| |
| """Render OpenAI-style requests with the official Ling-3.0 chat template. |
| |
| The output is the golden file for tests/chat_tools_test.cpp: each request is |
| rendered by transformers' own Jinja renderer, so the C++ prompt builder is |
| checked against the template rather than against a reading of it. The |
| template is inclusionAI/Ling-3.0-tiny@e3a47d5b986e7141b6efd62597d598ebb392060d |
| chat_template.jinja (pass its local path). Tool-call arguments travel as JSON |
| strings in the requests, as OpenAI clients send them; the template needs them |
| as mappings, as vLLM and llama.cpp convert them. |
| """ |
| import argparse |
| import copy |
| import json |
| from pathlib import Path |
|
|
| from transformers.utils.chat_template_utils import render_jinja_template |
|
|
| MODEL = "mindnano-ling3-tiny" |
| READ = {"type": "function", "function": {"name": "read_file", "description": "Read a file's contents.", |
| "parameters": {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}}} |
| PATCH = {"type": "function", "function": {"name": "patch", "description": "Apply a small text patch to a file.", |
| "parameters": {"type": "object", "properties": {"path": {"type": "string"}, "find": {"type": "string"}, |
| "replace": {"type": "string"}}, "required": ["path", "find", "replace"]}}} |
| RUN = {"type": "function", "function": {"name": "run", "description": "运行命令 — 可设超时。", |
| "parameters": {"type": "object", "properties": {"command": {"type": "string"}, "timeout": {"type": "integer"}, |
| "env": {"type": "object"}, "dry": {"type": "boolean"}}, "required": ["command"]}}} |
|
|
|
|
| def call(id_, name, **arguments): |
| return {"id": id_, "type": "function", "function": {"name": name, "arguments": json.dumps(arguments, ensure_ascii=False)}} |
|
|
|
|
| CASES = [ |
| ("no_tools_history", False, None, [ |
| {"role": "system", "content": "请用中文回答"}, {"role": "user", "content": "你好"}, |
| {"role": "assistant", "content": "你好！"}, {"role": "user", "content": "继续"}]), |
| ("tools_no_system", False, [READ], [{"role": "user", "content": "Reply with OK."}]), |
| ("tools_system", False, [READ, PATCH], [ |
| {"role": "system", "content": "You are terse."}, |
| {"role": "user", "content": "Use the tools to read /tmp/scratch.txt, then patch it to change 'foo' to 'bar'."}]), |
| ("tools_system_thinking_phrase", False, [READ], [ |
| {"role": "system", "content": "detailed thinking off\nBe brief."}, {"role": "user", "content": "Read /tmp/a."}]), |
| ("tool_loop", False, [READ, PATCH, RUN], [ |
| {"role": "system", "content": "You are terse."}, {"role": "user", "content": "Fix /tmp/a.txt."}, |
| {"role": "assistant", "content": None, "tool_calls": [ |
| call("call_1", "read_file", path="/tmp/a.txt"), |
| call("call_2", "run", command="ls -l", timeout=30, env={"A": "1", "B": [1, 2.5]}, dry=False)]}, |
| {"role": "tool", "tool_call_id": "call_1", "content": "foo\n"}, |
| {"role": "tool", "tool_call_id": "call_2", "content": "total 0"}, |
| {"role": "assistant", "content": "Read it.", "tool_calls": [ |
| call("call_3", "patch", path="/tmp/a.txt", find="foo", replace="bar\n")]}, |
| {"role": "tool", "tool_call_id": "call_3", "content": "ok"}]), |
| ("thinking_tool_loop", True, [READ], [ |
| {"role": "user", "content": "What is in /tmp/a?"}, |
| {"role": "assistant", "content": "", "reasoning_content": "\nI should read it.\n", |
| "tool_calls": [call("call_1", "read_file", path="/tmp/a")]}, |
| {"role": "tool", "tool_call_id": "call_1", "content": "foo"}]), |
| ("think_in_content", True, [READ], [ |
| {"role": "user", "content": "Hi"}, |
| {"role": "assistant", "content": "<think>\nplan\n</think>\n\nHello."}, |
| {"role": "user", "content": "读取 /tmp/文件 ✓"}]), |
| ("unicode_call", False, [RUN], [ |
| {"role": "user", "content": "打招呼"}, |
| {"role": "assistant", "content": None, "tool_calls": [call("call_1", "run", command="echo 你好")]}, |
| {"role": "tool", "tool_call_id": "call_1", "content": "你好"}]), |
| ] |
|
|
|
|
| def template_messages(messages): |
| messages = copy.deepcopy(messages) |
| for message in messages: |
| for tool_call in message.get("tool_calls", []): |
| tool_call["function"]["arguments"] = json.loads(tool_call["function"]["arguments"]) |
| return messages |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("--template", type=Path, required=True) |
| parser.add_argument("--output", type=Path, required=True) |
| args = parser.parse_args() |
| template = args.template.read_text() |
| golden = [] |
| for name, thinking, tools, messages in CASES: |
| rendered, _ = render_jinja_template(conversations=[template_messages(messages)], tools=tools, |
| chat_template=template, add_generation_prompt=True, |
| enable_thinking=thinking) |
| request = {"model": MODEL, "messages": messages, "enable_thinking": thinking} |
| if tools: request["tools"] = tools |
| golden.append({"name": name, "request": request, "prompt": rendered[0]}) |
| args.output.write_text(json.dumps(golden, ensure_ascii=False, indent=1) + "\n") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
