859 lines
33 KiB
Python
859 lines
33 KiB
Python
import ast
|
||
import json
|
||
import logging
|
||
import re
|
||
from abc import ABC, abstractmethod
|
||
from dataclasses import dataclass
|
||
from json import JSONDecodeError, JSONDecoder
|
||
from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Type
|
||
|
||
import partial_json_parser
|
||
from partial_json_parser.core.exceptions import MalformedJSON
|
||
from partial_json_parser.core.options import Allow
|
||
from pydantic import BaseModel
|
||
|
||
from sglang.srt.openai_api.protocol import (
|
||
StructuralTagResponseFormat,
|
||
StructuresResponseFormat,
|
||
Tool,
|
||
)
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
TOOLS_TAG_LIST = [
|
||
"<|plugin|>",
|
||
"<function=",
|
||
"<tool_call>",
|
||
"<|python_tag|>",
|
||
"[TOOL_CALLS]",
|
||
"<｜tool▁calls▁begin｜>",
|
||
]
|
||
|
||
|
||
class ToolCallItem(BaseModel):
|
||
"""Simple encapsulation of the parsed ToolCall result for easier usage in streaming contexts."""
|
||
|
||
tool_index: int
|
||
name: Optional[str] = None
|
||
parameters: str # JSON string
|
||
|
||
|
||
def _find_common_prefix(s1: str, s2: str) -> str:
|
||
prefix = ""
|
||
min_length = min(len(s1), len(s2))
|
||
for i in range(0, min_length):
|
||
if s1[i] == s2[i]:
|
||
prefix += s1[i]
|
||
else:
|
||
break
|
||
return prefix
|
||
|
||
|
||
def _partial_json_loads(input_str: str, flags: Allow) -> Tuple[Any, int]:
|
||
try:
|
||
return (partial_json_parser.loads(input_str, flags), len(input_str))
|
||
except JSONDecodeError as e:
|
||
if "Extra data" in e.msg:
|
||
dec = JSONDecoder()
|
||
return dec.raw_decode(input_str)
|
||
raise
|
||
|
||
|
||
def _is_complete_json(input_str: str) -> bool:
|
||
try:
|
||
json.loads(input_str)
|
||
return True
|
||
except JSONDecodeError:
|
||
return False
|
||
|
||
|
||
class StreamingParseResult:
|
||
"""Result of streaming incremental parsing."""
|
||
|
||
def __init__(
|
||
self, normal_text: str = "", calls: Optional[List[ToolCallItem]] = None
|
||
):
|
||
self.normal_text = normal_text
|
||
self.calls = calls or []
|
||
|
||
|
||
@dataclass
|
||
class StructureInfo:
|
||
begin: str
|
||
end: str
|
||
trigger: str
|
||
|
||
|
||
_GetInfoFunc = Callable[[str], StructureInfo]
|
||
"""
|
||
Helper alias of function
|
||
Usually it is a function that takes a name string and returns a StructureInfo object,
|
||
which can be used to construct a structural_tag object
|
||
"""
|
||
|
||
|
||
class BaseFormatDetector(ABC):
|
||
"""Base class providing two sets of interfaces: one-time and streaming incremental."""
|
||
|
||
def __init__(self):
|
||
# initialize properties used for state when parsing tool calls in
|
||
self._buffer = ""
|
||
# streaming mode
|
||
self.prev_tool_call_arr: List[Dict] = []
|
||
self.current_tool_id: int = -1
|
||
self.current_tool_name_sent: bool = False
|
||
self.streamed_args_for_tool: List[str] = (
|
||
[]
|
||
) # map what has been streamed for each tool so far to a list
|
||
self.bot_token = ""
|
||
self.eot_token = ""
|
||
|
||
def parse_base_json(self, action: Any, tools: List[Tool]) -> List[ToolCallItem]:
|
||
tool_indices = {
|
||
tool.function.name: i for i, tool in enumerate(tools) if tool.function.name
|
||
}
|
||
if not isinstance(action, list):
|
||
action = [action]
|
||
|
||
results = []
|
||
for act in action:
|
||
name = act.get("name")
|
||
if name and name in tool_indices:
|
||
results.append(
|
||
ToolCallItem(
|
||
tool_index=tool_indices[name],
|
||
name=name,
|
||
parameters=json.dumps(
|
||
act.get("parameters") or act.get("arguments", {}),
|
||
ensure_ascii=False,
|
||
),
|
||
)
|
||
)
|
||
else:
|
||
logger.warning(f"Model attempted to call undefined function: {name}")
|
||
|
||
return results
|
||
|
||
@abstractmethod
|
||
def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
|
||
"""
|
||
Parses the text in one go. Returns success=True if the format matches, otherwise False.
|
||
Note that leftover_text here represents "content that this parser will not consume further".
|
||
"""
|
||
action = json.loads(text)
|
||
return StreamingParseResult(calls=self.parse_base_json(action, tools))
|
||
|
||
def parse_streaming_increment(
|
||
self, new_text: str, tools: List[Tool]
|
||
) -> StreamingParseResult:
|
||
"""
|
||
Streaming incremental parsing with tool validation.
|
||
"""
|
||
# Append new text to buffer
|
||
self._buffer += new_text
|
||
current_text = self._buffer
|
||
if not (self.bot_token in current_text or current_text.startswith("{")):
|
||
self._buffer = ""
|
||
if self.eot_token in new_text:
|
||
new_text = new_text.replace(self.eot_token, "")
|
||
return StreamingParseResult(normal_text=new_text)
|
||
|
||
# Build tool indices if not already built
|
||
if not hasattr(self, "_tool_indices"):
|
||
self._tool_indices = {
|
||
tool.function.name: i
|
||
for i, tool in enumerate(tools)
|
||
if tool.function and tool.function.name
|
||
}
|
||
|
||
flags = Allow.ALL if self.current_tool_name_sent else Allow.ALL & ~Allow.STR
|
||
try:
|
||
tool_call_arr = []
|
||
is_complete = []
|
||
try:
|
||
start_idx = (
|
||
len(self.bot_token)
|
||
if current_text.startswith(self.bot_token)
|
||
else 0
|
||
)
|
||
while start_idx < len(current_text):
|
||
(obj, end_idx) = _partial_json_loads(
|
||
current_text[start_idx:], flags
|
||
)
|
||
is_complete.append(
|
||
_is_complete_json(current_text[start_idx : start_idx + end_idx])
|
||
)
|
||
start_idx += end_idx + len("; ")
|
||
|
||
# Validate tool name if present
|
||
if "name" in obj and obj["name"] not in self._tool_indices:
|
||
# Invalid tool name - reset state
|
||
self._buffer = ""
|
||
self.current_tool_id = -1
|
||
self.current_tool_name_sent = False
|
||
if self.streamed_args_for_tool:
|
||
self.streamed_args_for_tool.pop()
|
||
return StreamingParseResult()
|
||
|
||
# Handle parameters/arguments consistency
|
||
if "parameters" in obj:
|
||
assert (
|
||
"arguments" not in obj
|
||
), "model generated both parameters and arguments"
|
||
obj["arguments"] = obj["parameters"]
|
||
tool_call_arr.append(obj)
|
||
|
||
except MalformedJSON:
|
||
return StreamingParseResult()
|
||
|
||
if len(tool_call_arr) == 0:
|
||
return StreamingParseResult()
|
||
|
||
current_tool_call: Dict = (
|
||
tool_call_arr[self.current_tool_id] if len(tool_call_arr) > 0 else {}
|
||
)
|
||
|
||
# Handle new tool in array
|
||
if len(tool_call_arr) > 0 and len(tool_call_arr) > self.current_tool_id + 1:
|
||
if self.current_tool_id >= 0:
|
||
cur_arguments = current_tool_call.get("arguments")
|
||
if cur_arguments:
|
||
cur_args_json = json.dumps(cur_arguments)
|
||
sent = len(self.streamed_args_for_tool[self.current_tool_id])
|
||
argument_diff = cur_args_json[sent:]
|
||
|
||
res = StreamingParseResult(
|
||
calls=[
|
||
ToolCallItem(
|
||
tool_index=self.current_tool_id,
|
||
name="",
|
||
parameters=argument_diff,
|
||
)
|
||
],
|
||
)
|
||
self.streamed_args_for_tool[
|
||
self.current_tool_id
|
||
] += argument_diff
|
||
else:
|
||
res = StreamingParseResult()
|
||
else:
|
||
res = StreamingParseResult()
|
||
|
||
self.current_tool_id = len(tool_call_arr) - 1
|
||
self.current_tool_name_sent = False
|
||
self.streamed_args_for_tool.append("")
|
||
return res
|
||
|
||
# Handle tool name
|
||
elif not self.current_tool_name_sent:
|
||
function_name = current_tool_call.get("name")
|
||
if function_name and function_name in self._tool_indices:
|
||
res = StreamingParseResult(
|
||
calls=[
|
||
ToolCallItem(
|
||
tool_index=self._tool_indices[function_name],
|
||
name=function_name,
|
||
parameters="",
|
||
)
|
||
],
|
||
)
|
||
self.current_tool_name_sent = True
|
||
else:
|
||
res = StreamingParseResult()
|
||
|
||
# Handle streaming arguments
|
||
else:
|
||
cur_arguments = current_tool_call.get("arguments")
|
||
res = StreamingParseResult()
|
||
|
||
if cur_arguments:
|
||
sent = len(self.streamed_args_for_tool[self.current_tool_id])
|
||
cur_args_json = json.dumps(cur_arguments)
|
||
prev_arguments = self.prev_tool_call_arr[self.current_tool_id].get(
|
||
"arguments"
|
||
)
|
||
|
||
argument_diff = None
|
||
if is_complete[self.current_tool_id]:
|
||
argument_diff = cur_args_json[sent:]
|
||
self._buffer = ""
|
||
self.prev_tool_call_arr[self.current_tool_id].clear()
|
||
self.current_tool_name_sent = False
|
||
self.streamed_args_for_tool[self.current_tool_id] = ""
|
||
|
||
elif prev_arguments:
|
||
prev_args_json = json.dumps(prev_arguments)
|
||
if cur_args_json != prev_args_json:
|
||
prefix = _find_common_prefix(prev_args_json, cur_args_json)
|
||
argument_diff = prefix[sent:]
|
||
|
||
if argument_diff is not None:
|
||
res = StreamingParseResult(
|
||
calls=[
|
||
ToolCallItem(
|
||
tool_index=self.current_tool_id,
|
||
parameters=argument_diff,
|
||
)
|
||
],
|
||
)
|
||
if not is_complete[self.current_tool_id]:
|
||
self.streamed_args_for_tool[
|
||
self.current_tool_id
|
||
] += argument_diff
|
||
|
||
self.prev_tool_call_arr = tool_call_arr
|
||
return res
|
||
|
||
except Exception as e:
|
||
logger.error(f"Error in parse_streaming_increment: {e}")
|
||
return StreamingParseResult()
|
||
|
||
@abstractmethod
|
||
def has_tool_call(self, text: str) -> bool:
|
||
raise NotImplementedError()
|
||
|
||
@abstractmethod
|
||
def structure_info(self) -> _GetInfoFunc:
|
||
raise NotImplementedError()
|
||
|
||
|
||
class Qwen25Detector(BaseFormatDetector):
|
||
"""
|
||
Detector for Qwen 2.5 models.
|
||
Assumes function call format:
|
||
<tool_call>{"name":"xxx", "arguments":{...}}</tool_call>
|
||
"""
|
||
|
||
def __init__(self):
|
||
"""
|
||
Initializes the detector with necessary state variables.
|
||
"""
|
||
super().__init__()
|
||
self.bot_token = "<tool_call>"
|
||
self.eot_token = "</tool_call>"
|
||
|
||
def has_tool_call(self, text: str) -> bool:
|
||
"""Check if the text contains a Qwen 2.5 format tool call."""
|
||
return self.bot_token in text
|
||
|
||
def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
|
||
"""
|
||
One-time parsing: Detects and parses tool calls in the provided text.
|
||
|
||
:param text: The complete text to parse.
|
||
:param tools: List of available tools.
|
||
:return: ParseResult indicating success or failure, consumed text, leftover text, and parsed calls.
|
||
"""
|
||
idx = text.find(self.bot_token)
|
||
normal_text = text[:idx].strip() if idx != -1 else text
|
||
if self.bot_token not in text:
|
||
return StreamingParseResult(normal_text=normal_text, calls=[])
|
||
pattern = rf"{self.bot_token}(.*?){self.eot_token}"
|
||
match_result_list = re.findall(pattern, text, re.DOTALL)
|
||
calls = []
|
||
for match_result in match_result_list:
|
||
match_result = json.loads(match_result)
|
||
calls.extend(self.parse_base_json(match_result, tools))
|
||
return StreamingParseResult(normal_text=normal_text, calls=calls)
|
||
|
||
def structure_info(self) -> _GetInfoFunc:
|
||
return lambda name: StructureInfo(
|
||
begin='<tool_call>{"name":"' + name + '", "arguments":',
|
||
end="}</tool_call>",
|
||
trigger="<tool_call>",
|
||
)
|
||
|
||
|
||
class MistralDetector(BaseFormatDetector):
|
||
"""
|
||
Detector for Mistral models.
|
||
Assumes function call format:
|
||
<|action_start|><|plugin|>{"name":"xxx", "arguments":{...}}<|action_end|>
|
||
"""
|
||
|
||
def __init__(self):
|
||
"""
|
||
Initializes the detector with necessary state variables.
|
||
"""
|
||
super().__init__()
|
||
self.bot_token = "[TOOL_CALLS] ["
|
||
self.tool_call_regex = re.compile(r"\[{.*}\]", re.DOTALL)
|
||
|
||
def has_tool_call(self, text: str) -> bool:
|
||
"""Check if the text contains a Mistral format tool call."""
|
||
return self.bot_token in text
|
||
|
||
def _clean_text(self, text: str) -> str:
|
||
"""
|
||
clean text to only leave ''[TOOL_CALLS] [{"name": xxx, "arguments": {xxx}}]'
|
||
for example,
|
||
text = '[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"location": "Boston, MA", "unit": "fahrenheit"}}]\n\nToday\'s weather in Boston is :{function call result} (in Fahrenheit)\n\nIf you prefer Celsius, please let me know.'
|
||
return '[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"location": "Boston, MA", "unit": "fahrenheit"}}]'
|
||
The key pattern is [TOOL_CALLS] [...]
|
||
"""
|
||
find_results = re.findall(r"\[TOOL_CALLS\] \[.*?\]", text, re.DOTALL)
|
||
if len(find_results) > 0:
|
||
return find_results[0]
|
||
else:
|
||
return ""
|
||
|
||
def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
|
||
"""
|
||
One-time parsing: Detects and parses tool calls in the provided text.
|
||
|
||
:param text: The complete text to parse.
|
||
:param tools: List of available tools.
|
||
:return: ParseResult indicating success or failure, consumed text, leftover text, and parsed calls.
|
||
"""
|
||
idx = text.find(self.bot_token)
|
||
normal_text = text[:idx].strip() if idx != -1 else text
|
||
text = self._clean_text(text)
|
||
tool_content = text.replace("[TOOL_CALLS]", "").strip()
|
||
raw_tool_calls = self.tool_call_regex.findall(tool_content)
|
||
calls = []
|
||
if len(raw_tool_calls) > 0:
|
||
raw_tool_call = raw_tool_calls[0]
|
||
function_call_arr = json.loads(raw_tool_call)
|
||
for match_result in function_call_arr:
|
||
calls.extend(self.parse_base_json(match_result, tools))
|
||
return StreamingParseResult(normal_text=normal_text, calls=calls)
|
||
|
||
def structure_info(self) -> _GetInfoFunc:
|
||
return lambda name: StructureInfo(
|
||
begin='[TOOL_CALLS] [{"name":"' + name + '", "arguments":',
|
||
end="}]",
|
||
trigger="[TOOL_CALLS]",
|
||
)
|
||
|
||
|
||
class Llama32Detector(BaseFormatDetector):
|
||
"""
|
||
Detector for Llama 3.2 models.
|
||
Assumes function call format:
|
||
<|python_tag|>{"name":"xxx", "arguments":{...}}
|
||
"""
|
||
|
||
def __init__(self):
|
||
super().__init__()
|
||
self.bot_token = "<|python_tag|>"
|
||
|
||
def has_tool_call(self, text: str) -> bool:
|
||
"""Check if the text contains a Llama 3.2 format tool call."""
|
||
# depending on the prompt format the Llama model may or may not
|
||
# prefix the output with the <|python_tag|> token
|
||
return "<|python_tag|>" in text or text.startswith("{")
|
||
|
||
def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
|
||
"""Parse function calls from text, handling multiple JSON objects."""
|
||
if "<|python_tag|>" not in text and not text.startswith("{"):
|
||
return StreamingParseResult(normal_text=text, calls=[])
|
||
|
||
if "<|python_tag|>" in text:
|
||
normal_text, action_text = text.split("<|python_tag|>")
|
||
else:
|
||
normal_text, action_text = "", text
|
||
|
||
# Split by semicolon and process each part
|
||
json_parts = [part.strip() for part in action_text.split(";") if part.strip()]
|
||
all_actions = []
|
||
for part in json_parts:
|
||
try:
|
||
# Parse each individual JSON object
|
||
action = json.loads(part)
|
||
all_actions.append(action)
|
||
except json.JSONDecodeError as e:
|
||
logger.warning(f"Failed to parse JSON part: {part}")
|
||
logger.warning(f"JSON parse error: {str(e)}")
|
||
continue
|
||
calls = []
|
||
# Only process if we found valid JSON objects
|
||
if all_actions:
|
||
calls = self.parse_base_json(all_actions, tools)
|
||
return StreamingParseResult(normal_text=normal_text, calls=calls)
|
||
|
||
def structure_info(self) -> _GetInfoFunc:
|
||
return lambda name: StructureInfo(
|
||
begin='<|python_tag|>{"name":"' + name + '", "arguments":',
|
||
end="}",
|
||
trigger="<|python_tag|>",
|
||
)
|
||
|
||
|
||
class DeepSeekV3Detector(BaseFormatDetector):
|
||
"""
|
||
Detector for DeepSeek models.
|
||
Assumes function call format:
|
||
'<｜tool▁calls▁begin｜><｜tool▁call▁begin｜>function<｜tool▁sep｜>get_current_weather\n```json\n{"location": "Tokyo"}\n```<｜tool▁call▁end｜>\n<｜tool▁call▁begin｜>function<｜tool▁sep｜>get_current_weather\n```json\n{"location": "Paris"}\n```<｜tool▁call▁end｜><｜tool▁calls▁end｜><｜end▁of▁sentence｜>
|
||
"""
|
||
|
||
def __init__(self):
|
||
super().__init__()
|
||
self.bot_token = "<｜tool▁calls▁begin｜>"
|
||
self.eot_token = "<｜tool▁calls▁end｜>"
|
||
self.func_call_regex = r"<｜tool▁call▁begin｜>.*?<｜tool▁call▁end｜>"
|
||
self.func_detail_regex = r"<｜tool▁call▁begin｜>(.*)<｜tool▁sep｜>(.*)\n```json\n(.*)\n```<｜tool▁call▁end｜>"
|
||
self._last_arguments = ""
|
||
|
||
def has_tool_call(self, text: str) -> bool:
|
||
"""Check if the text contains a deepseek format tool call."""
|
||
return self.bot_token in text
|
||
|
||
def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
|
||
"""
|
||
One-time parsing: Detects and parses tool calls in the provided text.
|
||
|
||
:param text: The complete text to parse.
|
||
:param tools: List of available tools.
|
||
:return: ParseResult indicating success or failure, consumed text, leftover text, and parsed calls.
|
||
"""
|
||
idx = text.find(self.bot_token)
|
||
normal_text = text[:idx].strip() if idx != -1 else text
|
||
if self.bot_token not in text:
|
||
return StreamingParseResult(normal_text=normal_text, calls=[])
|
||
match_result_list = re.findall(self.func_call_regex, text, re.DOTALL)
|
||
calls = []
|
||
try:
|
||
for match_result in match_result_list:
|
||
# Get function name
|
||
func_detail = re.search(self.func_detail_regex, match_result, re.DOTALL)
|
||
func_name = func_detail.group(2)
|
||
func_args = func_detail.group(3)
|
||
func_args = json.loads(func_args)
|
||
# construct match_result for parse_base_json
|
||
match_result = {"name": func_name, "parameters": func_args}
|
||
calls.extend(self.parse_base_json(match_result, tools))
|
||
return StreamingParseResult(normal_text=normal_text, calls=calls)
|
||
except Exception as e:
|
||
logger.error(f"Error in detect_and_parse: {e}")
|
||
# return the normal text if parsing fails
|
||
return StreamingParseResult(normal_text=text)
|
||
|
||
def structure_info(self) -> _GetInfoFunc:
|
||
return lambda name: StructureInfo(
|
||
begin=">" + name + "\n```json\n",
|
||
end="\n```<",
|
||
trigger=">" + name + "\n```json\n",
|
||
)
|
||
|
||
def parse_streaming_increment(
|
||
self, new_text: str, tools: List[Tool]
|
||
) -> StreamingParseResult:
|
||
"""
|
||
Streaming incremental parsing tool calls for DeepSeekV3 format.
|
||
"""
|
||
self._buffer += new_text
|
||
current_text = self._buffer
|
||
|
||
if self.bot_token not in current_text:
|
||
self._buffer = ""
|
||
for e_token in [self.eot_token, "```", "<｜tool▁call▁end｜>"]:
|
||
if e_token in new_text:
|
||
new_text = new_text.replace(e_token, "")
|
||
return StreamingParseResult(normal_text=new_text)
|
||
|
||
if not hasattr(self, "_tool_indices"):
|
||
self._tool_indices = {
|
||
tool.function.name: i
|
||
for i, tool in enumerate(tools)
|
||
if tool.function and tool.function.name
|
||
}
|
||
|
||
calls: list[ToolCallItem] = []
|
||
try:
|
||
partial_match = re.search(
|
||
pattern=r"<｜tool▁call▁begin｜>(.*)<｜tool▁sep｜>(.*)\n```json\n(.*)",
|
||
string=current_text,
|
||
flags=re.DOTALL,
|
||
)
|
||
if partial_match:
|
||
func_name = partial_match.group(2).strip()
|
||
func_args_raw = partial_match.group(3).strip()
|
||
|
||
if not self.current_tool_name_sent:
|
||
calls.append(
|
||
ToolCallItem(
|
||
tool_index=self._tool_indices.get(func_name, 0),
|
||
name=func_name,
|
||
parameters="",
|
||
)
|
||
)
|
||
self.current_tool_name_sent = True
|
||
else:
|
||
argument_diff = (
|
||
func_args_raw[len(self._last_arguments) :]
|
||
if func_args_raw.startswith(self._last_arguments)
|
||
else func_args_raw
|
||
)
|
||
|
||
if argument_diff:
|
||
calls.append(
|
||
ToolCallItem(
|
||
tool_index=self._tool_indices.get(func_name, 0),
|
||
name=None,
|
||
parameters=argument_diff,
|
||
)
|
||
)
|
||
self._last_arguments += argument_diff
|
||
|
||
if _is_complete_json(func_args_raw):
|
||
result = StreamingParseResult(normal_text="", calls=calls)
|
||
self._buffer = ""
|
||
self._last_arguments = ""
|
||
self.current_tool_name_sent = False
|
||
return result
|
||
|
||
return StreamingParseResult(normal_text="", calls=calls)
|
||
|
||
except Exception as e:
|
||
logger.error(f"Error in parse_streaming_increment: {e}")
|
||
return StreamingParseResult(normal_text=current_text)
|
||
|
||
|
||
class MultiFormatParser:
|
||
def __init__(self, detectors: List[BaseFormatDetector]):
|
||
"""
|
||
:param detectors: A series of available Detector instances passed in
|
||
"""
|
||
self.detectors = detectors
|
||
|
||
def parse_once(
|
||
self, text: str, tools: List[Tool]
|
||
) -> Tuple[str, list[ToolCallItem]]:
|
||
"""
|
||
One-time parsing: Loop through detectors until there are no new matches or text is exhausted
|
||
Return: (final_text, all_calls)
|
||
- final_text: The remaining text after parsing that was not consumed by any Detector (can be treated as normal text)
|
||
- all_calls: All calls parsed by the Detectors
|
||
"""
|
||
final_calls = []
|
||
final_normal_text = text
|
||
for detector in self.detectors:
|
||
parsed_result = detector.detect_and_parse(text, tools)
|
||
tool_call_list = parsed_result.calls
|
||
if len(tool_call_list) > 0: # parsed successfully
|
||
final_calls = tool_call_list
|
||
final_normal_text = parsed_result.normal_text
|
||
break
|
||
|
||
# leftover_text is the normal text not consumed by any Detector
|
||
return final_normal_text, final_calls
|
||
|
||
def parse_streaming_increment(
|
||
self, new_text: str, tools: List[Tool]
|
||
) -> Tuple[str, list[ToolCallItem]]:
|
||
"""
|
||
Streaming incremental parsing: Feed new_text to each detector's parse_streaming_increment
|
||
and merge their produced normal_text/calls to return.
|
||
(The logic here can be "priority-based" or "parallel parsing" based on your needs)
|
||
"""
|
||
final_normal_text = ""
|
||
final_calls = []
|
||
|
||
for detector in self.detectors:
|
||
sp_result = detector.parse_streaming_increment(new_text, tools)
|
||
# Merge normal_text and calls
|
||
# If one sp_result contains result call, this should be a successful parse
|
||
# If one sp_result only contains normal_text, this can either be a successful
|
||
# parse or it is not using the desired parsing tool.
|
||
if sp_result.normal_text:
|
||
final_normal_text = sp_result.normal_text
|
||
if sp_result.calls:
|
||
final_calls.extend(sp_result.calls)
|
||
final_normal_text = sp_result.normal_text
|
||
break
|
||
|
||
return final_normal_text, final_calls
|
||
|
||
|
||
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 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("[")
|
||
end = self._buffer.find("]", start)
|
||
if start != -1 and end != -1:
|
||
call_text = self._buffer[start : end + 1]
|
||
result = self.detect_and_parse(call_text, tools)
|
||
self._buffer = self._buffer[end + 1 :]
|
||
return result
|
||
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="[", end="]", trigger="")
|
||
|
||
return info
|
||
|
||
|
||
class FunctionCallParser:
|
||
"""
|
||
In streaming scenarios, each time new_text is received, it calls multi_format_parser.parse_streaming_increment
|
||
and returns the resulting normal_text and calls to the upper layer (or SSE).
|
||
"""
|
||
|
||
ToolCallParserEnum: Dict[str, Type[BaseFormatDetector]] = {
|
||
"llama3": Llama32Detector,
|
||
"qwen25": Qwen25Detector,
|
||
"mistral": MistralDetector,
|
||
"deepseekv3": DeepSeekV3Detector,
|
||
"pythonic": PythonicDetector,
|
||
}
|
||
|
||
def __init__(self, tools: List[Tool], tool_call_parser: str):
|
||
detectors = []
|
||
if tool_call_parser:
|
||
detector_class = self.ToolCallParserEnum.get(tool_call_parser)
|
||
if detector_class:
|
||
detectors.append(detector_class())
|
||
else:
|
||
raise ValueError(f"Unsupported tool_call_parser: {tool_call_parser}")
|
||
else:
|
||
raise ValueError("Tool Call Parser Not Given!")
|
||
|
||
self.multi_format_parser = MultiFormatParser(detectors)
|
||
self.tools = tools
|
||
|
||
def has_tool_call(self, text: str) -> bool:
|
||
"""
|
||
Check if the given text contains a tool call in the format supported by this parser.
|
||
This delegates to the detector's implementation.
|
||
|
||
:param text: The text to check for tool calls
|
||
:return: True if the text contains a tool call, False otherwise
|
||
"""
|
||
# Check all detectors in the multi_format_parser
|
||
for detector in self.multi_format_parser.detectors:
|
||
if detector.has_tool_call(text):
|
||
return True
|
||
return False
|
||
|
||
def parse_non_stream(self, full_text: str) -> Tuple[str, list[ToolCallItem]]:
|
||
"""
|
||
Non-streaming call: one-time parsing
|
||
"""
|
||
full_normal_text, calls = self.multi_format_parser.parse_once(
|
||
full_text, self.tools
|
||
)
|
||
return full_normal_text, calls
|
||
|
||
def parse_stream_chunk(self, chunk_text: str) -> Tuple[str, list[ToolCallItem]]:
|
||
"""
|
||
Streaming call: incremental parsing
|
||
"""
|
||
normal_text, calls = self.multi_format_parser.parse_streaming_increment(
|
||
chunk_text, self.tools
|
||
)
|
||
return normal_text, calls
|
||
|
||
def structure_infos(self) -> List[_GetInfoFunc]:
|
||
"""
|
||
Returns a list of structure_info functions for each detector
|
||
"""
|
||
return [
|
||
detector.structure_info() for detector in self.multi_format_parser.detectors
|
||
]
|
||
|
||
def get_structure_tag(self) -> StructuralTagResponseFormat:
|
||
tool_structures: List[StructuresResponseFormat] = list()
|
||
tool_trigger_set: Set[str] = set()
|
||
|
||
for wrapper in self.structure_infos():
|
||
for tool in self.tools:
|
||
function = tool.function
|
||
name = function.name
|
||
assert name is not None
|
||
info = wrapper(name)
|
||
|
||
# accept all if not strict, otherwise only accept the schema
|
||
schema = function.parameters if function.strict else {}
|
||
|
||
tool_structures.append(
|
||
StructuresResponseFormat(
|
||
begin=info.begin,
|
||
schema=schema, # type: ignore
|
||
end=info.end,
|
||
)
|
||
)
|
||
tool_trigger_set.add(info.trigger)
|
||
|
||
return StructuralTagResponseFormat(
|
||
type="structural_tag",
|
||
structures=tool_structures,
|
||
triggers=list(tool_trigger_set),
|
||
)
|