update op.__file__

.pre-commit-config.yaml

@@ -81,6 +81,7 @@ repos:
           --disable=C3001,
           --disable=R1702,
           --disable=R0912,
+          --disable=R0915,
           --max-line-length=120,
           --max-statements=75,
         ]

docs/zh/guide/async_op_llm_guide.md

@@ -50,8 +50,6 @@ import json
 
 @C.register_op()
 class QAOp(BaseAsyncOp):
-    file_path: str = __file__  # 必须设置，用于自动查找 prompt 文件
-
     async def async_execute(self):
         """执行问答逻辑"""
         # 1. 读取输入
@@ -156,7 +154,6 @@ if __name__ == "__main__":
 6. **调用 LLM**：使用 `await self.llm.achat(messages=messages, ...)`
 7. **处理响应**：使用 `callback_fn` 处理或转换响应，返回处理后的结果
 8. **应用上下文**：必须在 `FlowLLMApp()` 上下文里调用
-9. **file_path**：Op 类中必须设置 `file_path = __file__`，用于自动查找 prompt 文件
 
 ---
 

docs/zh/guide/cmd_service_guide.md

@@ -15,8 +15,6 @@ from flowllm.core.op import BaseAsyncOp
 
 @C.register_op()
 class EchoOp(BaseAsyncOp):
-    file_path: str = __file__
-
     async def async_execute(self):
         text = self.context.get("text", "")
         self.context.response.answer = f"echo: {text}"

docs/zh/guide/http_service_guide.md

@@ -14,8 +14,6 @@ from flowllm.core.op import BaseAsyncOp
 
 @C.register_op()
 class EchoOp(BaseAsyncOp):
-    file_path: str = __file__
-
     async def async_execute(self):
         text = self.context.get("text", "")
         self.context.response.answer = f"echo: {text}"

docs/zh/guide/http_stream_guide.md

@@ -16,8 +16,6 @@ from flowllm.core.schema import FlowStreamChunk, Message
 
 @C.register_op()
 class StreamChatOp(BaseAsyncOp):
-    file_path: str = __file__
-
     async def async_execute(self):
         messages = self.context.messages
         system_prompt = self.context.system_prompt

docs/zh/guide/mcp_service_guide.md

@@ -15,7 +15,6 @@ from flowllm.core.op import BaseAsyncOp
 @C.register_op()
 class MockSearchOp(BaseAsyncOp):
     """Mock search operation that uses LLM to generate realistic search results."""
-    file_path: str = __file__
 
     async def async_execute(self):
         query = self.context.query

flowllm/core/llm/lite_llm.py

@@ -110,7 +110,12 @@ def stream_chat(
             **self.kwargs,
             **kwargs,
         }
-        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        log_kwargs: Dict[str, object] = {}
+        for k, v in chat_kwargs.items():
+            if k in ["messages", "tools"]:
+                log_kwargs[k] = len(v) if v is not None else 0
+            else:
+                log_kwargs[k] = v
         logger.info(f"LiteLLM.stream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):
@@ -217,7 +222,12 @@ async def astream_chat(
             **self.kwargs,
             **kwargs,
         }
-        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        log_kwargs: Dict[str, object] = {}
+        for k, v in chat_kwargs.items():
+            if k in ["messages", "tools"]:
+                log_kwargs[k] = len(v) if v is not None else 0
+            else:
+                log_kwargs[k] = v
         logger.info(f"LiteLLM.astream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):

flowllm/core/llm/openai_compatible_llm.py

@@ -106,7 +106,12 @@ def stream_chat(
             **self.kwargs,
             **kwargs,
         }
-        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        log_kwargs: Dict[str, object] = {}
+        for k, v in chat_kwargs.items():
+            if k in ["messages", "tools"]:
+                log_kwargs[k] = len(v) if v is not None else 0
+            else:
+                log_kwargs[k] = v
         logger.info(f"OpenAICompatibleLLM.stream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):
@@ -208,7 +213,12 @@ async def astream_chat(
             **self.kwargs,
             **kwargs,
         }
-        log_kwargs = {k: v for k, v in chat_kwargs.items() if k != "messages"}
+        log_kwargs: Dict[str, object] = {}
+        for k, v in chat_kwargs.items():
+            if k in ["messages", "tools"]:
+                log_kwargs[k] = len(v) if v is not None else 0
+            else:
+                log_kwargs[k] = v
         logger.info(f"OpenAICompatibleLLM.astream_chat: {log_kwargs}")
 
         for i in range(self.max_retries):

flowllm/core/op/base_op.py

@@ -6,6 +6,7 @@
 """
 
 import copy
+import inspect
 from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import Callable, List, Union
@@ -78,8 +79,6 @@ def execute(self):
         ```
     """
 
-    file_path: str = __file__
-
     def __new__(cls, *args, **kwargs):
         """Create a new instance and save initialization arguments for copying.
 
@@ -149,7 +148,9 @@ def __init__(
         self.raise_exception: bool = raise_exception
         self.enable_multithread: bool = enable_multithread
         self.language: str = language or C.language
-        default_prompt_path: str = self.file_path.replace("op.py", "prompt.yaml")
+
+        subclass_file_path: str = inspect.getfile(self.__class__)
+        default_prompt_path: str = subclass_file_path.replace("op.py", "prompt.yaml")
         self.prompt_path: Path = Path(prompt_path if prompt_path else default_prompt_path)
         self.prompt = PromptHandler(language=self.language).load_prompt_by_file(self.prompt_path)
         self._llm: BaseLLM | str = llm

flowllm/core/schema/message.py

@@ -95,6 +95,38 @@ def simple_dump(self, add_reasoning: bool = True) -> dict:
 
         return result
 
+    def format_message(
+            self,
+            i: int | None = None,
+            add_time_created: bool = False,
+            use_name_first: bool = False,
+            add_reasoning_content: bool = True,
+            add_tool_calls: bool = True
+    ) -> str:
+        content = ""
+        if i is not None:
+            content += f"round{i} "
+
+        if add_time_created:
+            content += f"[{self.time_created}] "
+
+        if use_name_first:
+            content += f"{self.name or self.role.value}:\n"
+        else:
+            content += f"{self.role.value}:\n"
+
+        if add_reasoning_content and self.reasoning_content:
+            content += self.reasoning_content + "\n"
+
+        if self.content:
+            content += self.content + "\n"
+
+        if add_tool_calls and self.tool_calls:
+            for tool_call in self.tool_calls:
+                content += f" - tool_call={tool_call.name} params={tool_call.arguments}\n"
+
+        return content.strip()
+
 
 class Trajectory(BaseModel):
     """Represents a conversation trajectory with messages and optional scoring."""

flowllm/core/vector_store/pgvector_vector_store.py

@@ -168,12 +168,23 @@ def _build_sql_filters(
             # Handle special keys that are stored as direct columns
             if key == "unique_id":
                 # unique_id is a direct column, not in metadata JSONB
-                if use_async:
-                    conditions.append(f"unique_id = ${param_idx}")
+                # Support both single value and list of values
+                if isinstance(filter_value, list):
+                    if use_async:
+                        placeholders = ", ".join(f"${param_idx + i}" for i in range(len(filter_value)))
+                        conditions.append(f"unique_id IN ({placeholders})")
+                    else:
+                        placeholders = ", ".join(["%s"] * len(filter_value))
+                        conditions.append(f"unique_id IN ({placeholders})")
+                    params.extend([str(v) for v in filter_value])
+                    param_idx += len(filter_value)
                 else:
-                    conditions.append("unique_id = %s")
-                params.append(str(filter_value))
-                param_idx += 1
+                    if use_async:
+                        conditions.append(f"unique_id = ${param_idx}")
+                    else:
+                        conditions.append("unique_id = %s")
+                    params.append(str(filter_value))
+                    param_idx += 1
                 continue
 
             # Strip "metadata." prefix if present (since we're already accessing metadata column)

flowllm/core/vector_store/qdrant_vector_store.py

@@ -190,9 +190,26 @@ def _build_qdrant_filters(filter_dict: Optional[Dict[str, Any]] = None):
         for key, filter_value in filter_dict.items():
             # Handle special keys that are stored at payload root level
             if key == "unique_id":
-                qdrant_key = "original_id"
+                # unique_id is stored as original_id in Qdrant payload
+                # Support both single value and list of values
+                if isinstance(filter_value, list):
+                    conditions.append(
+                        FieldCondition(
+                            key="original_id",
+                            match=MatchAny(any=filter_value),
+                        ),
+                    )
+                else:
+                    conditions.append(
+                        FieldCondition(
+                            key="original_id",
+                            match=MatchValue(value=filter_value),
+                        ),
+                    )
+                continue
+
             # Handle nested keys by prefixing with metadata.
-            elif not key.startswith("metadata."):
+            if not key.startswith("metadata."):
                 qdrant_key = f"metadata.{key}"
             else:
                 qdrant_key = key

flowllm/extensions/file_tool/edit_op.py

@@ -21,8 +21,6 @@ class EditOp(BaseAsyncToolOp):
     is specified. Supports creating new files when old_string is empty.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/exit_plan_mode_op.py

@@ -17,8 +17,6 @@ class ExitPlanModeOp(BaseAsyncToolOp):
     to the user for approval before proceeding with implementation.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/glob_op.py

@@ -28,8 +28,6 @@ class GlobOp(BaseAsyncToolOp):
     Supports gitignore patterns for filtering files.
     """
 
-    file_path = __file__
-
     def __init__(self, gitignore_patterns: List[str] = None, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/grep_op.py

@@ -25,8 +25,6 @@ class GrepOp(BaseAsyncToolOp):
     Supports glob pattern filtering and result limiting.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/ls_op.py

@@ -22,8 +22,6 @@ class LSOp(BaseAsyncToolOp):
     matching provided glob patterns.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/read_file_op.py

@@ -20,8 +20,6 @@ class ReadFileOp(BaseAsyncToolOp):
     For text files, it can read specific line ranges using offset and limit.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/read_many_files_op.py

@@ -24,8 +24,6 @@ class ReadManyFilesOp(BaseAsyncToolOp):
     and concatenates them with separators.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/rip_grep_op.py

@@ -22,8 +22,6 @@ class RipGrepOp(BaseAsyncToolOp):
     Supports glob pattern filtering and result limiting.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/shell_op.py

@@ -23,8 +23,6 @@ class ShellOp(BaseAsyncToolOp):
     Supports both foreground and background execution.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/smart_edit_op.py

@@ -24,8 +24,6 @@ class SmartEditOp(BaseAsyncToolOp):
     exact matching, flexible matching (ignoring indentation), and regex-based matching.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/task_op.py

@@ -16,8 +16,6 @@ class TaskOp(BaseAsyncToolOp):
     This operation delegates tasks to specialized subagents for autonomous execution.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/write_file_op.py

@@ -20,8 +20,6 @@ class WriteFileOp(BaseAsyncToolOp):
     it will be created. If parent directories don't exist, they will be created automatically.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/extensions/file_tool/write_todos_op.py

@@ -21,8 +21,6 @@ class WriteTodosOp(BaseAsyncToolOp):
     through different statuses: pending, in_progress, completed, cancelled.
     """
 
-    file_path = __file__
-
     def __init__(self, **kwargs):
         kwargs.setdefault("raise_exception", False)
         super().__init__(**kwargs)

flowllm/gallery/chat_op.py

@@ -17,8 +17,6 @@ class ChatOp(BaseAsyncOp):
     and system_prompt to be present in the context.
     """
 
-    file_path: str = __file__
-
     def __init__(
         self,
         llm: str = "qwen3_30b_instruct",

flowllm/gallery/think_tool_op.py

@@ -9,8 +9,6 @@
 class ThinkToolOp(BaseAsyncToolOp):
     """Utility operation that prompts the model for explicit reflection text."""
 
-    file_path = __file__
-
     def __init__(self, add_output_reflection: bool = False, **kwargs):
         super().__init__(**kwargs)
         self.add_output_reflection: bool = add_output_reflection