chore: import upstream snapshot with attribution

python/sglang/srt/function_call/minimax_m2.py

@@ -0,0 +1,522 @@
+import json
+import logging
+import re
+from typing import Any, Dict, List, Tuple
+
+from sglang.srt.entrypoints.openai.protocol import Tool
+from sglang.srt.function_call.base_format_detector import BaseFormatDetector
+from sglang.srt.function_call.core_types import (
+    StreamingParseResult,
+    ToolCallItem,
+    _GetInfoFunc,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class MinimaxM2Detector(BaseFormatDetector):
+    """
+    Detector for MiniMax M2 models.
+    Assumes function call format:
+        <minimax:tool_call>
+        <invoke name="func1">
+        <parameter name="param1">value1</parameter>
+        <parameter name="param2">value2</parameter>
+        </invoke>
+        </minimax:tool_call>
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.tool_call_start_token: str = "<minimax:tool_call>"
+        self.tool_call_end_token: str = "</minimax:tool_call>"
+        self.tool_call_prefix: str = '<invoke name="'
+        self.tool_call_function_end_token: str = "</invoke>"
+        self.tool_call_regex = re.compile(
+            r"<minimax:tool_call>(.*?)</minimax:tool_call>|<minimax:tool_call>(.*?)$",
+            re.DOTALL,
+        )
+        self.tool_call_function_regex = re.compile(
+            r"<invoke name=\"(.*?)</invoke>|<invoke name=\"(.*)$", re.DOTALL
+        )
+        self.tool_call_parameter_regex = re.compile(
+            r"<parameter name=\"(.*?)</parameter>|<parameter name=\"(.*?)$", re.DOTALL
+        )
+        self._buf: str = ""
+
+        # Streaming state variables
+        self._current_function_name: str = ""
+        self._current_parameters: Dict[str, Any] = {}
+        self._streamed_parameters: Dict[str, str] = (
+            {}
+        )  # Track what parameter content we've streamed
+        self._in_tool_call: bool = False
+        self._function_name_sent: bool = False
+
+    def has_tool_call(self, text: str) -> bool:
+        return self.tool_call_start_token in text
+
+    def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
+        normal, calls = self._extract(text, tools)
+        return StreamingParseResult(normal_text=normal, calls=calls)
+
+    def _convert_param_value(self, value: str, param_type: str) -> Any:
+        """Convert parameter value to the correct type (legacy single-type version)."""
+        return self._convert_param_value_with_types(value, [param_type])
+
+    def _extract_types_from_schema(self, schema: Any) -> list[str]:
+        """
+        Extract all possible types from a JSON schema definition.
+        Handles anyOf, oneOf, allOf, type arrays, and enum fields.
+
+        Args:
+            schema: The JSON schema definition for a parameter
+
+        Returns:
+            List of type strings (e.g., ["string", "integer", "null"])
+        """
+        if schema is None:
+            return ["string"]
+
+        if not isinstance(schema, dict):
+            return ["string"]
+
+        types: set[str] = set()
+
+        # Handle direct "type" field
+        if "type" in schema:
+            type_value = schema["type"]
+            if isinstance(type_value, str):
+                types.add(type_value)
+            elif isinstance(type_value, list):
+                for t in type_value:
+                    if isinstance(t, str):
+                        types.add(t)
+
+        # Handle enum - infer types from enum values
+        if "enum" in schema and isinstance(schema["enum"], list) and schema["enum"]:
+            for value in schema["enum"]:
+                if value is None:
+                    types.add("null")
+                elif isinstance(value, bool):
+                    types.add("boolean")
+                elif isinstance(value, int):
+                    types.add("integer")
+                elif isinstance(value, float):
+                    types.add("number")
+                elif isinstance(value, str):
+                    types.add("string")
+                elif isinstance(value, list):
+                    types.add("array")
+                elif isinstance(value, dict):
+                    types.add("object")
+
+        # Handle anyOf, oneOf, allOf - recursively extract types
+        for choice_field in ("anyOf", "oneOf", "allOf"):
+            if choice_field in schema and isinstance(schema[choice_field], list):
+                for choice in schema[choice_field]:
+                    extracted = self._extract_types_from_schema(choice)
+                    types.update(extracted)
+
+        # If no types found, default to string
+        if not types:
+            return ["string"]
+
+        return list(types)
+
+    def _convert_param_value_with_types(
+        self, value: str, param_types: list[str]
+    ) -> Any:
+        """
+        Convert parameter value to the correct type based on a list of possible types.
+        Tries each type in order until one succeeds.
+
+        Args:
+            value: The string value to convert
+            param_types: List of possible type strings
+
+        Returns:
+            The converted value
+        """
+        if value.lower() == "null":
+            return None
+
+        # Normalize types
+        normalized_types = [t.lower() for t in param_types]
+
+        # Try null first if it's in the list
+        if "null" in normalized_types or value.lower() in ("null", "none", "nil"):
+            return None
+
+        # Try each type in order of preference (most specific first, string as fallback)
+        # Priority: integer > number > boolean > object > array > string
+        type_priority = [
+            "integer",
+            "int",
+            "number",
+            "float",
+            "boolean",
+            "bool",
+            "object",
+            "array",
+            "string",
+            "str",
+            "text",
+        ]
+
+        for param_type in type_priority:
+            if param_type not in normalized_types:
+                continue
+
+            if param_type in ["string", "str", "text"]:
+                return value
+            elif param_type in ["integer", "int"]:
+                try:
+                    return int(value)
+                except (ValueError, TypeError):
+                    continue
+            elif param_type in ["number", "float"]:
+                try:
+                    val = float(value)
+                    return val if val != int(val) else int(val)
+                except (ValueError, TypeError):
+                    continue
+            elif param_type in ["boolean", "bool"]:
+                lower_val = value.lower().strip()
+                if lower_val in ["true", "1", "yes", "on"]:
+                    return True
+                elif lower_val in ["false", "0", "no", "off"]:
+                    return False
+                continue
+            elif param_type in ["object", "array"]:
+                try:
+                    return json.loads(value)
+                except json.JSONDecodeError:
+                    continue
+
+        # Fallback: try JSON parse, then return as string
+        try:
+            return json.loads(value)
+        except json.JSONDecodeError:
+            return value
+
+    def _get_param_types_from_config(
+        self, param_name: str, param_config: dict
+    ) -> list[str]:
+        """
+        Get parameter types from parameter configuration.
+        Handles anyOf, oneOf, allOf, and direct type definitions.
+
+        Args:
+            param_name: The name of the parameter
+            param_config: The properties dict from the tool schema
+
+        Returns:
+            List of type strings
+        """
+        if param_name not in param_config:
+            return ["string"]
+
+        param_schema = param_config[param_name]
+        if not isinstance(param_schema, dict):
+            return ["string"]
+
+        return self._extract_types_from_schema(param_schema)
+
+    def parse_streaming_increment(
+        self, new_text: str, tools: List[Tool]
+    ) -> StreamingParseResult:
+        self._buf += new_text
+        normal = ""
+        calls: List[ToolCallItem] = []
+
+        # Build tool indices for validation
+        if not hasattr(self, "_tool_indices"):
+            self._tool_indices = self._get_tool_indices(tools)
+
+        while True:
+            # If we're not in a tool call and don't see a start token, return normal text
+            if not self._in_tool_call and self.tool_call_start_token not in self._buf:
+                normal += self._buf
+                self._buf = ""
+                break
+
+            # Look for tool call start
+            if not self._in_tool_call:
+                s = self._buf.find(self.tool_call_start_token)
+                if s == -1:
+                    normal += self._buf
+                    self._buf = ""
+                    break
+
+                normal += self._buf[:s]
+                self._buf = self._buf[s:]
+
+                self._in_tool_call = True
+                self._function_name_sent = False
+                self._current_function_name = ""
+                self._current_parameters = {}
+                self._streamed_parameters = {}
+
+                # Remove the start token
+                self._buf = self._buf[len(self.tool_call_start_token) :]
+                continue
+
+            # We're in a tool call, try to parse function name if not sent yet
+            if not self._function_name_sent:
+                # Look for function name pattern: <invoke name=name>
+                function_match = re.search(r"<invoke name=\"([^>]+)\">", self._buf)
+                if function_match:
+                    function_name = function_match.group(1).strip()
+
+                    # Validate function name
+                    if function_name in self._tool_indices:
+                        self._current_function_name = function_name
+                        self._function_name_sent = True
+
+                        # Initialize tool call tracking
+                        if self.current_tool_id == -1:
+                            self.current_tool_id = 0
+
+                        # Ensure tracking arrays are large enough
+                        while len(self.prev_tool_call_arr) <= self.current_tool_id:
+                            self.prev_tool_call_arr.append({})
+                        while len(self.streamed_args_for_tool) <= self.current_tool_id:
+                            self.streamed_args_for_tool.append("")
+
+                        # Store tool call info
+                        self.prev_tool_call_arr[self.current_tool_id] = {
+                            "name": function_name,
+                            "arguments": {},
+                        }
+
+                        # Send tool name with empty parameters
+                        calls.append(
+                            ToolCallItem(
+                                tool_index=self.current_tool_id,
+                                name=function_name,
+                                parameters="",
+                            )
+                        )
+
+                        # Remove the processed function declaration
+                        self._buf = self._buf[function_match.end() :]
+                        continue
+                    else:
+                        # Invalid function name, reset state
+                        logger.warning(f"Invalid function name: {function_name}")
+                        self._reset_streaming_state()
+                        normal += self._buf
+                        self._buf = ""
+                        break
+                else:
+                    # Function name not complete yet, wait for more text
+                    break
+
+            # Parse parameters incrementally
+            if self._function_name_sent:
+                # Process parameters and get any calls to emit
+                parameter_calls = self._parse_and_stream_parameters(self._buf, tools)
+                calls.extend(parameter_calls)
+
+                # Check if tool call is complete
+                if self.tool_call_function_end_token in self._buf:
+                    end_pos = self._buf.find(self.tool_call_function_end_token)
+
+                    # Add closing brace to complete the JSON object
+                    current_streamed = self.streamed_args_for_tool[self.current_tool_id]
+                    if current_streamed:
+                        # Count opening and closing braces to check if JSON is complete
+                        open_braces = current_streamed.count("{")
+                        close_braces = current_streamed.count("}")
+                        if open_braces > close_braces:
+                            calls.append(
+                                ToolCallItem(
+                                    tool_index=self.current_tool_id,
+                                    name=None,
+                                    parameters="}",
+                                )
+                            )
+                            self.streamed_args_for_tool[self.current_tool_id] = (
+                                current_streamed + "}"
+                            )
+
+                    # Complete the tool call
+                    self._buf = self._buf[
+                        end_pos + len(self.tool_call_function_end_token) :
+                    ]
+                    self._reset_streaming_state(True)
+                    self.current_tool_id += 1
+                    continue
+                else:
+                    # Tool call not complete yet, wait for more text
+                    break
+
+        return StreamingParseResult(normal_text=normal, calls=calls)
+
+    def _parse_and_stream_parameters(
+        self, text_to_parse: str, tools: List[Tool]
+    ) -> List[ToolCallItem]:
+        """
+        Parse complete parameter blocks from text and return any tool call items to emit.
+
+        This method:
+        1. Finds all complete <parameter> blocks
+        2. Parses them into a dictionary
+        3. Compares with current parameters and generates diff if needed
+        4. Updates internal state
+
+        Args:
+            text_to_parse: The text to search for parameter blocks
+
+        Returns:
+            List of ToolCallItem objects to emit (may be empty)
+        """
+        calls: List[ToolCallItem] = []
+
+        # Find all complete parameter patterns
+        param_matches = list(
+            re.finditer(
+                r"<parameter name=\"([^>]+)\">(.*?)</parameter>",
+                text_to_parse,
+                re.DOTALL,
+            )
+        )
+
+        # Build new parameters dictionary
+        new_params = {}
+        for match in param_matches:
+            param_name = match.group(1).strip()
+            param_value = match.group(2)
+            new_params[param_name] = self._parse_parameter(
+                self._current_function_name, param_name, param_value, tools
+            )
+
+        # Calculate parameter diff to stream with proper incremental JSON building
+        if new_params != self._current_parameters:
+            previous_args_json = self.streamed_args_for_tool[self.current_tool_id]
+
+            # Build incremental JSON properly
+            if not self._current_parameters:
+                # First parameter(s) - start JSON object but don't close it yet
+                items = []
+                for key, value in new_params.items():
+                    items.append(
+                        f"{json.dumps(key, ensure_ascii=False)}: {json.dumps(value, ensure_ascii=False)}"
+                    )
+                json_fragment = "{" + ", ".join(items)
+
+                calls.append(
+                    ToolCallItem(
+                        tool_index=self.current_tool_id,
+                        name=None,
+                        parameters=json_fragment,
+                    )
+                )
+                self.streamed_args_for_tool[self.current_tool_id] = json_fragment
+
+            else:
+                # Additional parameters - add them incrementally
+                new_keys = set(new_params.keys()) - set(self._current_parameters.keys())
+                if new_keys:
+                    # Build the continuation part (no closing brace yet)
+                    continuation_parts = []
+                    for key in new_keys:
+                        value = new_params[key]
+                        continuation_parts.append(
+                            f"{json.dumps(key, ensure_ascii=False)}: {json.dumps(value, ensure_ascii=False)}"
+                        )
+
+                    json_fragment = ", " + ", ".join(continuation_parts)
+
+                    calls.append(
+                        ToolCallItem(
+                            tool_index=self.current_tool_id,
+                            name=None,
+                            parameters=json_fragment,
+                        )
+                    )
+                    self.streamed_args_for_tool[self.current_tool_id] = (
+                        previous_args_json + json_fragment
+                    )
+
+            # Update current state
+            self._current_parameters = new_params
+            self.prev_tool_call_arr[self.current_tool_id]["arguments"] = new_params
+
+        return calls
+
+    def _reset_streaming_state(self, still_in_tool_call: bool = False):
+        """Reset streaming state for the next tool call"""
+        self._in_tool_call = still_in_tool_call
+        self._function_name_sent = False
+        self._current_function_name = ""
+        self._current_parameters = {}
+        self._streamed_parameters = {}
+        self.current_tool_name_sent = False
+
+    def _extract(self, text: str, tools: List[Tool]) -> Tuple[str, List[ToolCallItem]]:
+        normal_parts: List[str] = []
+        calls: List[ToolCallItem] = []
+        cursor = 0
+        while True:
+            s = text.find(self.tool_call_start_token, cursor)
+            if s == -1:
+                normal_parts.append(text[cursor:])
+                break
+            normal_parts.append(text[cursor:s])
+            e = text.find(self.tool_call_end_token, s)
+            if e == -1:
+                normal_parts.append(text[s:])
+                break
+            block = text[s : e + len(self.tool_call_end_token)]
+            cursor = e + len(self.tool_call_end_token)
+            calls.extend(self._parse_block(block, tools))
+        return "".join(normal_parts), calls
+
+    def _parse_block(self, block: str, tools: List[Tool]) -> List[ToolCallItem]:
+        res: List[ToolCallItem] = []
+        for m in self.tool_call_function_regex.findall(block):
+            txt = m[0] if m[0] else m[1]
+            if '">' not in txt:
+                continue
+            idx = txt.index('">')
+            fname = txt[:idx].strip()
+            body = txt[idx + 2 :]
+            params: Dict[str, Any] = {}
+            for pm in self.tool_call_parameter_regex.findall(body):
+                ptxt = pm[0] if pm[0] else pm[1]
+                if '">' not in ptxt:
+                    continue
+                pidx = ptxt.index('">')
+                pname = ptxt[:pidx].strip()
+                pval = ptxt[pidx + 2 :].lstrip("\n").rstrip("\n")
+                params[pname] = self._parse_parameter(fname, pname, pval, tools)
+            raw = {"name": fname, "arguments": params}
+            try:
+                # TODO: fix idx in function call, the index for a function
+                # call will always be -1 in parse_base_json
+                res.extend(self.parse_base_json(raw, tools))
+            except Exception:
+                logger.warning("invalid tool call for %s dropped", fname)
+        return res
+
+    def _parse_parameter(
+        self, fname: str, pname: str, pval: str, tools: List[Tool]
+    ) -> Any:
+        param_config = {}
+        for tool in tools:
+            if tool.function.name == fname and tool.function.parameters is not None:
+                parameters = tool.function.parameters
+                if isinstance(parameters, dict) and "properties" in parameters:
+                    param_config = parameters["properties"]
+                    break
+
+        param_type = self._get_param_types_from_config(pname, param_config)
+        return self._convert_param_value_with_types(pval, param_type)
+
+    def supports_structural_tag(self) -> bool:
+        return False
+
+    def structure_info(self) -> _GetInfoFunc:
+        raise NotImplementedError