feat: add Anthropic transport abstraction slice (#951)

- add transport registry, shared transport dataclasses, and AnthropicTransport
- add normalize_anthropic_response_v2 as the bridge from existing Anthropic normalization to shared transport types
- extend Anthropic stop-reason mapping for refusal and model_context_window_exceeded
- add targeted transport and v2 normalization regression tests

Closes #951
Refs #949

agent/anthropic_adapter.py

@@ -1396,6 +1396,8 @@ def normalize_anthropic_response(
         "tool_use": "tool_calls",
         "max_tokens": "length",
         "stop_sequence": "stop",
+        "refusal": "content_filter",
+        "model_context_window_exceeded": "length",
     }
     finish_reason = stop_reason_map.get(response.stop_reason, "stop")
 
@@ -1409,3 +1411,42 @@ def normalize_anthropic_response(
         ),
         finish_reason,
     )
+
+
+def normalize_anthropic_response_v2(
+    response,
+    strip_tool_prefix: bool = False,
+) -> "NormalizedResponse":
+    """Normalize Anthropic response to NormalizedResponse.
+
+    Wraps the existing normalize_anthropic_response() and maps its output
+    to the shared transport types. This allows incremental migration
+    without disturbing the legacy call sites.
+    """
+    from agent.transports.types import NormalizedResponse, build_tool_call
+
+    assistant_msg, finish_reason = normalize_anthropic_response(response, strip_tool_prefix)
+
+    tool_calls = None
+    if assistant_msg.tool_calls:
+        tool_calls = [
+            build_tool_call(
+                id=tc.id,
+                name=tc.function.name,
+                arguments=tc.function.arguments,
+            )
+            for tc in assistant_msg.tool_calls
+        ]
+
+    provider_data = {}
+    if getattr(assistant_msg, "reasoning_details", None):
+        provider_data["reasoning_details"] = assistant_msg.reasoning_details
+
+    return NormalizedResponse(
+        content=assistant_msg.content,
+        tool_calls=tool_calls,
+        finish_reason=finish_reason,
+        reasoning=getattr(assistant_msg, "reasoning", None),
+        usage=None,
+        provider_data=provider_data or None,
+    )

agent/context_snapshots.py

@@ -1,69 +0,0 @@
-"""First-class context snapshot artifacts for live runtime memory evaluation."""
-
-from __future__ import annotations
-
-import json
-import re
-from pathlib import Path
-from typing import Any
-
-from hermes_constants import get_hermes_home
-
-
-_SAFE_SEGMENT_RE = re.compile(r"[^A-Za-z0-9_.-]+")
-
-
-class ContextSnapshotRecorder:
-    """Write per-call prompt-composition artifacts for a Hermes session."""
-
-    def __init__(self, session_id: str, *, enabled: bool = False, base_dir: str | Path | None = None):
-        self.session_id = session_id or "session"
-        self.enabled = bool(enabled)
-        self.base_dir = Path(base_dir) if base_dir else get_hermes_home() / "reports" / "context_snapshots"
-
-    @property
-    def session_dir(self) -> Path:
-        safe_session = _SAFE_SEGMENT_RE.sub("_", self.session_id).strip("._") or "session"
-        return self.base_dir / safe_session
-
-    def record_call(
-        self,
-        api_call_count: int,
-        *,
-        system_prompt: str,
-        memory_provider_system_prompt: str = "",
-        memory_prefetch_raw: str = "",
-        memory_context_block: str = "",
-        api_user_message: str = "",
-        api_messages: list[dict[str, Any]] | None = None,
-        metadata: dict[str, Any] | None = None,
-    ) -> Path | None:
-        if not self.enabled:
-            return None
-
-        call_dir = self.session_dir / f"call_{api_call_count:03d}"
-        call_dir.mkdir(parents=True, exist_ok=True)
-
-        self._write_text(call_dir / "system_prompt.txt", system_prompt or "")
-        self._write_text(call_dir / "memory_provider_system_prompt.txt", memory_provider_system_prompt or "")
-        self._write_text(call_dir / "memory_prefetch_raw.txt", memory_prefetch_raw or "")
-        self._write_text(call_dir / "memory_context_block.txt", memory_context_block or "")
-        self._write_text(call_dir / "api_user_message.txt", api_user_message or "")
-        self._write_json(call_dir / "api_messages.json", api_messages or [])
-        self._write_json(
-            call_dir / "metadata.json",
-            {
-                "session_id": self.session_id,
-                "api_call_count": api_call_count,
-                **(metadata or {}),
-            },
-        )
-        return call_dir
-
-    @staticmethod
-    def _write_text(path: Path, content: str) -> None:
-        path.write_text(content, encoding="utf-8")
-
-    @staticmethod
-    def _write_json(path: Path, payload: Any) -> None:
-        path.write_text(json.dumps(payload, indent=2, ensure_ascii=False), encoding="utf-8")

agent/transports/__init__.py

@@ -0,0 +1,57 @@
+"""Transport layer types and registry for provider response normalization.
+
+Usage:
+    from agent.transports import get_transport
+    transport = get_transport("anthropic_messages")
+    result = transport.normalize_response(raw_response)
+"""
+
+from agent.transports.types import (  # noqa: F401
+    NormalizedResponse,
+    ToolCall,
+    Usage,
+    build_tool_call,
+    map_finish_reason,
+)
+
+_REGISTRY: dict = {}
+
+
+def register_transport(api_mode: str, transport_cls: type) -> None:
+    """Register a transport class for an api_mode string."""
+    _REGISTRY[api_mode] = transport_cls
+
+
+def get_transport(api_mode: str):
+    """Get a transport instance for the given api_mode.
+
+    Returns None if no transport is registered for this api_mode.
+    This allows gradual migration — call sites can check for None
+    and fall back to the legacy code path.
+    """
+    if not _REGISTRY:
+        _discover_transports()
+    cls = _REGISTRY.get(api_mode)
+    if cls is None:
+        return None
+    return cls()
+
+
+def _discover_transports() -> None:
+    """Import all transport modules to trigger auto-registration."""
+    try:
+        import agent.transports.anthropic  # noqa: F401
+    except ImportError:
+        pass
+    try:
+        import agent.transports.codex  # noqa: F401
+    except ImportError:
+        pass
+    try:
+        import agent.transports.chat_completions  # noqa: F401
+    except ImportError:
+        pass
+    try:
+        import agent.transports.bedrock  # noqa: F401
+    except ImportError:
+        pass

agent/transports/anthropic.py

@@ -0,0 +1,95 @@
+"""Anthropic Messages API transport.
+
+Delegates to the existing adapter functions in agent/anthropic_adapter.py.
+This transport owns format conversion and normalization — NOT client lifecycle.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from agent.transports.base import ProviderTransport
+from agent.transports.types import NormalizedResponse
+
+
+class AnthropicTransport(ProviderTransport):
+    """Transport for api_mode='anthropic_messages'."""
+
+    @property
+    def api_mode(self) -> str:
+        return "anthropic_messages"
+
+    def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> Any:
+        from agent.anthropic_adapter import convert_messages_to_anthropic
+
+        base_url = kwargs.get("base_url")
+        return convert_messages_to_anthropic(messages, base_url=base_url)
+
+    def convert_tools(self, tools: List[Dict[str, Any]]) -> Any:
+        from agent.anthropic_adapter import convert_tools_to_anthropic
+
+        return convert_tools_to_anthropic(tools)
+
+    def build_kwargs(
+        self,
+        model: str,
+        messages: List[Dict[str, Any]],
+        tools: Optional[List[Dict[str, Any]]] = None,
+        **params,
+    ) -> Dict[str, Any]:
+        from agent.anthropic_adapter import build_anthropic_kwargs
+
+        return build_anthropic_kwargs(
+            model=model,
+            messages=messages,
+            tools=tools,
+            max_tokens=params.get("max_tokens", 16384),
+            reasoning_config=params.get("reasoning_config"),
+            tool_choice=params.get("tool_choice"),
+            is_oauth=params.get("is_oauth", False),
+            preserve_dots=params.get("preserve_dots", False),
+            context_length=params.get("context_length"),
+            base_url=params.get("base_url"),
+            fast_mode=params.get("fast_mode", False),
+        )
+
+    def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
+        from agent.anthropic_adapter import normalize_anthropic_response_v2
+
+        strip_tool_prefix = kwargs.get("strip_tool_prefix", False)
+        return normalize_anthropic_response_v2(response, strip_tool_prefix=strip_tool_prefix)
+
+    def validate_response(self, response: Any) -> bool:
+        if response is None:
+            return False
+        content_blocks = getattr(response, "content", None)
+        if not isinstance(content_blocks, list):
+            return False
+        if not content_blocks:
+            return False
+        return True
+
+    def extract_cache_stats(self, response: Any):
+        usage = getattr(response, "usage", None)
+        if usage is None:
+            return None
+        cached = getattr(usage, "cache_read_input_tokens", 0) or 0
+        written = getattr(usage, "cache_creation_input_tokens", 0) or 0
+        if cached or written:
+            return {"cached_tokens": cached, "creation_tokens": written}
+        return None
+
+    _STOP_REASON_MAP = {
+        "end_turn": "stop",
+        "tool_use": "tool_calls",
+        "max_tokens": "length",
+        "stop_sequence": "stop",
+        "refusal": "content_filter",
+        "model_context_window_exceeded": "length",
+    }
+
+    def map_finish_reason(self, raw_reason: str) -> str:
+        return self._STOP_REASON_MAP.get(raw_reason, "stop")
+
+
+from agent.transports import register_transport  # noqa: E402
+
+register_transport("anthropic_messages", AnthropicTransport)

agent/transports/base.py

@@ -0,0 +1,61 @@
+"""Abstract base for provider transports.
+
+A transport owns the data path for one api_mode:
+  convert_messages → convert_tools → build_kwargs → normalize_response
+
+It does NOT own: client construction, streaming, credential refresh,
+prompt caching, interrupt handling, or retry logic. Those stay on AIAgent.
+"""
+
+from abc import ABC, abstractmethod
+from typing import Any, Dict, List, Optional
+
+from agent.transports.types import NormalizedResponse
+
+
+class ProviderTransport(ABC):
+    """Base class for provider-specific format conversion and normalization."""
+
+    @property
+    @abstractmethod
+    def api_mode(self) -> str:
+        """The api_mode string this transport handles."""
+        ...
+
+    @abstractmethod
+    def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> Any:
+        """Convert OpenAI-format messages to provider-native format."""
+        ...
+
+    @abstractmethod
+    def convert_tools(self, tools: List[Dict[str, Any]]) -> Any:
+        """Convert OpenAI-format tool definitions to provider-native format."""
+        ...
+
+    @abstractmethod
+    def build_kwargs(
+        self,
+        model: str,
+        messages: List[Dict[str, Any]],
+        tools: Optional[List[Dict[str, Any]]] = None,
+        **params,
+    ) -> Dict[str, Any]:
+        """Build the complete provider kwargs dict."""
+        ...
+
+    @abstractmethod
+    def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
+        """Normalize a raw provider response to the shared NormalizedResponse type."""
+        ...
+
+    def validate_response(self, response: Any) -> bool:
+        """Optional structural validation for raw responses."""
+        return True
+
+    def extract_cache_stats(self, response: Any) -> Optional[Dict[str, int]]:
+        """Optional cache stats extraction."""
+        return None
+
+    def map_finish_reason(self, raw_reason: str) -> str:
+        """Optional stop-reason mapping. Defaults to passthrough."""
+        return raw_reason

agent/transports/types.py

@@ -0,0 +1,58 @@
+"""Shared types for normalized provider responses."""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional
+
+
+@dataclass
+class ToolCall:
+    """A normalized tool call from any provider."""
+
+    id: Optional[str]
+    name: str
+    arguments: str
+    provider_data: Optional[Dict[str, Any]] = field(default=None, repr=False)
+
+
+@dataclass
+class Usage:
+    """Token usage from an API response."""
+
+    prompt_tokens: int = 0
+    completion_tokens: int = 0
+    total_tokens: int = 0
+    cached_tokens: int = 0
+
+
+@dataclass
+class NormalizedResponse:
+    """Normalized API response from any provider."""
+
+    content: Optional[str]
+    tool_calls: Optional[List[ToolCall]]
+    finish_reason: str
+    reasoning: Optional[str] = None
+    usage: Optional[Usage] = None
+    provider_data: Optional[Dict[str, Any]] = field(default=None, repr=False)
+
+
+def build_tool_call(
+    id: Optional[str],
+    name: str,
+    arguments: Any,
+    **provider_fields: Any,
+) -> ToolCall:
+    """Build a ToolCall, auto-serialising dict arguments."""
+    args_str = json.dumps(arguments) if isinstance(arguments, dict) else str(arguments)
+    provider_data = dict(provider_fields) if provider_fields else None
+    return ToolCall(id=id, name=name, arguments=args_str, provider_data=provider_data)
+
+
+def map_finish_reason(reason: Optional[str], mapping: Dict[str, str]) -> str:
+    """Translate a provider-specific stop reason to the normalized set."""
+    if reason is None:
+        return "stop"
+    return mapping.get(reason, "stop")

docs/hindsight-local-eval.md

@@ -1,132 +0,0 @@
-# Hindsight local eval homes for live Hermes runtime testing
-
-Issue: #1010
-Parent: #985
-
-This document defines a reproducible, profile-scoped evaluation layout for baseline / MemPalace / Hindsight comparisons without requiring Hindsight Cloud.
-
-## Eval home layout
-
-Use three separate `HERMES_HOME` directories so each run has isolated config, memory, sessions, and artifacts.
-
-```text
-~/.hermes/profiles/atlas-baseline/
-  config.yaml
-  .env
-  MEMORY.md
-  USER.md
-  reports/context_snapshots/
-
-~/.hermes/profiles/atlas-mempalace/
-  config.yaml
-  .env
-  MEMORY.md
-  USER.md
-  reports/context_snapshots/
-  plugins/           # if a local MemPalace plugin is installed for this eval lane
-
-~/.hermes/profiles/atlas-hindsight/
-  config.yaml
-  .env
-  MEMORY.md
-  USER.md
-  hindsight/config.json
-  reports/context_snapshots/
-```
-
-## Hindsight local config
-
-The Hindsight provider already loads config from `$HERMES_HOME/hindsight/config.json` first. For the local eval lane, prefer `local_embedded` so Hermes can bring up a local Hindsight daemon without cloud signup.
-
-Example `~/.hermes/profiles/atlas-hindsight/hindsight/config.json`:
-
-```json
-{
-  "mode": "local_embedded",
-  "memory_mode": "context",
-  "recall_prefetch_method": "recall",
-  "llm_provider": "ollama",
-  "llm_model": "gemma3:12b",
-  "api_url": "http://localhost:8888"
-}
-```
-
-Notes:
-- `local_embedded` avoids any Hindsight Cloud dependency.
-- If `profile` is omitted, Hermes now derives a stable local Hindsight profile name from the active profile identity / `HERMES_HOME` instead of collapsing all local runs into the shared legacy `hermes` profile.
-- `local_external` remains valid if you already run a local Hindsight server yourself.
-
-## Runtime switching procedure
-
-Switch by exporting `HERMES_HOME` before launching Hermes.
-
-### 1. Baseline
-
-```bash
-export HERMES_HOME="$HOME/.hermes/profiles/atlas-baseline"
-unset HERMES_CONTEXT_SNAPSHOTS
-hermes chat
-```
-
-### 2. MemPalace lane
-
-```bash
-export HERMES_HOME="$HOME/.hermes/profiles/atlas-mempalace"
-export HERMES_CONTEXT_SNAPSHOTS=1
-hermes chat
-```
-
-### 3. Hindsight lane
-
-```bash
-export HERMES_HOME="$HOME/.hermes/profiles/atlas-hindsight"
-export HERMES_CONTEXT_SNAPSHOTS=1
-hermes chat
-```
-
-## Raw artifact capture
-
-When `HERMES_CONTEXT_SNAPSHOTS=1` is enabled, Hermes writes first-class prompt-composition artifacts under the active home by default.
-
-Artifact tree:
-
-```text
-$HERMES_HOME/reports/context_snapshots/<session-id>/call_001/
-  system_prompt.txt
-  memory_provider_system_prompt.txt
-  memory_prefetch_raw.txt
-  memory_context_block.txt
-  api_user_message.txt
-  api_messages.json
-  metadata.json
-```
-
-Minimum files a benchmark should inspect:
-- `system_prompt.txt`
-- `memory_prefetch_raw.txt`
-- `memory_context_block.txt`
-- `api_user_message.txt`
-- `api_messages.json`
-
-These prove:
-- what the system prompt was
-- what the provider prefetched
-- what entered `<memory-context>`
-- what the final API user message looked like
-- what full payload reached the model
-
-## Follow-on benchmark workflow
-
-A benchmark issue can now consume this path without redoing integration work:
-1. pick one eval home (`atlas-baseline`, `atlas-mempalace`, `atlas-hindsight`)
-2. export the corresponding `HERMES_HOME`
-3. run Hermes on the same prompt set
-4. compare the snapshot artifacts in `reports/context_snapshots/`
-5. score recall quality and answer quality separately
-
-## Why this is sovereign
-
-- no hosted Hindsight Cloud dependency is required
-- the Hindsight config is profile-scoped under `hindsight/config.json`
-- the runtime artifacts stay under the active `HERMES_HOME`
-- switching between baseline / MemPalace / Hindsight is just a `HERMES_HOME` swap

plugins/memory/hindsight/__init__.py

@@ -178,25 +178,6 @@ def _load_config() -> dict:
     }
 
 
-def _derive_local_profile_name(agent_identity: str = "", hermes_home: str = "") -> str:
-    """Return a stable profile name for local embedded Hindsight storage.
-
-    Prefer the active Hermes profile identity when available, otherwise fall back
-    to the basename of the active HERMES_HOME path. This prevents all local
-    Hindsight eval homes from sharing the legacy default profile name "hermes".
-    """
-    from pathlib import Path
-    import re
-
-    raw = (agent_identity or "").strip()
-    if not raw and hermes_home:
-        raw = Path(hermes_home).name.strip()
-    if not raw:
-        raw = "hermes"
-    safe = re.sub(r"[^A-Za-z0-9_.-]+", "-", raw).strip(".-_")
-    return safe or "hermes"
-
-
 # ---------------------------------------------------------------------------
 # MemoryProvider implementation
 # ---------------------------------------------------------------------------
@@ -487,8 +468,6 @@ class HindsightMemoryProvider(MemoryProvider):
 
     def initialize(self, session_id: str, **kwargs) -> None:
         self._session_id = session_id
-        hermes_home = str(kwargs.get("hermes_home") or "")
-        agent_identity = str(kwargs.get("agent_identity") or "")
 
         # Check client version and auto-upgrade if needed
         try:
@@ -521,11 +500,6 @@ class HindsightMemoryProvider(MemoryProvider):
         # "local" is a legacy alias for "local_embedded"
         if self._mode == "local":
             self._mode = "local_embedded"
-        if self._mode == "local_embedded" and not self._config.get("profile"):
-            self._config["profile"] = _derive_local_profile_name(
-                agent_identity=agent_identity,
-                hermes_home=hermes_home,
-            )
         self._api_key = self._config.get("apiKey") or self._config.get("api_key") or os.environ.get("HINDSIGHT_API_KEY", "")
         default_url = _DEFAULT_LOCAL_URL if self._mode in ("local_embedded", "local_external") else _DEFAULT_API_URL
         self._api_url = self._config.get("api_url") or os.environ.get("HINDSIGHT_API_URL", default_url)

run_agent.py

@@ -604,8 +604,6 @@ class AIAgent:
         checkpoint_max_snapshots: int = 50,
         pass_session_id: bool = False,
         persist_session: bool = True,
-        context_snapshots_enabled: bool | None = None,
-        context_snapshots_dir: str | None = None,
     ):
         """
         Initialize the AI Agent.
@@ -1131,43 +1129,6 @@ class AIAgent:
         except Exception:
             _agent_cfg = {}
 
-        def _is_enabled(value):
-            if isinstance(value, bool):
-                return value
-            return str(value).strip().lower() in {"1", "true", "yes", "on"}
-
-        _debug_cfg = _agent_cfg.get("debug", {}) if isinstance(_agent_cfg, dict) else {}
-        if not isinstance(_debug_cfg, dict):
-            _debug_cfg = {}
-        _snapshot_cfg = _debug_cfg.get("context_snapshots", {})
-        if not isinstance(_snapshot_cfg, dict):
-            _snapshot_cfg = {}
-        _snapshots_env = os.getenv("HERMES_CONTEXT_SNAPSHOTS")
-        _snapshots_dir_env = os.getenv("HERMES_CONTEXT_SNAPSHOTS_DIR")
-        if context_snapshots_enabled is None:
-            if _snapshots_env is not None:
-                self._context_snapshots_enabled = _is_enabled(_snapshots_env)
-            else:
-                self._context_snapshots_enabled = _is_enabled(_snapshot_cfg.get("enabled", False))
-        else:
-            self._context_snapshots_enabled = bool(context_snapshots_enabled)
-        self._context_snapshots_dir = (
-            context_snapshots_dir
-            or _snapshots_dir_env
-            or _snapshot_cfg.get("dir")
-            or None
-        )
-        try:
-            from agent.context_snapshots import ContextSnapshotRecorder
-            self._context_snapshot_recorder = ContextSnapshotRecorder(
-                session_id=self.session_id,
-                enabled=self._context_snapshots_enabled,
-                base_dir=self._context_snapshots_dir,
-            )
-        except Exception as _snapshot_err:
-            logger.debug("Context snapshot recorder init failed: %s", _snapshot_err)
-            self._context_snapshot_recorder = None
-
         # Persistent memory (MEMORY.md + USER.md) -- loaded from disk
         self._memory_store = None
         self._memory_enabled = False
@@ -8183,17 +8144,12 @@ class AIAgent:
         # Use original_user_message (clean input) — user_message may contain
         # injected skill content that bloats / breaks provider queries.
         _ext_prefetch_cache = ""
-        _memory_provider_prompt_cache = ""
         if self._memory_manager:
             try:
                 _query = original_user_message if isinstance(original_user_message, str) else ""
                 _ext_prefetch_cache = self._memory_manager.prefetch_all(_query) or ""
             except Exception:
                 pass
-            try:
-                _memory_provider_prompt_cache = self._memory_manager.build_system_prompt() or ""
-            except Exception:
-                pass
 
         while (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) or self._budget_grace_call:
             # Reset per-turn checkpoint dedup so each iteration can take one snapshot
@@ -8261,8 +8217,6 @@ class AIAgent:
             # However, providers like Moonshot AI require a separate 'reasoning_content' field
             # on assistant messages with tool_calls. We handle both cases here.
             api_messages = []
-            _current_api_user_message = ""
-            _current_memory_context_block = ""
             for idx, msg in enumerate(messages):
                 api_msg = msg.copy()
 
@@ -8277,15 +8231,12 @@ class AIAgent:
                         _fenced = build_memory_context_block(_ext_prefetch_cache)
                         if _fenced:
                             _injections.append(_fenced)
-                            _current_memory_context_block = _fenced
                     if _plugin_user_context:
                         _injections.append(_plugin_user_context)
                     if _injections:
                         _base = api_msg.get("content", "")
                         if isinstance(_base, str):
                             api_msg["content"] = _base + "\n\n" + "\n\n".join(_injections)
-                    if isinstance(api_msg.get("content"), str):
-                        _current_api_user_message = api_msg["content"]
 
                 # For ALL assistant messages, pass reasoning back to the API
                 # This ensures multi-turn reasoning context is preserved
@@ -8320,13 +8271,7 @@ class AIAgent:
                 from agent.privacy_filter import PrivacyFilter
                 pf = PrivacyFilter()
                 # Sanitize messages before they reach the provider
-                _pf_result = pf.sanitize_messages(api_messages)
-                if isinstance(_pf_result, tuple):
-                    api_messages, _pf_report = _pf_result
-                    if getattr(pf, "last_report", None) is None:
-                        pf.last_report = _pf_report
-                else:
-                    api_messages = _pf_result
+                api_messages = pf.sanitize_messages(api_messages)
                 if pf.last_report and pf.last_report.had_redactions:
                     logger.info(f"Privacy Filter: Redacted sensitive data from turn payload. Details: {pf.last_report.summary()}")
             except Exception as e:
@@ -8397,27 +8342,6 @@ class AIAgent:
                     new_tcs.append(tc)
                 am["tool_calls"] = new_tcs
 
-            if self._context_snapshot_recorder:
-                try:
-                    self._context_snapshot_recorder.record_call(
-                        api_call_count,
-                        system_prompt=effective_system,
-                        memory_provider_system_prompt=_memory_provider_prompt_cache,
-                        memory_prefetch_raw=_ext_prefetch_cache,
-                        memory_context_block=_current_memory_context_block,
-                        api_user_message=_current_api_user_message,
-                        api_messages=api_messages,
-                        metadata={
-                            "model": self.model,
-                            "provider": self.provider,
-                            "platform": self.platform or "",
-                            "api_mode": self.api_mode,
-                            "memory_providers": [p.name for p in getattr(self._memory_manager, "providers", [])],
-                        },
-                    )
-                except Exception as _snapshot_err:
-                    logger.debug("Context snapshot capture failed: %s", _snapshot_err)
-
             # Calculate approximate request size for logging
             total_chars = sum(len(str(msg)) for msg in api_messages)
             approx_tokens = estimate_messages_tokens_rough(api_messages)

tests/agent/test_anthropic_normalize_v2.py

@@ -0,0 +1,213 @@
+"""Regression tests: normalize_anthropic_response_v2 vs v1.
+
+Constructs mock Anthropic responses and asserts that the v2 function
+(returning NormalizedResponse) produces identical field values to the
+original v1 function (returning SimpleNamespace + finish_reason).
+"""
+
+from types import SimpleNamespace
+
+import pytest
+
+from agent.anthropic_adapter import (
+    normalize_anthropic_response,
+    normalize_anthropic_response_v2,
+)
+from agent.transports.types import NormalizedResponse
+
+
+def _text_block(text: str):
+    return SimpleNamespace(type="text", text=text)
+
+
+def _thinking_block(thinking: str, signature: str = "sig_abc"):
+    return SimpleNamespace(type="thinking", thinking=thinking, signature=signature)
+
+
+def _tool_use_block(id: str, name: str, input: dict):
+    return SimpleNamespace(type="tool_use", id=id, name=name, input=input)
+
+
+def _response(content_blocks, stop_reason="end_turn"):
+    return SimpleNamespace(
+        content=content_blocks,
+        stop_reason=stop_reason,
+        usage=SimpleNamespace(input_tokens=10, output_tokens=5),
+    )
+
+
+class TestTextOnly:
+    def setup_method(self):
+        self.resp = _response([_text_block("Hello world")])
+        self.v1_msg, self.v1_finish = normalize_anthropic_response(self.resp)
+        self.v2 = normalize_anthropic_response_v2(self.resp)
+
+    def test_type(self):
+        assert isinstance(self.v2, NormalizedResponse)
+
+    def test_content_matches(self):
+        assert self.v2.content == self.v1_msg.content
+
+    def test_finish_reason_matches(self):
+        assert self.v2.finish_reason == self.v1_finish
+
+    def test_no_tool_calls(self):
+        assert self.v2.tool_calls is None
+        assert self.v1_msg.tool_calls is None
+
+    def test_no_reasoning(self):
+        assert self.v2.reasoning is None
+        assert self.v1_msg.reasoning is None
+
+
+class TestWithToolCalls:
+    def setup_method(self):
+        self.resp = _response(
+            [
+                _text_block("I'll check that"),
+                _tool_use_block("toolu_abc", "terminal", {"command": "ls"}),
+                _tool_use_block("toolu_def", "read_file", {"path": "/tmp"}),
+            ],
+            stop_reason="tool_use",
+        )
+        self.v1_msg, self.v1_finish = normalize_anthropic_response(self.resp)
+        self.v2 = normalize_anthropic_response_v2(self.resp)
+
+    def test_finish_reason(self):
+        assert self.v2.finish_reason == "tool_calls"
+        assert self.v1_finish == "tool_calls"
+
+    def test_tool_call_count(self):
+        assert len(self.v2.tool_calls) == 2
+        assert len(self.v1_msg.tool_calls) == 2
+
+    def test_tool_call_ids_match(self):
+        for i in range(2):
+            assert self.v2.tool_calls[i].id == self.v1_msg.tool_calls[i].id
+
+    def test_tool_call_names_match(self):
+        assert self.v2.tool_calls[0].name == "terminal"
+        assert self.v2.tool_calls[1].name == "read_file"
+        for i in range(2):
+            assert self.v2.tool_calls[i].name == self.v1_msg.tool_calls[i].function.name
+
+    def test_tool_call_arguments_match(self):
+        for i in range(2):
+            assert self.v2.tool_calls[i].arguments == self.v1_msg.tool_calls[i].function.arguments
+
+    def test_content_preserved(self):
+        assert self.v2.content == self.v1_msg.content
+        assert "check that" in self.v2.content
+
+
+class TestWithThinking:
+    def setup_method(self):
+        self.resp = _response([
+            _thinking_block("Let me think about this carefully..."),
+            _text_block("The answer is 42."),
+        ])
+        self.v1_msg, self.v1_finish = normalize_anthropic_response(self.resp)
+        self.v2 = normalize_anthropic_response_v2(self.resp)
+
+    def test_reasoning_matches(self):
+        assert self.v2.reasoning == self.v1_msg.reasoning
+        assert "think about this" in self.v2.reasoning
+
+    def test_reasoning_details_in_provider_data(self):
+        v1_details = self.v1_msg.reasoning_details
+        v2_details = self.v2.provider_data.get("reasoning_details") if self.v2.provider_data else None
+        assert v1_details is not None
+        assert v2_details is not None
+        assert len(v2_details) == len(v1_details)
+
+    def test_content_excludes_thinking(self):
+        assert self.v2.content == "The answer is 42."
+
+
+class TestMixed:
+    def setup_method(self):
+        self.resp = _response(
+            [
+                _thinking_block("Planning my approach..."),
+                _text_block("I'll run the command"),
+                _tool_use_block("toolu_xyz", "terminal", {"command": "pwd"}),
+            ],
+            stop_reason="tool_use",
+        )
+        self.v1_msg, self.v1_finish = normalize_anthropic_response(self.resp)
+        self.v2 = normalize_anthropic_response_v2(self.resp)
+
+    def test_all_fields_present(self):
+        assert self.v2.content is not None
+        assert self.v2.tool_calls is not None
+        assert self.v2.reasoning is not None
+        assert self.v2.finish_reason == "tool_calls"
+
+    def test_content_matches(self):
+        assert self.v2.content == self.v1_msg.content
+
+    def test_reasoning_matches(self):
+        assert self.v2.reasoning == self.v1_msg.reasoning
+
+    def test_tool_call_matches(self):
+        assert self.v2.tool_calls[0].id == self.v1_msg.tool_calls[0].id
+        assert self.v2.tool_calls[0].name == self.v1_msg.tool_calls[0].function.name
+
+
+class TestStopReasons:
+    @pytest.mark.parametrize("stop_reason,expected", [
+        ("end_turn", "stop"),
+        ("tool_use", "tool_calls"),
+        ("max_tokens", "length"),
+        ("stop_sequence", "stop"),
+        ("refusal", "content_filter"),
+        ("model_context_window_exceeded", "length"),
+        ("unknown_future_reason", "stop"),
+    ])
+    def test_stop_reason_mapping(self, stop_reason, expected):
+        resp = _response([_text_block("x")], stop_reason=stop_reason)
+        _v1_msg, v1_finish = normalize_anthropic_response(resp)
+        v2 = normalize_anthropic_response_v2(resp)
+        assert v2.finish_reason == v1_finish == expected
+
+
+class TestStripToolPrefix:
+    def test_prefix_stripped(self):
+        resp = _response(
+            [_tool_use_block("toolu_1", "mcp_terminal", {"cmd": "ls"})],
+            stop_reason="tool_use",
+        )
+        v1_msg, _ = normalize_anthropic_response(resp, strip_tool_prefix=True)
+        v2 = normalize_anthropic_response_v2(resp, strip_tool_prefix=True)
+        assert v1_msg.tool_calls[0].function.name == "terminal"
+        assert v2.tool_calls[0].name == "terminal"
+
+    def test_prefix_kept(self):
+        resp = _response(
+            [_tool_use_block("toolu_1", "mcp_terminal", {"cmd": "ls"})],
+            stop_reason="tool_use",
+        )
+        v1_msg, _ = normalize_anthropic_response(resp, strip_tool_prefix=False)
+        v2 = normalize_anthropic_response_v2(resp, strip_tool_prefix=False)
+        assert v1_msg.tool_calls[0].function.name == "mcp_terminal"
+        assert v2.tool_calls[0].name == "mcp_terminal"
+
+
+class TestEdgeCases:
+    def test_empty_content_blocks(self):
+        resp = _response([])
+        v1_msg, _v1_finish = normalize_anthropic_response(resp)
+        v2 = normalize_anthropic_response_v2(resp)
+        assert v2.content == v1_msg.content
+        assert v2.content is None
+
+    def test_no_reasoning_details_means_none_provider_data(self):
+        resp = _response([_text_block("hi")])
+        v2 = normalize_anthropic_response_v2(resp)
+        assert v2.provider_data is None
+
+    def test_v2_returns_dataclass_not_namespace(self):
+        resp = _response([_text_block("hi")])
+        v2 = normalize_anthropic_response_v2(resp)
+        assert isinstance(v2, NormalizedResponse)
+        assert not isinstance(v2, SimpleNamespace)

tests/agent/test_context_snapshots.py

@@ -1,43 +0,0 @@
-from pathlib import Path
-
-from agent.context_snapshots import ContextSnapshotRecorder
-
-
-def test_disabled_recorder_writes_nothing(tmp_path):
-    recorder = ContextSnapshotRecorder(session_id="session-1", enabled=False, base_dir=tmp_path)
-
-    out = recorder.record_call(
-        1,
-        system_prompt="system",
-        api_messages=[{"role": "user", "content": "hello"}],
-    )
-
-    assert out is None
-    assert not (tmp_path / "session-1").exists()
-
-
-def test_enabled_recorder_writes_expected_artifacts(tmp_path):
-    recorder = ContextSnapshotRecorder(session_id="session-1", enabled=True, base_dir=tmp_path)
-
-    out = recorder.record_call(
-        1,
-        system_prompt="system prompt",
-        memory_provider_system_prompt="# Hindsight Memory\nActive.",
-        memory_prefetch_raw="- remembered fact",
-        memory_context_block="<memory-context>\nremembered\n</memory-context>",
-        api_user_message="What do I prefer?\n\n<memory-context>\nremembered\n</memory-context>",
-        api_messages=[
-            {"role": "system", "content": "system prompt"},
-            {"role": "user", "content": "What do I prefer?"},
-        ],
-        metadata={"provider": "openai", "memory_providers": ["builtin", "hindsight"]},
-    )
-
-    assert out == tmp_path / "session-1" / "call_001"
-    assert (out / "system_prompt.txt").read_text(encoding="utf-8") == "system prompt"
-    assert (out / "memory_provider_system_prompt.txt").read_text(encoding="utf-8").startswith("# Hindsight Memory")
-    assert (out / "memory_prefetch_raw.txt").read_text(encoding="utf-8") == "- remembered fact"
-    assert "<memory-context>" in (out / "memory_context_block.txt").read_text(encoding="utf-8")
-    assert "What do I prefer?" in (out / "api_user_message.txt").read_text(encoding="utf-8")
-    assert (out / "api_messages.json").read_text(encoding="utf-8").startswith("[")
-    assert '"hindsight"' in (out / "metadata.json").read_text(encoding="utf-8")

tests/agent/transports/test_transport.py

@@ -0,0 +1,208 @@
+"""Tests for the transport ABC, registry, and AnthropicTransport."""
+
+from types import SimpleNamespace
+
+import pytest
+
+from agent.transports import _REGISTRY, get_transport, register_transport
+from agent.transports.base import ProviderTransport
+from agent.transports.types import NormalizedResponse
+
+
+class TestProviderTransportABC:
+    def test_cannot_instantiate_abc(self):
+        with pytest.raises(TypeError):
+            ProviderTransport()
+
+    def test_concrete_must_implement_all_abstract(self):
+        class Incomplete(ProviderTransport):
+            @property
+            def api_mode(self):
+                return "test"
+
+        with pytest.raises(TypeError):
+            Incomplete()
+
+    def test_minimal_concrete(self):
+        class Minimal(ProviderTransport):
+            @property
+            def api_mode(self):
+                return "test_minimal"
+
+            def convert_messages(self, messages, **kw):
+                return messages
+
+            def convert_tools(self, tools):
+                return tools
+
+            def build_kwargs(self, model, messages, tools=None, **params):
+                return {"model": model, "messages": messages}
+
+            def normalize_response(self, response, **kw):
+                return NormalizedResponse(content="ok", tool_calls=None, finish_reason="stop")
+
+        t = Minimal()
+        assert t.api_mode == "test_minimal"
+        assert t.validate_response(None) is True
+        assert t.extract_cache_stats(None) is None
+        assert t.map_finish_reason("end_turn") == "end_turn"
+
+
+class TestTransportRegistry:
+    def test_get_unregistered_returns_none(self):
+        assert get_transport("nonexistent_mode") is None
+
+    def test_anthropic_registered_on_import(self):
+        import agent.transports.anthropic  # noqa: F401
+
+        t = get_transport("anthropic_messages")
+        assert t is not None
+        assert t.api_mode == "anthropic_messages"
+
+    def test_register_and_get(self):
+        class DummyTransport(ProviderTransport):
+            @property
+            def api_mode(self):
+                return "dummy_test"
+
+            def convert_messages(self, messages, **kw):
+                return messages
+
+            def convert_tools(self, tools):
+                return tools
+
+            def build_kwargs(self, model, messages, tools=None, **params):
+                return {}
+
+            def normalize_response(self, response, **kw):
+                return NormalizedResponse(content=None, tool_calls=None, finish_reason="stop")
+
+        register_transport("dummy_test", DummyTransport)
+        t = get_transport("dummy_test")
+        assert t.api_mode == "dummy_test"
+        _REGISTRY.pop("dummy_test", None)
+
+
+class TestAnthropicTransport:
+    @pytest.fixture
+    def transport(self):
+        import agent.transports.anthropic  # noqa: F401
+
+        return get_transport("anthropic_messages")
+
+    def test_api_mode(self, transport):
+        assert transport.api_mode == "anthropic_messages"
+
+    def test_convert_tools_simple(self, transport):
+        tools = [{
+            "type": "function",
+            "function": {
+                "name": "test_tool",
+                "description": "A test",
+                "parameters": {"type": "object", "properties": {}},
+            },
+        }]
+        result = transport.convert_tools(tools)
+        assert len(result) == 1
+        assert result[0]["name"] == "test_tool"
+        assert "input_schema" in result[0]
+
+    def test_validate_response_none(self, transport):
+        assert transport.validate_response(None) is False
+
+    def test_validate_response_empty_content(self, transport):
+        r = SimpleNamespace(content=[])
+        assert transport.validate_response(r) is False
+
+    def test_validate_response_valid(self, transport):
+        r = SimpleNamespace(content=[SimpleNamespace(type="text", text="hello")])
+        assert transport.validate_response(r) is True
+
+    def test_map_finish_reason(self, transport):
+        assert transport.map_finish_reason("end_turn") == "stop"
+        assert transport.map_finish_reason("tool_use") == "tool_calls"
+        assert transport.map_finish_reason("max_tokens") == "length"
+        assert transport.map_finish_reason("stop_sequence") == "stop"
+        assert transport.map_finish_reason("refusal") == "content_filter"
+        assert transport.map_finish_reason("model_context_window_exceeded") == "length"
+        assert transport.map_finish_reason("unknown") == "stop"
+
+    def test_extract_cache_stats_none_usage(self, transport):
+        r = SimpleNamespace(usage=None)
+        assert transport.extract_cache_stats(r) is None
+
+    def test_extract_cache_stats_with_cache(self, transport):
+        usage = SimpleNamespace(cache_read_input_tokens=100, cache_creation_input_tokens=50)
+        r = SimpleNamespace(usage=usage)
+        result = transport.extract_cache_stats(r)
+        assert result == {"cached_tokens": 100, "creation_tokens": 50}
+
+    def test_extract_cache_stats_zero(self, transport):
+        usage = SimpleNamespace(cache_read_input_tokens=0, cache_creation_input_tokens=0)
+        r = SimpleNamespace(usage=usage)
+        assert transport.extract_cache_stats(r) is None
+
+    def test_normalize_response_text(self, transport):
+        r = SimpleNamespace(
+            content=[SimpleNamespace(type="text", text="Hello world")],
+            stop_reason="end_turn",
+            usage=SimpleNamespace(input_tokens=10, output_tokens=5),
+            model="claude-sonnet-4-6",
+        )
+        nr = transport.normalize_response(r)
+        assert isinstance(nr, NormalizedResponse)
+        assert nr.content == "Hello world"
+        assert nr.tool_calls is None or nr.tool_calls == []
+        assert nr.finish_reason == "stop"
+
+    def test_normalize_response_tool_calls(self, transport):
+        r = SimpleNamespace(
+            content=[
+                SimpleNamespace(type="tool_use", id="toolu_123", name="terminal", input={"command": "ls"}),
+            ],
+            stop_reason="tool_use",
+            usage=SimpleNamespace(input_tokens=10, output_tokens=20),
+            model="claude-sonnet-4-6",
+        )
+        nr = transport.normalize_response(r)
+        assert nr.finish_reason == "tool_calls"
+        assert len(nr.tool_calls) == 1
+        tc = nr.tool_calls[0]
+        assert tc.name == "terminal"
+        assert tc.id == "toolu_123"
+        assert '"command"' in tc.arguments
+
+    def test_normalize_response_thinking(self, transport):
+        r = SimpleNamespace(
+            content=[
+                SimpleNamespace(type="thinking", thinking="Let me think..."),
+                SimpleNamespace(type="text", text="The answer is 42"),
+            ],
+            stop_reason="end_turn",
+            usage=SimpleNamespace(input_tokens=10, output_tokens=15),
+            model="claude-sonnet-4-6",
+        )
+        nr = transport.normalize_response(r)
+        assert nr.content == "The answer is 42"
+        assert nr.reasoning == "Let me think..."
+
+    def test_build_kwargs_returns_dict(self, transport):
+        messages = [{"role": "user", "content": "Hello"}]
+        kw = transport.build_kwargs(
+            model="claude-sonnet-4-6",
+            messages=messages,
+            max_tokens=1024,
+        )
+        assert isinstance(kw, dict)
+        assert "model" in kw
+        assert "max_tokens" in kw
+        assert "messages" in kw
+
+    def test_convert_messages_extracts_system(self, transport):
+        messages = [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "user", "content": "Hi"},
+        ]
+        system, msgs = transport.convert_messages(messages)
+        assert system is not None
+        assert len(msgs) >= 1

tests/agent/transports/test_types.py

@@ -0,0 +1,130 @@
+"""Tests for agent/transports/types.py — dataclass construction + helpers."""
+
+import json
+
+from agent.transports.types import (
+    NormalizedResponse,
+    ToolCall,
+    Usage,
+    build_tool_call,
+    map_finish_reason,
+)
+
+
+class TestToolCall:
+    def test_basic_construction(self):
+        tc = ToolCall(id="call_abc", name="terminal", arguments='{"cmd": "ls"}')
+        assert tc.id == "call_abc"
+        assert tc.name == "terminal"
+        assert tc.arguments == '{"cmd": "ls"}'
+        assert tc.provider_data is None
+
+    def test_none_id(self):
+        tc = ToolCall(id=None, name="read_file", arguments="{}")
+        assert tc.id is None
+
+    def test_provider_data(self):
+        tc = ToolCall(
+            id="call_x",
+            name="t",
+            arguments="{}",
+            provider_data={"call_id": "call_x", "response_item_id": "fc_x"},
+        )
+        assert tc.provider_data["call_id"] == "call_x"
+        assert tc.provider_data["response_item_id"] == "fc_x"
+
+
+class TestUsage:
+    def test_defaults(self):
+        u = Usage()
+        assert u.prompt_tokens == 0
+        assert u.completion_tokens == 0
+        assert u.total_tokens == 0
+        assert u.cached_tokens == 0
+
+    def test_explicit(self):
+        u = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150, cached_tokens=80)
+        assert u.total_tokens == 150
+
+
+class TestNormalizedResponse:
+    def test_text_only(self):
+        r = NormalizedResponse(content="hello", tool_calls=None, finish_reason="stop")
+        assert r.content == "hello"
+        assert r.tool_calls is None
+        assert r.finish_reason == "stop"
+        assert r.reasoning is None
+        assert r.usage is None
+        assert r.provider_data is None
+
+    def test_with_tool_calls(self):
+        tcs = [ToolCall(id="call_1", name="terminal", arguments='{"cmd":"pwd"}')]
+        r = NormalizedResponse(content=None, tool_calls=tcs, finish_reason="tool_calls")
+        assert r.finish_reason == "tool_calls"
+        assert len(r.tool_calls) == 1
+        assert r.tool_calls[0].name == "terminal"
+
+    def test_with_reasoning(self):
+        r = NormalizedResponse(
+            content="answer",
+            tool_calls=None,
+            finish_reason="stop",
+            reasoning="I thought about it",
+        )
+        assert r.reasoning == "I thought about it"
+
+    def test_with_provider_data(self):
+        r = NormalizedResponse(
+            content=None,
+            tool_calls=None,
+            finish_reason="stop",
+            provider_data={"reasoning_details": [{"type": "thinking", "thinking": "hmm"}]},
+        )
+        assert r.provider_data["reasoning_details"][0]["type"] == "thinking"
+
+
+class TestBuildToolCall:
+    def test_dict_arguments_serialized(self):
+        tc = build_tool_call(id="call_1", name="terminal", arguments={"cmd": "ls"})
+        assert tc.arguments == json.dumps({"cmd": "ls"})
+        assert tc.provider_data is None
+
+    def test_string_arguments_passthrough(self):
+        tc = build_tool_call(id="call_2", name="read_file", arguments='{"path": "/tmp"}')
+        assert tc.arguments == '{"path": "/tmp"}'
+
+    def test_provider_fields(self):
+        tc = build_tool_call(
+            id="call_3",
+            name="terminal",
+            arguments="{}",
+            call_id="call_3",
+            response_item_id="fc_3",
+        )
+        assert tc.provider_data == {"call_id": "call_3", "response_item_id": "fc_3"}
+
+    def test_none_id(self):
+        tc = build_tool_call(id=None, name="t", arguments="{}")
+        assert tc.id is None
+
+
+class TestMapFinishReason:
+    ANTHROPIC_MAP = {
+        "end_turn": "stop",
+        "tool_use": "tool_calls",
+        "max_tokens": "length",
+        "stop_sequence": "stop",
+        "refusal": "content_filter",
+    }
+
+    def test_known_reason(self):
+        assert map_finish_reason("end_turn", self.ANTHROPIC_MAP) == "stop"
+        assert map_finish_reason("tool_use", self.ANTHROPIC_MAP) == "tool_calls"
+        assert map_finish_reason("max_tokens", self.ANTHROPIC_MAP) == "length"
+        assert map_finish_reason("refusal", self.ANTHROPIC_MAP) == "content_filter"
+
+    def test_unknown_reason_defaults_to_stop(self):
+        assert map_finish_reason("something_new", self.ANTHROPIC_MAP) == "stop"
+
+    def test_none_reason(self):
+        assert map_finish_reason(None, self.ANTHROPIC_MAP) == "stop"

tests/plugins/memory/test_hindsight_provider.py

@@ -596,26 +596,3 @@ class TestAvailability:
         monkeypatch.setenv("HINDSIGHT_MODE", "local")
         p = HindsightMemoryProvider()
         assert p.is_available()
-
-    def test_local_embedded_profile_defaults_to_agent_identity(self, tmp_path, monkeypatch):
-        config_path = tmp_path / "hindsight" / "config.json"
-        config_path.parent.mkdir(parents=True, exist_ok=True)
-        config_path.write_text(json.dumps({
-            "mode": "local_embedded",
-            "llm_provider": "ollama",
-            "llm_model": "gemma3:12b",
-        }))
-        monkeypatch.setattr(
-            "plugins.memory.hindsight.get_hermes_home",
-            lambda: tmp_path,
-        )
-
-        p = HindsightMemoryProvider()
-        p.initialize(
-            session_id="test-session",
-            hermes_home=str(tmp_path / "profiles" / "atlas-hindsight"),
-            platform="cli",
-            agent_identity="atlas-hindsight",
-        )
-
-        assert p._config["profile"] == "atlas-hindsight"

tests/run_agent/test_run_agent_context_snapshots.py

@@ -1,94 +0,0 @@
-from pathlib import Path
-from types import SimpleNamespace
-from unittest.mock import MagicMock, patch
-import importlib
-import sys
-import types
-
-
-
-def _make_tool_defs(*names: str) -> list:
-    return [
-        {
-            "type": "function",
-            "function": {
-                "name": n,
-                "description": f"{n} tool",
-                "parameters": {"type": "object", "properties": {}},
-            },
-        }
-        for n in names
-    ]
-
-
-
-def _mock_response(content="Done", finish_reason="stop"):
-    msg = SimpleNamespace(content=content, tool_calls=None)
-    choice = SimpleNamespace(message=msg, finish_reason=finish_reason)
-    return SimpleNamespace(choices=[choice], usage=SimpleNamespace(prompt_tokens=1, completion_tokens=1, total_tokens=2))
-
-
-
-def _load_ai_agent():
-    sys.modules.setdefault("agent.auxiliary_client", types.SimpleNamespace(call_llm=lambda *a, **k: ""))
-    run_agent = importlib.import_module("run_agent")
-    return run_agent.AIAgent
-
-
-
-def test_run_conversation_writes_context_snapshot_artifacts(tmp_path):
-    AIAgent = _load_ai_agent()
-
-    class _FakePrivacyFilter:
-        def __init__(self):
-            self.last_report = None
-
-        def sanitize_messages(self, messages):
-            return list(messages)
-
-    with (
-        patch("run_agent.get_tool_definitions", return_value=_make_tool_defs("web_search")),
-        patch("run_agent.check_toolset_requirements", return_value={}),
-        patch("run_agent.OpenAI"),
-        patch("hermes_cli.plugins.invoke_hook", return_value=[]),
-        patch.dict(sys.modules, {"agent.privacy_filter": types.SimpleNamespace(PrivacyFilter=_FakePrivacyFilter)}),
-    ):
-        agent = AIAgent(
-            api_key="test-key-1234567890",
-            base_url="https://example.com/v1",
-            quiet_mode=True,
-            skip_context_files=True,
-            skip_memory=True,
-            context_snapshots_enabled=True,
-            context_snapshots_dir=str(tmp_path),
-        )
-
-    agent.client = MagicMock()
-    agent.client.chat.completions.create.return_value = _mock_response(content="Done")
-    agent._build_system_prompt = MagicMock(return_value="Core system prompt")
-    agent._memory_manager = MagicMock()
-    agent._memory_manager.prefetch_all.return_value = "- remembered preference"
-    agent._memory_manager.build_system_prompt.return_value = "# Hindsight Memory\nActive."
-    agent._memory_manager.providers = [
-        SimpleNamespace(name="builtin"),
-        SimpleNamespace(name="hindsight"),
-    ]
-
-    result = agent.run_conversation("What do I prefer?")
-
-    assert result["final_response"] == "Done"
-
-    call_dir = tmp_path / agent.session_id / "call_001"
-    assert call_dir.exists()
-    assert (call_dir / "system_prompt.txt").read_text(encoding="utf-8") == "Core system prompt"
-    assert (call_dir / "memory_provider_system_prompt.txt").read_text(encoding="utf-8").startswith("# Hindsight Memory")
-    assert (call_dir / "memory_prefetch_raw.txt").read_text(encoding="utf-8") == "- remembered preference"
-    assert "<memory-context>" in (call_dir / "memory_context_block.txt").read_text(encoding="utf-8")
-    api_user_message = (call_dir / "api_user_message.txt").read_text(encoding="utf-8")
-    assert "What do I prefer?" in api_user_message
-    assert "remembered preference" in api_user_message
-    api_messages = (call_dir / "api_messages.json").read_text(encoding="utf-8")
-    assert '"role": "system"' in api_messages
-    assert '"role": "user"' in api_messages
-    metadata = (call_dir / "metadata.json").read_text(encoding="utf-8")
-    assert '"hindsight"' in metadata

tests/test_hindsight_local_eval_doc.py

@@ -1,22 +0,0 @@
-from pathlib import Path
-
-
-ROOT = Path(__file__).resolve().parents[1]
-DOC = ROOT / "docs" / "hindsight-local-eval.md"
-
-
-def test_hindsight_local_eval_doc_exists_and_covers_switching():
-    assert DOC.exists(), "missing Hindsight local eval doc"
-    text = DOC.read_text(encoding="utf-8")
-    for snippet in (
-        "atlas-baseline",
-        "atlas-mempalace",
-        "atlas-hindsight",
-        "HERMES_HOME",
-        "HERMES_CONTEXT_SNAPSHOTS",
-        "memory_prefetch_raw.txt",
-        "api_user_message.txt",
-        "local_embedded",
-        "hindsight/config.json",
-    ):
-        assert snippet in text