Speech Support Workflow

工作流概述

这是一个包含22个节点的复杂工作流,主要用于自动化处理各种任务。

工作流源代码

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{
  "id": "Fdbft9uw8mLGXMoE",
  "meta": {
    "instanceId": "13d96e1ebd7901d1ed300d36db3a4447107e9ad60df51fe711e45683875362aa",
    "templateCredsSetupCompleted": true
  },
  "name": "Speech Support Workflow",
  "tags": [
    {
      "id": "88Rkm7VaAFefsT34",
      "name": "AI",
      "createdAt": "2025-05-06T22:52:26.053Z",
      "updatedAt": "2025-05-06T22:52:26.053Z"
    },
    {
      "id": "s1UA6FThbKhQYbLu",
      "name": "MultiModal",
      "createdAt": "2025-05-06T22:52:35.914Z",
      "updatedAt": "2025-05-06T22:52:35.914Z"
    },
    {
      "id": "ANT04PP2WxQmkjzl",
      "name": "Integrations",
      "createdAt": "2025-05-06T22:53:02.798Z",
      "updatedAt": "2025-05-06T22:53:02.798Z"
    }
  ],
  "nodes": [
    {
      "id": "8868fc75-4a21-4900-b2b9-7860ee981a9e",
      "name": "AI Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        1640,
        240
      ],
      "parameters": {
        "text": "={{ $('Route Flow Based on Message Content').item.json.text }}",
        "options": {
          "systemMessage": "={{ $json.system_prompt }}

You are generating text for a Telegram message. The text should be plain. No * or **"
        },
        "promptType": "define"
      },
      "typeVersion": 1.8
    },
    {
      "id": "23f48680-a190-48a5-bb7c-e070db41b9e7",
      "name": "Google Gemini Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1620,
        800
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-001"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "zCkkU4GKPR7wANF5",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "6a909fb0-f550-4b5e-94db-6e16682d70bd",
      "name": "Recieve Telegram Message",
      "type": "n8n-nodes-base.telegramTrigger",
      "position": [
        -480,
        240
      ],
      "webhookId": "20140af0-c902-44db-9c53-051def981f9a",
      "parameters": {
        "updates": [
          "message"
        ],
        "additionalFields": {}
      },
      "credentials": {
        "telegramApi": {
          "id": "WvBkWguhZJQm5FpM",
          "name": "Telegram account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "73d19e09-efc4-43c4-a4e9-382ae66c7651",
      "name": "Check For Text or Voice Message",
      "type": "n8n-nodes-base.set",
      "position": [
        -260,
        240
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "b37e51e5-e2c7-4328-b02b-80d08164d595",
              "name": "text",
              "type": "string",
              "value": "={{ $json.message.text||\"\" }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "a7ade841-258d-45b2-9150-a56490a4c37f",
      "name": "Download Audio File",
      "type": "n8n-nodes-base.telegram",
      "position": [
        180,
        120
      ],
      "webhookId": "68e0f93e-5dd0-41aa-89e4-4e7a6be9d3b2",
      "parameters": {
        "fileId": "={{ $('Recieve Telegram Message').item.json.message.voice.file_id }}",
        "resource": "file"
      },
      "credentials": {
        "telegramApi": {
          "id": "WvBkWguhZJQm5FpM",
          "name": "Telegram account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "73cb448e-f00e-4879-8fa2-facb259b76b2",
      "name": "Transcribe Audio File",
      "type": "@n8n/n8n-nodes-langchain.openAi",
      "position": [
        400,
        120
      ],
      "parameters": {
        "options": {},
        "resource": "audio",
        "operation": "transcribe"
      },
      "credentials": {
        "openAiApi": {
          "id": "cDXozPn1syyex1aJ",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.8
    },
    {
      "id": "a1999ecd-cabf-4740-a9a6-98486a868b7f",
      "name": "If Voice Message",
      "type": "n8n-nodes-base.if",
      "position": [
        -60,
        240
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "d60f6ce2-afd0-4ee1-a7c3-3d5bbdb68ea2",
              "operator": {
                "type": "string",
                "operation": "empty",
                "singleValue": true
              },
              "leftValue": "={{ $json.text }}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "ac5cad34-3756-4fe3-9269-ae96e5b49e8f",
      "name": "Code to remove unwanted characters from LLM response",
      "type": "n8n-nodes-base.code",
      "position": [
        2060,
        240
      ],
      "parameters": {
        "language": "python",
        "pythonCode": "import re

def clean_markdown_for_telegram(text):
  \"\"\"
  Removes common Markdown formatting characters from a string.

  Args:
    text: The input string.

  Returns:
    A new string with Markdown characters removed.
  \"\"\"
  markdown_chars = r\"[*_~`\[\]()#+\-=|{}.!]\"
  cleaned_text = re.sub(markdown_chars, \"\", text)
  cleaned_text = \" \".join(cleaned_text.split()).strip()
  return cleaned_text

# Loop over input items and create new items with the cleaned text
output_items = []
for item in _input.all():
  feedback_text = item.json.get(\"output\", \"\")
  cleaned_feedback = clean_markdown_for_telegram(feedback_text)
  output_items.append({\"json\": {\"cleanedText\": cleaned_feedback}})

return output_items"
      },
      "typeVersion": 2
    },
    {
      "id": "82761634-7472-4ce1-806a-2b80aca985e3",
      "name": "Code to split output into chunks under 4000 characters",
      "type": "n8n-nodes-base.code",
      "position": [
        2280,
        240
      ],
      "parameters": {
        "language": "python",
        "pythonCode": "def split_text_for_telegram(text, max_length=4000):
  \"\"\"
  Splits a long text into a list of strings, each with a maximum length
  suitable for Telegram messages.

  Args:
    text: The input string to split.
    max_length: The maximum length of each resulting string (default: 4000).

  Returns:
    A list of strings, where each string is a chunk of the original text
    with a maximum length of max_length.
  \"\"\"
  if len(text) <= max_length:
    return [text]

  chunks = []
  start_index = 0
  while start_index < len(text):
    end_index = min(start_index + max_length, len(text))

    split_point = end_index
    if end_index < len(text):
      last_sentence_end = -1
      for i in range(start_index + max_length - 1, start_index - 1, -1):
        if i < len(text) and text[i] in ['.', '?', '!']:
          last_sentence_end = i + 1
          break
      if last_sentence_end > start_index:
        split_point = last_sentence_end

    chunks.append(text[start_index:split_point])
    start_index = split_point

  return chunks

output_items = []
max_length = 4000

for item in _input.all():
  text = item.json.get(\"cleanedText\", \"\")
  text_chunks = split_text_for_telegram(text, max_length)
  for chunk in text_chunks:
    output_items.append({\"json\": {\"telegramTextChunk\": chunk}})

return output_items"
      },
      "typeVersion": 2
    },
    {
      "id": "9adbfd4c-bbb9-4c92-bf07-a3b50a92aa02",
      "name": "Respond to Telegram Message",
      "type": "n8n-nodes-base.telegram",
      "position": [
        2500,
        240
      ],
      "webhookId": "4c77b108-e066-4538-986a-7535143cfaac",
      "parameters": {
        "text": "={{ $json.telegramTextChunk }}",
        "chatId": "={{ $('Recieve Telegram Message').item.json.message.chat.id }}",
        "additionalFields": {
          "appendAttribution": false
        }
      },
      "credentials": {
        "telegramApi": {
          "id": "WvBkWguhZJQm5FpM",
          "name": "Telegram account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "5bdb6ec5-339e-4e8d-a746-9cdbe4d5f12f",
      "name": "Wipe Conversation Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryManager",
      "position": [
        940,
        -20
      ],
      "parameters": {
        "mode": "delete",
        "deleteMode": "all"
      },
      "typeVersion": 1.1
    },
    {
      "id": "aae703f4-e891-4681-aae4-c426ebba5146",
      "name": "Store Conversation Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        1120,
        800
      ],
      "parameters": {
        "sessionKey": "={{ $('Recieve Telegram Message').item.json.message.from.id }}",
        "sessionIdType": "customKey",
        "contextWindowLength": 25
      },
      "typeVersion": 1.3
    },
    {
      "id": "7457f085-9b19-4a00-9ad6-af2ca8ee16d5",
      "name": "Set prompt to start a new speech",
      "type": "n8n-nodes-base.set",
      "position": [
        1340,
        -20
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "d5b33b03-241b-4193-915a-4eb4dfef05e9",
              "name": "system_prompt",
              "type": "string",
              "value": "\"I am preparing to give a speech. Your role is to act as my speech preparation assistant. Please guide me through the process of getting ready to deliver this speech effectively. Ask me relevant questions and suggest steps we should take to ensure a successful presentation.

Potential areas we can work on include:

Defining the core message and key takeaways.
Understanding the audience's needs and expectations.
Structuring the speech for maximum impact.
Crafting engaging content and supporting materials.
Developing effective opening and closing remarks.
Practicing delivery and managing speaking anxiety.
Anticipating potential questions from the audience.
Considering the logistics of the presentation (e.g., time limits, equipment).
Where should we begin?"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "0a9f2c04-7f7e-488c-866c-717a78bf7db1",
      "name": "Set prompt to generate a speech based on the feedback",
      "type": "n8n-nodes-base.set",
      "position": [
        1340,
        220
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "ddbff433-f4bb-4ac1-a954-7fb32c942a9b",
              "name": "system_prompt",
              "type": "string",
              "value": "I want you to act as a speech synthesizer and improvement agent. You have access to the content of several speeches I have previously provided, along with the constructive feedback I received on each and with this information your task is to generate a new speech.

This new speech should incorporate the following:

Key themes and ideas that were present and well-received in my previous speeches.
Structural elements and transitions that were identified as effective in past feedback.
Engagement techniques that were noted as successful.
Avoidance of areas for improvement highlighted in the feedback (e.g., rambling sections, unclear points, pacing issues).
Incorporation of specific suggestions for improvement that were given.
A similar tone and style to my previous speeches, while aiming for enhanced clarity and impact based on the feedback.
Please provide the complete text of the new speech. Feel free to ask clarifying questions if needed about the new topic, audience, or goal, or if you need a reminder of specific feedback points from my previous speeches. I am ready when you are.\""
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "f242361e-6bf4-4c4e-8cd0-72da06823842",
      "name": "Set prompt to provide feedback on speech",
      "type": "n8n-nodes-base.set",
      "position": [
        1340,
        420
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "b86d5905-872a-40fa-9855-054cd8991a0d",
              "name": "system_prompt",
              "type": "string",
              "value": "I'd like you to act as a speech feedback agent. I will deliver a speech to you, and I want you to provide constructive criticism and insights on various aspects of my delivery and content.  Please pay attention to:  Clarity and Conciseness: Was the message easy to understand? Were there any parts that felt rambling or unnecessary? Engagement: How engaging was the speech overall? Were there moments where your attention might have drifted? Structure and Flow: Did the speech progress logically? Were the transitions smooth? Pacing and Timing: Was the speech delivered at an appropriate pace? Did it feel rushed or too slow? Vocal Delivery (if applicable): (If you are able to describe vocal elements) How was the tone, pitch, and volume? Did it enhance or detract from the message? Content and Impact: Was the content compelling and relevant? Did the speech achieve its intended purpose (as I will describe beforehand)? What was the overall impact of the message? Strengths: What were the most effective aspects of the speech? Areas for Improvement: What specific suggestions do you have to make the speech even better? Before I begin, I will briefly tell you the topic, my intended audience, and my goal for the speech. Are you ready?"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "c1f69bc3-2c93-404e-b338-82663deb975b",
      "name": "Route Flow Based on Message Content",
      "type": "n8n-nodes-base.switch",
      "position": [
        680,
        260
      ],
      "parameters": {
        "rules": {
          "values": [
            {
              "outputKey": "new_speech",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": false,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "8b36fb19-1a5a-4fe1-aec2-7de8b5829972",
                    "operator": {
                      "type": "string",
                      "operation": "contains"
                    },
                    "leftValue": "={{ $json.text }}",
                    "rightValue": "new speech"
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "generate_speech",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": false,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "708d114d-1146-4d8a-b972-cfb5a53a8d77",
                    "operator": {
                      "name": "filter.operator.equals",
                      "type": "string",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $json.text }}",
                    "rightValue": "generate speech"
                  }
                ]
              },
              "renameOutput": true
            }
          ]
        },
        "options": {
          "ignoreCase": true,
          "fallbackOutput": "extra"
        }
      },
      "typeVersion": 3.2
    },
    {
      "id": "6cf41698-2345-4ff8-bd1e-9549e372b454",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1280,
        -300
      ],
      "parameters": {
        "width": 220,
        "height": 900,
        "content": "## Dynamic System Prompting:

This node sets the AI's system prompt according to the user's request identified in the incoming message."
      },
      "typeVersion": 1
    },
    {
      "id": "1d967631-9300-4fb6-b488-8c09beccbb05",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2000,
        -300
      ],
      "parameters": {
        "width": 440,
        "height": 720,
        "content": "## Telegram-Ready Output: Formatting and Length Management:

These code nodes perform two crucial tasks:
1.  **Formatting:** Removing characters that could cause issues with Telegram's message parsing.
2.  **Chunking:** Dividing messages longer than Telegram's 4000-character limit into multiple shorter messages for sequential delivery."
      },
      "typeVersion": 1
    },
    {
      "id": "c480550b-c94f-40ee-8338-3deb6bea28d8",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        900,
        -300
      ],
      "parameters": {
        "width": 340,
        "height": 420,
        "content": "## Clearing AI Agent Memory:

This node clears the AI agent's short-term memory. This helps to minimize the influence of past interactions on future responses, thereby reducing the likelihood of the AI generating inaccurate or irrelevant information (hallucinations)."
      },
      "typeVersion": 1
    },
    {
      "id": "bd36f9a8-30d9-4e0a-978b-a74806685adc",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -320,
        -300
      ],
      "parameters": {
        "width": 1160,
        "height": 740,
        "content": "## Processing Telegram Messages:

This section handles incoming messages from Telegram. It first checks if the message contains text.

1.  **Text Message:** If the message includes text, it's directly routed to the analysis switch node.
2.  **Audio Message:** If the message is an audio file:
    * The audio file is downloaded.
    * The audio is transcribed into text.
    * The transcribed text is then sent to the analysis switch node.

Finally, the analyzed text (whether directly from a text message or transcribed from audio) is forwarded for further processing based on the analysis results."
      },
      "typeVersion": 1
    },
    {
      "id": "cf7d8897-b963-4bb5-9b0e-3ab628e478c7",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1620,
        -300
      ],
      "parameters": {
        "width": 300,
        "height": 740,
        "content": "## Gemini-Powered Response and Conversation Storage:

This node utilizes the Google Gemini model to generate a response to the user's prompt and stores the ongoing conversation."
      },
      "typeVersion": 1
    },
    {
      "id": "9fffb613-536e-4b4d-8841-7b4bd3121eab",
      "name": "Sticky Note5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -300,
        -500
      ],
      "parameters": {
        "color": 4,
        "width": 2740,
        "height": 140,
        "content": "## This n8n workflow acts as your personal AI speechwriting coach, directly accessible through Telegram. It listens to your spoken or typed drafts, provides insightful feedback on clarity, engagement, structure, and content, and iteratively refines your message based on your updates. Once you're ready, it synthesizes a brand-new speech or talk incorporating all the improvements and your accumulated ideas. This tool streamlines the speechwriting process, offering on-demand AI assistance to help you craft impactful and well-structured presentations."
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "4aaa8457-2661-4261-a601-0a0ffaffacff",
  "connections": {
    "AI Agent": {
      "main": [
        [
          {
            "node": "Code to remove unwanted characters from LLM response",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "If Voice Message": {
      "main": [
        [
          {
            "node": "Download Audio File",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Route Flow Based on Message Content",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Download Audio File": {
      "main": [
        [
          {
            "node": "Transcribe Audio File",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Transcribe Audio File": {
      "main": [
        [
          {
            "node": "Route Flow Based on Message Content",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Recieve Telegram Message": {
      "main": [
        [
          {
            "node": "Check For Text or Voice Message",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Wipe Conversation Memory": {
      "main": [
        [
          {
            "node": "Set prompt to start a new speech",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Store Conversation Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Agent",
            "type": "ai_memory",
            "index": 0
          },
          {
            "node": "Wipe Conversation Memory",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Check For Text or Voice Message": {
      "main": [
        [
          {
            "node": "If Voice Message",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set prompt to start a new speech": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Route Flow Based on Message Content": {
      "main": [
        [
          {
            "node": "Wipe Conversation Memory",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Set prompt to generate a speech based on the feedback",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Set prompt to provide feedback on speech",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set prompt to provide feedback on speech": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Code to remove unwanted characters from LLM response": {
      "main": [
        [
          {
            "node": "Code to split output into chunks under 4000 characters",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set prompt to generate a speech based on the feedback": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Code to split output into chunks under 4000 characters": {
      "main": [
        [
          {
            "node": "Respond to Telegram Message",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

功能特点

  • 自动检测新邮件
  • AI智能内容分析
  • 自定义分类规则
  • 批量处理能力
  • 详细的处理日志

技术分析

节点类型及作用

  • @N8N/N8N Nodes Langchain.Agent
  • @N8N/N8N Nodes Langchain.Lmchatgooglegemini
  • Telegramtrigger
  • Set
  • Telegram

复杂度评估

配置难度:
★★★★☆
维护难度:
★★☆☆☆
扩展性:
★★★★☆

实施指南

前置条件

  • 有效的Gmail账户
  • n8n平台访问权限
  • Google API凭证
  • AI分类服务订阅

配置步骤

  1. 在n8n中导入工作流JSON文件
  2. 配置Gmail节点的认证信息
  3. 设置AI分类器的API密钥
  4. 自定义分类规则和标签映射
  5. 测试工作流执行
  6. 配置定时触发器(可选)

关键参数

参数名称 默认值 说明
maxEmails 50 单次处理的最大邮件数量
confidenceThreshold 0.8 分类置信度阈值
autoLabel true 是否自动添加标签

最佳实践

优化建议

  • 定期更新AI分类模型以提高准确性
  • 根据邮件量调整处理批次大小
  • 设置合理的分类置信度阈值
  • 定期清理过期的分类规则

安全注意事项

  • 妥善保管API密钥和认证信息
  • 限制工作流的访问权限
  • 定期审查处理日志
  • 启用双因素认证保护Gmail账户

性能优化

  • 使用增量处理减少重复工作
  • 缓存频繁访问的数据
  • 并行处理多个邮件分类任务
  • 监控系统资源使用情况

故障排除

常见问题

邮件未被正确分类

检查AI分类器的置信度阈值设置,适当降低阈值或更新训练数据。

Gmail认证失败

确认Google API凭证有效且具有正确的权限范围,重新进行OAuth授权。

调试技巧

  • 启用详细日志记录查看每个步骤的执行情况
  • 使用测试邮件验证分类逻辑
  • 检查网络连接和API服务状态
  • 逐步执行工作流定位问题节点

错误处理

工作流包含以下错误处理机制:

  • 网络超时自动重试(最多3次)
  • API错误记录和告警
  • 处理失败邮件的隔离机制
  • 异常情况下的回滚操作