Text Generation
Transformers
Safetensors
qwen3_next
qwen3
Mixture of Experts
int2
quantized
autoround
2-bit precision
conversational
2-bit
auto-round
Instructions to use YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound") model = AutoModelForCausalLM.from_pretrained("YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound
- SGLang
How to use YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound with Docker Model Runner:
docker model run hf.co/YCWTG/Qwen3-Coder-Next-int2-mixed-AutoRound
Delete qwen3_coder_detector_sgl.py
Browse files- qwen3_coder_detector_sgl.py +0 -474
qwen3_coder_detector_sgl.py
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import ast
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import json
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import logging
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import re
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from typing import Any, List, Optional
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-
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from sglang.srt.entrypoints.openai.protocol import Tool
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from sglang.srt.function_call.base_format_detector import BaseFormatDetector
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from sglang.srt.function_call.core_types import (
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StreamingParseResult,
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ToolCallItem,
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_GetInfoFunc,
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)
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logger = logging.getLogger(__name__)
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class Qwen3CoderDetector(BaseFormatDetector):
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def __init__(self):
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super().__init__()
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# Sentinel tokens
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self.tool_call_start_token: str = "<tool_call>"
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self.tool_call_end_token: str = "</tool_call>"
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self.tool_call_prefix: str = "<function="
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self.function_end_token: str = "</function>"
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self.parameter_prefix: str = "<parameter="
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self.parameter_end_token: str = "</parameter>"
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# Regex for non-streaming fallback
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self.tool_call_regex = re.compile(r"<tool_call>(.*?)</tool_call>", re.DOTALL)
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self.tool_call_function_regex = re.compile(
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r"<function=(.*?)</function>|<function=(.*)$", re.DOTALL
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)
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self.tool_call_parameter_regex = re.compile(
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r"<parameter=(.*?)(?:</parameter>|(?=<parameter=)|(?=</function>)|$)",
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re.DOTALL,
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)
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# Streaming State
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# Base class already initializes _buffer, we just use it directly
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# No need to check with hasattr - we control the lifecycle through inheritance
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# Index pointing to the next character to be processed in buffer
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self.parsed_pos: int = 0
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# Parameter count inside the current tool being processed, used to determine whether to add comma
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self.current_tool_param_count: int = 0
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# Flag indicating whether current tool has already sent '{'
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self.json_started: bool = False
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# [FIX] New state flag: mark whether inside tool_call structure block
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self.is_inside_tool_call: bool = False
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# Initialize attributes that were missing in the original PR
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self.current_func_name: Optional[str] = None
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def has_tool_call(self, text: str) -> bool:
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return self.tool_call_start_token in text
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def _get_arguments_config(
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self, func_name: str, tools: Optional[list[Tool]]
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) -> dict:
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"""Extract argument configuration for a function."""
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if tools is None:
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return {}
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for config in tools:
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try:
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config_type = config.type
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config_function = config.function
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config_function_name = config_function.name
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except AttributeError:
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continue
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if config_type == "function" and config_function_name == func_name:
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try:
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params = config_function.parameters
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except AttributeError:
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return {}
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if isinstance(params, dict) and "properties" in params:
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return params["properties"]
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elif isinstance(params, dict):
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return params
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else:
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return {}
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logger.warning(f"Tool '{func_name}' is not defined in the tools list.")
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return {}
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def _convert_param_value(
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self, param_value: str, param_name: str, param_config: dict, func_name: str
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) -> Any:
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"""Convert parameter value based on its type in the schema."""
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# Handle null value for any type
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if param_value.lower() == "null":
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return None
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if param_name not in param_config:
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if param_config != {}:
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logger.warning(
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f"Parsed parameter '{param_name}' is not defined in the tool "
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f"parameters for tool '{func_name}', directly returning the string value."
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)
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return param_value
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if (
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isinstance(param_config[param_name], dict)
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and "type" in param_config[param_name]
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):
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param_type = str(param_config[param_name]["type"]).strip().lower()
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else:
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param_type = "string"
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if param_type in ["string", "str", "text", "varchar", "char", "enum"]:
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return param_value
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elif (
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param_type.startswith("int")
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or param_type.startswith("uint")
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or param_type.startswith("long")
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or param_type.startswith("short")
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or param_type.startswith("unsigned")
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):
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try:
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param_value = int(param_value)
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except Exception:
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logger.warning(
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f"Parsed value '{param_value}' of parameter '{param_name}' is not an integer in tool "
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f"'{func_name}', degenerating to string."
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)
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return param_value
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elif param_type.startswith("num") or param_type.startswith("float"):
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try:
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maybe_convert = (
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False if "." in param_value or "e" in param_value.lower() else True
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)
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param_value: float = float(param_value)
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if maybe_convert and param_value.is_integer():
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param_value = int(param_value)
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except Exception:
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logger.warning(
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f"Parsed value '{param_value}' of parameter '{param_name}' is not a float in tool "
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f"'{func_name}', degenerating to string."
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)
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return param_value
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elif param_type in ["boolean", "bool", "binary"]:
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param_value = param_value.lower()
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if param_value not in ["true", "false"]:
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logger.warning(
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f"Parsed value '{param_value}' of parameter '{param_name}' is not a boolean (`true` of `false`) in tool '{func_name}', degenerating to false."
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)
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return param_value == "true"
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else:
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if (
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param_type in ["object", "array", "arr"]
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or param_type.startswith("dict")
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or param_type.startswith("list")
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):
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try:
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param_value = json.loads(param_value)
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return param_value
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except Exception:
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logger.warning(
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f"Parsed value '{param_value}' of parameter '{param_name}' cannot be parsed with json.loads in tool "
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f"'{func_name}', will try other methods to parse it."
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)
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try:
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param_value = ast.literal_eval(param_value) # safer
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except Exception:
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logger.warning(
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f"Parsed value '{param_value}' of parameter '{param_name}' cannot be converted via Python `ast.literal_eval()` in tool '{func_name}', degenerating to string."
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)
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return param_value
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def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
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"""One-shot parsing for non-streaming scenarios."""
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if self.tool_call_start_token not in text:
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return StreamingParseResult(normal_text=text)
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calls = []
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try:
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# Simple cleanup of the text to find tool calls
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# Note: This is a simplified regex approach consistent with vLLM
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raw_tool_calls = self.tool_call_regex.findall(text)
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if not raw_tool_calls:
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# Fallback: maybe the whole text is inside the tag or tags are stripped
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if self.tool_call_prefix in text:
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raw_tool_calls = [text]
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tool_idx = 0
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for tool_content in raw_tool_calls:
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# Find function calls
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funcs = self.tool_call_function_regex.findall(tool_content)
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for func_match in funcs:
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func_body = func_match[0] or func_match[1]
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if ">" not in func_body:
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continue
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name_end = func_body.index(">")
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func_name = func_body[:name_end]
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params_str = func_body[name_end + 1 :]
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param_config = self._get_arguments_config(func_name, tools)
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parsed_params = {}
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for p_match in self.tool_call_parameter_regex.findall(params_str):
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if ">" not in p_match:
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continue
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p_idx = p_match.index(">")
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p_name = p_match[:p_idx]
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p_val = p_match[p_idx + 1 :]
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# Remove prefixing and trailing \n
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if p_val.startswith("\n"):
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p_val = p_val[1:]
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if p_val.endswith("\n"):
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p_val = p_val[:-1]
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parsed_params[p_name] = self._convert_param_value(
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p_val, p_name, param_config, func_name
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)
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calls.append(
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ToolCallItem(
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tool_index=tool_idx,
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name=func_name,
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parameters=json.dumps(parsed_params, ensure_ascii=False),
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)
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| 225 |
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)
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tool_idx += 1
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| 227 |
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| 228 |
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# Determine normal text (text before the first tool call)
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| 229 |
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start_idx = text.find(self.tool_call_start_token)
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| 230 |
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if start_idx == -1:
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| 231 |
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start_idx = text.find(self.tool_call_prefix)
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| 232 |
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normal_text = text[:start_idx] if start_idx > 0 else ""
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| 233 |
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| 234 |
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return StreamingParseResult(normal_text=normal_text, calls=calls)
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| 235 |
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| 236 |
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except Exception as e:
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| 237 |
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logger.error(f"Error in detect_and_parse: {e}")
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| 238 |
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return StreamingParseResult(normal_text=text)
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| 239 |
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| 240 |
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def parse_streaming_increment(
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| 241 |
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self, new_text: str, tools: List[Tool]
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| 242 |
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) -> StreamingParseResult:
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| 243 |
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"""
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| 244 |
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Robust cursor-based streaming parser.
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| 245 |
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"""
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| 246 |
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self._buffer += new_text
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| 247 |
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| 248 |
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# Guard against empty buffer
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| 249 |
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if not self._buffer:
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| 250 |
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return StreamingParseResult()
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| 251 |
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| 252 |
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calls = []
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| 253 |
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normal_text_chunks = []
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| 254 |
-
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| 255 |
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while True:
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| 256 |
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# Working text slice
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| 257 |
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current_slice = self._buffer[self.parsed_pos :]
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| 258 |
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| 259 |
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# Optimization: If almost empty, wait for more
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| 260 |
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if not current_slice:
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break
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| 262 |
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| 263 |
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# -------------------------------------------------------
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| 264 |
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# 1. Priority detection: check if it's the start of Tool Call
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| 265 |
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# -------------------------------------------------------
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| 266 |
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if current_slice.startswith(self.tool_call_start_token):
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| 267 |
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self.parsed_pos += len(self.tool_call_start_token)
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| 268 |
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self.is_inside_tool_call = True
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| 269 |
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continue
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| 270 |
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| 271 |
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# -------------------------------------------------------
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| 272 |
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# 2. Function Name: <function=name>
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| 273 |
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# -------------------------------------------------------
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| 274 |
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if current_slice.startswith(self.tool_call_prefix):
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| 275 |
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end_angle = current_slice.find(">")
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| 276 |
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if end_angle != -1:
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| 277 |
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func_name = current_slice[len(self.tool_call_prefix) : end_angle]
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| 278 |
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| 279 |
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self.current_tool_id += 1
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| 280 |
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self.current_tool_name_sent = True
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| 281 |
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self.current_tool_param_count = 0
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| 282 |
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self.json_started = False
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| 283 |
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self.current_func_name = func_name
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| 284 |
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| 285 |
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calls.append(
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ToolCallItem(
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| 287 |
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tool_index=self.current_tool_id,
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| 288 |
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name=func_name,
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| 289 |
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parameters="",
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| 290 |
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)
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| 291 |
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)
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| 292 |
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| 293 |
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self.parsed_pos += end_angle + 1
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| 294 |
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continue
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| 295 |
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else:
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| 296 |
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# Incomplete tag
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| 297 |
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break
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| 298 |
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| 299 |
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# -------------------------------------------------------
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| 300 |
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# 3. Parameter: <parameter=name>value...
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| 301 |
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# -------------------------------------------------------
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| 302 |
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if current_slice.startswith(self.parameter_prefix):
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| 303 |
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name_end = current_slice.find(">")
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| 304 |
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if name_end != -1:
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| 305 |
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value_start_idx = name_end + 1
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| 306 |
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rest_of_slice = current_slice[value_start_idx:]
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| 307 |
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| 308 |
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# A parameter can end in multiple ways:
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| 309 |
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# 1. [Normal] Encounter </parameter>
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| 310 |
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# 2. [Abnormal] Encounter next <parameter=
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| 311 |
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# 3. [Abnormal] Encounter </function>
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| 312 |
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# So we need to find the smallest one as the parameter end position.
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| 313 |
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cand_end_param = rest_of_slice.find(self.parameter_end_token)
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| 314 |
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cand_next_param = rest_of_slice.find(self.parameter_prefix)
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| 315 |
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cand_end_func = rest_of_slice.find(self.function_end_token)
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| 316 |
-
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| 317 |
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candidates = []
|
| 318 |
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if cand_end_param != -1:
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| 319 |
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candidates.append(
|
| 320 |
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(cand_end_param, len(self.parameter_end_token))
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| 321 |
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)
|
| 322 |
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if cand_next_param != -1:
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| 323 |
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candidates.append((cand_next_param, 0))
|
| 324 |
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if cand_end_func != -1:
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| 325 |
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candidates.append((cand_end_func, 0))
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| 326 |
-
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| 327 |
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if candidates:
|
| 328 |
-
best_cand = min(candidates, key=lambda x: x[0])
|
| 329 |
-
end_pos = best_cand[0]
|
| 330 |
-
end_token_len = best_cand[1]
|
| 331 |
-
|
| 332 |
-
param_name = current_slice[
|
| 333 |
-
len(self.parameter_prefix) : name_end
|
| 334 |
-
]
|
| 335 |
-
raw_value = rest_of_slice[:end_pos]
|
| 336 |
-
|
| 337 |
-
# Cleanup value
|
| 338 |
-
if raw_value.startswith("\n"):
|
| 339 |
-
raw_value = raw_value[1:]
|
| 340 |
-
if raw_value.endswith("\n"):
|
| 341 |
-
raw_value = raw_value[:-1]
|
| 342 |
-
|
| 343 |
-
# JSON Construction
|
| 344 |
-
if not self.json_started:
|
| 345 |
-
calls.append(
|
| 346 |
-
ToolCallItem(
|
| 347 |
-
tool_index=self.current_tool_id, parameters="{"
|
| 348 |
-
)
|
| 349 |
-
)
|
| 350 |
-
self.json_started = True
|
| 351 |
-
|
| 352 |
-
param_config = self._get_arguments_config(
|
| 353 |
-
self.current_func_name, tools
|
| 354 |
-
)
|
| 355 |
-
converted_val = self._convert_param_value(
|
| 356 |
-
raw_value, param_name, param_config, self.current_func_name
|
| 357 |
-
)
|
| 358 |
-
|
| 359 |
-
# Construct JSON fragment: "key": value
|
| 360 |
-
# Note: We must be careful with json.dumps to ensure valid JSON streaming
|
| 361 |
-
json_key_val = f"{json.dumps(param_name)}: {json.dumps(converted_val, ensure_ascii=False)}"
|
| 362 |
-
|
| 363 |
-
if self.current_tool_param_count > 0:
|
| 364 |
-
fragment = f", {json_key_val}"
|
| 365 |
-
else:
|
| 366 |
-
fragment = json_key_val
|
| 367 |
-
|
| 368 |
-
calls.append(
|
| 369 |
-
ToolCallItem(
|
| 370 |
-
tool_index=self.current_tool_id, parameters=fragment
|
| 371 |
-
)
|
| 372 |
-
)
|
| 373 |
-
self.current_tool_param_count += 1
|
| 374 |
-
|
| 375 |
-
# Advance cursor
|
| 376 |
-
total_len = (name_end + 1) + end_pos + end_token_len
|
| 377 |
-
self.parsed_pos += total_len
|
| 378 |
-
continue
|
| 379 |
-
|
| 380 |
-
# Incomplete parameter tag or value
|
| 381 |
-
break
|
| 382 |
-
|
| 383 |
-
# -------------------------------------------------------
|
| 384 |
-
# 4. Function End: </function>
|
| 385 |
-
# -------------------------------------------------------
|
| 386 |
-
if current_slice.startswith(self.function_end_token):
|
| 387 |
-
if not self.json_started:
|
| 388 |
-
calls.append(
|
| 389 |
-
ToolCallItem(tool_index=self.current_tool_id, parameters="{")
|
| 390 |
-
)
|
| 391 |
-
self.json_started = True
|
| 392 |
-
|
| 393 |
-
calls.append(
|
| 394 |
-
ToolCallItem(tool_index=self.current_tool_id, parameters="}")
|
| 395 |
-
)
|
| 396 |
-
self.parsed_pos += len(self.function_end_token)
|
| 397 |
-
self.current_func_name = None
|
| 398 |
-
continue
|
| 399 |
-
|
| 400 |
-
# -------------------------------------------------------
|
| 401 |
-
# 5. Tool Call End: </tool_call>
|
| 402 |
-
# -------------------------------------------------------
|
| 403 |
-
if current_slice.startswith(self.tool_call_end_token):
|
| 404 |
-
self.parsed_pos += len(self.tool_call_end_token)
|
| 405 |
-
self.is_inside_tool_call = False # [FIX] Exit tool call region
|
| 406 |
-
continue
|
| 407 |
-
|
| 408 |
-
# -------------------------------------------------------
|
| 409 |
-
# 6. Handling content / whitespace / normal text
|
| 410 |
-
# -------------------------------------------------------
|
| 411 |
-
# If current position is not the start of a tag (i.e., doesn't start with <), it might be plain text,
|
| 412 |
-
# or a newline between two tags.
|
| 413 |
-
# But we need to be careful not to output truncated tags like "<fun" as text.
|
| 414 |
-
|
| 415 |
-
next_open_angle = current_slice.find("<")
|
| 416 |
-
|
| 417 |
-
if next_open_angle == -1:
|
| 418 |
-
# This entire segment is plain text
|
| 419 |
-
if not self.is_inside_tool_call:
|
| 420 |
-
normal_text_chunks.append(current_slice)
|
| 421 |
-
# [FIX] If inside tool call, discard this text (usually \n), don't append
|
| 422 |
-
self.parsed_pos += len(current_slice)
|
| 423 |
-
continue
|
| 424 |
-
|
| 425 |
-
elif next_open_angle == 0:
|
| 426 |
-
# Looks like a Tag, but doesn't match any known Tag above
|
| 427 |
-
|
| 428 |
-
possible_tags = [
|
| 429 |
-
self.tool_call_start_token,
|
| 430 |
-
self.tool_call_end_token,
|
| 431 |
-
self.tool_call_prefix,
|
| 432 |
-
self.function_end_token,
|
| 433 |
-
self.parameter_prefix,
|
| 434 |
-
self.parameter_end_token,
|
| 435 |
-
]
|
| 436 |
-
|
| 437 |
-
is_potential_tag = False
|
| 438 |
-
for tag in possible_tags:
|
| 439 |
-
if tag.startswith(current_slice):
|
| 440 |
-
is_potential_tag = True
|
| 441 |
-
break
|
| 442 |
-
|
| 443 |
-
if is_potential_tag:
|
| 444 |
-
break # Wait for more
|
| 445 |
-
else:
|
| 446 |
-
# Just a plain '<' symbol
|
| 447 |
-
if not self.is_inside_tool_call:
|
| 448 |
-
normal_text_chunks.append("<")
|
| 449 |
-
self.parsed_pos += 1
|
| 450 |
-
continue
|
| 451 |
-
|
| 452 |
-
else:
|
| 453 |
-
# '<' is in the middle
|
| 454 |
-
text_segment = current_slice[:next_open_angle]
|
| 455 |
-
if not self.is_inside_tool_call:
|
| 456 |
-
normal_text_chunks.append(text_segment)
|
| 457 |
-
# [FIX] If inside tool call, discard whitespace/text before Tag
|
| 458 |
-
self.parsed_pos += next_open_angle
|
| 459 |
-
continue
|
| 460 |
-
|
| 461 |
-
# Memory Cleanup: Slice the buffer
|
| 462 |
-
# Keep unparsed part, discard parsed part
|
| 463 |
-
if self.parsed_pos > 0:
|
| 464 |
-
self._buffer = self._buffer[self.parsed_pos :]
|
| 465 |
-
self.parsed_pos = 0
|
| 466 |
-
|
| 467 |
-
normal_text = "".join(normal_text_chunks) if normal_text_chunks else ""
|
| 468 |
-
return StreamingParseResult(calls=calls, normal_text=normal_text)
|
| 469 |
-
|
| 470 |
-
def supports_structural_tag(self) -> bool:
|
| 471 |
-
return False
|
| 472 |
-
|
| 473 |
-
def structure_info(self) -> _GetInfoFunc:
|
| 474 |
-
raise NotImplementedError
|
|
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