chore: 添加虚拟环境到仓库

- 添加 backend_service/venv 虚拟环境
- 包含所有Python依赖包
- 注意：虚拟环境约393MB，包含12655个文件

backend_service/venv/lib/python3.13/site-packages/chromadb/execution/expression/__init__.py

@@ -0,0 +1,90 @@
+"""
+Chromadb execution expression module for search operations.
+"""
+
+from chromadb.execution.expression.operator import (
+    # Field proxy for building Where conditions
+    Key,
+    K,
+    # Where expressions
+    Where,
+    And,
+    Or,
+    Eq,
+    Ne,
+    Gt,
+    Gte,
+    Lt,
+    Lte,
+    In,
+    Nin,
+    Regex,
+    NotRegex,
+    Contains,
+    NotContains,
+    # Search configuration
+    Limit,
+    Select,
+    # Rank expressions
+    Rank,
+    Abs,
+    Div,
+    Exp,
+    Log,
+    Max,
+    Min,
+    Mul,
+    Knn,
+    Rrf,
+    Sub,
+    Sum,
+    Val,
+)
+
+from chromadb.execution.expression.plan import (
+    Search,
+)
+
+SearchWhere = Where
+
+__all__ = [
+    # Main search class
+    "Search",
+    # Field proxy
+    "Key",
+    "K",
+    # Where expressions
+    "SearchWhere",
+    "Where",
+    "And",
+    "Or",
+    "Eq",
+    "Ne",
+    "Gt",
+    "Gte",
+    "Lt",
+    "Lte",
+    "In",
+    "Nin",
+    "Regex",
+    "NotRegex",
+    "Contains",
+    "NotContains",
+    # Search configuration
+    "Limit",
+    "Select",
+    # Rank expressions
+    "Rank",
+    "Abs",
+    "Div",
+    "Exp",
+    "Log",
+    "Max",
+    "Min",
+    "Mul",
+    "Knn",
+    "Rrf",
+    "Sub",
+    "Sum",
+    "Val",
+]

backend_service/venv/lib/python3.13/site-packages/chromadb/execution/expression/plan.py

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+from dataclasses import dataclass, field
+from typing import List, Dict, Any, Union, Set, Optional
+
+from chromadb.execution.expression.operator import (
+    KNN,
+    Filter,
+    Limit,
+    Projection,
+    Scan,
+    Rank,
+    Select,
+    Val,
+    Where,
+    Key,
+)
+
+
+@dataclass
+class CountPlan:
+    scan: Scan
+
+
+@dataclass
+class GetPlan:
+    scan: Scan
+    filter: Filter = field(default_factory=Filter)
+    limit: Limit = field(default_factory=Limit)
+    projection: Projection = field(default_factory=Projection)
+
+
+@dataclass
+class KNNPlan:
+    scan: Scan
+    knn: KNN
+    filter: Filter = field(default_factory=Filter)
+    projection: Projection = field(default_factory=Projection)
+
+
+class Search:
+    """Payload for hybrid search operations.
+
+    Can be constructed directly or using builder pattern:
+
+    Direct construction with expressions:
+        Search(
+            where=Key("status") == "active",
+            rank=Knn(query=[0.1, 0.2]),
+            limit=Limit(limit=10),
+            select=Select(keys={Key.DOCUMENT})
+        )
+
+    Direct construction with dicts:
+        Search(
+            where={"status": "active"},
+            rank={"$knn": {"query": [0.1, 0.2]}},
+            limit=10,  # Creates Limit(limit=10, offset=0)
+            select=["#document", "#score"]
+        )
+
+    Builder pattern:
+        (Search()
+            .where(Key("status") == "active")
+            .rank(Knn(query=[0.1, 0.2]))
+            .limit(10)
+            .select(Key.DOCUMENT))
+
+    Builder pattern with dicts:
+        (Search()
+            .where({"status": "active"})
+            .rank({"$knn": {"query": [0.1, 0.2]}})
+            .limit(10)
+            .select(Key.DOCUMENT))
+
+    Filter by IDs:
+        Search().where(Key.ID.is_in(["id1", "id2", "id3"]))
+
+    Combined with metadata filtering:
+        Search().where((Key.ID.is_in(["id1", "id2"])) & (Key("status") == "active"))
+
+    Empty Search() is valid and will use defaults:
+        - where: None (no filtering)
+        - rank: None (no ranking - results ordered by default order)
+        - limit: No limit
+        - select: Empty selection
+    """
+
+    def __init__(
+        self,
+        where: Optional[Union[Where, Dict[str, Any]]] = None,
+        rank: Optional[Union[Rank, Dict[str, Any]]] = None,
+        limit: Optional[Union[Limit, Dict[str, Any], int]] = None,
+        select: Optional[Union[Select, Dict[str, Any], List[str], Set[str]]] = None,
+    ):
+        """Initialize a Search with optional parameters.
+
+        Args:
+            where: Where expression or dict for filtering results (defaults to None - no filtering)
+                   Dict will be converted using Where.from_dict()
+            rank: Rank expression or dict for scoring (defaults to None - no ranking)
+                  Dict will be converted using Rank.from_dict()
+                  Note: Primitive numbers are not accepted - use {"$val": number} for constant ranks
+            limit: Limit configuration for pagination (defaults to no limit)
+                   Can be a Limit object, a dict for Limit.from_dict(), or an int
+                   When passing an int, it creates Limit(limit=value, offset=0)
+            select: Select configuration for keys (defaults to empty selection)
+                    Can be a Select object, a dict for Select.from_dict(), 
+                    or a list/set of strings (e.g., ["#document", "#score"])
+        """
+        # Handle where parameter
+        if where is None:
+            self._where = None
+        elif isinstance(where, Where):
+            self._where = where
+        elif isinstance(where, dict):
+            self._where = Where.from_dict(where)
+        else:
+            raise TypeError(
+                f"where must be a Where object, dict, or None, got {type(where).__name__}"
+            )
+        
+        # Handle rank parameter
+        if rank is None:
+            self._rank = None
+        elif isinstance(rank, Rank):
+            self._rank = rank
+        elif isinstance(rank, dict):
+            self._rank = Rank.from_dict(rank)
+        else:
+            raise TypeError(
+                f"rank must be a Rank object, dict, or None, got {type(rank).__name__}"
+            )
+        
+        # Handle limit parameter
+        if limit is None:
+            self._limit = Limit()
+        elif isinstance(limit, Limit):
+            self._limit = limit
+        elif isinstance(limit, int):
+            self._limit = Limit.from_dict({"limit": limit, "offset": 0})
+        elif isinstance(limit, dict):
+            self._limit = Limit.from_dict(limit)
+        else:
+            raise TypeError(
+                f"limit must be a Limit object, dict, int, or None, got {type(limit).__name__}"
+            )
+        
+        # Handle select parameter
+        if select is None:
+            self._select = Select()
+        elif isinstance(select, Select):
+            self._select = select
+        elif isinstance(select, dict):
+            self._select = Select.from_dict(select)
+        elif isinstance(select, (list, set)):
+            # Convert list/set of strings to Select object
+            self._select = Select.from_dict({"keys": list(select)})
+        else:
+            raise TypeError(
+                f"select must be a Select object, dict, list, set, or None, got {type(select).__name__}"
+            )
+
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert the Search to a dictionary for JSON serialization"""
+        return {
+            "filter": self._where.to_dict() if self._where is not None else None,
+            "rank": self._rank.to_dict() if self._rank is not None else None,
+            "limit": self._limit.to_dict(),
+            "select": self._select.to_dict(),
+        }
+
+    # Builder methods for chaining
+    def select_all(self) -> "Search":
+        """Select all predefined keys (document, embedding, metadata, score)"""
+        new_select = Select(keys={Key.DOCUMENT, Key.EMBEDDING, Key.METADATA, Key.SCORE})
+        return Search(
+            where=self._where, rank=self._rank, limit=self._limit, select=new_select
+        )
+
+    def select(self, *keys: Union[Key, str]) -> "Search":
+        """Select specific keys
+
+        Args:
+            *keys: Variable number of Key objects or string key names
+
+        Returns:
+            New Search object with updated select configuration
+        """
+        new_select = Select(keys=set(keys))
+        return Search(
+            where=self._where, rank=self._rank, limit=self._limit, select=new_select
+        )
+
+    def where(self, where: Optional[Union[Where, Dict[str, Any]]]) -> "Search":
+        """Set the where clause for filtering
+
+        Args:
+            where: A Where expression, dict, or None for filtering
+                   Dicts will be converted using Where.from_dict()
+
+        Example:
+            search.where((Key("status") == "active") & (Key("score") > 0.5))
+            search.where({"status": "active"})
+            search.where({"$and": [{"status": "active"}, {"score": {"$gt": 0.5}}]})
+        """
+        # Convert dict to Where if needed
+        if where is None:
+            converted_where = None
+        elif isinstance(where, Where):
+            converted_where = where
+        elif isinstance(where, dict):
+            converted_where = Where.from_dict(where)
+        else:
+            raise TypeError(
+                f"where must be a Where object, dict, or None, got {type(where).__name__}"
+            )
+        
+        return Search(
+            where=converted_where, rank=self._rank, limit=self._limit, select=self._select
+        )
+
+    def rank(self, rank_expr: Optional[Union[Rank, Dict[str, Any]]]) -> "Search":
+        """Set the ranking expression
+
+        Args:
+            rank_expr: A Rank expression, dict, or None for scoring
+                       Dicts will be converted using Rank.from_dict()
+                       Note: Primitive numbers are not accepted - use {"$val": number} for constant ranks
+
+        Example:
+            search.rank(Knn(query=[0.1, 0.2]) * 0.8 + Val(0.5) * 0.2)
+            search.rank({"$knn": {"query": [0.1, 0.2]}})
+            search.rank({"$sum": [{"$knn": {"query": [0.1, 0.2]}}, {"$val": 0.5}]})
+        """
+        # Convert dict to Rank if needed
+        if rank_expr is None:
+            converted_rank = None
+        elif isinstance(rank_expr, Rank):
+            converted_rank = rank_expr
+        elif isinstance(rank_expr, dict):
+            converted_rank = Rank.from_dict(rank_expr)
+        else:
+            raise TypeError(
+                f"rank_expr must be a Rank object, dict, or None, got {type(rank_expr).__name__}"
+            )
+        
+        return Search(
+            where=self._where, rank=converted_rank, limit=self._limit, select=self._select
+        )
+
+    def limit(self, limit: int, offset: int = 0) -> "Search":
+        """Set the limit and offset for pagination
+
+        Args:
+            limit: Maximum number of results to return
+            offset: Number of results to skip (default: 0)
+
+        Example:
+            search.limit(20, offset=10)
+        """
+        new_limit = Limit(offset=offset, limit=limit)
+        return Search(
+            where=self._where, rank=self._rank, limit=new_limit, select=self._select
+        )