Add files using upload-large-folder tool

README.md

@@ -0,0 +1,238 @@
+---
+library_name: transformers
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen3-Coder-Next/blob/main/LICENSE
+pipeline_tag: text-generation
+tags:
+- vLLM
+- sglang
+base_model:
+  - Qwen/Qwen3-Coder-Next
+base_model_relation: quantized
+---
+# Qwen3-Coder-Next-E336
+Base model: [Qwen/Qwen3-Coder-Next](https://www.modelscope.cn/models/Qwen/Qwen3-Coder-Next)
+
+This repo trims 34% of the experts (512 → 336); 
+
+The model format and serving setup (vLLM/SGLang versions and launch commands) match the original release.
+
+### 【Logs】
+```
+2026-02-05
+1. Initial commit
+```
+
+### 【Model Files】
+| File Size | Last Updated |
+|-----------|--------------|
+| `99 GiB`  | `2026-02-05` |
+
+### 【Model Download】
+```python
+from modelscope import snapshot_download
+snapshot_download('tclf90/Qwen3-Coder-Next-E336', cache_dir="your_local_path")
+```
+
+### 【Overview】
+# Qwen3-Coder-Next
+
+## Highlights
+
+Today, we're announcing **Qwen3-Coder-Next**, an open-weight language model designed specifically for coding agents and local development. It features the following key enhancements:  
+
+- **Super Efficient with Significant Performance**: With only 3B activated parameters (80B total parameters), it achieves performance comparable to models with 10–20x more active parameters, making it highly cost-effective for agent deployment.
+- **Advanced Agentic Capabilities**: Through an elaborate training recipe, it excels at long-horizon reasoning, complex tool usage, and recovery from execution failures, ensuring robust performance in dynamic coding tasks.
+- **Versatile Integration with Real-World IDE**: Its 256k context length, combined with adaptability to various scaffold templates, enables seamless integration with different CLI/IDE platforms (e.g., Claude Code, Qwen Code, Qoder, Kilo, Trae, Cline, etc.), supporting diverse development environments.
+
+![image/jpeg](https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/Qwen3-Coder-Next/benchmarks.png)
+
+![image/jpeg](https://qianwen-res.oss-accelerate-overseas.aliyuncs.com/Qwen3-Coder-Next/swebench_pro.png)
+
+## Model Overview
+
+**Qwen3-Coder-Next** has the following features:
+- Type: Causal Language Models
+- Training Stage: Pretraining & Post-training
+- Number of Parameters: 80B in total and 3B activated
+- Number of Parameters (Non-Embedding): 79B
+- Hidden Dimension: 2048
+- Number of Layers: 48
+  - Hybrid Layout: 12 \* (3 \* (Gated DeltaNet -> MoE) -> 1 \* (Gated Attention -> MoE))
+- Gated Attention:
+  - Number of Attention Heads: 16 for Q and 2 for KV
+  - Head Dimension: 256
+  - Rotary Position Embedding Dimension: 64
+- Gated DeltaNet:
+  - Number of Linear Attention Heads: 32 for V and 16 for QK
+  - Head Dimension: 128
+- Mixture of Experts:
+  - Number of Experts: 512
+  - Number of Activated Experts: 10
+  - Number of Shared Experts: 1
+  - Expert Intermediate Dimension: 512
+- Context Length: 262,144 natively
+
+**NOTE: This model supports only non-thinking mode and does not generate ``<think></think>`` blocks in its output. Meanwhile, specifying `enable_thinking=False` is no longer required.**
+
+For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our [blog](https://qwen.ai/blog?id=qwen3-coder-next), [GitHub](https://github.com/QwenLM/Qwen3-Coder), and [Documentation](https://qwen.readthedocs.io/en/latest/).
+
+
+## Quickstart
+
+We advise you to use the latest version of `transformers`.
+
+The following contains a code snippet illustrating how to use the model generate content based on given inputs. 
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "Qwen/Qwen3-Coder-Next"
+
+# load the tokenizer and the model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+  model_name,
+  torch_dtype="auto",
+  device_map="auto"
+)
+
+# prepare the model input
+prompt = "Write a quick sort algorithm."
+messages = [
+  {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+  messages,
+  tokenize=False,
+  add_generation_prompt=True,
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+# conduct text completion
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=65536
+)
+output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist() 
+
+content = tokenizer.decode(output_ids, skip_special_tokens=True)
+
+print("content:", content)
+```
+
+**Note: If you encounter out-of-memory (OOM) issues, consider reducing the context length to a shorter value, such as `32,768`.**
+
+For local use, applications such as Ollama, LMStudio, MLX-LM, llama.cpp, and KTransformers have also supported Qwen3.
+
+## Deployment
+
+For deployment, you can use the latest `sglang` or `vllm` to create an OpenAI-compatible API endpoint.
+
+### SGLang
+
+[SGLang](https://github.com/sgl-project/sglang) is a fast serving framework for large language models and vision language models.
+SGLang could be used to launch a server with OpenAI-compatible API service. 
+
+`sglang>=v0.5.8` is required for Qwen3-Coder-Next, which can be installed using:
+```shell
+pip install 'sglang[all]>=v0.5.8'
+```
+See [its documentation](https://docs.sglang.ai/get_started/install.html) for more details.
+
+The following command can be used to create an API endpoint at `http://localhost:30000/v1` with maximum context length 256K tokens using tensor parallel on 4 GPUs.
+```shell
+python -m sglang.launch_server --model Qwen/Qwen3-Coder-Next --port 30000 --tp-size 2 --tool-call-parser qwen3_coder
+```
+
+> [!Note]
+> The default context length is 256K. Consider reducing the context length to a smaller value, e.g., `32768`, if the server fails to start.
+
+
+### vLLM
+
+[vLLM](https://github.com/vllm-project/vllm) is a high-throughput and memory-efficient inference and serving engine for LLMs.
+vLLM could be used to launch a server with OpenAI-compatible API service. 
+
+`vllm>=0.15.0` is required for Qwen3-Coder-Next, which can be installed using:
+```shell
+pip install 'vllm>=0.15.0'
+```
+See [its documentation](https://docs.vllm.ai/en/stable/getting_started/installation/index.html) for more details.
+
+The following command can be used to create an API endpoint at `http://localhost:8000/v1` with maximum context length 256K tokens using tensor parallel on 4 GPUs.
+```shell
+vllm serve Qwen/Qwen3-Coder-Next --port 8000 --tensor-parallel-size 2 --enable-auto-tool-choice --tool-call-parser qwen3_coder
+```
+
+> [!Note]
+> The default context length is 256K. Consider reducing the context length to a smaller value, e.g., `32768`, if the server fails to start.
+
+
+## Agentic Coding
+
+Qwen3-Coder-Next excels in tool calling capabilities. 
+
+You can simply define or use any tools as following example.
+```python
+# Your tool implementation
+def square_the_number(num: float) -> dict:
+    return num ** 2
+
+# Define Tools
+tools=[
+    {
+        "type":"function",
+        "function":{
+            "name": "square_the_number",
+            "description": "output the square of the number.",
+            "parameters": {
+                "type": "object",
+                "required": ["input_num"],
+                "properties": {
+                    'input_num': {
+                        'type': 'number', 
+                        'description': 'input_num is a number that will be squared'
+                        }
+                },
+            }
+        }
+    }
+]
+
+from openai import OpenAI
+# Define LLM
+client = OpenAI(
+    # Use a custom endpoint compatible with OpenAI API
+    base_url='http://localhost:8000/v1',  # api_base
+    api_key="EMPTY"
+)
+ 
+messages = [{'role': 'user', 'content': 'square the number 1024'}]
+
+completion = client.chat.completions.create(
+    messages=messages,
+    model="Qwen3-Coder-Next",
+    max_tokens=65536,
+    tools=tools,
+)
+
+print(completion.choices[0])
+```
+
+## Best Practices
+
+To achieve optimal performance, we recommend the following sampling parameters: `temperature=1.0`, `top_p=0.95`, `top_k=40`.
+
+
+## Citation
+
+If you find our work helpful, feel free to give us a cite.
+
+```
+@techreport{qwen_qwen3_coder_next_tech_report,
+  title        = {Qwen3-Coder-Next Technical Report},
+  author       = {{Qwen Team}},
+  url          = {https://github.com/QwenLM/Qwen3-Coder/blob/main/qwen3_coder_next_tech_report.pdf},
+  note         = {Accessed: 2026-02-03}
+}
+```

configuration.json

@@ -0,0 +1 @@
+{"framework":"Pytorch","task":"text-generation"}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 1.0,
+  "top_k": 40,
+  "top_p": 0.95,
+  "transformers_version": "4.57.3"
+}

model-00022-of-00036.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bbb5a850149bdb1e22421ddca3aaf7b521df8d7fe5118bc068d60e94a563daf3
+size 2998993464

model-00035-of-00036.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0ec2c6e3455ab2506a14430721a04b156919a1d7bb2c9514483608ef1aebb0af
+size 2973172496

qwen3_coder_detector_sgl.py

@@ -0,0 +1,474 @@
+import ast
+import json
+import logging
+import re
+from typing import Any, List, Optional
+
+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 Qwen3CoderDetector(BaseFormatDetector):
+    def __init__(self):
+        super().__init__()
+
+        # Sentinel tokens
+        self.tool_call_start_token: str = "<tool_call>"
+        self.tool_call_end_token: str = "</tool_call>"
+        self.tool_call_prefix: str = "<function="
+        self.function_end_token: str = "</function>"
+        self.parameter_prefix: str = "<parameter="
+        self.parameter_end_token: str = "</parameter>"
+
+        # Regex for non-streaming fallback
+        self.tool_call_regex = re.compile(r"<tool_call>(.*?)</tool_call>", re.DOTALL)
+        self.tool_call_function_regex = re.compile(
+            r"<function=(.*?)</function>|<function=(.*)$", re.DOTALL
+        )
+        self.tool_call_parameter_regex = re.compile(
+            r"<parameter=(.*?)(?:</parameter>|(?=<parameter=)|(?=</function>)|$)",
+            re.DOTALL,
+        )
+
+        # Streaming State
+        # Base class already initializes _buffer, we just use it directly
+        # No need to check with hasattr - we control the lifecycle through inheritance
+
+        # Index pointing to the next character to be processed in buffer
+        self.parsed_pos: int = 0
+        # Parameter count inside the current tool being processed, used to determine whether to add comma
+        self.current_tool_param_count: int = 0
+        # Flag indicating whether current tool has already sent '{'
+        self.json_started: bool = False
+
+        # [FIX] New state flag: mark whether inside tool_call structure block
+        self.is_inside_tool_call: bool = False
+
+        # Initialize attributes that were missing in the original PR
+        self.current_func_name: Optional[str] = None
+
+    def has_tool_call(self, text: str) -> bool:
+        return self.tool_call_start_token in text
+
+    def _get_arguments_config(
+        self, func_name: str, tools: Optional[list[Tool]]
+    ) -> dict:
+        """Extract argument configuration for a function."""
+        if tools is None:
+            return {}
+        for config in tools:
+            try:
+                config_type = config.type
+                config_function = config.function
+                config_function_name = config_function.name
+            except AttributeError:
+                continue
+
+            if config_type == "function" and config_function_name == func_name:
+                try:
+                    params = config_function.parameters
+                except AttributeError:
+                    return {}
+
+                if isinstance(params, dict) and "properties" in params:
+                    return params["properties"]
+                elif isinstance(params, dict):
+                    return params
+                else:
+                    return {}
+        logger.warning(f"Tool '{func_name}' is not defined in the tools list.")
+        return {}
+
+    def _convert_param_value(
+        self, param_value: str, param_name: str, param_config: dict, func_name: str
+    ) -> Any:
+        """Convert parameter value based on its type in the schema."""
+        # Handle null value for any type
+        if param_value.lower() == "null":
+            return None
+
+        if param_name not in param_config:
+            if param_config != {}:
+                logger.warning(
+                    f"Parsed parameter '{param_name}' is not defined in the tool "
+                    f"parameters for tool '{func_name}', directly returning the string value."
+                )
+            return param_value
+
+        if (
+            isinstance(param_config[param_name], dict)
+            and "type" in param_config[param_name]
+        ):
+            param_type = str(param_config[param_name]["type"]).strip().lower()
+        else:
+            param_type = "string"
+        if param_type in ["string", "str", "text", "varchar", "char", "enum"]:
+            return param_value
+        elif (
+            param_type.startswith("int")
+            or param_type.startswith("uint")
+            or param_type.startswith("long")
+            or param_type.startswith("short")
+            or param_type.startswith("unsigned")
+        ):
+            try:
+                param_value = int(param_value)
+            except Exception:
+                logger.warning(
+                    f"Parsed value '{param_value}' of parameter '{param_name}' is not an integer in tool "
+                    f"'{func_name}', degenerating to string."
+                )
+            return param_value
+        elif param_type.startswith("num") or param_type.startswith("float"):
+            try:
+                maybe_convert = (
+                    False if "." in param_value or "e" in param_value.lower() else True
+                )
+                param_value: float = float(param_value)
+                if maybe_convert and param_value.is_integer():
+                    param_value = int(param_value)
+            except Exception:
+                logger.warning(
+                    f"Parsed value '{param_value}' of parameter '{param_name}' is not a float in tool "
+                    f"'{func_name}', degenerating to string."
+                )
+            return param_value
+        elif param_type in ["boolean", "bool", "binary"]:
+            param_value = param_value.lower()
+            if param_value not in ["true", "false"]:
+                logger.warning(
+                    f"Parsed value '{param_value}' of parameter '{param_name}' is not a boolean (`true` of `false`) in tool '{func_name}', degenerating to false."
+                )
+            return param_value == "true"
+        else:
+            if (
+                param_type in ["object", "array", "arr"]
+                or param_type.startswith("dict")
+                or param_type.startswith("list")
+            ):
+                try:
+                    param_value = json.loads(param_value)
+                    return param_value
+                except Exception:
+                    logger.warning(
+                        f"Parsed value '{param_value}' of parameter '{param_name}' cannot be parsed with json.loads in tool "
+                        f"'{func_name}', will try other methods to parse it."
+                    )
+            try:
+                param_value = ast.literal_eval(param_value)  # safer
+            except Exception:
+                logger.warning(
+                    f"Parsed value '{param_value}' of parameter '{param_name}' cannot be converted via Python `ast.literal_eval()` in tool '{func_name}', degenerating to string."
+                )
+            return param_value
+
+    def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
+        """One-shot parsing for non-streaming scenarios."""
+        if self.tool_call_start_token not in text:
+            return StreamingParseResult(normal_text=text)
+
+        calls = []
+        try:
+            # Simple cleanup of the text to find tool calls
+            # Note: This is a simplified regex approach consistent with vLLM
+            raw_tool_calls = self.tool_call_regex.findall(text)
+            if not raw_tool_calls:
+                # Fallback: maybe the whole text is inside the tag or tags are stripped
+                if self.tool_call_prefix in text:
+                    raw_tool_calls = [text]
+
+            tool_idx = 0
+            for tool_content in raw_tool_calls:
+                # Find function calls
+                funcs = self.tool_call_function_regex.findall(tool_content)
+                for func_match in funcs:
+                    func_body = func_match[0] or func_match[1]
+                    if ">" not in func_body:
+                        continue
+
+                    name_end = func_body.index(">")
+                    func_name = func_body[:name_end]
+                    params_str = func_body[name_end + 1 :]
+
+                    param_config = self._get_arguments_config(func_name, tools)
+                    parsed_params = {}
+
+                    for p_match in self.tool_call_parameter_regex.findall(params_str):
+                        if ">" not in p_match:
+                            continue
+                        p_idx = p_match.index(">")
+                        p_name = p_match[:p_idx]
+                        p_val = p_match[p_idx + 1 :]
+                        # Remove prefixing and trailing \n
+                        if p_val.startswith("\n"):
+                            p_val = p_val[1:]
+                        if p_val.endswith("\n"):
+                            p_val = p_val[:-1]
+
+                        parsed_params[p_name] = self._convert_param_value(
+                            p_val, p_name, param_config, func_name
+                        )
+
+                    calls.append(
+                        ToolCallItem(
+                            tool_index=tool_idx,
+                            name=func_name,
+                            parameters=json.dumps(parsed_params, ensure_ascii=False),
+                        )
+                    )
+                    tool_idx += 1
+
+            # Determine normal text (text before the first tool call)
+            start_idx = text.find(self.tool_call_start_token)
+            if start_idx == -1:
+                start_idx = text.find(self.tool_call_prefix)
+            normal_text = text[:start_idx] if start_idx > 0 else ""
+
+            return StreamingParseResult(normal_text=normal_text, calls=calls)
+
+        except Exception as e:
+            logger.error(f"Error in detect_and_parse: {e}")
+            return StreamingParseResult(normal_text=text)
+
+    def parse_streaming_increment(
+        self, new_text: str, tools: List[Tool]
+    ) -> StreamingParseResult:
+        """
+        Robust cursor-based streaming parser.
+        """
+        self._buffer += new_text
+
+        # Guard against empty buffer
+        if not self._buffer:
+            return StreamingParseResult()
+
+        calls = []
+        normal_text_chunks = []
+
+        while True:
+            # Working text slice
+            current_slice = self._buffer[self.parsed_pos :]
+
+            # Optimization: If almost empty, wait for more
+            if not current_slice:
+                break
+
+            # -------------------------------------------------------
+            # 1. Priority detection: check if it's the start of Tool Call
+            # -------------------------------------------------------
+            if current_slice.startswith(self.tool_call_start_token):
+                self.parsed_pos += len(self.tool_call_start_token)
+                self.is_inside_tool_call = True
+                continue
+
+            # -------------------------------------------------------
+            # 2. Function Name: <function=name>
+            # -------------------------------------------------------
+            if current_slice.startswith(self.tool_call_prefix):
+                end_angle = current_slice.find(">")
+                if end_angle != -1:
+                    func_name = current_slice[len(self.tool_call_prefix) : end_angle]
+
+                    self.current_tool_id += 1
+                    self.current_tool_name_sent = True
+                    self.current_tool_param_count = 0
+                    self.json_started = False
+                    self.current_func_name = func_name
+
+                    calls.append(
+                        ToolCallItem(
+                            tool_index=self.current_tool_id,
+                            name=func_name,
+                            parameters="",
+                        )
+                    )
+
+                    self.parsed_pos += end_angle + 1
+                    continue
+                else:
+                    # Incomplete tag
+                    break
+
+            # -------------------------------------------------------
+            # 3. Parameter: <parameter=name>value...
+            # -------------------------------------------------------
+            if current_slice.startswith(self.parameter_prefix):
+                name_end = current_slice.find(">")
+                if name_end != -1:
+                    value_start_idx = name_end + 1
+                    rest_of_slice = current_slice[value_start_idx:]
+
+                    # A parameter can end in multiple ways:
+                    # 1. [Normal] Encounter </parameter>
+                    # 2. [Abnormal] Encounter next <parameter=
+                    # 3. [Abnormal] Encounter </function>
+                    # So we need to find the smallest one as the parameter end position.
+                    cand_end_param = rest_of_slice.find(self.parameter_end_token)
+                    cand_next_param = rest_of_slice.find(self.parameter_prefix)
+                    cand_end_func = rest_of_slice.find(self.function_end_token)
+
+                    candidates = []
+                    if cand_end_param != -1:
+                        candidates.append(
+                            (cand_end_param, len(self.parameter_end_token))
+                        )
+                    if cand_next_param != -1:
+                        candidates.append((cand_next_param, 0))
+                    if cand_end_func != -1:
+                        candidates.append((cand_end_func, 0))
+
+                    if candidates:
+                        best_cand = min(candidates, key=lambda x: x[0])
+                        end_pos = best_cand[0]
+                        end_token_len = best_cand[1]
+
+                        param_name = current_slice[
+                            len(self.parameter_prefix) : name_end
+                        ]
+                        raw_value = rest_of_slice[:end_pos]
+
+                        # Cleanup value
+                        if raw_value.startswith("\n"):
+                            raw_value = raw_value[1:]
+                        if raw_value.endswith("\n"):
+                            raw_value = raw_value[:-1]
+
+                        # JSON Construction
+                        if not self.json_started:
+                            calls.append(
+                                ToolCallItem(
+                                    tool_index=self.current_tool_id, parameters="{"
+                                )
+                            )
+                            self.json_started = True
+
+                        param_config = self._get_arguments_config(
+                            self.current_func_name, tools
+                        )
+                        converted_val = self._convert_param_value(
+                            raw_value, param_name, param_config, self.current_func_name
+                        )
+
+                        # Construct JSON fragment: "key": value
+                        # Note: We must be careful with json.dumps to ensure valid JSON streaming
+                        json_key_val = f"{json.dumps(param_name)}: {json.dumps(converted_val, ensure_ascii=False)}"
+
+                        if self.current_tool_param_count > 0:
+                            fragment = f", {json_key_val}"
+                        else:
+                            fragment = json_key_val
+
+                        calls.append(
+                            ToolCallItem(
+                                tool_index=self.current_tool_id, parameters=fragment
+                            )
+                        )
+                        self.current_tool_param_count += 1
+
+                        # Advance cursor
+                        total_len = (name_end + 1) + end_pos + end_token_len
+                        self.parsed_pos += total_len
+                        continue
+
+                # Incomplete parameter tag or value
+                break
+
+            # -------------------------------------------------------
+            # 4. Function End: </function>
+            # -------------------------------------------------------
+            if current_slice.startswith(self.function_end_token):
+                if not self.json_started:
+                    calls.append(
+                        ToolCallItem(tool_index=self.current_tool_id, parameters="{")
+                    )
+                    self.json_started = True
+
+                calls.append(
+                    ToolCallItem(tool_index=self.current_tool_id, parameters="}")
+                )
+                self.parsed_pos += len(self.function_end_token)
+                self.current_func_name = None
+                continue
+
+            # -------------------------------------------------------
+            # 5. Tool Call End: </tool_call>
+            # -------------------------------------------------------
+            if current_slice.startswith(self.tool_call_end_token):
+                self.parsed_pos += len(self.tool_call_end_token)
+                self.is_inside_tool_call = False  # [FIX] Exit tool call region
+                continue
+
+            # -------------------------------------------------------
+            # 6. Handling content / whitespace / normal text
+            # -------------------------------------------------------
+            # If current position is not the start of a tag (i.e., doesn't start with <), it might be plain text,
+            # or a newline between two tags.
+            # But we need to be careful not to output truncated tags like "<fun" as text.
+
+            next_open_angle = current_slice.find("<")
+
+            if next_open_angle == -1:
+                # This entire segment is plain text
+                if not self.is_inside_tool_call:
+                    normal_text_chunks.append(current_slice)
+                # [FIX] If inside tool call, discard this text (usually \n), don't append
+                self.parsed_pos += len(current_slice)
+                continue
+
+            elif next_open_angle == 0:
+                # Looks like a Tag, but doesn't match any known Tag above
+
+                possible_tags = [
+                    self.tool_call_start_token,
+                    self.tool_call_end_token,
+                    self.tool_call_prefix,
+                    self.function_end_token,
+                    self.parameter_prefix,
+                    self.parameter_end_token,
+                ]
+
+                is_potential_tag = False
+                for tag in possible_tags:
+                    if tag.startswith(current_slice):
+                        is_potential_tag = True
+                        break
+
+                if is_potential_tag:
+                    break  # Wait for more
+                else:
+                    # Just a plain '<' symbol
+                    if not self.is_inside_tool_call:
+                        normal_text_chunks.append("<")
+                    self.parsed_pos += 1
+                    continue
+
+            else:
+                # '<' is in the middle
+                text_segment = current_slice[:next_open_angle]
+                if not self.is_inside_tool_call:
+                    normal_text_chunks.append(text_segment)
+                # [FIX] If inside tool call, discard whitespace/text before Tag
+                self.parsed_pos += next_open_angle
+                continue
+
+        # Memory Cleanup: Slice the buffer
+        # Keep unparsed part, discard parsed part
+        if self.parsed_pos > 0:
+            self._buffer = self._buffer[self.parsed_pos :]
+            self.parsed_pos = 0
+
+        normal_text = "".join(normal_text_chunks) if normal_text_chunks else ""
+        return StreamingParseResult(calls=calls, normal_text=normal_text)
+
+    def supports_structural_tag(self) -> bool:
+        return False
+
+    def structure_info(self) -> _GetInfoFunc:
+        raise NotImplementedError

tokenizer_config.json

@@ -0,0 +1,239 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151665": {
+      "content": "<tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151666": {
+      "content": "</tool_response>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151667": {
+      "content": "<think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151668": {
+      "content": "</think>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% macro render_extra_keys(json_dict, handled_keys) %}\n    {%- if json_dict is mapping %}\n        {%- for json_key in json_dict if json_key not in handled_keys %}\n            {%- if json_dict[json_key] is string %}\n                {{-'\\n<' ~ json_key ~ '>' ~ (json_dict[json_key] | string) ~ '</' ~ json_key ~ '>' }}\n            {%- else %}\n                {{- '\\n<' ~ json_key ~ '>' ~ (json_dict[json_key] | tojson | safe) ~ '</' ~ json_key ~ '>' }}\n            {%- endif %}\n        {%- endfor %}\n    {%- endif %}\n{%- endmacro %}\n\n{%- if messages[0][\"role\"] == \"system\" %}\n    {%- set system_message = messages[0][\"content\"] %}\n    {%- set loop_messages = messages[1:] %}\n{%- else %}\n    {%- set loop_messages = messages %}\n{%- endif %}\n\n{%- if not tools is defined %}\n    {%- set tools = [] %}\n{%- endif %}\n\n{%- if system_message is defined %}\n    {{- \"<|im_start|>system\\n\" + system_message }}\n{%- else %}\n    {%- if tools is iterable and tools | length > 0 %}\n        {{- \"<|im_start|>system\\nYou are Qwen, a helpful AI assistant that can interact with a computer to solve tasks.\" }}\n    {%- endif %}\n{%- endif %}\n{%- if tools is iterable and tools | length > 0 %}\n    {{- \"\\n\\n# Tools\\n\\nYou have access to the following functions:\\n\\n\" }}\n    {{- \"<tools>\" }}\n    {%- for tool in tools %}\n        {%- if tool.function is defined %}\n            {%- set tool = tool.function %}\n        {%- endif %}\n        {{- \"\\n<function>\\n<name>\" ~ tool.name ~ \"</name>\" }}\n        {%- if tool.description is defined %}\n            {{- '\\n<description>' ~ (tool.description | trim) ~ '</description>' }}\n        {%- endif %}\n        {{- '\\n<parameters>' }}\n        {%- if tool.parameters is defined and tool.parameters is mapping and tool.parameters.properties is defined and tool.parameters.properties is mapping %}\n            {%- for param_name, param_fields in tool.parameters.properties|items %}\n                {{- '\\n<parameter>' }}\n                {{- '\\n<name>' ~ param_name ~ '</name>' }}\n                {%- if param_fields.type is defined %}\n                    {{- '\\n<type>' ~ (param_fields.type | string) ~ '</type>' }}\n                {%- endif %}\n                {%- if param_fields.description is defined %}\n                    {{- '\\n<description>' ~ (param_fields.description | trim) ~ '</description>' }}\n                {%- endif %}\n                {%- set handled_keys = ['name', 'type', 'description'] %}\n                {{- render_extra_keys(param_fields, handled_keys) }}\n                {{- '\\n</parameter>' }}\n            {%- endfor %}\n        {%- endif %}\n        {%- set handled_keys = ['type', 'properties'] %}\n        {{- render_extra_keys(tool.parameters, handled_keys) }}\n        {{- '\\n</parameters>' }}\n        {%- set handled_keys = ['type', 'name', 'description', 'parameters'] %}\n        {{- render_extra_keys(tool, handled_keys) }}\n        {{- '\\n</function>' }}\n    {%- endfor %}\n    {{- \"\\n</tools>\" }}\n    {{- '\\n\\nIf you choose to call a function ONLY reply in the following format with NO suffix:\\n\\n<tool_call>\\n<function=example_function_name>\\n<parameter=example_parameter_1>\\nvalue_1\\n</parameter>\\n<parameter=example_parameter_2>\\nThis is the value for the second parameter\\nthat can span\\nmultiple lines\\n</parameter>\\n</function>\\n</tool_call>\\n\\n<IMPORTANT>\\nReminder:\\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\\n- Required parameters MUST be specified\\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\\n</IMPORTANT>' }}\n{%- endif %}\n{%- if system_message is defined %}\n    {{- '<|im_end|>\\n' }}\n{%- else %}\n    {%- if tools is iterable and tools | length > 0 %}\n        {{- '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in loop_messages %}\n    {%- if message.role == \"assistant\" and message.tool_calls is defined and message.tool_calls is iterable and message.tool_calls | length > 0 %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content is defined and message.content is string and message.content | trim | length > 0 %}\n            {{- '\\n' + message.content | trim + '\\n' }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n<function=' + tool_call.name + '>\\n' }}\n            {%- if tool_call.arguments is defined %}\n                {%- for args_name, args_value in tool_call.arguments|items %}\n                    {{- '<parameter=' + args_name + '>\\n' }}\n                    {%- set args_value = args_value if args_value is string else args_value | tojson | safe %}\n                    {{- args_value }}\n                    {{- '\\n</parameter>\\n' }}\n                {%- endfor %}\n            {%- endif %}\n            {{- '</function>\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"user\" or message.role == \"system\" or message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.previtem and loop.previtem.role != \"tool\" %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if not loop.last and loop.nextitem.role != \"tool\" %}\n            {{- '<|im_end|>\\n' }}\n        {%- elif loop.last %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- else %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 1048576,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "add_bos_token": false
+}