added field check

lightrag/api/lightrag_server.py

@@ -626,55 +626,125 @@ class DocumentManager:
 
 
 class QueryRequest(BaseModel):
-    query: str
+    query: str = Field(
-
+        min_length=1,
-    """Specifies the retrieval mode"""
+        description="The query text",
-    mode: Literal["local", "global", "hybrid", "naive", "mix"] = Field(default="hybrid")
-
-    """If True, only returns the retrieved context without generating a response."""
-    only_need_context: Optional[bool] = Field(default=None)
-
-    """If True, only returns the generated prompt without producing a response."""
-    only_need_prompt: Optional[bool] = Field(default=None)
-
-    """Defines the response format. Examples: 'Multiple Paragraphs', 'Single Paragraph', 'Bullet Points'."""
-    response_type: Optional[str] = Field(min_length=1, default=None)
-
-    """Number of top items to retrieve. Represents entities in 'local' mode and relationships in 'global' mode."""
-    top_k: Optional[int] = Field(gt=1, default=None)
-
-    """Maximum number of tokens allowed for each retrieved text chunk."""
-    max_token_for_text_unit: Optional[int] = Field(gt=1, default=None)
-
-    """Maximum number of tokens allocated for relationship descriptions in global retrieval."""
-    max_token_for_global_context: Optional[int] = Field(gt=1, default=None)
-
-    """Maximum number of tokens allocated for entity descriptions in local retrieval."""
-    max_token_for_local_context: Optional[int] = Field(gt=1, default=None)
-
-    """List of high-level keywords to prioritize in retrieval."""
-    hl_keywords: Optional[List[str]] = Field(min_length=1, default=None)
-
-    """List of low-level keywords to refine retrieval focus."""
-    ll_keywords: Optional[List[str]] = Field(min_length=1, default=None)
-
-    """Stores past conversation history to maintain context.
-    Format: [{"role": "user/assistant", "content": "message"}].
-    """
-    conversation_history: Optional[List[dict[str, Any]]] = Field(
-        min_length=1, default=None
     )
 
-    """Number of complete conversation turns (user-assistant pairs) to consider in the response context."""
+    mode: Literal["local", "global", "hybrid", "naive", "mix"] = Field(
-    history_turns: Optional[int] = Field(gt=1, default=None)
+        default="hybrid",
+        description="Query mode",
+    )
+
+    only_need_context: Optional[bool] = Field(
+        default=None,
+        description="If True, only returns the retrieved context without generating a response.",
+    )
+
+    only_need_prompt: Optional[bool] = Field(
+        default=None,
+        description="If True, only returns the generated prompt without producing a response.",
+    )
+
+    response_type: Optional[str] = Field(
+        min_length=1,
+        default=None,
+        description="Defines the response format. Examples: 'Multiple Paragraphs', 'Single Paragraph', 'Bullet Points'.",
+    )
+
+    top_k: Optional[int] = Field(
+        gt=1,
+        default=None,
+        description="Number of top items to retrieve. Represents entities in 'local' mode and relationships in 'global' mode.",
+    )
+
+    max_token_for_text_unit: Optional[int] = Field(
+        gt=1,
+        default=None,
+        description="Maximum number of tokens allowed for each retrieved text chunk.",
+    )
+
+    max_token_for_global_context: Optional[int] = Field(
+        gt=1,
+        default=None,
+        description="Maximum number of tokens allocated for relationship descriptions in global retrieval.",
+    )
+
+    max_token_for_local_context: Optional[int] = Field(
+        gt=1,
+        default=None,
+        description="Maximum number of tokens allocated for entity descriptions in local retrieval.",
+    )
+
+    hl_keywords: Optional[List[str]] = Field(
+        min_length=1,
+        default=None,
+        description="List of high-level keywords to prioritize in retrieval.",
+    )
+
+    ll_keywords: Optional[List[str]] = Field(
+        min_length=1,
+        default=None,
+        description="List of low-level keywords to refine retrieval focus.",
+    )
+
+    conversation_history: Optional[List[dict[str, Any]]] = Field(
+        min_length=1,
+        default=None,
+        description="Stores past conversation history to maintain context. Format: [{'role': 'user/assistant', 'content': 'message'}].",
+    )
+
+    history_turns: Optional[int] = Field(
+        gt=1,
+        default=None,
+        description="Number of complete conversation turns (user-assistant pairs) to consider in the response context.",
+    )
+
+    @field_validator("query", mode="after")
+    @classmethod
+    def query_strip_after(cls, query: str) -> str:
+        return query.strip()
+
+    @field_validator("hl_keywords", mode="after")
+    @classmethod
+    def hl_keywords_strip_after(cls, hl_keywords: List[str] | None) -> List[str] | None:
+        if hl_keywords is None:
+            return None
+        return [keyword.strip() for keyword in hl_keywords]
+
+    @field_validator("ll_keywords", mode="after")
+    @classmethod
+    def ll_keywords_strip_after(cls, ll_keywords: List[str] | None) -> List[str] | None:
+        if ll_keywords is None:
+            return None
+        return [keyword.strip() for keyword in ll_keywords]
+
+    @field_validator("conversation_history", mode="after")
+    @classmethod
+    def conversation_history_role_check(
+        cls, conversation_history: List[dict[str, Any]] | None
+    ) -> List[dict[str, Any]] | None:
+        if conversation_history is None:
+            return None
+        for msg in conversation_history:
+            if "role" not in msg or msg["role"] not in {"user", "assistant"}:
+                raise ValueError(
+                    "Each message must have a 'role' key with value 'user' or 'assistant'."
+                )
+        return conversation_history
 
 
 class QueryResponse(BaseModel):
-    response: str
+    response: str = Field(
+        description="The generated response",
+    )
 
 
 class InsertTextRequest(BaseModel):
-    text: str = Field(min_length=1)
+    text: str = Field(
+        min_length=1,
+        description="The text to insert",
+    )
 
     @field_validator("text", mode="after")
     @classmethod
@@ -683,7 +753,10 @@ class InsertTextRequest(BaseModel):
 
 
 class InsertTextsRequest(BaseModel):
-    texts: list[str] = Field(min_length=1)
+    texts: list[str] = Field(
+        min_length=1,
+        description="The texts to insert",
+    )
 
     @field_validator("texts", mode="after")
     @classmethod