feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27

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feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
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copilot/update-average-tokens-configuration

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平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。

Changes

  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段

    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500

  • src/rate_limiter.py:

    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典

  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request

  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参

  • env.example: 添加环境变量说明

配置优先级

  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值

使用示例

# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt

This section details on the original issue you should resolve

<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>
<issue_description>## 问题描述
平均 Token 数硬编码导致并发计算不准确。

受影响的文件

  • src/rate_limiter.py 行 420-423

硬编码值

  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500

问题

这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。

解决方案

应该支持按租户/服务配置平均 token 数。</issue_description>

Comments on the Issue (you are @copilot in this section)

💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.

CopilotAIand others added 2 commits December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI changed the title [WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI requested a review from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy requested changes Dec 15, 2025
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ds_ocr.avg_tokens_per_request
ds_ocr.tokens_per_minute
这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?

Comment threadsrc/deepseek_ocr_client.py
Comment on lines -83 to +84
tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)

@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request
ds_ocr.tokens_per_minute
这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot

CopilotAIDec 15, 2025

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这两个参数的作用不同：

  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。

  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。

虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：

  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限

不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。

CopilotAI requested a review from BukeLyDecember 15, 2025 10:21
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Average tokens per request hardcoded - inaccurate concurrency calculation

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@BukeLy
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27
Draft
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Draft
feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Conversation
CopilotAI
commented
Dec 15, 2025•

edited

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Contributor
平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。
Changes
  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段
    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500
  • src/rate_limiter.py:
    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典
  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request
  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参
  • env.example: 添加环境变量说明
配置优先级
  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值
使用示例
# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt
This section details on the original issue you should resolve
<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>

<issue_description>## 问题描述

平均 Token 数硬编码导致并发计算不准确。
受影响的文件
  • src/rate_limiter.py 行 420-423
硬编码值
  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500
问题
这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。
解决方案
应该支持按租户/服务配置平均 token 数。</issue_description>
Comments on the Issue (you are @copilot in this section)
💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.
CopilotAIand others
added 2 commits
December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI
changed the title
[WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI
requested a review
from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy
requested changes
Dec 15, 2025
View reviewed changes
@BukeLyBukeLy
left a comment


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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?
Comment threadsrc/deepseek_ocr_client.py

Comment on lines

-83
 to 
+84

 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
 avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)
@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot
CopilotAIDec 15, 2025

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这两个参数的作用不同：
  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。
  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。
虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：
  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限
不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。
CopilotAI
requested a review
from BukeLyDecember 15, 2025 10:21
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Average tokens per request hardcoded - inaccurate concurrency calculation


2 participants

@BukeLy

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27
Draft
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Draft
feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Conversation
CopilotAI
commented
Dec 15, 2025•

edited

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平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。
Changes
  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段
    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500
  • src/rate_limiter.py:
    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典
  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request
  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参
  • env.example: 添加环境变量说明
配置优先级
  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值
使用示例
# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt
This section details on the original issue you should resolve
<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>

<issue_description>## 问题描述

平均 Token 数硬编码导致并发计算不准确。
受影响的文件
  • src/rate_limiter.py 行 420-423
硬编码值
  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500
问题
这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。
解决方案
应该支持按租户/服务配置平均 token 数。</issue_description>
Comments on the Issue (you are @copilot in this section)
💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.
CopilotAIand others
added 2 commits
December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI
changed the title
[WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI
requested a review
from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy
requested changes
Dec 15, 2025
View reviewed changes
@BukeLyBukeLy
left a comment


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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?
Comment threadsrc/deepseek_ocr_client.py

Comment on lines

-83
 to 
+84

 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
 avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)
@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot
CopilotAIDec 15, 2025

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这两个参数的作用不同：
  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。
  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。
虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：
  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限
不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。
CopilotAI
requested a review
from BukeLyDecember 15, 2025 10:21
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Average tokens per request hardcoded - inaccurate concurrency calculation


2 participants

@BukeLy

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27
Draft
BukeLy with Copilot wants to merge 3 commits into
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copilot/update-average-tokens-configuration
Draft
feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
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CopilotAI
commented
Dec 15, 2025•

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平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。
Changes
  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段
    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500
  • src/rate_limiter.py:
    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典
  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request
  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参
  • env.example: 添加环境变量说明
配置优先级
  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值
使用示例
# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt
This section details on the original issue you should resolve
<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>

<issue_description>## 问题描述

平均 Token 数硬编码导致并发计算不准确。
受影响的文件
  • src/rate_limiter.py 行 420-423
硬编码值
  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500
问题
这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。
解决方案
应该支持按租户/服务配置平均 token 数。</issue_description>
Comments on the Issue (you are @copilot in this section)
💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.
CopilotAIand others
added 2 commits
December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI
changed the title
[WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI
requested a review
from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy
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Dec 15, 2025
View reviewed changes
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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?
Comment threadsrc/deepseek_ocr_client.py

Comment on lines

-83
 to 
+84

 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
 avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)
@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot
CopilotAIDec 15, 2025

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这两个参数的作用不同：
  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。
  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。
虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：
  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限
不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。
CopilotAI
requested a review
from BukeLyDecember 15, 2025 10:21
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Average tokens per request hardcoded - inaccurate concurrency calculation


2 participants

@BukeLy

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27
Draft
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Draft
feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Conversation
CopilotAI
commented
Dec 15, 2025•

edited

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Contributor
平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。
Changes
  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段
    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500
  • src/rate_limiter.py:
    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典
  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request
  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参
  • env.example: 添加环境变量说明
配置优先级
  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值
使用示例
# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt
This section details on the original issue you should resolve
<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>

<issue_description>## 问题描述

平均 Token 数硬编码导致并发计算不准确。
受影响的文件
  • src/rate_limiter.py 行 420-423
硬编码值
  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500
问题
这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。
解决方案
应该支持按租户/服务配置平均 token 数。</issue_description>
Comments on the Issue (you are @copilot in this section)
💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.
CopilotAIand others
added 2 commits
December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI
changed the title
[WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI
requested a review
from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy
requested changes
Dec 15, 2025
View reviewed changes
@BukeLyBukeLy
left a comment


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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?
Comment threadsrc/deepseek_ocr_client.py

Comment on lines

-83
 to 
+84

 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
 avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)
@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot
CopilotAIDec 15, 2025

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ContributorAuthor
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这两个参数的作用不同：
  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。
  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。
虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：
  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限
不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。
CopilotAI
requested a review
from BukeLyDecember 15, 2025 10:21
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Successfully merging this pull request may close these issues.

Average tokens per request hardcoded - inaccurate concurrency calculation


2 participants

@BukeLy

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27
Draft
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Draft
feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Conversation
CopilotAI
commented
Dec 15, 2025•

edited

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Contributor
平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。
Changes
  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段
    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500
  • src/rate_limiter.py:
    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典
  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request
  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参
  • env.example: 添加环境变量说明
配置优先级
  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值
使用示例
# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt
This section details on the original issue you should resolve
<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>

<issue_description>## 问题描述

平均 Token 数硬编码导致并发计算不准确。
受影响的文件
  • src/rate_limiter.py 行 420-423
硬编码值
  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500
问题
这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。
解决方案
应该支持按租户/服务配置平均 token 数。</issue_description>
Comments on the Issue (you are @copilot in this section)
💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.
CopilotAIand others
added 2 commits
December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI
changed the title
[WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI
requested a review
from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy
requested changes
Dec 15, 2025
View reviewed changes
@BukeLyBukeLy
left a comment


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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?
Comment threadsrc/deepseek_ocr_client.py

Comment on lines

-83
 to 
+84

 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
 avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)
@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot
CopilotAIDec 15, 2025

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这两个参数的作用不同：
  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。
  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。
虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：
  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限
不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。
CopilotAI
requested a review
from BukeLyDecember 15, 2025 10:21
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Successfully merging this pull request may close these issues.

Average tokens per request hardcoded - inaccurate concurrency calculation


2 participants

@BukeLy

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27
Draft
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Draft
feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
Conversation
CopilotAI
commented
Dec 15, 2025•

edited

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平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。
Changes
  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段
    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500
  • src/rate_limiter.py:
    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典
  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request
  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参
  • env.example: 添加环境变量说明
配置优先级
  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值
使用示例
# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt
This section details on the original issue you should resolve
<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>

<issue_description>## 问题描述

平均 Token 数硬编码导致并发计算不准确。
受影响的文件
  • src/rate_limiter.py 行 420-423
硬编码值
  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500
问题
这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。
解决方案
应该支持按租户/服务配置平均 token 数。</issue_description>
Comments on the Issue (you are @copilot in this section)
💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.
CopilotAIand others
added 2 commits
December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI
changed the title
[WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI
requested a review
from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy
requested changes
Dec 15, 2025
View reviewed changes
@BukeLyBukeLy
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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?
Comment threadsrc/deepseek_ocr_client.py

Comment on lines

-83
 to 
+84

 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
 avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)
@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot
CopilotAIDec 15, 2025

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这两个参数的作用不同：
  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。
  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。
虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：
  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限
不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。
CopilotAI
requested a review
from BukeLyDecember 15, 2025 10:21
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Average tokens per request hardcoded - inaccurate concurrency calculation


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@BukeLy

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} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
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feat: 支持按租户/服务配置平均 token 数以优化并发计算 - #27
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BukeLy with Copilot wants to merge 3 commits into
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copilot/update-average-tokens-configuration
Draft
feat: 支持按租户/服务配置平均 token 数以优化并发计算#27
BukeLy with Copilot wants to merge 3 commits into
mainfrom 
copilot/update-average-tokens-configuration
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CopilotAI
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Dec 15, 2025•

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平均 Token 数硬编码在 rate_limiter.py 导致并发计算不准确。Insert 和 Query 场景的 token 消耗差异大，固定保守值限制了系统吞吐量。
Changes
  • src/config.py: 各服务配置类新增 avg_tokens_per_request 字段
    • LLM/DS_OCR: 3500 (default)
    • Embedding: 20000
    • Rerank: 500
  • src/rate_limiter.py:
    • get_rate_limiter() 新增 avg_tokens_per_request 参数
    • 提取默认配置到 SERVICE_DEFAULTS 字典
  • src/tenant_config.py: 各服务合并方法传递 avg_tokens_per_request
  • src/multi_tenant.py / src/deepseek_ocr_client.py: 更新调用传参
  • env.example: 添加环境变量说明
配置优先级
  1. 租户配置 (API)
  2. 环境变量 (LLM_AVG_TOKENS_PER_REQUEST)
  3. 代码默认值
使用示例
# Insert 密集场景，降低平均 token 提升并发
LLM_AVG_TOKENS_PER_REQUEST=2500
// 租户 APIPUT /tenants/{tenant_id}/config
{
"llm_config": {
"avg_tokens_per_request": 4000
}
}
Original prompt
This section details on the original issue you should resolve
<issue_title>Average tokens per request hardcoded - inaccurate concurrency calculation</issue_title>

<issue_description>## 问题描述

平均 Token 数硬编码导致并发计算不准确。
受影响的文件
  • src/rate_limiter.py 行 420-423
硬编码值
  • llm: 3500
  • embedding: 500
  • rerank: 500
  • ds_ocr: 3500
问题
这些值因场景而异（Query vs Insert），但被固定为保守值，导致不必要的速率限制，降低系统吞吐量。
解决方案
应该支持按租户/服务配置平均 token 数。</issue_description>
Comments on the Issue (you are @copilot in this section)
💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.
CopilotAIand others
added 2 commits
December 15, 2025 09:43
@BukeLy
feat: 支持按租户/服务配置平均 token 数以优化并发计算
b14fda4
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
@BukeLy
refactor: 提取 rate_limiter 默认配置到字典以提高可维护性
f5d0441
Co-authored-by: BukeLy <19304666+BukeLy@users.noreply.github.com>
CopilotAI
changed the title
[WIP] Update average tokens per request for better concurrency calculationfeat: 支持按租户/服务配置平均 token 数以优化并发计算Dec 15, 2025
CopilotAI
requested a review
from BukeLyDecember 15, 2025 09:48
BukeLy
BukeLy
requested changes
Dec 15, 2025
View reviewed changes
@BukeLyBukeLy
left a comment


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Owner
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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢?
Comment threadsrc/deepseek_ocr_client.py

Comment on lines

-83
 to 
+84

 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute)
 tokens_per_minute=getattr(self.config, 'tokens_per_minute', config.ds_ocr.tokens_per_minute),
 avg_tokens_per_request=getattr(self.config, 'avg_tokens_per_request', config.ds_ocr.avg_tokens_per_request)
@BukeLyBukeLyDec 15, 2025

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ds_ocr.avg_tokens_per_request

ds_ocr.tokens_per_minute

这两个参数的目的是什么?在没有设置TPM/RPM情况下估算吗?还有就是我记得关于Token我引入了Transform的tokenizer来计算,为什么还需要这两个参数呢? @copilot
CopilotAIDec 15, 2025

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ContributorAuthor
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这两个参数的作用不同：
  1. tokens_per_minute - API 服务商的 TPM 限制（如硅基流动 40000），用于 RateLimiter 控制每分钟最大 token 消耗，防止 429 错误。
  2. avg_tokens_per_request - 用于启动时预估安全并发数的参数。在 calculate_optimal_concurrent() 中计算：concurrent = TPM / avg_tokens / max_in_flight。
虽然 count_tokens() 用 tiktoken 精确计算每个请求的实际 token（运行时扣减 TPM 配额），但 avg_tokens_per_request 是初始化时预估应允许多少并发请求。这是两个不同用途：
  • 运行时：count_tokens() 精确计算实际消耗
  • 初始化：avg_tokens_per_request 预估并发上限
不同场景（Insert vs Query）的平均 token 差异大，现在可配置这个预估值来优化并发。
CopilotAI
requested a review
from BukeLyDecember 15, 2025 10:21
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@BukeLyBukeLyAwaiting requested review from BukeLy

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Successfully merging this pull request may close these issues.

Average tokens per request hardcoded - inaccurate concurrency calculation


2 participants

@BukeLy