Possibly related PRs

• Updating Docs & Packages with 3.0.0 SDK #356 — Renames/updates session context API from get_context() to context(), which the main PR's example code directly uses via a wrapper function.
• feat(examples): add Honcho memory skill for Zo Computer #495 — Adds the same Honcho memory toolkit (client, get_context, query_memory, save_memory) and corresponding examples across different integrations.

Suggested reviewers

• ajspig
• VVoruganti

Poem

🐰 A bunny hops through memory halls,
Smolagents whisper through Honcho's calls,
Context flows, tools remember all,
Dialectic dances at semantic's call,
Fluffy persistence, never to fall!

🚥 Pre-merge checks | ✅ 3

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately describes the primary change: adding a complete Smolagents memory integration example with documentation and functional code.
Docstring Coverage	✅ Passed	Docstring coverage is 83.33% which is sufficient. The required threshold is 80.00%.

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✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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