# System Registry & Wiring Architecture
**Status**: Active / Canonical
**Last Updated**: 2025-12-06

This document serves as the **Source of Truth** for the architectural wiring of the agent framework. It defines the strict rules for decorators, protocol markers, and the tool registry to prevent regression and ensure correct system behavior.

---

## 1. Decorator Registry

The agent framework relies on a strict decorator stack to inject functionality into `ChatClient` implementations. The **order of application** is critical for correct behavior.

### Standard Stack (Bottom-Up Order)

| Order | Decorator | Purpose | Source | Critical Notes |
|:--|:---|:---|:---|:---|
| **1 (Inner)** | `@use_chat_middleware` | Handles request/response middleware processing (e.g. logging, filtering). | `agent_framework._middleware` | Must be closest to the class. |
| **2** | `@use_observability` | Injects tracing and metrics (OpenTelemetry/logging). | `agent_framework.observability` | Wraps the middleware-enhanced client. |
| **3 (Outer)** | `@use_function_invocation` | **CRITICAL**: Intercepts `FunctionCallContent` in responses, **executes the Python function**, and recursively calls the LLM with the result. | `agent_framework._tools` | **MUST NOT** be used if `__function_invoking_chat_client__ = True` is set (see Markers). |

### Correct Usage Example

```python
@use_function_invocation  # <--- 3. Handles tool execution loop
@use_observability        # <--- 2. Adds tracing
@use_chat_middleware      # <--- 1. Adds middleware support
class MyChatClient(BaseChatClient):
    ...
```

---

## 2. Protocol Markers

Special class attributes (dunder methods/variables) that control framework behavior.

| Marker | Value | Purpose | Set By | Read By | Impact of Misuse |
|:---|:---|:---|:---|:---|:---|
| `__function_invoking_chat_client__` | `bool` | Signals that this client **natively handles** the tool execution loop internally. | `ChatClient` Class Body | `@use_function_invocation` | **CRITICAL BUG**: If set to `True` but the client *doesn't* execute tools, tool calls will be generated by the LLM but **never executed**. The agent will hang or hallucinate results. |

### Wiring Rules
*   **Default Clients (OpenAI/HuggingFace):** Should generally **NOT** set this marker. Rely on `@use_function_invocation` to handle execution.
*   **Special Clients:** Only set to `True` if you are implementing a custom loop that executes tools and feeds results back without the framework's help.

### Setting Responsibility
*   **Default:** Do not set `__function_invoking_chat_client__` in the class body. The `@use_function_invocation` decorator sets it automatically after wrapping.
*   **Custom Loop:** Only set to `True` if you have implemented a custom tool execution loop that does not rely on the framework's decorator.

---

## 3. Tool Inventory

### 3.1 AI Functions (Agent-Callable Tools)

These are the `@ai_function` decorated functions that agents can invoke. The framework executes these via `@use_function_invocation`.

| Function Name | File Path | Description |
|:---|:---|:---|
| `search_pubmed` | `src/agents/tools.py:20` | Searches PubMed for biomedical literature |
| `search_clinical_trials` | `src/agents/tools.py:80` | Searches ClinicalTrials.gov for clinical studies |
| `search_preprints` | `src/agents/tools.py:120` | Searches Europe PMC for preprints and papers |
| `get_bibliography` | `src/agents/tools.py:160` | Returns collected references for final report |
| `search_web` | `src/agents/retrieval_agent.py:17` | Searches web using DuckDuckGo |
| ~~`execute_python_code`~~ | ~~`src/agents/code_executor_agent.py`~~ | REMOVED in PR #130 (Modal deleted) |

### 3.2 Tool Classes (Internal Wrappers)

These are **internal implementation wrappers** used by the AI Functions. They are NOT directly callable by agents.

| Class | File Path | Used By |
|:---|:---|:---|
| `PubMedTool` | `src/tools/pubmed.py` | `search_pubmed` |
| `ClinicalTrialsTool` | `src/tools/clinicaltrials.py` | `search_clinical_trials` |
| `EuropePMCTool` | `src/tools/europepmc.py` | `search_preprints` |
| `OpenAlexTool` | `src/tools/openalex.py` | OpenAlex search (used in SearchHandler) |
| `WebSearchTool` | `src/tools/web_search.py` | `search_web` (DuckDuckGo) |
| `SearchHandler` | `src/tools/search_handler.py` | Orchestrates parallel searches |
| `RateLimiter` | `src/tools/rate_limiter.py` | Rate limiting via `limits` library |
| `BaseTool` | `src/tools/base.py` | Abstract base class for tools |
| ~~`ModalCodeExecutor`~~ | ~~`src/tools/code_execution.py`~~ | REMOVED in PR #130 |

---

## 4. Client Implementation Guide

When adding a new LLM provider, follow this strict pattern:

### A. The "Native Execution" Fallacy
Do not assume that because an API supports "function calling" (parsing JSON), the client supports "function execution" (running Python code).
*   **Function Calling:** LLM -> JSON (Client responsibility)
*   **Function Execution:** JSON -> Python Result -> LLM (Framework responsibility via `@use_function_invocation`)

### B. Reference Implementation

```python
from agent_framework import BaseChatClient
from agent_framework._tools import use_function_invocation
from agent_framework.observability import use_observability
from agent_framework._middleware import use_chat_middleware

# 1. Apply decorators in this EXACT order
@use_function_invocation
@use_observability
@use_chat_middleware
class NewProviderChatClient(BaseChatClient):
    
    # 2. DO NOT set this unless you know what you are doing
    # __function_invoking_chat_client__ = True  <-- DELETE THIS
    
    async def _inner_get_response(self, ...):
        # 3. Parse API response -> FunctionCallContent
        # 4. Return ChatResponse with contents=[FunctionCallContent(...)]
        pass
        
    async def _inner_get_streaming_response(self, ...):
        # 5. Yield FunctionCallContent when tool calls are detected
        pass
```

---

## 5. Known Issues & Gotchas

*   **~~P1 Bug - Premature Marker Setting~~ (FIXED):** The `HuggingFaceChatClient` previously set `__function_invoking_chat_client__ = True` in the class body, which caused `@use_function_invocation` to skip wrapping. **Resolution:** Marker removed; decorator now sets it correctly.
*   **HuggingFace Provider Routing:** Large models (70B+) may be routed to third-party inference providers (Novita, Hyperbolic) instead of native HF infrastructure. See `CLAUDE.md` for current model recommendations.
*   **Model Hallucination:** If tool execution fails (due to incorrect wiring), models like Qwen2.5-7B will often **hallucinate** fake tool results as text. Always verify `AgentRunResponse` contains actual `FunctionResultContent`.

---

## 6. Verification Checklist

When adding or modifying a ChatClient:

- [ ] Decorators applied in correct order: `@use_function_invocation` → `@use_observability` → `@use_chat_middleware`
- [ ] `__function_invoking_chat_client__` is NOT set in class body (unless implementing custom execution loop)
- [ ] Verify `@use_function_invocation` decorator actually wraps methods (check `__wrapped__` attribute at runtime)
- [ ] Tool calls parsed into `FunctionCallContent` objects
- [ ] Streaming yields `FunctionCallContent` at end of stream
- [ ] Run `make check` to verify all tests pass