[sgl-router] Match DeepSeek V4 rendering to SGLang (#40530)
Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com> Co-authored-by: Shangming Cai <csmthu@gmail.com>
This commit is contained in:
Kan Wu
co-authored by
Claude Fable 5.1
Shangming Cai
Claude Fable 5.1
Shangming Cai
parent
2016f5e7a1
commit
0abb251a20
@@ -0,0 +1,79 @@
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// SPDX-FileCopyrightText: Copyright (c) 2026 The SGLang Authors
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// SPDX-License-Identifier: Apache-2.0
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use std::path::PathBuf;
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use serde_json::{json, Value};
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use sgl_router::tokenizer::{adapter, chat_formatter::ChatFormatter};
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use sha2::{Digest, Sha256};
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fn check_fixture(fixture: &str, model_type: &str) {
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let fixture: Value = serde_json::from_str(fixture).unwrap();
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let dir = tempfile::tempdir().unwrap();
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let path = dir.path().join("tokenizer.json");
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std::fs::write(&path, "{}").unwrap();
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let hf_home = std::env::var_os("HF_HOME")
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.map(PathBuf::from)
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.or_else(|| dirs::home_dir().map(|p| p.join(".cache/huggingface")));
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let cached = hf_home.map(|p| {
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p.join("hub")
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.join(format!(
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"models--{}",
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fixture["model"].as_str().unwrap().replace('/', "--")
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))
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.join("snapshots")
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.join(fixture["revision"].as_str().unwrap())
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.join("tokenizer.json")
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});
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let tokenizer = cached
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.filter(|p| p.is_file())
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.map(|p| adapter::load(p.to_str().unwrap()).unwrap());
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if tokenizer.is_none() {
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eprintln!(
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"{}: checking rendered text; pinned tokenizer is not cached",
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fixture["model"]
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);
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}
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for case in fixture["cases"].as_array().unwrap() {
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std::fs::write(
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dir.path().join("config.json"),
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json!({"model_type":model_type, "dsv4_reasoning_effort_profile":case["profile"]})
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.to_string(),
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)
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.unwrap();
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let formatter = ChatFormatter::load("served-alias", path.to_str().unwrap())
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.unwrap()
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.unwrap();
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let text = formatter
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.render(&case["request"])
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.unwrap_or_else(|e| panic!("{}: {e:#}", case["name"]));
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assert_eq!(text, case["prompt"].as_str().unwrap(), "{}", case["name"]);
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if let Some(tokenizer) = &tokenizer {
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let ids = formatter.encode(tokenizer, &case["request"]).unwrap();
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let mut hash = Sha256::new();
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for id in &ids {
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hash.update(id.to_le_bytes());
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}
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assert_eq!(
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ids.len() as u64,
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case["token_count"].as_u64().unwrap(),
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"{}",
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case["name"]
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);
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assert_eq!(
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format!("{:x}", hash.finalize()),
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case["token_sha256"].as_str().unwrap(),
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"{}",
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case["name"]
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);
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}
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}
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}
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#[test]
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fn v4_matches_sglang_serving() {
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check_fixture(
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include_str!("../../fixtures/deepseek/v4.json"),
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"deepseek_v4",
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);
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}
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@@ -4,3 +4,5 @@
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mod kimi;
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mod parity;
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mod render_parity;
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mod deepseek;
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@@ -0,0 +1,26 @@
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{"model": "deepseek-ai/DeepSeek-V4-Flash", "revision": "60d8d70770c6776ff598c94bb586a859a38244f1", "cases": [
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{"name":"preview/user","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}]},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜></think>","token_count":5,"token_sha256":"95aeed952d0173ec8849b13faec66eb61ec4412cd9c41dae0c405257559365a6"},
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{"name":"preview/system","profile":"preview","request":{"model":"m","messages":[{"role":"system","content":"Be terse"},{"role":"user","content":"Hi"}]},"prompt":"<｜begin▁of▁sentence｜>Be terse<｜User｜>Hi<｜Assistant｜></think>","token_count":8,"token_sha256":"a577612d73073798010b2fca019f9f261242a452e826a7e1fc1e746f07e088b0"},
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{"name":"preview/multi_turn","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"},{"role":"assistant","content":"Answer","reasoning_content":"Prior reasoning"},{"role":"user","content":"Again"}]},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜></think>Answer<｜end▁of▁sentence｜><｜User｜>Again<｜Assistant｜></think>","token_count":11,"token_sha256":"5ab68a07b5a4b1fa1811d68fe156ece6b5284af15cac9b76933c28d9909e4ee2"},
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{"name":"preview/parts","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":[{"type":"text","text":"Hello"},{"type":"text","text":"world"}]}]},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hello world<｜Assistant｜></think>","token_count":6,"token_sha256":"ca8d375f13a4fe4f95b6ec298e03d412f93f3c2d353aa0647223efe74065e51b"},
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{"name":"preview/continuation_parts","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"},{"role":"assistant","content":[{"type":"text","text":"Hello"},{"type":"text","text":"world"}]}],"continue_final_message":true},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜></think>Hello world","token_count":7,"token_sha256":"f436ace77f4a14b4d21ac6e87347a1263253e87cbb23d5e7a4ffc8af1cb36f21"},
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{"name":"preview/continuation_bos","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"},{"role":"assistant","content":"<｜begin▁of▁sentence｜>abc"}],"continue_final_message":true},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜></think><｜begin▁of▁sentence｜>abc","token_count":6,"token_sha256":"defef25e49dca2301b583fb67cabe122b8aa1bdd889727ea1e8b083be7149c14"},
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{"name":"preview/tools","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"tools":[{"type":"function","function":{"name":"foo","parameters":{"type":"object","properties":{}}}},{"type":"function","function":{"name":"bar","description":"第二个","strict":true}}]},"prompt":"<｜begin▁of▁sentence｜>\n\n## Tools\n\nYou have access to a set of tools to help answer the user's question. You can invoke tools by writing a \"<｜DSML｜tool_calls>\" block like the following:\n\n<｜DSML｜tool_calls>\n<｜DSML｜invoke name=\"$TOOL_NAME\">\n<｜DSML｜parameter name=\"$PARAMETER_NAME\" string=\"true|false\">$PARAMETER_VALUE</｜DSML｜parameter>\n...\n</｜DSML｜invoke>\n<｜DSML｜invoke name=\"$TOOL_NAME2\">\n...\n</｜DSML｜invoke>\n</｜DSML｜tool_calls>\n\nString parameters should be specified as is and set `string=\"true\"`. For all other types (numbers, booleans, arrays, objects), pass the value in JSON format and set `string=\"false\"`.\n\nIf thinking_mode is enabled (triggered by <think>), you MUST output your complete reasoning inside <think>...</think> BEFORE any tool calls or final response.\n\nOtherwise, output directly after </think> with tool calls or final response.\n\n### Available Tool Schemas\n\n{\"description\": null, \"name\": \"foo\", \"parameters\": {\"type\": \"object\", \"properties\": {}}, \"strict\": false}\n{\"description\": \"第二个\", \"name\": \"bar\", \"parameters\": null, \"strict\": true}\n\nYou MUST strictly follow the above defined tool name and parameter schemas to invoke tool calls.\n<｜User｜>Hi<｜Assistant｜></think>","token_count":279,"token_sha256":"b8bcd88b2fc3015ee81bd9be25dfa2025765e2590cc407b227b6b5e241fe3adb"},
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{"name":"preview/tools_none","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"tools":[{"type":"function","function":{"name":"foo","parameters":{"type":"object","properties":{}}}},{"type":"function","function":{"name":"bar","description":"第二个","strict":true}}],"tool_choice":"none"},"prompt":"<｜begin▁of▁sentence｜>\n\n## Tools\n\nYou have access to a set of tools to help answer the user's question. You can invoke tools by writing a \"<｜DSML｜tool_calls>\" block like the following:\n\n<｜DSML｜tool_calls>\n<｜DSML｜invoke name=\"$TOOL_NAME\">\n<｜DSML｜parameter name=\"$PARAMETER_NAME\" string=\"true|false\">$PARAMETER_VALUE</｜DSML｜parameter>\n...\n</｜DSML｜invoke>\n<｜DSML｜invoke name=\"$TOOL_NAME2\">\n...\n</｜DSML｜invoke>\n</｜DSML｜tool_calls>\n\nString parameters should be specified as is and set `string=\"true\"`. For all other types (numbers, booleans, arrays, objects), pass the value in JSON format and set `string=\"false\"`.\n\nIf thinking_mode is enabled (triggered by <think>), you MUST output your complete reasoning inside <think>...</think> BEFORE any tool calls or final response.\n\nOtherwise, output directly after </think> with tool calls or final response.\n\n### Available Tool Schemas\n\n{\"description\": null, \"name\": \"foo\", \"parameters\": {\"type\": \"object\", \"properties\": {}}, \"strict\": false}\n{\"description\": \"第二个\", \"name\": \"bar\", \"parameters\": null, \"strict\": true}\n\nYou MUST strictly follow the above defined tool name and parameter schemas to invoke tool calls.\n<｜User｜>Hi<｜Assistant｜></think>","token_count":279,"token_sha256":"b8bcd88b2fc3015ee81bd9be25dfa2025765e2590cc407b227b6b5e241fe3adb"},
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{"name":"preview/tools_named","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"tools":[{"type":"function","function":{"name":"foo","parameters":{"type":"object","properties":{}}}},{"type":"function","function":{"name":"bar","description":"第二个","strict":true}}],"tool_choice":{"type":"function","function":{"name":"bar"}}},"prompt":"<｜begin▁of▁sentence｜>\n\n## Tools\n\nYou have access to a set of tools to help answer the user's question. You can invoke tools by writing a \"<｜DSML｜tool_calls>\" block like the following:\n\n<｜DSML｜tool_calls>\n<｜DSML｜invoke name=\"$TOOL_NAME\">\n<｜DSML｜parameter name=\"$PARAMETER_NAME\" string=\"true|false\">$PARAMETER_VALUE</｜DSML｜parameter>\n...\n</｜DSML｜invoke>\n<｜DSML｜invoke name=\"$TOOL_NAME2\">\n...\n</｜DSML｜invoke>\n</｜DSML｜tool_calls>\n\nString parameters should be specified as is and set `string=\"true\"`. For all other types (numbers, booleans, arrays, objects), pass the value in JSON format and set `string=\"false\"`.\n\nIf thinking_mode is enabled (triggered by <think>), you MUST output your complete reasoning inside <think>...</think> BEFORE any tool calls or final response.\n\nOtherwise, output directly after </think> with tool calls or final response.\n\n### Available Tool Schemas\n\n{\"description\": null, \"name\": \"foo\", \"parameters\": {\"type\": \"object\", \"properties\": {}}, \"strict\": false}\n{\"description\": \"第二个\", \"name\": \"bar\", \"parameters\": null, \"strict\": true}\n\nYou MUST strictly follow the above defined tool name and parameter schemas to invoke tool calls.\n<｜User｜>Hi<｜Assistant｜></think>","token_count":279,"token_sha256":"b8bcd88b2fc3015ee81bd9be25dfa2025765e2590cc407b227b6b5e241fe3adb"},
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{"name":"preview/message_tools","profile":"preview","request":{"model":"m","messages":[{"role":"system","content":"SYS","tools":[{"type":"function","function":{"name":"foo","parameters":{"type":"object","properties":{}}}},{"type":"function","function":{"name":"bar","description":"第二个","strict":true}}]},{"role":"user","content":"Hi"}]},"prompt":"<｜begin▁of▁sentence｜>SYS\n\n## Tools\n\nYou have access to a set of tools to help answer the user's question. You can invoke tools by writing a \"<｜DSML｜tool_calls>\" block like the following:\n\n<｜DSML｜tool_calls>\n<｜DSML｜invoke name=\"$TOOL_NAME\">\n<｜DSML｜parameter name=\"$PARAMETER_NAME\" string=\"true|false\">$PARAMETER_VALUE</｜DSML｜parameter>\n...\n</｜DSML｜invoke>\n<｜DSML｜invoke name=\"$TOOL_NAME2\">\n...\n</｜DSML｜invoke>\n</｜DSML｜tool_calls>\n\nString parameters should be specified as is and set `string=\"true\"`. For all other types (numbers, booleans, arrays, objects), pass the value in JSON format and set `string=\"false\"`.\n\nIf thinking_mode is enabled (triggered by <think>), you MUST output your complete reasoning inside <think>...</think> BEFORE any tool calls or final response.\n\nOtherwise, output directly after </think> with tool calls or final response.\n\n### Available Tool Schemas\n\n{\"description\": null, \"name\": \"foo\", \"parameters\": {\"type\": \"object\", \"properties\": {}}, \"strict\": false}\n{\"description\": \"第二个\", \"name\": \"bar\", \"parameters\": null, \"strict\": true}\n\nYou MUST strictly follow the above defined tool name and parameter schemas to invoke tool calls.\n<｜User｜>Hi<｜Assistant｜></think>","token_count":281,"token_sha256":"d43bde4fa301d6ef32903e59288c6c35febe0e3e60df344a144b7e90f2234d4c"},
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{"name":"preview/empty_message_tools","profile":"preview","request":{"model":"m","messages":[{"role":"system","content":"SYS","tools":[]},{"role":"user","content":"Hi"}]},"prompt":"<｜begin▁of▁sentence｜>SYS<｜User｜>Hi<｜Assistant｜></think>","token_count":7,"token_sha256":"c8211376cce728f63cfce621a7a28ac296a8701a27e084a8e8aa57ced3e6c973"},
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{"name":"preview/tool_results","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"},{"role":"assistant","content":null,"tool_calls":[{"id":"a","type":"function","function":{"name":"foo","arguments":"{\"x\":\"雪\", \"y\":[1, true]}"}},{"id":"b","type":"function","function":{"name":"bar","arguments":{"z":2}}}],"reasoning_content":"Call both"},{"role":"tool","content":[{"type":"text","text":"Hello"},{"type":"text","text":"world"}],"tool_call_id":"b"},{"role":"tool","content":null,"tool_call_id":"a"}],"tools":[{"type":"function","function":{"name":"foo","parameters":{"type":"object","properties":{}}}},{"type":"function","function":{"name":"bar","description":"第二个","strict":true}}],"chat_template_kwargs":{"thinking":true}},"prompt":"<｜begin▁of▁sentence｜>\n\n## Tools\n\nYou have access to a set of tools to help answer the user's question. You can invoke tools by writing a \"<｜DSML｜tool_calls>\" block like the following:\n\n<｜DSML｜tool_calls>\n<｜DSML｜invoke name=\"$TOOL_NAME\">\n<｜DSML｜parameter name=\"$PARAMETER_NAME\" string=\"true|false\">$PARAMETER_VALUE</｜DSML｜parameter>\n...\n</｜DSML｜invoke>\n<｜DSML｜invoke name=\"$TOOL_NAME2\">\n...\n</｜DSML｜invoke>\n</｜DSML｜tool_calls>\n\nString parameters should be specified as is and set `string=\"true\"`. For all other types (numbers, booleans, arrays, objects), pass the value in JSON format and set `string=\"false\"`.\n\nIf thinking_mode is enabled (triggered by <think>), you MUST output your complete reasoning inside <think>...</think> BEFORE any tool calls or final response.\n\nOtherwise, output directly after </think> with tool calls or final response.\n\n### Available Tool Schemas\n\n{\"description\": null, \"name\": \"foo\", \"parameters\": {\"type\": \"object\", \"properties\": {}}, \"strict\": false}\n{\"description\": \"第二个\", \"name\": \"bar\", \"parameters\": null, \"strict\": true}\n\nYou MUST strictly follow the above defined tool name and parameter schemas to invoke tool calls.\n<｜User｜>Hi<｜Assistant｜><think>Call both</think>\n\n<｜DSML｜tool_calls>\n<｜DSML｜invoke name=\"foo\">\n<｜DSML｜parameter name=\"x\" string=\"true\">雪</｜DSML｜parameter>\n<｜DSML｜parameter name=\"y\" string=\"false\">[1, true]</｜DSML｜parameter>\n</｜DSML｜invoke>\n<｜DSML｜invoke name=\"bar\">\n<｜DSML｜parameter name=\"z\" string=\"false\">2</｜DSML｜parameter>\n</｜DSML｜invoke>\n</｜DSML｜tool_calls><｜end▁of▁sentence｜><｜User｜><tool_result></tool_result>\n\n<tool_result>Hello world</tool_result><｜Assistant｜><think>","token_count":394,"token_sha256":"943afa4c1eaabc806f8e1b6b4a51aceb2bef811c308aa04033e7424ae9889e62"},
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{"name":"preview/kwargs_effort","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"chat_template_kwargs":{"thinking":true,"reasoning_effort":"max"}},"prompt":"<｜begin▁of▁sentence｜>Reasoning Effort: Absolute maximum with no shortcuts permitted.\nYou MUST be very thorough in your thinking and comprehensively decompose the problem to resolve the root cause, rigorously stress-testing your logic against all potential paths, edge cases, and adversarial scenarios.\nExplicitly write out your entire deliberation process, documenting every intermediate step, considered alternative, and rejected hypothesis to ensure absolutely no assumption is left unchecked.\n\n<｜User｜>Hi<｜Assistant｜><think>","token_count":84,"token_sha256":"daf853d041e8dde87f07e95a201f8f07459c88482fe53e46472605d63fbdbeac"},
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{"name":"preview/effort_conflict","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"reasoning_effort":"high","chat_template_kwargs":{"reasoning_effort":"low"}},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜><think>","token_count":5,"token_sha256":"c6c0b4c94f78803396fe1b21a3613dd337930a46baf38d285233fe84a60ae7c7"},
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{"name":"preview/drop_thinking_ignored","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"},{"role":"assistant","content":"Answer","reasoning_content":"Prior reasoning"},{"role":"user","content":"Again"}],"chat_template_kwargs":{"thinking":true,"drop_thinking":false}},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜></think>Answer<｜end▁of▁sentence｜><｜User｜>Again<｜Assistant｜><think>","token_count":11,"token_sha256":"73695fa1d286fac76f65bccacff0cd8b2dbee97ca18c3cdc3939dc9048a9037a"},
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{"name":"preview/thinking_false","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"reasoning_effort":"high","chat_template_kwargs":{"thinking":false}},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜></think>","token_count":5,"token_sha256":"95aeed952d0173ec8849b13faec66eb61ec4412cd9c41dae0c405257559365a6"},
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{"name":"preview/thinking_none","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"reasoning_effort":"none","chat_template_kwargs":{"thinking":true}},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜><think>","token_count":5,"token_sha256":"c6c0b4c94f78803396fe1b21a3613dd337930a46baf38d285233fe84a60ae7c7"},
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{"name":"preview/task_after_developer","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"},{"role":"developer","content":"Instruction"}],"task":"domain"},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜User｜>Instruction<｜domain｜>","token_count":6,"token_sha256":"0e73d27ea0537f419ab6c581e697be2217299186a5101bb84d193f1e5569a73b"},
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{"name":"preview/consecutive_task","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"},{"role":"user","content":"Again"}],"task":"domain"},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi\n\nAgain<｜Assistant｜></think>","token_count":7,"token_sha256":"d05e248d8a06f2c06df20b7a71af0d4dfae1cd91ce9f614719b5842674042d6b"},
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{"name":"preview/effort_high","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"reasoning_effort":"high"},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜><think>","token_count":5,"token_sha256":"c6c0b4c94f78803396fe1b21a3613dd337930a46baf38d285233fe84a60ae7c7"},
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{"name":"preview/effort_max","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"reasoning_effort":"max"},"prompt":"<｜begin▁of▁sentence｜>Reasoning Effort: Absolute maximum with no shortcuts permitted.\nYou MUST be very thorough in your thinking and comprehensively decompose the problem to resolve the root cause, rigorously stress-testing your logic against all potential paths, edge cases, and adversarial scenarios.\nExplicitly write out your entire deliberation process, documenting every intermediate step, considered alternative, and rejected hypothesis to ensure absolutely no assumption is left unchecked.\n\n<｜User｜>Hi<｜Assistant｜><think>","token_count":84,"token_sha256":"daf853d041e8dde87f07e95a201f8f07459c88482fe53e46472605d63fbdbeac"},
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{"name":"preview/task_action","profile":"preview","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"task":"action"},"prompt":"<｜begin▁of▁sentence｜><｜User｜>Hi<｜Assistant｜></think><｜action｜>","token_count":6,"token_sha256":"925bcaae248cc41efabd3e5d8f660f17513e43174f1d34aba51a1399aba76e8e"},
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{"name":"official/effort_high","profile":"official","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"reasoning_effort":"high"},"prompt":"<｜begin▁of▁sentence｜>Reasoning Effort: Absolute maximum with no shortcuts permitted.\nYou MUST be very thorough in your thinking and comprehensively decompose the problem to resolve the root cause, rigorously stress-testing your logic against all potential paths, edge cases, and adversarial scenarios.\nExplicitly write out your entire deliberation process, documenting every intermediate step, considered alternative, and rejected hypothesis to ensure absolutely no assumption is left unchecked.\n\n<｜User｜>Hi<｜Assistant｜><think>","token_count":84,"token_sha256":"daf853d041e8dde87f07e95a201f8f07459c88482fe53e46472605d63fbdbeac"},
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{"name":"official/effort_max","profile":"official","request":{"model":"m","messages":[{"role":"user","content":"Hi"}],"reasoning_effort":"max"},"prompt":"<｜begin▁of▁sentence｜>Reasoning Effort: Beyond maximum — exhaustive, relentless, and uncompromising.\nYou MUST reason with the utmost depth and rigor, leaving absolutely nothing to chance: exhaustively decompose the problem into its most fundamental components, trace every causal chain to its root, and resolve the underlying cause rather than any surface symptom.\nDo not stop reasoning until you have independently verified the solution from multiple angles and are certain that no assumption remains unchecked and no error remains undiscovered.\n\n<｜User｜>Hi<｜Assistant｜><think>","token_count":97,"token_sha256":"82ee92542b8545282dcc47a141cb9262d6ab3e20463e0baf445557ca0a9b905c"}
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]}
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@@ -0,0 +1,93 @@
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"""Regenerate native DeepSeek fixtures with SGLang's actual serving pipeline.
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Run from experimental/sgl-router in a SGLang Python environment:
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python tests/scripts/generate_deepseek_parity.py
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||||
|
||||
The Rust tests always compare rendered text, even without cached model files.
|
||||
With the pinned HF snapshot cached they also compare exact token-ID digests.
|
||||
"""
|
||||
|
||||
import copy
|
||||
import hashlib
|
||||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
from types import SimpleNamespace
|
||||
|
||||
from huggingface_hub import snapshot_download
|
||||
from transformers import AutoTokenizer
|
||||
|
||||
os.environ["SGLANG_DEFAULT_THINKING"] = "false"
|
||||
os.environ["SGLANG_DSV4_REASONING_EFFORT"] = ""
|
||||
|
||||
from sglang.srt.entrypoints.openai.protocol import ChatCompletionRequest
|
||||
from sglang.srt.entrypoints.openai.serving_chat import OpenAIServingChat
|
||||
|
||||
ROOT = Path(__file__).resolve().parents[1] / "fixtures/deepseek"
|
||||
MODELS = {
|
||||
"v4": ("deepseek-ai/DeepSeek-V4-Flash", "60d8d70770c6776ff598c94bb586a859a38244f1"),
|
||||
}
|
||||
|
||||
|
||||
class RecordingTokenizer:
|
||||
def __init__(self, tokenizer):
|
||||
self.tokenizer = tokenizer
|
||||
self.texts = []
|
||||
|
||||
def encode(self, text):
|
||||
self.texts.append(text)
|
||||
return self.tokenizer.encode(text)
|
||||
|
||||
def __getattr__(self, name):
|
||||
return getattr(self.tokenizer, name)
|
||||
|
||||
|
||||
def main():
|
||||
ROOT.mkdir(exist_ok=True)
|
||||
for family, (model, revision) in MODELS.items():
|
||||
path = snapshot_download(model, revision=revision, local_files_only=True)
|
||||
tok = RecordingTokenizer(
|
||||
AutoTokenizer.from_pretrained(path, local_files_only=True)
|
||||
)
|
||||
server = object.__new__(OpenAIServingChat)
|
||||
server.chat_encoding_spec = "ds" + family
|
||||
server.tokenizer_manager = SimpleNamespace(tokenizer=tok)
|
||||
server.template_manager = SimpleNamespace(
|
||||
jinja_template_content_format="string"
|
||||
)
|
||||
fixture_path = ROOT / (family + ".json")
|
||||
fixture = json.loads(fixture_path.read_text())
|
||||
for case in fixture["cases"]:
|
||||
server._dsv4_reasoning_effort_profile = case["profile"]
|
||||
tok.texts.clear()
|
||||
request = ChatCompletionRequest(**copy.deepcopy(case["request"]))
|
||||
# _convert_to_internal_request: kwargs effort replaces the request effort.
|
||||
if request.chat_template_kwargs:
|
||||
effort = request.chat_template_kwargs.pop("reasoning_effort", None)
|
||||
if effort is not None:
|
||||
request.reasoning_effort = effort
|
||||
ids = server._apply_jinja_template(
|
||||
request, tools=None, is_multimodal=False
|
||||
).prompt_ids
|
||||
case.update(
|
||||
prompt="".join(tok.texts),
|
||||
token_count=len(ids),
|
||||
token_sha256=hashlib.sha256(
|
||||
b"".join(i.to_bytes(4, "little") for i in ids)
|
||||
).hexdigest(),
|
||||
)
|
||||
metadata = {k: v for k, v in fixture.items() if k != "cases"}
|
||||
fixture_path.write_text(
|
||||
json.dumps(metadata)[:-1]
|
||||
+ ', "cases": [\n'
|
||||
+ ",\n".join(
|
||||
json.dumps(c, ensure_ascii=False, separators=(",", ":"))
|
||||
for c in fixture["cases"]
|
||||
)
|
||||
+ "\n]}\n"
|
||||
)
|
||||
print(f"wrote {family}: {len(fixture['cases'])} cases")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user