diff --git a/docker/yao-knowledge-dev/compose.yml b/docker/yao-knowledge-dev/compose.yml
index 31eac0d..03f6ab9 100644
--- a/docker/yao-knowledge-dev/compose.yml
+++ b/docker/yao-knowledge-dev/compose.yml
@@ -12,7 +12,7 @@ services:
       - "5080"
       - --scheme
       - http
-    image: semitechnologies/weaviate:1.18.3
+    image: semitechnologies/weaviate:latest
     ports:
       - 5080:5080
     restart: on-failure:0
diff --git a/neo/neo.yml b/neo/neo.yml
index 1df105d..b54dc0c 100644
--- a/neo/neo.yml
+++ b/neo/neo.yml
@@ -18,7 +18,7 @@ prompts:
       - Answer my questions in Chinese from now on.
 
 option:
-  temperature: 0.8
+  temperature: 0.6
 
 allows:
   - "http://127.0.0.1:8000"
diff --git a/scripts/doc.js b/scripts/doc.js
index edbd674..ceb8857 100644
--- a/scripts/doc.js
+++ b/scripts/doc.js
@@ -1,3 +1,8 @@
+/**
+ * vector database (on Weaviate)
+ * Will be replaced by the new vector process
+ */
+
 /**
  * Document schema structure
  */
@@ -581,6 +586,244 @@ function Delete(fingerprint) {
   return ids;
 }
 
+/**
+ * Search the part of file with the input
+ * yao run scripts.doc.Query '::{"input":"YAO 怎么写关联查询", "distance": 0.2}' 1 2
+ *
+ * @param {*} input
+ */
+function Query(params, page, pagesize) {
+  params = params || {};
+  page = page ? parseInt(page) : 1;
+  pagesize = pagesize ? parseInt(pagesize) : 20;
+
+  const input = params.input || "";
+  const distance = params.distance || 0.2;
+  const connector = "openai.text-embedding-ada-002";
+
+  if (!input || input == "") {
+    throw new Exception("input is required", 400);
+  }
+
+  const resp = Process("openai.Embeddings", connector, input);
+  if (!resp || resp.code || !resp.data) {
+    const message = resp.message || "openai.Embeddings error";
+    const code = resp.code || 500;
+    throw new Exception(message, code);
+  }
+
+  const vector = JSON.stringify(resp.data[0].embedding || []);
+  const offset = page ? (page - 1) * pagesize : 0;
+  const cfg = setting();
+  const url = `${cfg.host}/v1/graphql`;
+
+  let payload = {
+    query: `{
+      Aggregate {
+        Document (
+          nearVector: {
+            vector: ${vector}
+            distance: ${distance}
+          }
+        )
+        { 
+          meta { 
+            count 
+          } 
+        }
+      }
+      Get {
+        Document(
+          limit: ${pagesize}
+          offset: ${offset}
+          nearVector: {
+            vector: ${vector}
+            distance: ${distance}
+          }
+        ) 
+        {
+          name
+          summary
+          content
+          path
+          type
+          url
+          part
+          fingerprint
+          _additional{
+            id
+            lastUpdateTimeUnix,
+            distance
+          }
+        }
+      }
+    }`,
+  };
+
+  response = post(url, payload, cfg.key);
+  if (response && response.code && response.code != 200 && response.message) {
+    throw new Exception(response.message, response.code);
+  }
+
+  if (response && response.errors) {
+    throw new Exception(response.errors[0].message, 500);
+  }
+
+  let data = response.data || {
+    Get: { Document: [] },
+    Aggregate: { Document: [{ meta: { count: 0 } }] },
+  };
+
+  const meta =
+    data.Aggregate.Document[0] && data.Aggregate.Document[0].meta
+      ? data.Aggregate.Document[0].meta
+      : { count: 0 };
+
+  let total = meta.count;
+  let pages = Math.ceil(total / pagesize);
+  let prev = page > 1 ? page - 1 : 1;
+  let next = page < pages ? page + 1 : pages;
+  let items = data.Get.Document || [];
+  for (let i = 0; i < items.length; i++) {
+    let item = items[i];
+    item.id = item._additional.id;
+    item.lastUpdateTimeUnix = item._additional.lastUpdateTimeUnix;
+    item.distance = item._additional.distance;
+    delete item._additional;
+  }
+
+  return {
+    data: items,
+    next: next,
+    page: parseInt(page),
+    pagecnt: pages,
+    prev: prev,
+    total: total,
+  };
+}
+
+/**
+ * Search the file of file with the input
+ * yao run scripts.doc.Search '::{"input":"YAO 怎么写关联查询", "distance": 0.2}' 1 10
+ *
+ * const distance = 0.2;
+ * const distancePrompts = 2;
+ * @param {*} input
+ */
+function Search(params, page, pagesize) {
+  params = params || {};
+  page = page ? parseInt(page) : 1;
+  pagesize = pagesize ? parseInt(pagesize) : 20;
+
+  const input = params.input || "";
+  const distance = params.distance || 0.2;
+  const connector = "openai.text-embedding-ada-002";
+
+  if (!input || input == "") {
+    throw new Exception("input is required", 400);
+  }
+
+  const resp = Process("openai.Embeddings", connector, input);
+  if (!resp || resp.code || !resp.data) {
+    const message = resp.message || "openai.Embeddings error";
+    const code = resp.code || 500;
+    throw new Exception(message, code);
+  }
+
+  const vector = JSON.stringify(resp.data[0].embedding || []);
+  const offset = page ? (page - 1) * pagesize : 0;
+  const cfg = setting();
+  const url = `${cfg.host}/v1/graphql`;
+
+  let payload = {
+    query: `{
+      Aggregate {
+        Document (
+          nearVector: {
+            vector: ${vector}
+            distance: ${distance}
+          }
+          groupBy: ["fingerprint"]
+        )
+        { 
+          meta { 
+            count 
+          }
+          groupedBy { value path }
+        }
+      }
+      Get {
+        Document(
+          limit: ${pagesize}
+          offset: ${offset}
+          nearVector: {
+            vector: ${vector}
+            distance: ${distance}
+          }
+          groupBy: {
+            path: ["fingerprint"]
+            groups: ${pagesize}
+            objectsPerGroup: 9999
+          }
+        ) 
+        {
+          name
+          summary
+          content
+          path
+          type
+          url
+          part
+          fingerprint
+          _additional{
+            id
+            lastUpdateTimeUnix,
+            distance
+            group {
+              groupedBy { value path }
+            }
+          }
+        }
+      }
+    }`,
+  };
+
+  response = post(url, payload, cfg.key);
+  if (response && response.code && response.code != 200 && response.message) {
+    throw new Exception(response.message, response.code);
+  }
+  if (response && response.errors) {
+    throw new Exception(response.errors[0].message, 500);
+  }
+
+  let data = response.data || {
+    Get: { Document: [] },
+    Aggregate: { Document: [{ meta: { count: 0 } }] },
+  };
+
+  let total = data.Aggregate.Document.length;
+  let pages = Math.ceil(total / pagesize);
+  let prev = page > 1 ? page - 1 : 1;
+  let next = page < pages ? page + 1 : pages;
+  let items = data.Get.Document || [];
+  for (let i = 0; i < items.length; i++) {
+    let item = items[i];
+    item.id = item._additional.id;
+    item.lastUpdateTimeUnix = item._additional.lastUpdateTimeUnix;
+    item.distance = item._additional.distance;
+    delete item._additional;
+  }
+
+  return {
+    data: items,
+    next: next,
+    page: parseInt(page),
+    pagecnt: pages,
+    prev: prev,
+    total: total,
+  };
+}
+
 /**
  * Check if schema exists
  * yao run scripts.doc.SchemaExists
diff --git a/scripts/stat.js b/scripts/stat.js
deleted file mode 100644
index 64acdbb..0000000
--- a/scripts/stat.js
+++ /dev/null
@@ -1,94 +0,0 @@
-
-/**
- * before:data hook
- * @param {*} params
- * @returns
- */
-function BeforeData(params) {
- log.Info("[chart] before data hook: %s", JSON.stringify(params));
- return [params];
-}
-   
-/**
- * after:data hook
- * @param {*} data
- * @returns
- */
-function AfterData(data) {
- log.Info("[chart] after data hook: %s", JSON.stringify(data));
- return data;
-}
-   
-/**
- * Get Data
- * @param {*} params
- */
-function Data(params) {
- log.Info("[chart] process data query: %s", JSON.stringify(params));
- return {
-   income: [
-	 { value: 40300, date: "2022-1-1" },
-	 { value: 50800, date: "2022-2-1" },
-	 { value: 31300, date: "2022-3-1" },
-	 { value: 48800, date: "2022-4-1" },
-	 { value: 69900, date: "2022-5-1" },
-	 { value: 37800, date: "2022-6-1" },
-   ],
-   cost: [
-	 { value: 28100, date: "2022-1-1" },
-	 { value: 23000, date: "2022-2-1" },
-	 { value: 29300, date: "2022-3-1" },
-	 { value: 26700, date: "2022-4-1" },
-	 { value: 26400, date: "2022-5-1" },
-	 { value: 31200, date: "2022-6-1" },
-   ],
-   rate: [
-	 { value: 8.0, date: "2022-1-1" },
-	 { value: 7.6, date: "2022-2-1" },
-	 { value: 9.1, date: "2022-3-1" },
-	 { value: 8.4, date: "2022-4-1" },
-	 { value: 6.9, date: "2022-5-1" },
-	 { value: 9.0, date: "2022-6-1" },
-   ],
-   pet_count: 54,
-   pet_type: 8,
-   income_monthly: 68900,
-   doctor_count: 23,
-   prev_pet_count: { current: 54, prev: 45 },
-   prev_pet_type: { current: 8, prev: 13 },
-   prev_income_monthly: { current: 68900, prev: 92000 },
-   prev_doctor_count: { current: 23, prev: 27 },
-   datasource_type: [
-	 { type: "猫猫", count: 18 },
-	 { type: "狗狗", count: 6 },
-	 { type: "其他", count: 3 },
-   ],
-   datasource_status: [
-	 { status: "已查看", count: 3 },
-	 { status: "治疗中", count: 12 },
-	 { status: "已治愈", count: 9 },
-   ],
-   datasource_cost: [
-	 { name: "毛毛", stay: 3, cost: 2000 },
-	 { name: "阿布", stay: 6, cost: 4200 },
-	 { name: "咪咪", stay: 7, cost: 6000 },
-	 { name: "狗蛋", stay: 1, cost: 1000 },
-   ],
- };
-}
-
-/**
- * Compute out
- * @param {*} field
- * @param {*} value
- * @param {*} data
- * @returns
- */
-function Income(field, value, data) {
- log.Info(
-   "[chart] Income Compute: %s",
-   JSON.stringify({ field: field, value: value, data: data })
- );
- return value;
-}   
-	
\ No newline at end of file
diff --git a/scripts/vector.js b/scripts/vector.js
index c606207..03e95a0 100644
--- a/scripts/vector.js
+++ b/scripts/vector.js
@@ -4,31 +4,17 @@
  */
 
 const MaxTokens = 1536;
-const distance = 0.2;
-const distancePrompts = 2;
-const pageSize = 9;
 
 /**
- * Query content from the vector database
+ * Match content from the vector database
+ * yao run scripts.vector.Match '::{"pathname":"/x/Table"}' '::[{"role":"user", "content":"Yao 是什么"}]'
+ *
  * @param {*} context
  * @param {*} messages
  * @returns
  */
 function Match(context, messages) {
-  console.log(context, messages);
-  return [
-    {
-      role: "system",
-      content: `{"name":"test.pdf", "url":"https://www.google.com"}`,
-    },
-    {
-      role: "system",
-      content: `
-      - The above content is my knowledge base.
-      - Please prioritize answering user questions based on my knowledge base provided to you.
-     `,
-    },
-  ];
+  return match(context, messages, 2048);
 }
 
 /**
@@ -121,12 +107,12 @@ function Save(payload) {
   });
 
   // debug
-  console.log(pages);
+  // console.log(pages);
   return { code: 200, message: "ok" };
 }
 
 /**
- * Validate the token size
+ * Reduce the content size
  * @param {*} content
  */
 function Reduce(content) {
@@ -164,595 +150,75 @@ function ReadFile(file) {
 }
 
 /**
- * the schema of the vector database
- */
-const DocumentSchema = {
-  class: "Document",
-  description: "Used to store documents",
-  vectorizer: "text2vec-openai",
-  moduleConfig: {
-    "text2vec-openai": { model: "ada", modelVersion: "002", type: "text" },
-  },
-  properties: [
-    {
-      name: "type",
-      dataType: ["string"],
-      description:
-        "The type of the document (e.g. note, ppt, doc, xls, pdf, url, etc.)",
-      moduleConfig: {
-        "text2vec-openai": { skip: false, vectorizePropertyName: false },
-      },
-    },
-    {
-      name: "path",
-      dataType: ["string"],
-      description: "the file path of the document",
-      moduleConfig: {
-        "text2vec-openai": { skip: true, vectorizePropertyName: false },
-      },
-    },
-    {
-      name: "user",
-      dataType: ["string"],
-      description: "the user of the document",
-      moduleConfig: {
-        "text2vec-openai": { skip: true, vectorizePropertyName: false },
-      },
-    },
-    {
-      name: "url",
-      dataType: ["string"],
-      description: "the url of the document",
-      moduleConfig: {
-        "text2vec-openai": { skip: true, vectorizePropertyName: false },
-      },
-    },
-    {
-      name: "summary",
-      dataType: ["string"],
-      description: "The summary of the document",
-      moduleConfig: {
-        "text2vec-openai": { skip: false, vectorizePropertyName: false },
-      },
-    },
-    {
-      name: "content",
-      dataType: ["text"],
-      description: "The content of the document",
-      moduleConfig: {
-        "text2vec-openai": { skip: false, vectorizePropertyName: false },
-      },
-    },
-  ],
-};
-
-/**
- * Create a schema (run when the application setup)
- * yao run scripts.vector.SchemaCreate
- */
-function SchemaCreate() {
-  let cfg = setting();
-  let url = `${cfg.host}/v1/schema`;
-  post(url, DocumentSchema, cfg.key);
-  return "Document";
-}
-
-/**
- * Create a schema (run when the application setup)
- * yao run scripts.vector.SchemaDelete
- */
-function SchemaDelete() {
-  let cfg = setting();
-  let url = `${cfg.host}/v1/schema/Document`;
-  let response = http.Delete(url);
-  if (response.code != 200) {
-    let errors = response.data.error || response.data;
-    let message = errors.length > 0 ? errors[0].message : "unknown";
-    throw new Exception(message, response.code || 500);
-  }
-
-  return true;
-}
-
-/**
- * Create a schema (run when the application setup)
- * yao run scripts.vector.SchemaReset
- */
-function SchemaReset() {
-  SchemaDelete();
-  return SchemaCreate();
-}
-
-/**
- * SchemaGet
- * yao run scripts.vector.SchemaGet
- * @returns
- */
-function SchemaGet() {
-  let cfg = setting();
-  let url = `${cfg.host}/v1/schema`;
-  let data = get(url, {}, cfg.key);
-  if (data.classes.length < 1) {
-    throw new Exception("Document not found", 404);
-  }
-  return data.classes[0];
-}
-
-/**
- * Make a test
- * yao run scripts.vector.Test
- */
-function Test() {
-  console.log("请稍等,这将花费一些时间...");
-  let text = testContent();
-  let contents = [];
-
-  try {
-    contents = JSON.parse(text);
-  } catch (err) {
-    console.log(err, text);
-  }
-
-  let ids = [];
-  contents.forEach((object) => {
-    let id = Insert(object);
-    ids.push(id);
-  });
-  return ids;
-}
-
-/**
- * Insert Data
- *
- * yao run scripts.vector.Insert '::{"content": "这是一直测试文档，你需要从这里开始。"}'
- *
- * @param {*} data
- */
-function Insert(data) {
-  data = data || {};
-  if (!data.content) {
-    throw new Exception("content is required", 400);
-  }
-
-  let cfg = setting();
-  let url = `${cfg.host}/v1/objects?consistency_level=ALL`;
-
-  let properties = {};
-  properties.type = data.type || "note";
-  properties.path = data.path || "";
-  properties.user = data.user || "__public";
-  properties.url = data.url || "";
-  properties.content = data.content; // required
-  properties.summary = data.summary || getSummary(data.content);
-  let res = post(url, { class: "Document", properties: properties }, cfg.key);
-  return res.id;
-}
-
-/**
- * Get Objects
- * yao run scripts.vector.Objects
- */
-function Objects() {
-  let cfg = setting();
-  let url = `${cfg.host}/v1/objects`;
-  return get(url, {}, cfg.key);
-}
-
-/**
- * Query Data
- * yao run scripts.vector.Query 帮我写一份心血管健康研究的报告 张三
- * yao run scripts.vector.Query 帮我写一份心血管健康研究的报告
- * @param {*} input
- * @param {*} user
+ * match the content
+ * @param {*} context
+ * @param {*} messages
  */
-function Query(input, user) {
-  let vector = getVector(input);
-  let cfg = setting();
-  let url = `${cfg.host}/v1/graphql`;
-
-  let where = `{ 
-    operator: Or,
-    operands: {
-      path: ["user"],
-      operator: Equal,
-      valueString: "__public"
-    }
-  }`;
-
-  if (user) {
-    where = `{ 
-      operator: Or,
-      operands: [
-        {
-          path: ["user"],
-          operator: Equal,
-          valueString: "${user}"
-        },{
-          path: ["user"],
-          operator: Equal,
-          valueString: "__public"
-        }
-      ]
-    }`;
-  }
-
-  let payload = {
-    query: `{
-      Get {
-        Document(
-          limit: 10
-          nearVector: {
-            vector: ${vector}
-            distance: ${distancePrompts}
-          }
-          where: ${where}
-        ) 
-        {
-          user
-          path
-          type
-          url
-          summary
-          content
-          _additional{
-            id
-            distance
-            lastUpdateTimeUnix
-          }
-        }
-      }
-    }`,
-  };
-
-  let response = post(url, payload, cfg.key);
-  let data = response.data || { Get: { Document: [] } };
-  let items = data.Get.Document || [];
-  for (let i = 0; i < items.length; i++) {
-    let item = items[i];
-    item.id = item._additional.id;
-    item.lastUpdateTimeUnix = item._additional.lastUpdateTimeUnix;
-    item.distance = item._additional.distance;
-    delete item._additional;
-  }
-  return items;
-}
+function match(context, messages, maxTokenSize) {
+  // =============================================================================
+  // You can add your own code here
+  // Change the code to match your own knowledge base
+  // ==============================================================================
 
-/**
- *
- * Search Data
- * yao run scripts.vector.Search 帮我写一份心血管健康研究的报告 1 张三
- * yao run scripts.vector.Search 帮我写一份心血管健康研究的报告
- * @param {*} input
- * @param {*} page
- * @param {*} user
- * @returns
- */
-function Search(input, page, user) {
-  page = page ? parseInt(page) : 1;
-  let offset = page ? (page - 1) * pageSize : 0;
-  let vector = getVector(input);
-  let cfg = setting();
-  let url = `${cfg.host}/v1/graphql`;
-  if (!user) {
-    let info = Process("session.Get", "user") || {};
-    user = info.id;
+  messages = messages || [];
+  if (messages.length == 0) {
+    throw new Exception("messages is empty", 400);
   }
 
-  let where = `{ 
-    operator: Or,
-    operands: {
-      path: ["user"],
-      operator: Equal,
-      valueString: "__public"
-    }
-  }`;
-
-  if (user) {
-    where = `{ 
-      operator: Or,
-      operands: [
-        {
-          path: ["user"],
-          operator: Equal,
-          valueString: "${user}"
-        },{
-          path: ["user"],
-          operator: Equal,
-          valueString: "__public"
-        }
-      ]
-    }`;
+  const input = messages[messages.length - 1].content || "";
+  if (input == "") {
+    throw new Exception("input is empty", 400);
   }
 
-  let payload = {
-    query: `{
-      Aggregate {
-        Document (
-          nearVector: {
-            vector: ${vector}
-            distance: ${distance}
-          }
-          where: ${where}
-        )
-        {
-          meta {
-            count
-          }
-        }
-      }
-      Get {
-        Document(
-          limit: ${pageSize}
-          offset: ${offset}
-          nearVector: {
-            vector: ${vector}
-            distance: ${distance}
-          }
-          where: ${where}
-        ) 
-        {
-          user
-          path
-          type
-          url
-          summary
-          content
-          _additional{
-            id
-            lastUpdateTimeUnix,
-            distance
-          }
-        }
-      }
-    }`,
-  };
-
-  response = post(url, payload, cfg.key);
-  data = response.data || {
-    Get: { Document: [] },
-    Aggregate: { Document: [{ meta: { count: 0 } }] },
-  };
-
-  let total = data.Aggregate.Document[0].meta.count;
-  let pages = Math.ceil(total / pageSize);
-  let prev = page > 1 ? page - 1 : 1;
-  let next = page < pages ? page + 1 : pages;
-  let items = data.Get.Document || [];
-  for (let i = 0; i < items.length; i++) {
-    let item = items[i];
-    item.id = item._additional.id;
-    item.lastUpdateTimeUnix = item._additional.lastUpdateTimeUnix;
-    item.distance = item._additional.distance;
-    delete item._additional;
+  const payload = { input: input, distance: 1.9 };
+  const resp = Process("scripts.doc.Query", payload, 1, 20);
+  if (resp && resp.code && resp.message) {
+    throw new Exception(resp.message, resp.code);
   }
 
-  return {
-    items: items,
-    total: total,
-    prev: prev,
-    next: next,
-    curr: page,
-    pages: pages,
-  };
+  const docs = resp.data || [];
+  return ReduceMessage(messages, docs, maxTokenSize);
 }
 
-function Find(id) {
-  let cfg = setting();
-  let url = `${cfg.host}/v1/objects/Document/${id}`;
-  let response = get(url, { consistency_level: "ONE" }, cfg.key);
-  response = response || {};
-  response.properties = response.properties || {};
-  for (let key in response.properties) {
-    response[key] = response.properties[key];
-  }
-  delete response.properties;
-  return response;
-}
-
-// === utils =================================
-
-function getVector(input, user) {
-  let response = Process(
-    "openai.Embeddings",
-    "openai.text-embedding-ada-002",
-    input,
-    user
-  );
-
-  let data = response.data || [];
-  let embedding = data.length > 0 ? data[0].embedding : [];
-  return JSON.stringify(embedding);
-}
+function ReduceMessage(messages, docs, maxTokenSize) {
+  // =============================================================================
+  // You can add your own code here
+  // Change the code to match your own knowledge base
+  // ==============================================================================
 
-function getSummary(content) {
-  let response = Process("openai.chat.Completions", "openai.gpt-3_5-turbo", [
+  maxTokenSize = maxTokenSize == undefined ? MaxTokens : maxTokenSize;
+  newMessages = [
     {
       role: "system",
       content: `
-      你只能回复200字的内容摘要。
-      不要解释你的答案，也不要使用标点符号。
-    `,
+      - The above content is my knowledge base.
+      - The field "content" is the content of the document.
+      - The field "summary" is the summary of the document.
+      - The field "name" is the title of the document.
+      - The field "path" is the file path of the document.
+      - The field "type" is the type of the document.
+      - Please prioritize answering user questions based on my knowledge base provided to you.
+     `,
     },
-    { role: "user", content: content },
-  ]);
-
-  let choices = response.choices || [];
-  if (choices.length < 1) {
-    throw new Exception("answer error", 400);
-  }
-
-  let message = choices[0].message || {};
-  return message.content;
-}
+  ];
 
-function makeRequest(question, user, sid) {
-  sid = sid || Process("utils.str.UUID");
-  let history = getHistory(sid); // get the conversation history
-  let docs = getDocs(question, history, user); // query the knowledge base
-  let summaries = getSummaries(docs); // get the summaries of the knowledge base
-
-  let messages = [];
-  let size = 0;
-
-  while (history.messages.length >= 0) {
-    messages = [
-      {
-        role: "system",
-        content: `
-    - The above content is my knowledge base.
-    - Please prioritize answering user questions based on my knowledge base provided to you.
-    `,
-      },
-      ...history.messages,
-      { role: "user", content: question },
-    ];
-
-    size = Process("scripts.openai.TokenSize", JSON.stringify(messages));
-    if (size < MaxTokens - 1000) {
+  messageText = JSON.stringify(messages);
+  let tokenSize = 0;
+  while (tokenSize < maxTokenSize) {
+    const doc = docs.shift();
+    if (!doc) {
       break;
     }
-
-    history.messages.shift();
-    history.messages.shift();
-  }
-
-  // add the documents to the messages
-  if (docs.length > 0) {
-    messages = [
-      { role: "system", content: JSON.stringify(docs[0]) },
-      ...messages,
-    ];
-
-    size = Process("scripts.openai.TokenSize", JSON.stringify(messages));
+    newMessages.unshift({ role: "system", content: JSON.stringify(doc) });
+    const text = JSON.stringify(newMessages) + messageText;
+    tokenSize = Process("openai.Tiktoken", "gpt-3.5-turbo", text);
   }
 
-  // add the summary to the messages
-  if (size < MaxTokens && summaries.length > 0) {
-    messages = [
-      { role: "system", content: JSON.stringify(summaries) },
-      ...messages,
-    ];
+  console.log("--- Vector Query------", messages);
 
-    size = Process("scripts.openai.TokenSize", JSON.stringify(messages));
+  if (newMessages.length > 1) {
+    console.log("--- Vector Match ---", newMessages);
   }
 
-  // add more documents to the messages
-  if (size < MaxTokens && docs.length > 1) {
-    for (let i = 1; i < docs.length; i++) {
-      messages = [
-        { role: "system", content: JSON.stringify(docs[i]) },
-        ...messages,
-      ];
-
-      size = Process("scripts.openai.TokenSize", JSON.stringify(messages));
-      if (size >= MaxTokens) {
-        break;
-      }
-    }
-  }
-
-  return messages;
-}
-
-/**
- * Generate test data
- * yao run scripts.vector.testContent
- */
-function testContent() {
-  let response = Process("openai.chat.Completions", "openai.gpt-3_5-turbo", [
-    { role: "system", content: JSON.stringify(DocumentSchema.properties) },
-    {
-      role: "system",
-      content: `
-      - Generate a set of data according to the data type given to your data structure.
-      - You can only respond with: [{"<properties.name>":"<your generated data>", ...}...]"
-      - The type property is required, and the value can only be: "note", "ppt", "doc", "xls", "pdf", "url"
-      - If the type is url, the url property is required, otherwise, the path property is required.
-      - The property value should be Chinese generated according to the data type.
-      - The content property is required.
-      - The summary property value should be the summary of content property.
-      - all properties are required, but some properties can be empty.
-      - Do not explain your answer, and do not use punctuation.
-      `,
-    },
-    {
-      role: "user",
-      content: `Generate 5 items, You must only respond JSON Object.`,
-    },
-  ]);
-
-  let choices = response.choices || [];
-  if (choices.length < 1) {
-    throw new Exception("answer error", 400);
-  }
-
-  let message = choices[0].message || {};
-  return message.content;
-}
-
-/**
- * Post data
- * @param {*} url
- * @param {*} payload
- * @param {*} key
- * @returns
- */
-function get(url, query, key) {
-  let response = http.Get(url, query, null, null, {
-    "X-OpenAI-Api-Key": key,
-  });
-
-  if (response.code == 404) {
-    throw new Exception(`not found`, 404);
-  }
-
-  if (response.code != 200) {
-    if (response.data && response.data.message && response.data.code) {
-      throw new Exception(
-        response.data.message.split(":")[0],
-        response.data.code
-      );
-    }
-
-    let errors = response.data.error || response.data;
-    let message = errors.length > 0 ? errors[0].message : "unknown";
-    throw new Exception(message, response.code || 500);
-  }
-
-  return response.data;
-}
-
-/**
- * Post data
- * @param {*} url
- * @param {*} payload
- * @param {*} key
- * @returns
- */
-function post(url, payload, key) {
-  let response = http.Post(url, payload, null, null, {
-    "X-OpenAI-Api-Key": key,
-  });
-
-  if (response.code != 200) {
-    let errors = response.data.error || response.data;
-    let message = errors.length > 0 ? errors[0].message : "unknown";
-    throw new Exception(message, response.code || 500);
-  }
-
-  return response.data;
-}
-
-/**
- * Get Weaviate setting
- * @returns {Map}
- */
-function setting() {
-  let vars = Process("utils.env.GetMany", "WEAVIATE_HOST", "OPENAI_KEY");
-  return {
-    key: vars["OPENAI_KEY"],
-    host: vars["WEAVIATE_HOST"]
-      ? vars["WEAVIATE_HOST"]
-      : "http://127.0.0.1:5080",
-  };
+  return newMessages.length > 1 ? newMessages : [];
 }