<local-command-caveat>Caveat: The messages below were generated by the user while running local commands. DO NOT respond to these messages or otherwise consider them in your response unless the user explicitly asks you to.</local-command-caveat>


<command-name>/clear</command-name>
            <command-message>clear</command-message>
            <command-args></command-args>


<local-command-stdout></local-command-stdout>


我刚才在slack的health bot输入“同步佳明数据”，为什么它同步的是昨天的数据，而不是最新的


我来帮你解决这个问题。首先，我需要查看项目的代码结构，找到处理"同步佳明数据"请求的相关代码，看看为什么它同步的是昨天的数据而不是最新的。

让我先查看项目的基本结构。


让我先查看项目的基本结构，找到处理同步佳明数据的代码。


Bash

列出项目根目录的文件和文件夹


total 1456
drwxr-xr-x 20 root root    4096 Mar  6 10:08 .
drwxr-xr-x  5  501 games     60 Mar  3 20:01 ..
drwxr-xr-x  3  501 games     37 Jan 22 10:06 .agent
-rw-r--r--  1 root root   24803 Mar  2 10:58 BOT_FEATURES_REFERENCE.md
-rw-r--r--  1  501 games   2812 Feb  2 10:56 BOT_FIX_SUMMARY.md
-rw-r--r--  1  501 games 751467 Feb 15 10:48 bulter-tag20260215.tgz
-rw-r--r--  1  501 games   5114 Jan 22 11:30 Butler-Bot使用指南.md
-rw-r--r--  1 root root  317105 Mar  2 10:48 butler-tag20260302.tgz
drwxr-xr-x  3  501 games     49 Mar  6 11:02 .claude
-rw-r--r--  1  501 games   1236 Jan 19 13:35 CLAUDE.md
-rw-r--r--  1 root root    2950 Mar  2 10:57 CONFIGURATION_SUMMARY.md
-rw-r--r--  1 root root   53248 Mar  2 17:44 .coverage
drwxr-xr-x  3  501 games     54 Feb  6 15:21 data
-rw-r--r--  1  501 games  24884 Feb  5 20:43 debug_failed_payload.json
-rw-r--r--  1  501 games  23142 Feb  6 11:23 debug_request.json
-rw-r--r--  1  501 games     95 Feb  6 11:23 debug_response.json
-rw-r--r--  1  501 games   4596 Jan 19 14:04 decision.md
-rw-r--r--  1  501 games   6743 Jan 22 14:49 distilled_insights.md
drwxr-xr-x  3  501 games   4096 Mar  2 23:18 docs
-rw-r--r--  1 root root    1095 Mar  3 20:05 .env
-rw-r--r--  1  501 games    879 Jan 20 18:22 .env.backup
-rw-r--r--  1  501 games    876 Jan 20 18:30 .env.backup.20260120_183006
-rw-r--r--  1 root root    1304 Mar  2 11:57 .env.example
-rw-r--r--  1  501 games    489 Jan 20 18:16 .env.gemini.example
-rw-r--r--  1  501 games    120 Jan 20 18:30 .env.updated
drwxr-xr-x  2  501 games    168 Mar  2 09:41 experiments
-rw-r--r--  1  501 games     85 Jan 23 12:00 .gemini.api.env
lrwxrwxrwx  1  501 games     22 Feb  6 15:33 .gemini.current.env -> .gemini.openrouter.env
-rw-r--r--  1  501 games    120 Feb  6 14:24 .gemini.local.env
-rw-r--r--  1  501 games    284 Feb  6 11:05 .gemini.notools.env
-rw-r--r--  1  501 games    312 Feb  6 15:19 .gemini.openrouter.env
drwxr-xr-x  9  501 games    142 Mar  2 17:26 health
-rw-r--r--  1  501 games   4188 Jan 19 13:46 health.md
-rwxr-xr-x  1  501 games   3989 Feb  4 15:26 h.sh
drwxr-xr-x  2 root root    4096 Mar  2 17:44 htmlcov
-rw-r--r--  1  501 games    481 Jan 22 14:46 list_samples.py
drwxr-xr-x  2  501 games   4096 Mar  9 11:00 logs
-rw-r--r--  1  501 games    473 Feb  2 10:25 m1.py
-rw-r--r--  1  501 games    473 Feb  2 10:25 m2.py
-rw-r--r--  1  501 games   5361 Jan 20 14:49 mannul-data-input.md
-rw-r--r--  1 root root    3044 Mar  2 14:32 methodology.md
-rwxr-xr-x  1  501 games   2034 Jan 20 13:23 monitor-current-claude-endpoint.sh
-rw-r--r--  1 root root   18310 Mar  6 09:31 POWELL_REVISE.md
drwxr-xr-x  3  501 games     70 Jan 20 08:58 .pytest_cache
-rw-r--r--  1 root root     334 Mar  2 15:29 pytest.ini
-rw-r--r--  1  501 games   1926 Jan 20 18:32 quick_test.py
-rw-r--r--  1 root root   32992 Mar  2 10:57 README.md
-rw-r--r--  1  501 games   3830 Jan 22 13:26 REPLY-SAMPLE.md
-rw-r--r--  1 root root     814 Mar  3 19:19 requirements.txt
drwxr-xr-x  3  501 games   4096 Mar  6 10:45 scripts
drwxr-xr-x  2  501 games    139 Jan 20 17:38 skills
drwxr-xr-x 10  501 games   4096 Mar  3 19:35 slack_bot
-rw-r--r--  1  501 games   5700 Jan 20 18:06 SLACK_BOT_OPTIMIZATION.md
-rw-r--r--  1  501 games   2450 Jan 20 18:04 smoke_test.py
drwxr-xr-x 12  501 games   4096 Feb 15 10:47 tag20260215
drwxr-xr-x 14 root root    4096 Mar  2 10:38 tag20260302
drwxr-xr-x  7  501 games   4096 Mar  2 17:42 tests
-rw-r--r--  1  501 games      0 Feb 15 10:30 tmate-out-62841.log
drwxr-xr-x  2  501 games     24 Feb  5 18:21 tools
drwxr-xr-x  6 root root      87 Mar  3 11:52 venv
-rw-r--r--  1 root root    3077 Mar  2 14:27 writing_style.md
-rw-r--r--  1 root root    6241 Mar  6 10:08 zhihu-bot-style.md
-rw-r--r--  1 root root    3008 Mar  4 11:14 zhihu-hunter-guide.md
drwxr-xr-x  2  501 games    153 Feb  4 10:44 zhihu-sample
-rw-r--r--  1 root root   16005 Mar  5 18:25 zhihu-style.md


好的，现在我需要找到处理“同步佳明数据”的代码。根据项目结构和之前的记忆，应该在 slack_bot 或者 health 目录下。我先看一下 slack_bot 目录下的内容，特别是 main.py 文件。


让我查看 slack_bot 目录，找到处理健康机器人的主要代码：


/root/projects/butler/slack_bot/__init__.py
/root/projects/butler/slack_bot/llm/base.py
/root/projects/butler/slack_bot/context/compressor.py
/root/projects/butler/slack_bot/tools/obsidian.py
/root/projects/butler/slack_bot/context/storage.py
/root/projects/butler/slack_bot/tools/health_write.py
/root/projects/butler/slack_bot/tools/garmin.py
/root/projects/butler/slack_bot/utils/mrkdwn.py
/root/projects/butler/slack_bot/tools/analytics.py
/root/projects/butler/slack_bot/obsidian/__init__.py
/root/projects/butler/slack_bot/obsidian/cli.py
/root/projects/butler/slack_bot/shell/manager.py
/root/projects/butler/slack_bot/shell/__init__.py
/root/projects/butler/slack_bot/tools/shell_tool.py
/root/projects/butler/slack_bot/shell/session.py
/root/projects/butler/slack_bot/tools/file_ops.py
/root/projects/butler/slack_bot/tools/system_ops.py
/root/projects/butler/slack_bot/tools/web.py
/root/projects/butler/slack_bot/tools/process_ops.py
/root/projects/butler/slack_bot/obsidian/indexer.py
/root/projects/butler/slack_bot/tools/registry.py
/root/projects/butler/slack_bot/dispatcher.backup.py
/root/projects/butler/slack_bot/main.py
/root/projects/butler/slack_bot/tools/groups.py
/root/projects/butler/slack_bot/shell/help_text.py
/root/projects/butler/slack_bot/shell_main.py
/root/projects/butler/slack_bot/llm/gemini.py
/root/projects/butler/slack_bot/dispatcher.py
/root/projects/butler/slack_bot/tools/health_read.py
/root/projects/butler/slack_bot/obsidian/embeddings.py
/root/projects/butler/slack_bot/obsidian/vector_store.py
/root/projects/butler/slack_bot/zhihu/__init__.py
/root/projects/butler/slack_bot/obsidian/note_ingester.py
/root/projects/butler/slack_bot/zhihu/slack_interactive_gateway.py
/root/projects/butler/slack_bot/zhihu/zhihu_playwright_engine.py
/root/projects/butler/slack_bot/obsidian/dispatcher.py
/root/projects/butler/slack_bot/zhihu/zhihu_hunter.py
/root/projects/butler/slack_bot/obsidian/generators.py


太好了，我找到了几个可能相关的文件：
1. `/root/projects/butler/slack_bot/tools/garmin.py` - 处理 Garmin 数据同步的工具
2. `/root/projects/butler/slack_bot/main.py` - 健康机器人的主要入口点
3. `/root/projects/butler/health/` - 健康数据处理的核心代码

我先查看 `garmin.py` 文件，因为它最可能包含同步佳明数据的逻辑。


让我查看处理佳明数据同步的 garmin.py 文件：


     1→from datetime import date
     2→from health.services.data_sync import HealthDataSync
     3→from health.utils.logging_config import setup_logger
     4→
     5→logger = setup_logger(__name__)
     6→
     7→class GarminTool:
     8→    @staticmethod
     9→    def sync_garmin(target_date: str = None) -> str:
    10→        """
    11→        Sync health data from Garmin Connect.
    12→        Args:
    13→            target_date: YYYY-MM-DD or None (defaults to today)
    14→        """
    15→        try:
    16→            if target_date:
    17→                date_obj = date.fromisoformat(target_date)
    18→            else:
    19→                date_obj = date.today()
    20→
    21→            logger.info(f"Starting Garmin sync for {date_obj}...")
    22→            sync = HealthDataSync()
    23→            sync.authenticate()
    24→
    25→            # Sync for the specific single date, force update
    26→            results = sync.sync_all_metrics(date_obj, date_obj, force=True)
    27→
    28→            summary_parts = []
    29→            for metric, stats in results.items():
    30→                if stats.get("synced", 0) > 0:
    31→                    summary_parts.append(f"{metric}: {stats['synced']} files")
    32→
    33→            if not summary_parts:
    34→                return f"Sync complete for {date_obj}, but no new data found."
    35→
    36→            # If we synced successfully, fetch the latest data to return to the user
    37→            from .health_read import HealthReader
    38→            latest_stats = HealthReader.get_daily_detailed_stats(target_date=date_obj.isoformat())
    39→
    40→            return f"Successfully synced Garmin data for {date_obj}: {', '.join(summary_parts)}.\n\nLatest Stats: {latest_stats}"
    41→
    42→        except Exception as e:
    43→            logger.error(f"Garmin sync error: {e}")
    44→            return f"Error syncing Garmin: {str(e)}"
    45→

<system-reminder>
Whenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.
</system-reminder>

from datetime import date
from health.services.data_sync import HealthDataSync
from health.utils.logging_config import setup_logger

logger = setup_logger(__name__)

class GarminTool:
    @staticmethod
    def sync_garmin(target_date: str = None) -> str:
        """
        Sync health data from Garmin Connect.
        Args:
            target_date: YYYY-MM-DD or None (defaults to today)
        """
        try:
            if target_date:
                date_obj = date.fromisoformat(target_date)
            else:
                date_obj = date.today()

            logger.info(f"Starting Garmin sync for {date_obj}...")
            sync = HealthDataSync()
            sync.authenticate()

            # Sync for the specific single date, force update
            results = sync.sync_all_metrics(date_obj, date_obj, force=True)

            summary_parts = []
            for metric, stats in results.items():
                if stats.get("synced", 0) > 0:
                    summary_parts.append(f"{metric}: {stats['synced']} files")

            if not summary_parts:
                return f"Sync complete for {date_obj}, but no new data found."

            # If we synced successfully, fetch the latest data to return to the user
            from .health_read import HealthReader
            latest_stats = HealthReader.get_daily_detailed_stats(target_date=date_obj.isoformat())

            return f"Successfully synced Garmin data for {date_obj}: {', '.join(summary_parts)}.\n\nLatest Stats: {latest_stats}"

        except Exception as e:
            logger.error(f"Garmin sync error: {e}")
            return f"Error syncing Garmin: {str(e)}"


好的，我看到 garmin.py 文件里的 sync_garmin 函数默认使用 date.today()。现在让我查看 HealthDataSync 类，看看它的实现是什么样的，特别是 sync_all_metrics 函数。


现在让我查看 HealthDataSync 类的实现，特别是 sync_all_metrics 函数：


Found 1 file
health/services/data_sync.py


好的，找到了 HealthDataSync 类在 /root/projects/butler/health/services/data_sync.py 文件中。我现在查看这个文件的内容。


     1→"""
     2→Data synchronization orchestration service.
     3→
     4→Coordinates Garmin API data fetching, storage, and incremental sync logic.
     5→"""
     6→
     7→from datetime import date, timedelta
     8→from typing import List, Dict, Any, Optional, Tuple
     9→from pathlib import Path
    10→
    11→from health import config
    12→from health.services.garmin_client import GarminHealthClient
    13→from health.services.storage import HealthStorage
    14→from health.db.repository import HealthRepository
    15→from health.utils.exceptions import SyncError, GarminAPIError
    16→from health.utils.date_utils import (
    17→    parse_date,
    18→    date_range,
    19→    split_date_range,
    20→    get_yesterday,
    21→    format_date,
    22→)
    23→from health.utils.logging_config import setup_logger
    24→
    25→logger = setup_logger(__name__)
    26→
    27→
    28→class HealthDataSync:
    29→    """Service for orchestrating health data synchronization."""
    30→
    31→    def __init__(
    32→        self,
    33→        client: Optional[GarminHealthClient] = None,
    34→        storage: Optional[HealthStorage] = None,
    35→        repo: Optional[HealthRepository] = None,
    36→    ) -> None:
    37→        """Initialize sync service.
    38→
    39→        Args:
    40→            client: Optional Garmin client (creates new if not provided)
    41→            storage: Optional storage service (creates new if not provided)
    42→            repo: Optional repository (creates new if not provided)
    43→        """
    44→        self.client = client or GarminHealthClient()
    45→        self.storage = storage or HealthStorage()
    46→        self.repo = repo or HealthRepository()
    47→
    48→    def authenticate(self) -> None:
    49→        """Authenticate with Garmin Connect.
    50→
    51→        Raises:
    52→            GarminAuthError: If authentication fails
    53→        """
    54→        logger.info("Authenticating with Garmin...")
    55→        self.client.authenticate()
    56→        logger.info("Authentication successful")
    57→
    58→    def sync_daily_metric(
    59→        self, metric_type: str, target_date: date, force: bool = False
    60→    ) -> bool:
    61→        """Sync a single daily metric for a specific date.
    62→
    63→        Args:
    64→            metric_type: Type of metric to sync
    65→            target_date: Date to sync
    66→            force: If True, re-sync even if data already exists
    67→
    68→        Returns:
    69→            True if data was synced, False if skipped or no data available
    70→        """
    71→        # Check if already synced (unless forcing)
    72→        if not force and self.storage.metric_exists(metric_type, target_date):
    73→            logger.debug(f"Skipping {metric_type} for {target_date} (already synced)")
    74→            return False
    75→
    76→        # Get the appropriate fetch method
    77→        fetch_method = getattr(self.client, f"fetch_{metric_type}", None)
    78→        if not fetch_method:
    79→            logger.warning(f"No fetch method for metric type: {metric_type}")
    80→            return False
    81→
    82→        try:
    83→            # Fetch data from Garmin
    84→            data = fetch_method(target_date)
    85→
    86→            if not data:
    87→                logger.debug(f"No {metric_type} data available for {target_date}")
    88→                return False
    89→
    90→            # Save to storage
    91→            self.storage.save_daily_metric(data, metric_type)
    92→            logger.info(f"✓ Synced {metric_type} for {target_date}")
    93→            return True
    94→
    95→        except GarminAPIError as e:
    96→            logger.error(f"API error syncing {metric_type} for {target_date}: {e}")
    97→            raise
    98→        except Exception as e:
    99→            logger.error(f"Error syncing {metric_type} for {target_date}: {e}")
   100→            return False
   101→
   102→    def sync_daily_metrics_range(
   103→        self,
   104→        metric_type: str,
   105→        start_date: date,
   106→        end_date: date,
   107→        force: bool = False,
   108→    ) -> Dict[str, int]:
   109→        """Sync a daily metric for a date range.
   110→
   111→        Args:
   112→            metric_type: Type of metric to sync
   113→            start_date: Start date (inclusive)
   114→            end_date: End date (inclusive)
   115→            force: If True, re-sync existing data
   116→
   117→        Returns:
   118→            Statistics dictionary with sync counts
   119→        """
   120→        logger.info(
   121→            f"Syncing {metric_type} from {start_date} to {end_date} "
   122→            f"({(end_date - start_date).days + 1} days)"
   123→        )
   124→
   125→        stats = {"synced": 0, "skipped": 0, "errors": 0}
   126→
   127→        for current_date in date_range(start_date, end_date):
   128→            try:
   129→                if self.sync_daily_metric(metric_type, current_date, force=force):
   130→                    stats["synced"] += 1
   131→                else:
   132→                    stats["skipped"] += 1
   133→
   134→            except GarminAPIError as e:
   135→                logger.error(f"API error on {current_date}: {e}")
   136→                stats["errors"] += 1
   137→                # Continue with other dates even if one fails
   138→                continue
   139→
   140→        logger.info(
   141→            f"{metric_type} sync complete: "
   142→            f"{stats['synced']} synced, {stats['skipped']} skipped, "
   143→            f"{stats['errors']} errors"
   144→        )
   145→
   146→        return stats
   147→
   148→    def sync_activities_range(
   149→        self, start_date: date, end_date: date, force: bool = False
   150→    ) -> Dict[str, int]:
   151→        """Sync activities for a date range.
   152→
   153→        Args:
   154→            start_date: Start date
   155→            end_date: End date
   156→            force: If True, re-sync existing activities
   157→
   158→        Returns:
   159→            Statistics dictionary
   160→        """
   161→        logger.info(
   162→            f"Syncing activities from {start_date} to {end_date}"
   163→        )
   164→
   165→        stats = {"synced": 0, "skipped": 0, "errors": 0}
   166→
   167→        try:
   168→            # Fetch all activities in the range
   169→            activities = self.client.fetch_activities(start_date, end_date)
   170→
   171→            logger.info(f"Found {len(activities)} activities")
   172→
   173→            for activity in activities:
   174→                try:
   175→                    # Check if already synced
   176→                    if not force and self.storage.activity_exists(activity.activity_id):
   177→                        logger.debug(
   178→                            f"Skipping activity {activity.activity_id} (already synced)"
   179→                        )
   180→                        stats["skipped"] += 1
   181→                        continue
   182→
   183→                    # Save activity
   184→                    self.storage.save_activity(activity)
   185→                    stats["synced"] += 1
   186→                    logger.info(
   187→                        f"✓ Synced activity {activity.activity_id} "
   188→                        f"({activity.activity_type}) on {activity.date}"
   189→                    )
   190→
   191→                except Exception as e:
   192→                    logger.error(f"Error saving activity {activity.activity_id}: {e}")
   193→                    stats["errors"] += 1
   194→                    continue
   195→
   196→        except GarminAPIError as e:
   197→            logger.error(f"API error fetching activities: {e}")
   198→            stats["errors"] += 1
   199→
   200→        logger.info(
   201→            f"Activity sync complete: "
   202→            f"{stats['synced']} synced, {stats['skipped']} skipped, "
   203→            f"{stats['errors']} errors"
   204→        )
   205→
   206→        return stats
   207→
   208→    def sync_all_metrics(
   209→        self,
   210→        start_date: date,
   211→        end_date: date,
   212→        metric_types: Optional[List[str]] = None,
   213→        force: bool = False,
   214→    ) -> Dict[str, Dict[str, int]]:
   215→        """Sync all (or specified) metrics for a date range.
   216→
   217→        Args:
   218→            start_date: Start date
   219→            end_date: End date
   220→            metric_types: Optional list of metric types to sync (defaults to all)
   221→            force: If True, re-sync existing data
   222→
   223→        Returns:
   224→            Dictionary mapping metric type to sync statistics
   225→        """
   226→        # Default to all configured metric types except activities
   227→        if not metric_types:
   228→            metric_types = [
   229→                mt
   230→                for mt in config.DATA_TYPE_CONFIG.keys()
   231→                if mt != "activities"  # Handle activities separately
   232→            ]
   233→        else:
   234→            # Even if metric_types is provided, filter out activities to handle separately
   235→            metric_types = [mt for mt in metric_types if mt != "activities"]
   236→
   237→        logger.info(
   238→            f"Syncing {len(metric_types)} metric types from {start_date} to {end_date}"
   239→        )
   240→
   241→        results = {}
   242→
   243→        for metric_type in metric_types:
   244→            try:
   245→                stats = self.sync_daily_metrics_range(
   246→                    metric_type, start_date, end_date, force=force
   247→                )
   248→                results[metric_type] = stats
   249→
   250→                # Update last sync state
   251→                if stats["synced"] > 0:
   252→                    self.repo.update_last_sync_state(
   253→                        metric_type, end_date, total_records=stats["synced"]
   254→                    )
   255→
   256→            except Exception as e:
   257→                logger.error(f"Failed to sync {metric_type}: {e}")
   258→                results[metric_type] = {"synced": 0, "skipped": 0, "errors": 1}
   259→                continue
   260→
   261→        # Sync activities (always, regardless of metric_types parameter)
   262→        try:
   263→            activity_stats = self.sync_activities_range(start_date, end_date, force=force)
   264→            results["activities"] = activity_stats
   265→
   266→            if activity_stats["synced"] > 0:
   267→                self.repo.update_last_sync_state(
   268→                    "activities", end_date, total_records=activity_stats["synced"]
   269→                )
   270→
   271→        except Exception as e:
   272→            logger.error(f"Failed to sync activities: {e}")
   273→            results["activities"] = {"synced": 0, "skipped": 0, "errors": 1}
   274→
   275→        # Create sync record
   276→        total_synced = sum(r.get("synced", 0) for r in results.values())
   277→        total_errors = sum(r.get("errors", 0) for r in results.values())
   278→
   279→        status = "success" if total_errors == 0 else ("partial" if total_synced > 0 else "failed")
   280→
   281→        self.repo.create_sync_record(
   282→            data_type="all_metrics",
   283→            start_date=start_date,
   284→            end_date=end_date,
   285→            status=status,
   286→            records_synced=total_synced,
   287→            error_message=f"{total_errors} errors" if total_errors > 0 else None,
   288→        )
   289→
   290→        return results
   291→
   292→    def sync_incremental(
   293→        self,
   294→        metric_types: Optional[List[str]] = None,
   295→        until_date: Optional[date] = None,
   296→    ) -> Dict[str, Dict[str, int]]:
   297→        """Perform incremental sync for all metrics since last sync.
   298→
   299→        Args:
   300→            metric_types: Optional list of metric types to sync
   301→            until_date: Optional end date (defaults to yesterday)
   302→
   303→        Returns:
   304→            Dictionary mapping metric type to sync statistics
   305→        """
   306→        if not until_date:
   307→            until_date = get_yesterday()
   308→
   309→        if not metric_types:
   310→            metric_types = list(config.DATA_TYPE_CONFIG.keys())
   311→
   312→        logger.info(f"Starting incremental sync (until {until_date})")
   313→
   314→        results = {}
   315→
   316→        for metric_type in metric_types:
   317→            try:
   318→                # Get last sync date
   319→                last_sync = self.repo.get_last_sync_date(metric_type)
   320→
   321→                # Determine start_date for historical sync
   322→                if last_sync:
   323→                    start_date = last_sync + timedelta(days=1)
   324→                else:
   325→                    # First sync - use default start date
   326→                    start_date = parse_date(config.HISTORICAL_START_DATE)
   327→                    logger.info(
   328→                        f"{metric_type} not synced before, starting from {start_date}"
   329→                    )
   330→
   331→                stats = {"synced": 0, "skipped": 0, "errors": 0}
   332→                today = date.today()
   333→                yesterday = today - timedelta(days=1)
   334→
   335→                # 1. Sync Historical Data (start_date to min(until_date, yesterday))
   336→                # Only if we have a valid range before today
   337→                historical_end = min(until_date, yesterday)
   338→
   339→                if start_date <= historical_end:
   340→                    if metric_type == "activities":
   341→                        h_stats = self.sync_activities_range(start_date, historical_end, force=False)
   342→                    else:
   343→                        h_stats = self.sync_daily_metrics_range(
   344→                            metric_type, start_date, historical_end, force=False
   345→                        )
   346→
   347→                    stats["synced"] += h_stats.get("synced", 0)
   348→                    stats["skipped"] += h_stats.get("skipped", 0)
   349→                    stats["errors"] += h_stats.get("errors", 0)
   350→
   351→                # 2. Sync Today (if requested) - Always Force
   352→                # If until_date includes today, we force sync today regardless of last_sync
   353→                if until_date >= today:
   354→                    logger.info(f"Force syncing {metric_type} for today ({today})")
   355→                    if metric_type == "activities":
   356→                        t_stats = self.sync_activities_range(today, today, force=True)
   357→                    else:
   358→                        t_stats = self.sync_daily_metrics_range(
   359→                            metric_type, today, today, force=True
   360→                        )
   361→
   362→                    stats["synced"] += t_stats.get("synced", 0)
   363→                    stats["skipped"] += t_stats.get("skipped", 0)
   364→                    stats["errors"] += t_stats.get("errors", 0)
   365→
   366→                # Log if skipped everything
   367→                if stats["synced"] == 0 and stats["errors"] == 0 and stats["skipped"] == 0:
   368→                     if start_date > historical_end and until_date < today:
   369→                         logger.info(f"{metric_type} already up to date")
   370→
   371→                results[metric_type] = stats
   372→
   373→                # Update last sync state if we synced anything
   374→                if stats["synced"] > 0:
   375→                    self.repo.update_last_sync_state(metric_type, until_date)
   376→
   377→            except Exception as e:
   378→                logger.error(f"Incremental sync failed for {metric_type}: {e}")
   379→                results[metric_type] = {"synced": 0, "skipped": 0, "errors": 1}
   380→                continue
   381→
   382→        return results
   383→
   384→    def backfill_historical(
   385→        self,
   386→        start_date: date,
   387→        end_date: Optional[date] = None,
   388→        metric_types: Optional[List[str]] = None,
   389→        batch_size: int = config.DEFAULT_BATCH_SIZE_DAYS,
   390→    ) -> Dict[str, Dict[str, int]]:
   391→        """Backfill historical data in batches.
   392→
   393→        Args:
   394→            start_date: Start date for backfill
   395→            end_date: End date (defaults to yesterday)
   396→            metric_types: Optional list of metric types
   397→            batch_size: Days per batch (default: 30)
   398→
   399→        Returns:
   400→            Aggregated sync statistics
   401→        """
   402→        if not end_date:
   403→            end_date = get_yesterday()
   404→
   405→        if not metric_types:
   406→            metric_types = list(config.DATA_TYPE_CONFIG.keys())
   407→
   408→        logger.info(
   409→            f"Starting historical backfill from {start_date} to {end_date} "
   410→            f"({(end_date - start_date).days + 1} days, batch size: {batch_size})"
   411→        )
   412→
   413→        # Split into batches
   414→        batches = split_date_range(start_date, end_date, batch_size)
   415→        logger.info(f"Processing {len(batches)} batches")
   416→
   417→        # Aggregate results
   418→        aggregated_results: Dict[str, Dict[str, int]] = {
   419→            mt: {"synced": 0, "skipped": 0, "errors": 0} for mt in metric_types
   420→        }
   421→
   422→        for i, (batch_start, batch_end) in enumerate(batches, 1):
   423→            logger.info(
   424→                f"\n📦 Batch {i}/{len(batches)}: {batch_start} to {batch_end}"
   425→            )
   426→
   427→            batch_results = self.sync_all_metrics(
   428→                batch_start, batch_end, metric_types=metric_types
   429→            )
   430→
   431→            # Aggregate statistics
   432→            for metric_type, stats in batch_results.items():
   433→                if metric_type not in aggregated_results:
   434→                    aggregated_results[metric_type] = {"synced": 0, "skipped": 0, "errors": 0}
   435→
   436→                aggregated_results[metric_type]["synced"] += stats.get("synced", 0)
   437→                aggregated_results[metric_type]["skipped"] += stats.get("skipped", 0)
   438→                aggregated_results[metric_type]["errors"] += stats.get("errors", 0)
   439→
   440→        logger.info("\n✅ Historical backfill complete!")
   441→        logger.info("\n📊 Final Statistics:")
   442→        for metric_type, stats in aggregated_results.items():
   443→            logger.info(
   444→                f"  {metric_type}: {stats['synced']} synced, "
   445→                f"{stats['skipped']} skipped, {stats['errors']} errors"
   446→            )
   447→
   448→        return aggregated_results
   449→
   450→    def get_sync_status(self) -> Dict[str, Any]:
   451→        """Get current sync status for all data types.
   452→
   453→        Returns:
   454→            Dictionary with sync status information
   455→        """
   456→        status = {}
   457→        all_states = self.repo.get_all_last_sync_states()
   458→
   459→        for data_type in config.DATA_TYPE_CONFIG.keys():
   460→            if data_type in all_states:
   461→                state = all_states[data_type]
   462→                status[data_type] = {
   463→                    "last_sync_date": state["last_sync_date"],
   464→                    "total_records": state["total_records"],
   465→                    "updated_at": state["updated_at"],
   466→                    "status": "synced",
   467→                }
   468→            else:
   469→                status[data_type] = {
   470→                    "last_sync_date": None,
   471→                    "total_records": 0,
   472→                    "updated_at": None,
   473→                    "status": "never_synced",
   474→                }
   475→
   476→        return status
   477→

<system-reminder>
Whenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.
</system-reminder>

"""
Data synchronization orchestration service.

Coordinates Garmin API data fetching, storage, and incremental sync logic.
"""

from datetime import date, timedelta
from typing import List, Dict, Any, Optional, Tuple
from pathlib import Path

from health import config
from health.services.garmin_client import GarminHealthClient
from health.services.storage import HealthStorage
from health.db.repository import HealthRepository
from health.utils.exceptions import SyncError, GarminAPIError
from health.utils.date_utils import (
    parse_date,
    date_range,
    split_date_range,
    get_yesterday,
    format_date,
)
from health.utils.logging_config import setup_logger

logger = setup_logger(__name__)

class HealthDataSync:
    """Service for orchestrating health data synchronization."""

    def __init__(
        self,
        client: Optional[GarminHealthClient] = None,
        storage: Optional[HealthStorage] = None,
        repo: Optional[HealthRepository] = None,
    ) -> None:
        """Initialize sync service.

        Args:
            client: Optional Garmin client (creates new if not provided)
            storage: Optional storage service (creates new if not provided)
            repo: Optional repository (creates new if not provided)
        """
        self.client = client or GarminHealthClient()
        self.storage = storage or HealthStorage()
        self.repo = repo or HealthRepository()

    def authenticate(self) -> None:
        """Authenticate with Garmin Connect.

        Raises:
            GarminAuthError: If authentication fails
        """
        logger.info("Authenticating with Garmin...")
        self.client.authenticate()
        logger.info("Authentication successful")

    def sync_daily_metric(
        self, metric_type: str, target_date: date, force: bool = False
    ) -> bool:
        """Sync a single daily metric for a specific date.

        Args:
            metric_type: Type of metric to sync
            target_date: Date to sync
            force: If True, re-sync even if data already exists

        Returns:
            True if data was synced, False if skipped or no data available
        """
        # Check if already synced (unless forcing)
        if not force and self.storage.metric_exists(metric_type, target_date):
            logger.debug(f"Skipping {metric_type} for {target_date} (already synced)")
            return False

        # Get the appropriate fetch method
        fetch_method = getattr(self.client, f"fetch_{metric_type}", None)
        if not fetch_method:
            logger.warning(f"No fetch method for metric type: {metric_type}")
            return False

        try:
            # Fetch data from Garmin
            data = fetch_method(target_date)

            if not data:
                logger.debug(f"No {metric_type} data available for {target_date}")
                return False

            # Save to storage
            self.storage.save_daily_metric(data, metric_type)
            logger.info(f"✓ Synced {metric_type} for {target_date}")
            return True

        except GarminAPIError as e:
            logger.error(f"API error syncing {metric_type} for {target_date}: {e}")
            raise
        except Exception as e:
            logger.error(f"Error syncing {metric_type} for {target_date}: {e}")
            return False

    def sync_daily_metrics_range(
        self,
        metric_type: str,
        start_date: date,
        end_date: date,
        force: bool = False,
    ) -> Dict[str, int]:
        """Sync a daily metric for a date range.

        Args:
            metric_type: Type of metric to sync
            start_date: Start date (inclusive)
            end_date: End date (inclusive)
            force: If True, re-sync existing data

        Returns:
            Statistics dictionary with sync counts
        """
        logger.info(
            f"Syncing {metric_type} from {start_date} to {end_date} "
            f"({(end_date - start_date).days + 1} days)"
        )

        stats = {"synced": 0, "skipped": 0, "errors": 0}

        for current_date in date_range(start_date, end_date):
            try:
                if self.sync_daily_metric(metric_type, current_date, force=force):
                    stats["synced"] += 1
                else:
                    stats["skipped"] += 1

            except GarminAPIError as e:
                logger.error(f"API error on {current_date}: {e}")
                stats["errors"] += 1
                # Continue with other dates even if one fails
                continue

        logger.info(
            f"{metric_type} sync complete: "
            f"{stats['synced']} synced, {stats['skipped']} skipped, "
            f"{stats['errors']} errors"
        )

        return stats

    def sync_activities_range(
        self, start_date: date, end_date: date, force: bool = False
    ) -> Dict[str, int]:
        """Sync activities for a date range.

        Args:
            start_date: Start date
            end_date: End date
            force: If True, re-sync existing activities

        Returns:
            Statistics dictionary
        """
        logger.info(
            f"Syncing activities from {start_date} to {end_date}"
        )

        stats = {"synced": 0, "skipped": 0, "errors": 0}

        try:
            # Fetch all activities in the range
            activities = self.client.fetch_activities(start_date, end_date)

            logger.info(f"Found {len(activities)} activities")

            for activity in activities:
                try:
                    # Check if already synced
                    if not force and self.storage.activity_exists(activity.activity_id):
                        logger.debug(
                            f"Skipping activity {activity.activity_id} (already synced)"
                        )
                        stats["skipped"] += 1
                        continue

                    # Save activity
                    self.storage.save_activity(activity)
                    stats["synced"] += 1
                    logger.info(
                        f"✓ Synced activity {activity.activity_id} "
                        f"({activity.activity_type}) on {activity.date}"
                    )

                except Exception as e:
                    logger.error(f"Error saving activity {activity.activity_id}: {e}")
                    stats["errors"] += 1
                    continue

        except GarminAPIError as e:
            logger.error(f"API error fetching activities: {e}")
            stats["errors"] += 1

        logger.info(
            f"Activity sync complete: "
            f"{stats['synced']} synced, {stats['skipped']} skipped, "
            f"{stats['errors']} errors"
        )

        return stats

    def sync_all_metrics(
        self,
        start_date: date,
        end_date: date,
        metric_types: Optional[List[str]] = None,
        force: bool = False,
    ) -> Dict[str, Dict[str, int]]:
        """Sync all (or specified) metrics for a date range.

        Args:
            start_date: Start date
            end_date: End date
            metric_types: Optional list of metric types to sync (defaults to all)
            force: If True, re-sync existing data

        Returns:
            Dictionary mapping metric type to sync statistics
        """
        # Default to all configured metric types except activities
        if not metric_types:
            metric_types = [
                mt
                for mt in config.DATA_TYPE_CONFIG.keys()
                if mt != "activities"  # Handle activities separately
            ]
        else:
            # Even if metric_types is provided, filter out activities to handle separately
            metric_types = [mt for mt in metric_types if mt != "activities"]

        logger.info(
            f"Syncing {len(metric_types)} metric types from {start_date} to {end_date}"
        )

        results = {}

        for metric_type in metric_types:
            try:
                stats = self.sync_daily_metrics_range(
                    metric_type, start_date, end_date, force=force
                )
                results[metric_type] = stats

                # Update last sync state
                if stats["synced"] > 0:
                    self.repo.update_last_sync_state(
                        metric_type, end_date, total_records=stats["synced"]
                    )

            except Exception as e:
                logger.error(f"Failed to sync {metric_type}: {e}")
                results[metric_type] = {"synced": 0, "skipped": 0, "errors": 1}
                continue

        # Sync activities (always, regardless of metric_types parameter)
        try:
            activity_stats = self.sync_activities_range(start_date, end_date, force=force)
            results["activities"] = activity_stats

            if activity_stats["synced"] > 0:
                self.repo.update_last_sync_state(
                    "activities", end_date, total_records=activity_stats["synced"]
                )

        except Exception as e:
            logger.error(f"Failed to sync activities: {e}")
            results["activities"] = {"synced": 0, "skipped": 0, "errors": 1}

        # Create sync record
        total_synced = sum(r.get("synced", 0) for r in results.values())
        total_errors = sum(r.get("errors", 0) for r in results.values())

        status = "success" if total_errors == 0 else ("partial" if total_synced > 0 else "failed")

        self.repo.create_sync_record(
            data_type="all_metrics",
            start_date=start_date,
            end_date=end_date,
            status=status,
            records_synced=total_synced,
            error_message=f"{total_errors} errors" if total_errors > 0 else None,
        )

        return results

    def sync_incremental(
        self,
        metric_types: Optional[List[str]] = None,
        until_date: Optional[date] = None,
    ) -> Dict[str, Dict[str, int]]:
        """Perform incremental sync for all metrics since last sync.

        Args:
            metric_types: Optional list of metric types to sync
            until_date: Optional end date (defaults to yesterday)

        Returns:
            Dictionary mapping metric type to sync statistics
        """
        if not until_date:
            until_date = get_yesterday()

        if not metric_types:
            metric_types = list(config.DATA_TYPE_CONFIG.keys())

        logger.info(f"Starting incremental sync (until {until_date})")

        results = {}

        for metric_type in metric_types:
            try:
                # Get last sync date
                last_sync = self.repo.get_last_sync_date(metric_type)

                # Determine start_date for historical sync
                if last_sync:
                    start_date = last_sync + timedelta(days=1)
                else:
                    # First sync - use default start date
                    start_date = parse_date(config.HISTORICAL_START_DATE)
                    logger.info(
                        f"{metric_type} not synced before, starting from {start_date}"
                    )

                stats = {"synced": 0, "skipped": 0, "errors": 0}
                today = date.today()
                yesterday = today - timedelta(days=1)

                # 1. Sync Historical Data (start_date to min(until_date, yesterday))
                # Only if we have a valid range before today
                historical_end = min(until_date, yesterday)

                if start_date <= historical_end:
                    if metric_type == "activities":
                        h_stats = self.sync_activities_range(start_date, historical_end, force=False)
                    else:
                        h_stats = self.sync_daily_metrics_range(
                            metric_type, start_date, historical_end, force=False
                        )

                    stats["synced"] += h_stats.get("synced", 0)
                    stats["skipped"] += h_stats.get("skipped", 0)
                    stats["errors"] += h_stats.get("errors", 0)

                # 2. Sync Today (if requested) - Always Force
                # If until_date includes today, we force sync today regardless of last_sync
                if until_date >= today:
                    logger.info(f"Force syncing {metric_type} for today ({today})")
                    if metric_type == "activities":
                        t_stats = self.sync_activities_range(today, today, force=True)
                    else:
                        t_stats = self.sync_daily_metrics_range(
                            metric_type, today, today, force=True
                        )

                    stats["synced"] += t_stats.get("synced", 0)
                    stats["skipped"] += t_stats.get("skipped", 0)
                    stats["errors"] += t_stats.get("errors", 0)

                # Log if skipped everything
                if stats["synced"] == 0 and stats["errors"] == 0 and stats["skipped"] == 0:
                     if start_date > historical_end and until_date < today:
                         logger.info(f"{metric_type} already up to date")

                results[metric_type] = stats

                # Update last sync state if we synced anything
                if stats["synced"] > 0:
                    self.repo.update_last_sync_state(metric_type, until_date)

            except Exception as e:
                logger.error(f"Incremental sync failed for {metric_type}: {e}")
                results[metric_type] = {"synced": 0, "skipped": 0, "errors": 1}
                continue

        return results

    def backfill_historical(
        self,
        start_date: date,
        end_date: Optional[date] = None,
        metric_types: Optional[List[str]] = None,
        batch_size: int = config.DEFAULT_BATCH_SIZE_DAYS,
    ) -> Dict[str, Dict[str, int]]:
        """Backfill historical data in batches.

        Args:
            start_date: Start date for backfill
            end_date: End date (defaults to yesterday)
            metric_types: Optional list of metric types
            batch_size: Days per batch (default: 30)

        Returns:
            Aggregated sync statistics
        """
        if not end_date:
            end_date = get_yesterday()

        if not metric_types:
            metric_types = list(config.DATA_TYPE_CONFIG.keys())

        logger.info(
            f"Starting historical backfill from {start_date} to {end_date} "
            f"({(end_date - start_date).days + 1} days, batch size: {batch_size})"
        )

        # Split into batches
        batches = split_date_range(start_date, end_date, batch_size)
        logger.info(f"Processing {len(batches)} batches")

        # Aggregate results
        aggregated_results: Dict[str, Dict[str, int]] = {
            mt: {"synced": 0, "skipped": 0, "errors": 0} for mt in metric_types
        }

        for i, (batch_start, batch_end) in enumerate(batches, 1):
            logger.info(
                f"\n📦 Batch {i}/{len(batches)}: {batch_start} to {batch_end}"
            )

            batch_results = self.sync_all_metrics(
                batch_start, batch_end, metric_types=metric_types
            )

            # Aggregate statistics
            for metric_type, stats in batch_results.items():
                if metric_type not in aggregated_results:
                    aggregated_results[metric_type] = {"synced": 0, "skipped": 0, "errors": 0}

                aggregated_results[metric_type]["synced"] += stats.get("synced", 0)
                aggregated_results[metric_type]["skipped"] += stats.get("skipped", 0)
                aggregated_results[metric_type]["errors"] += stats.get("errors", 0)

        logger.info("\n✅ Historical backfill complete!")
        logger.info("\n📊 Final Statistics:")
        for metric_type, stats in aggregated_results.items():
            logger.info(
                f"  {metric_type}: {stats['synced']} synced, "
                f"{stats['skipped']} skipped, {stats['errors']} errors"
            )

        return aggregated_results

    def get_sync_status(self) -> Dict[str, Any]:
        """Get current sync status for all data types.

        Returns:
            Dictionary with sync status information
        """
        status = {}
        all_states = self.repo.get_all_last_sync_states()

        for data_type in config.DATA_TYPE_CONFIG.keys():
            if data_type in all_states:
                state = all_states[data_type]
                status[data_type] = {
                    "last_sync_date": state["last_sync_date"],
                    "total_records": state["total_records"],
                    "updated_at": state["updated_at"],
                    "status": "synced",
                }
            else:
                status[data_type] = {
                    "last_sync_date": None,
                    "total_records": 0,
                    "updated_at": None,
                    "status": "never_synced",
                }

        return status


好的，我需要查看 slack bot 是如何调用这些函数的。让我查看 main.py 文件，特别是健康 bot 的入口点，看看它如何处理用户输入的“同步佳明数据”请求。


让我查看 slack bot 的主入口文件 main.py，看看它是如何处理“同步佳明数据”请求的：


     1→import os
     2→import sys
     3→import click
     4→from slack_bolt import App
     5→from slack_bolt.adapter.socket_mode import SocketModeHandler
     6→from dotenv import load_dotenv
     7→
     8→# Add project root to path
     9→sys.path.append(os.getcwd())
    10→
    11→from health.utils.logging_config import setup_logger
    12→from health.utils.env_loader import load_env_with_extras
    13→from slack_bot.dispatcher import MessageDispatcher
    14→from slack_bot.context.storage import ContextStorage
    15→
    16→logger = setup_logger(__name__)
    17→
    18→# Load environment variables
    19→load_env_with_extras()
    20→
    21→
    22→@click.command()
    23→@click.option("--model", default=None, help="Gemini model to use (overrides .env)")
    24→def main(model: str):
    25→    """Butler Slack Bot - Gemini Edition."""
    26→
    27→    # Override model in environment only if specified via CLI
    28→    if model:
    29→        os.environ["GEMINI_MODEL"] = model
    30→        logger.info(f"Using model from CLI: {model}")
    31→
    32→    # Get the actual model being used (from CLI or .env)
    33→    actual_model = os.environ.get("GEMINI_MODEL", "gemini-2.0-flash-exp")
    34→    base_url = os.environ.get("GEMINI_BASE_URL", "Not set (will use direct API)")
    35→    config_path = os.environ.get("GEMINI_CONFIG_PATH", ".env")
    36→
    37→    logger.info(f"Starting Butler Bot with configuration:")
    38→    logger.info(f"  Config file: {config_path}")
    39→    logger.info(f"  Model: {actual_model}")
    40→    logger.info(f"  Base URL: {base_url}")
    41→    logger.info(f"  Using proxy: {'Yes' if base_url and 'http' in base_url else 'No (Direct Google API)'}")
    42→
    43→    # Initialize Slack App
    44→    bot_token = os.environ.get("SLACK_BOT_TOKEN")
    45→    app_token = os.environ.get("SLACK_APP_TOKEN")
    46→
    47→    if not bot_token or not app_token:
    48→        logger.error("Missing SLACK_BOT_TOKEN or SLACK_APP_TOKEN in .env")
    49→        sys.exit(1)
    50→
    51→    app = App(token=bot_token)
    52→
    53→    # Tool mode: 'none' (no tools), 'light' (5), 'standard' (10), 'full' (15), 'all' (21)
    54→    # Use 'none' if your proxy doesn't support function calling
    55→    tool_mode = os.environ.get("TOOL_MODE", "light")
    56→    dispatcher = MessageDispatcher(tool_mode=tool_mode)
    57→    logger.info(f"Dispatcher initialized in '{tool_mode}' mode")
    58→
    59→    # Message deduplication: Track processed message IDs
    60→    processed_messages = set()
    61→    MAX_TRACKED_MESSAGES = 1000
    62→
    63→    # Command Handler: Clear Context
    64→    @app.message(r"^/(clear|reset)$")
    65→    def handle_clear_context(message, say):
    66→        """Clear conversation context for the current channel."""
    67→        try:
    68→            channel = message["channel"]
    69→            storage = ContextStorage(channel)
    70→
    71→            # Get context size before clearing
    72→            old_context = storage.get_context()
    73→            old_count = len(old_context)
    74→
    75→            storage.clear()
    76→
    77→            logger.info(f"✅ Context cleared for channel {channel} (removed {old_count} messages)")
    78→            say(f"✅ 对话历史已清空,我们重新开始!\n\n_Context cleared ({old_count} messages removed). Starting fresh conversation._")
    79→        except Exception as e:
    80→            logger.error(f"Error clearing context: {e}", exc_info=True)
    81→            say(f"❌ 清空对话历史失败: {e}")
    82→
    83→    # Command Handler: Show Context Stats
    84→    @app.message(r"^/stats$")
    85→    def handle_context_stats(message, say):
    86→        """Show conversation context statistics."""
    87→        try:
    88→            channel = message["channel"]
    89→            storage = ContextStorage(channel)
    90→            context = storage.get_context()
    91→
    92→            # Calculate token estimate (rough: 1 token ≈ 3 chars for Chinese/English mix)
    93→            total_chars = sum(len(msg.get("content", "")) for msg in context)
    94→            estimated_tokens = total_chars // 3
    95→
    96→            stats_msg = (
    97→                f"📊 **对话上下文统计 (Context Stats)**\n\n"
    98→                f"• 消息数量 (Messages): {len(context)}\n"
    99→                f"• 总字符数 (Total chars): {total_chars:,}\n"
   100→                f"• 预估 Token (Est. tokens): ~{estimated_tokens:,}\n\n"
   101→                f"_使用 `/clear` 可以清空对话历史_"
   102→            )
   103→
   104→            say(stats_msg)
   105→            logger.info(f"Context stats for {channel}: {len(context)} messages, ~{estimated_tokens} tokens")
   106→        except Exception as e:
   107→            logger.error(f"Error getting context stats: {e}", exc_info=True)
   108→            say(f"❌ 获取统计信息失败: {e}")
   109→
   110→    # Message Handler
   111→    @app.event("message")
   112→    def handle_message(message, say):
   113→
   114→        try:
   115→            # Skip command messages (they're handled by command handlers)
   116→            text = message.get("text", "")
   117→            if text.startswith("/clear") or text.startswith("/reset") or text.startswith("/stats"):
   118→                logger.debug("Skipping command message in general handler")
   119→                return
   120→
   121→            # Deduplicate using client_msg_id or event_ts
   122→            msg_id = message.get("client_msg_id") or message.get("ts")
   123→
   124→            if msg_id in processed_messages:
   125→                logger.debug(f"Skipping duplicate message: {msg_id}")
   126→                return
   127→
   128→            # Add to processed set
   129→            processed_messages.add(msg_id)
   130→
   131→            # Limit memory usage by keeping only recent message IDs
   132→            if len(processed_messages) > MAX_TRACKED_MESSAGES:
   133→                # Remove oldest half
   134→                to_remove = list(processed_messages)[:MAX_TRACKED_MESSAGES // 2]
   135→                for old_id in to_remove:
   136→                    processed_messages.discard(old_id)
   137→
   138→            text = message.get("text", "")
   139→            channel = message["channel"]
   140→            user = message["user"]
   141→            files = message.get("files", [])
   142→
   143→            # Generate Request ID
   144→            import uuid
   145→            import time
   146→            request_id = str(uuid.uuid4())[:8]
   147→            start_time = time.time()
   148→
   149→            logger.info(f"[{request_id}] 📥 Received message from {user} in {channel}: {text} (Files: {len(files)})")
   150→
   151→            # Send temporary "Processing..." message
   152→            ack_response = say(f"⏳ Butler is thinking...")
   153→            ack_ts = ack_response["ts"]
   154→
   155→            # Dispatch to Gemini with the timestamp to update
   156→            dispatcher.dispatch(text, channel, user, response_ts=ack_ts, request_id=request_id, files=files)
   157→
   158→            elapsed = time.time() - start_time
   159→            logger.info(f"[{request_id}] ✅ Request completed in {elapsed:.2f}s")
   160→
   161→        except Exception as e:
   162→            logger.error(f"Error handling message: {e}", exc_info=True)
   163→            try:
   164→                say(f"🐛 Butler encountered an error: {e}")
   165→            except Exception:
   166→                pass
   167→
   168→    # Start Socket Mode
   169→    try:
   170→        handler = SocketModeHandler(app, app_token)
   171→        logger.info("⚡ Butler (Gemini) is connected to Slack!")
   172→        handler.start()
   173→    except Exception as e:
   174→        logger.error(f"Failed to start SocketModeHandler: {e}")
   175→        sys.exit(1)
   176→
   177→
   178→if __name__ == "__main__":
   179→    main()
   180→

<system-reminder>
Whenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.
</system-reminder>

import os
import sys
import click
from slack_bolt import App
from slack_bolt.adapter.socket_mode import SocketModeHandler
from dotenv import load_dotenv

# Add project root to path
sys.path.append(os.getcwd())

from health.utils.logging_config import setup_logger
from health.utils.env_loader import load_env_with_extras
from slack_bot.dispatcher import MessageDispatcher
from slack_bot.context.storage import ContextStorage

logger = setup_logger(__name__)

# Load environment variables
load_env_with_extras()

@click.command()
@click.option("--model", default=None, help="Gemini model to use (overrides .env)")
def main(model: str):
    """Butler Slack Bot - Gemini Edition."""

    # Override model in environment only if specified via CLI
    if model:
        os.environ["GEMINI_MODEL"] = model
        logger.info(f"Using model from CLI: {model}")

    # Get the actual model being used (from CLI or .env)
    actual_model = os.environ.get("GEMINI_MODEL", "gemini-2.0-flash-exp")
    base_url = os.environ.get("GEMINI_BASE_URL", "Not set (will use direct API)")
    config_path = os.environ.get("GEMINI_CONFIG_PATH", ".env")

    logger.info(f"Starting Butler Bot with configuration:")
    logger.info(f"  Config file: {config_path}")
    logger.info(f"  Model: {actual_model}")
    logger.info(f"  Base URL: {base_url}")
    logger.info(f"  Using proxy: {'Yes' if base_url and 'http' in base_url else 'No (Direct Google API)'}")

    # Initialize Slack App
    bot_token = os.environ.get("SLACK_BOT_TOKEN")
    app_token = os.environ.get("SLACK_APP_TOKEN")

    if not bot_token or not app_token:
        logger.error("Missing SLACK_BOT_TOKEN or SLACK_APP_TOKEN in .env")
        sys.exit(1)

    app = App(token=bot_token)

    # Tool mode: 'none' (no tools), 'light' (5), 'standard' (10), 'full' (15), 'all' (21)
    # Use 'none' if your proxy doesn't support function calling
    tool_mode = os.environ.get("TOOL_MODE", "light")
    dispatcher = MessageDispatcher(tool_mode=tool_mode)
    logger.info(f"Dispatcher initialized in '{tool_mode}' mode")

    # Message deduplication: Track processed message IDs
    processed_messages = set()
    MAX_TRACKED_MESSAGES = 1000

    # Command Handler: Clear Context
    @app.message(r"^/(clear|reset)$")
    def handle_clear_context(message, say):
        """Clear conversation context for the current channel."""
        try:
            channel = message["channel"]
            storage = ContextStorage(channel)

            # Get context size before clearing
            old_context = storage.get_context()
            old_count = len(old_context)

            storage.clear()

            logger.info(f"✅ Context cleared for channel {channel} (removed {old_count} messages)")
            say(f"✅ 对话历史已清空,我们重新开始!\n\n_Context cleared ({old_count} messages removed). Starting fresh conversation._")
        except Exception as e:
            logger.error(f"Error clearing context: {e}", exc_info=True)
            say(f"❌ 清空对话历史失败: {e}")

    # Command Handler: Show Context Stats
    @app.message(r"^/stats$")
    def handle_context_stats(message, say):
        """Show conversation context statistics."""
        try:
            channel = message["channel"]
            storage = ContextStorage(channel)
            context = storage.get_context()

            # Calculate token estimate (rough: 1 token ≈ 3 chars for Chinese/English mix)
            total_chars = sum(len(msg.get("content", "")) for msg in context)
            estimated_tokens = total_chars // 3

            stats_msg = (
                f"📊 **对话上下文统计 (Context Stats)**\n\n"
                f"• 消息数量 (Messages): {len(context)}\n"
                f"• 总字符数 (Total chars): {total_chars:,}\n"
                f"• 预估 Token (Est. tokens): ~{estimated_tokens:,}\n\n"
                f"_使用 `/clear` 可以清空对话历史_"
            )

            say(stats_msg)
            logger.info(f"Context stats for {channel}: {len(context)} messages, ~{estimated_tokens} tokens")
        except Exception as e:
            logger.error(f"Error getting context stats: {e}", exc_info=True)
            say(f"❌ 获取统计信息失败: {e}")

    # Message Handler
    @app.event("message")
    def handle_message(message, say):

        try:
            # Skip command messages (they're handled by command handlers)
            text = message.get("text", "")
            if text.startswith("/clear") or text.startswith("/reset") or text.startswith("/stats"):
                logger.debug("Skipping command message in general handler")
                return

            # Deduplicate using client_msg_id or event_ts
            msg_id = message.get("client_msg_id") or message.get("ts")

            if msg_id in processed_messages:
                logger.debug(f"Skipping duplicate message: {msg_id}")
                return

            # Add to processed set
            processed_messages.add(msg_id)

            # Limit memory usage by keeping only recent message IDs
            if len(processed_messages) > MAX_TRACKED_MESSAGES:
                # Remove oldest half
                to_remove = list(processed_messages)[:MAX_TRACKED_MESSAGES // 2]
                for old_id in to_remove:
                    processed_messages.discard(old_id)

            text = message.get("text", "")
            channel = message["channel"]
            user = message["user"]
            files = message.get("files", [])

            # Generate Request ID
            import uuid
            import time
            request_id = str(uuid.uuid4())[:8]
            start_time = time.time()

            logger.info(f"[{request_id}] 📥 Received message from {user} in {channel}: {text} (Files: {len(files)})")

            # Send temporary "Processing..." message
            ack_response = say(f"⏳ Butler is thinking...")
            ack_ts = ack_response["ts"]

            # Dispatch to Gemini with the timestamp to update
            dispatcher.dispatch(text, channel, user, response_ts=ack_ts, request_id=request_id, files=files)

            elapsed = time.time() - start_time
            logger.info(f"[{request_id}] ✅ Request completed in {elapsed:.2f}s")

        except Exception as e:
            logger.error(f"Error handling message: {e}", exc_info=True)
            try:
                say(f"🐛 Butler encountered an error: {e}")
            except Exception:
                pass

    # Start Socket Mode
    try:
        handler = SocketModeHandler(app, app_token)
        logger.info("⚡ Butler (Gemini) is connected to Slack!")
        handler.start()
    except Exception as e:
        logger.error(f"Failed to start SocketModeHandler: {e}")
        sys.exit(1)

if __name__ == "__main__":
    main()


好的，main.py 文件中使用了 MessageDispatcher 来处理用户的请求。我需要查看 dispatcher.py 文件，特别是看看它是如何解析用户输入的“同步佳明数据”请求，并调用相应的工具的。


现在让我查看 MessageDispatcher 类，看看它是如何解析用户输入并调用相应工具的：