feat(Tool Calling): Support required and specific function mode (#6550)

python/sglang/srt/function_call/pythonic_detector.py

@@ -0,0 +1,163 @@
+import ast
+import json
+import logging
+import re
+from typing import List, Optional
+
+from sglang.srt.function_call.base_format_detector import BaseFormatDetector
+from sglang.srt.function_call.core_types import (
+    StreamingParseResult,
+    StructureInfo,
+    ToolCallItem,
+    _GetInfoFunc,
+)
+from sglang.srt.function_call.ebnf_composer import EBNFComposer
+from sglang.srt.openai_api.protocol import Tool
+
+logger = logging.getLogger(__name__)
+
+
+class PythonicDetector(BaseFormatDetector):
+    """
+    Detector for Llama-3.2 and Llama-4 models with pythonic tool call format.
+    Assumes function call format:
+      [tool1(arg1=val1, arg2=val2), tool2(arg1=val3)]
+    Arguments are Python literals (not JSON).
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.tool_call_regex = re.compile(
+            r"\[([a-zA-Z]+\w*\(([a-zA-Z]+\w*=.*,\s*)*([a-zA-Z]+\w*=.*\s)?\),\s*)*([a-zA-Z]+\w*\(([a-zA-Z]+\w*=.*,\s*)*([a-zA-Z]+\w*=.*\s*)?\)\s*)+\]",
+            re.DOTALL,
+        )
+
+    def has_tool_call(self, text: str) -> bool:
+        return bool(self.tool_call_regex.match(text.strip()))
+
+    def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
+        # Try parsing the text as a Python list of function calls
+        text = text.strip()
+        if not (text.startswith("[") and text.endswith("]")):
+            # Not a pythonic tool call format
+            return StreamingParseResult(normal_text=text, calls=[])
+        try:
+            module = ast.parse(text)
+            parsed = getattr(module.body[0], "value", None)
+            if not (
+                isinstance(parsed, ast.List)
+                and all(isinstance(e, ast.Call) for e in parsed.elts)
+            ):
+                return StreamingParseResult(normal_text=text, calls=[])
+            calls = []
+            tool_indices = {
+                tool.function.name: i
+                for i, tool in enumerate(tools)
+                if tool.function.name
+            }
+            for call in parsed.elts:
+                if not isinstance(call.func, ast.Name):
+                    continue
+                function_name = call.func.id
+                arguments = {}
+                for keyword in call.keywords:
+                    arguments[keyword.arg] = self._get_parameter_value(keyword.value)
+                calls.append(
+                    ToolCallItem(
+                        tool_index=tool_indices.get(function_name, -1),
+                        name=function_name,
+                        parameters=json.dumps(arguments, ensure_ascii=False),
+                    )
+                )
+            return StreamingParseResult(normal_text="", calls=calls)
+        except Exception:
+            logger.exception("Error in pythonic tool call parsing.")
+            return StreamingParseResult(normal_text=text, calls=[])
+
+    def _find_matching_bracket(self, buffer: str, start: int) -> int:
+        """
+        Find the matching closing bracket for the opening bracket at start position.
+        Properly handles nested brackets.
+
+        Args:
+            buffer: The text buffer to search in
+            start: Position of the opening bracket '['
+
+        Returns:
+            Position of the matching closing bracket ']', or -1 if not found
+        """
+        bracket_count = 0
+        for i in range(start, len(buffer)):
+            if buffer[i] == "[":
+                bracket_count += 1
+            elif buffer[i] == "]":
+                bracket_count -= 1
+                if bracket_count == 0:
+                    return i
+        return -1  # No matching bracket found
+
+    def parse_streaming_increment(
+        self, new_text: str, tools: List[Tool]
+    ) -> StreamingParseResult:
+        """
+        Streaming incremental parsing for pythonic tool calls.
+        Buffers input until a complete pythonic tool call (from [ to ]) is found,
+        then parses and emits any detected calls.
+        """
+        self._buffer += new_text
+        start = self._buffer.find("[")
+
+        if start == -1:
+            normal_text = self._buffer
+            self._buffer = ""
+            return StreamingParseResult(normal_text=normal_text)
+
+        normal_text = self._buffer[:start] if start > 0 else ""
+
+        end = self._find_matching_bracket(self._buffer, start)
+        if end != -1:
+            call_text = self._buffer[start : end + 1]
+            result = self.detect_and_parse(call_text, tools)
+            self._buffer = self._buffer[end + 1 :]
+
+            # If we had normal text before the tool call, add it to the result
+            if normal_text:
+                result.normal_text = normal_text + (result.normal_text or "")
+
+            return result
+
+        # We have an opening bracket but no closing bracket yet
+        if normal_text:
+            self._buffer = self._buffer[start:]
+            return StreamingParseResult(normal_text=normal_text)
+
+        # Otherwise, we're still accumulating a potential tool call
+        return StreamingParseResult(normal_text="")
+
+    def _get_parameter_value(self, val):
+        if isinstance(val, ast.Constant):
+            return val.value
+        elif isinstance(val, ast.Dict):
+            return {
+                k.value: self._get_parameter_value(v)
+                for k, v in zip(val.keys, val.values)
+            }
+        elif isinstance(val, ast.List):
+            return [self._get_parameter_value(v) for v in val.elts]
+        else:
+            raise ValueError("Tool call arguments must be literals")
+
+    def structure_info(self) -> _GetInfoFunc:
+        def info(name: str):
+            return StructureInfo(begin=f"[{name}(", end=")]", trigger=f"[{name}(")
+
+        return info
+
+    def build_ebnf(self, tools: List[Tool]) -> Optional[str]:
+        return EBNFComposer.build_ebnf(
+            tools,
+            bot_token="[",
+            eot_token="]",
+            tool_call_separator=",",
+            function_format="pythonic",
+        )