chore: import upstream snapshot with attribution

python/sglang/srt/function_call/pythonic_detector.py

@@ -0,0 +1,224 @@
+import ast
+import json
+import logging
+import re
+from typing import List
+
+from sglang.srt.entrypoints.openai.protocol import Tool
+from sglang.srt.environ import envs
+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 PythonicDetector(BaseFormatDetector):
+    """
+    Detector for Llama-4 models with Pythonic tool call format.
+
+    The Pythonic format uses Python function call syntax within square brackets,
+    with arguments as Python literals rather than JSON.
+
+    Format Structure:
+    ```
+    [tool1(arg1=val1, arg2=val2), tool2(arg1=val3)]
+    ```
+
+    Reference: https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct?chat_template=default
+    """
+
+    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,
+        )
+
+    @staticmethod
+    def _text_strip(text: str) -> str:
+        # Llama 4 model sometime will output <|python_start|> and <|python_end|> tokens
+        # remove those tokens
+        text = text.replace("<|python_start|>", "")
+        text = text.replace("<|python_end|>", "")
+        return text
+
+    def has_tool_call(self, text: str) -> bool:
+        return bool(self.tool_call_regex.search(self._text_strip(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()
+
+        # Remove unexpected <|python_start|> and <|python_end|> for llama4
+        text = self._text_strip(text)
+
+        match = self.tool_call_regex.search(text)
+        if match is None:
+            return StreamingParseResult(normal_text=text, calls=[])
+
+        # Extract the tool call part and any text before/after it
+        tool_call_start = match.start()
+        tool_call_end = match.end()
+
+        normal_text_before = text[:tool_call_start] if tool_call_start > 0 else ""
+        tool_call_text = text[tool_call_start:tool_call_end]
+        normal_text_after = text[tool_call_end:] if tool_call_end < len(text) else ""
+
+        # Combine normal text
+        normal_text = normal_text_before + normal_text_after
+
+        try:
+            module = ast.parse(tool_call_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=normal_text, calls=[])
+
+            calls = []
+            tool_indices = self._get_tool_indices(tools)
+            for call_index, call in enumerate(parsed.elts):
+                if not isinstance(call.func, ast.Name):
+                    continue
+                function_name = call.func.id
+                # Validate that the function exists in the tools
+                if function_name not in tool_indices:
+                    logger.warning(
+                        f"Model attempted to call undefined function: {function_name}"
+                    )
+                    if not envs.SGLANG_FORWARD_UNKNOWN_TOOLS.get():
+                        continue  # Skip unknown tools (default legacy behavior)
+
+                arguments = {}
+                for keyword in call.keywords:
+                    arguments[keyword.arg] = self._get_parameter_value(keyword.value)
+                calls.append(
+                    ToolCallItem(
+                        tool_index=call_index,  # Use the call index in the response, not tool position
+                        name=function_name,
+                        parameters=json.dumps(arguments, ensure_ascii=False),
+                    )
+                )
+
+            return StreamingParseResult(normal_text=normal_text, calls=calls)
+        except Exception:
+            logger.exception("Error in pythonic tool call parsing.")
+            return StreamingParseResult(normal_text=normal_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 _strip_and_split_buffer(self, buffer: str) -> tuple[str, str]:
+        """
+        Strip special tokens from buffer and split into safe_text and held_back_text.
+
+        Returns:
+            tuple of (safe_text_to_output, text_to_hold_in_buffer)
+        """
+        # Check if original buffer ends with a partial token at the end
+        special_tokens = ["<|python_start|>", "<|python_end|>"]
+
+        for token in special_tokens:
+            partial_length = self._ends_with_partial_token(buffer, token)
+            if partial_length > 0:
+                # Split buffer: safe part + held back partial token
+                safe_text = buffer[:-partial_length]
+                held_back = buffer[-partial_length:]
+                # Strip complete special tokens from safe part only
+                safe_text = self._text_strip(safe_text)
+                return safe_text, held_back
+
+        # No partial tokens found, strip complete tokens from entire buffer
+        safe_text = self._text_strip(buffer)
+        return safe_text, ""
+
+    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
+
+        # Strip special tokens from entire buffer and handle partial tokens
+        stripped_buffer, held_back = self._strip_and_split_buffer(self._buffer)
+
+        start = stripped_buffer.find("[")
+
+        if start == -1:
+            # No tool call bracket found
+            self._buffer = held_back
+            return StreamingParseResult(normal_text=stripped_buffer)
+
+        normal_text = stripped_buffer[:start] if start > 0 else ""
+
+        end = self._find_matching_bracket(stripped_buffer, start)
+        if end != -1:
+            # Found complete tool call
+            call_text = stripped_buffer[start : end + 1]
+            result = self.detect_and_parse(call_text, tools)
+
+            # Update buffer with remaining text after tool call plus any held back text
+            remaining_text = stripped_buffer[end + 1 :] + held_back
+            self._buffer = remaining_text
+
+            # 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
+        # Put back everything from the bracket onwards plus held back text
+        self._buffer = stripped_buffer[start:] + held_back
+
+        if normal_text:
+            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 supports_structural_tag(self) -> bool:
+        return False
+
+    def structure_info(self) -> _GetInfoFunc:
+        raise NotImplementedError