diff --git a/.gitignore b/.gitignore
index 41dbbf2d8..4501eb521 100644
--- a/.gitignore
+++ b/.gitignore
@@ -8,6 +8,8 @@ data/
# Workspace
workspace/
+config/
+
### Python ###
# Byte-compiled / optimized / DLL files
__pycache__/
diff --git a/.vscode/settings.json b/.vscode/settings.json
index d3aa302bb..511290989 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -16,5 +16,6 @@
},
"files.insertFinalNewline": true,
"files.trimTrailingWhitespace": true,
- "editor.formatOnSave": true
+ "editor.formatOnSave": true,
+ "liveServer.settings.port": 5501
}
diff --git a/app/agent/data_analysis.py b/app/agent/data_analysis.py
index 79b9c2967..f564f3ecd 100644
--- a/app/agent/data_analysis.py
+++ b/app/agent/data_analysis.py
@@ -4,9 +4,23 @@
from app.config import config
from app.prompt.visualization import NEXT_STEP_PROMPT, SYSTEM_PROMPT
from app.tool import Terminate, ToolCollection
+from app.tool.chart_visualization.python_execute import NormalPythonExecute
+# from app.tool.chart_visualization.chart_prepare import VisualizationPrepare
+# from app.tool.chart_visualization.data_visualization import DataVisualization
+# from app.tool.chart_visualization.initial_report_generation import GenerateInitialReport
+# from app.tool.chart_visualization.final_report_generation import GenerateFinalReport
+# from app.tool.chart_visualization.search_report_template import SearchReportTemplate
+# from app.tool.chart_visualization.report_template_generation import ReportTemplateGeneration
+# from app.tool.chart_visualization.initial_information_collection import InitialInformationCollection
from app.tool.chart_visualization.chart_prepare import VisualizationPrepare
+from app.tool.chart_visualization.select_insights import SelectInsights
+from app.tool.chart_visualization.add_insights import AddInsights
from app.tool.chart_visualization.data_visualization import DataVisualization
-from app.tool.chart_visualization.python_execute import NormalPythonExecute
+from app.tool.chart_visualization.v2.search_html_library import SearchHtmlLibrary
+from app.tool.chart_visualization.v2.initial_report_generation import GenerateInitialReport
+from app.tool.chart_visualization.v2.report_template_generation import ReportTemplateGeneration
+from app.tool.chart_visualization.v2.final_report_generation import GenerateFinalReport
+from app.tool.chart_visualization.v2.report_beautify import ReportBeautify
class DataAnalysis(ToolCallAgent):
@@ -18,7 +32,34 @@ class DataAnalysis(ToolCallAgent):
"""
name: str = "Data_Analysis"
- description: str = "An analytical agent that utilizes python and data visualization tools to solve diverse data analysis tasks"
+ description: str = """
+ A data science agent specializing in Python-based analytics and advanced visualization techniques
+ for solving complex data analysis challenges.
+
+ Standard Report Generation Workflow:
+ 1. Template Preparation:
+ - SearchHtmlLibrary: Identify suitable visualization templates
+ - ReportTemplateGeneration & GenerateInitialReport: Create initial report structure
+
+ 2. Visualization Pipeline:
+ - VisualizationPrepare: Configure data for visualization
+ - DataVisualization: Generate interactive charts and graphs
+
+ 3. Insight Enhancement:
+ - SelectInsights: Extract key findings from visualizations
+ - AddInsights: Annotate charts with analytical insights
+
+ 4. Report Finalization:
+ - GenerateFinalReport: Replace the placeholders with charts
+ - ReportBeautify: Apply professional styling and formatting
+
+ Operational Protocol:
+ - First determine optimal visualization types based on dataset characteristics
+ - Utilize HTML template library to establish report framework
+ - Execute visualization pipeline to create data representations
+ - Enhance each chart with key insights you selected
+ - Assemble final report by embedding enriched visualizations
+ """
system_prompt: str = SYSTEM_PROMPT.format(directory=config.workspace_root)
next_step_prompt: str = NEXT_STEP_PROMPT
@@ -30,8 +71,15 @@ class DataAnalysis(ToolCallAgent):
available_tools: ToolCollection = Field(
default_factory=lambda: ToolCollection(
NormalPythonExecute(),
+ SearchHtmlLibrary(),
+ ReportTemplateGeneration(),
+ GenerateInitialReport(),
+ GenerateFinalReport(),
+ ReportBeautify(),
+ AddInsights(),
VisualizationPrepare(),
DataVisualization(),
+ SelectInsights(),
Terminate(),
)
)
diff --git a/app/prompt/visualization.py b/app/prompt/visualization.py
index 8e4fecc53..e5f4bdac6 100644
--- a/app/prompt/visualization.py
+++ b/app/prompt/visualization.py
@@ -1,7 +1,33 @@
SYSTEM_PROMPT = """You are an AI agent designed to data analysis / visualization task. You have various tools at your disposal that you can call upon to efficiently complete complex requests.
# Note:
1. The workspace directory is: {directory}; Read / write file in workspace
-2. Generate analysis conclusion report in the end"""
+2. Generate analysis conclusion report in the end
+
+Standard Report Generation Workflow:
+1. Template Preparation:
+ - SearchHtmlLibrary: Identify suitable visualization templates
+ - ReportTemplateGeneration & GenerateInitialReport: Create initial report structure
+
+2. Visualization Pipeline:
+ - VisualizationPrepare: Configure data for visualization
+ - DataVisualization: Generate interactive charts and graphs
+
+3. Insight Enhancement:
+ - SelectInsights: Extract key findings from visualizations
+ - AddInsights: Annotate charts with analytical insights
+
+4. Report Finalization:
+ - GenerateFinalReport: Replace the placeholders with charts
+ - ReportBeautify: Apply professional styling and formatting
+
+Operational Protocol:
+- First determine optimal visualization types based on dataset characteristics
+- Utilize HTML template library to establish report framework
+- Execute visualization pipeline to create data representations
+- Enhance each chart with key insights you selected
+- Assemble final report by embedding enriched visualizations
+
+"""
NEXT_STEP_PROMPT = """Based on user needs, break down the problem and use different tools step by step to solve it.
# Note
diff --git a/app/tool/chart_visualization/__init__.py b/app/tool/chart_visualization/__init__.py
index ea7d51a39..eda63d1ba 100644
--- a/app/tool/chart_visualization/__init__.py
+++ b/app/tool/chart_visualization/__init__.py
@@ -1,6 +1,3 @@
from app.tool.chart_visualization.chart_prepare import VisualizationPrepare
from app.tool.chart_visualization.data_visualization import DataVisualization
from app.tool.chart_visualization.python_execute import NormalPythonExecute
-
-
-__all__ = ["DataVisualization", "VisualizationPrepare", "NormalPythonExecute"]
diff --git a/app/tool/chart_visualization/add_insights.py b/app/tool/chart_visualization/add_insights.py
new file mode 100644
index 000000000..d61b3642e
--- /dev/null
+++ b/app/tool/chart_visualization/add_insights.py
@@ -0,0 +1,228 @@
+import sys
+import asyncio
+import json
+import os
+print(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))))
+sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))))
+
+from typing import Any, Hashable
+
+import pandas as pd
+from pydantic import Field, model_validator
+
+from app.config import config
+from app.llm import LLM
+from app.logger import logger
+from app.tool.base import BaseTool
+
+
+class AddInsights(BaseTool):
+ name: str = "add_insights"
+ description: str = (
+ "Enhances charts by adding insights markers and annotations "
+ "using JSON data generated by the insights_selection tool. "
+ "This creates the final annotated visualization output."
+ )
+
+ parameters: dict = {
+ "type": "object",
+ "properties": {
+ "json_path": {
+ "type": "string",
+ "description": """Path to the JSON file generated by insights_selection tool.
+Contains chart insights data in format:
+{
+ "chartPath": string,
+ "insights_id": number[]
+}""",
+ },
+ "output_type": {
+ "type": "string",
+ "description": "Visualization output format selection",
+ "default": "html",
+ "enum": [
+ "png", # Static image format
+ "html" # Interactive web format (recommended)
+ ],
+ },
+ },
+ "required": ["json_path"],
+ }
+ llm: LLM = Field(default_factory=LLM, description="Language model instance")
+
+ @model_validator(mode="after")
+ def initialize_llm(self):
+ """Initialize llm with default settings if not provided."""
+ if self.llm is None or not isinstance(self.llm, LLM):
+ self.llm = LLM(config_name=self.name.lower())
+ return self
+
+ def load_chart_with_css(self, chart_path):
+ # 读取 HTML 文件
+ with open(chart_path, 'r', encoding='utf-8') as f:
+ html_content = f.read()
+ html_content = html_content.replace('`', "'")
+
+ # 在 里插入 CSS
+ css = """
+
+ """
+
+ # 如果原文件没有 ，直接插入到最前面
+ if "" in html_content:
+ html_content = html_content.replace("", "" + css)
+ else:
+ html_content = css + html_content
+
+ with open(chart_path, 'w', encoding='utf-8') as f:
+ f.write(html_content)
+
+ def get_file_path(
+ self,
+ json_info: list[dict[str, str]],
+ path_str: str,
+ directory: str = None,
+ ) -> list[str]:
+ res = []
+ for item in json_info:
+ if os.path.exists(item[path_str]):
+ res.append(item[path_str])
+ elif os.path.exists(
+ os.path.join(f"{directory or config.workspace_root}", item[path_str])
+ ):
+ res.append(
+ os.path.join(
+ f"{directory or config.workspace_root}", item[path_str]
+ )
+ )
+ else:
+ raise Exception(f"No such file or directory: {item[path_str]}")
+ return res
+
+ async def add_insights(
+ self, json_info: list[dict[str, str]], output_type: str
+ ) -> str:
+ data_list = []
+ chart_file_path = self.get_file_path(
+ json_info, "chartPath", os.path.join(config.workspace_root, "visualization")
+ )
+ for index, item in enumerate(json_info):
+ if "insights_id" in item:
+ data_list.append(
+ {
+ "file_name": os.path.basename(chart_file_path[index]).replace(
+ f".{output_type}", ""
+ ),
+ "insights_id": item["insights_id"],
+ }
+ )
+ tasks = [
+ self.invoke_vmind(
+ insights_id=item["insights_id"],
+ file_name=item["file_name"],
+ output_type=output_type,
+ task_type="insight",
+ )
+ for item in data_list
+ ]
+ results = await asyncio.gather(*tasks)
+ error_list = []
+ success_list = []
+ for index, result in enumerate(results):
+ chart_path = chart_file_path[index]
+ if "error" in result and "chart_path" not in result:
+ error_list.append(f"Error in {chart_path}: {result['error']}")
+ else:
+ success_list.append(chart_path)
+ self.load_chart_with_css(chart_path)
+
+ success_template = (
+ f"# Charts Update with Insights\n{','.join(success_list)}"
+ if len(success_list) > 0
+ else ""
+ )
+ if len(error_list) > 0:
+ return {
+ "observation": f"# Error in chart insights:{'\n'.join(error_list)}\n{success_template}",
+ "success": False,
+ }
+ else:
+ return {"observation": f"{success_template}"}
+
+ async def execute(
+ self,
+ json_path: str,
+ output_type: str | None = "html",
+ tool_type: str | None = "visualization",
+ language: str | None = "en",
+ ) -> str:
+ try:
+ logger.info(f"📈 data_visualization with {json_path} in: {tool_type} ")
+ with open(json_path, "r", encoding="utf-8") as file:
+ json_info = json.load(file)
+ return await self.add_insights(json_info, output_type)
+ except Exception as e:
+ return {
+ "observation": f"Error: {e}",
+ "success": False,
+ }
+
+ async def invoke_vmind(
+ self,
+ file_name: str,
+ output_type: str,
+ task_type: str,
+ insights_id: list[str] = None,
+ dict_data: list[dict[Hashable, Any]] = None,
+ chart_description: str = None,
+ language: str = "en",
+ ):
+ llm_config = {
+ "base_url": self.llm.base_url,
+ "model": self.llm.model,
+ "api_key": self.llm.api_key,
+ }
+ vmind_params = {
+ "llm_config": llm_config,
+ "user_prompt": chart_description,
+ "dataset": dict_data,
+ "file_name": file_name,
+ "output_type": output_type,
+ "insights_id": insights_id,
+ "task_type": task_type,
+ "directory": str(config.workspace_root),
+ "language": language,
+ }
+
+ process = await asyncio.create_subprocess_exec(
+ "npx",
+ "ts-node",
+ "src/chartVisualize.ts",
+ stdin=asyncio.subprocess.PIPE,
+ stdout=asyncio.subprocess.PIPE,
+ stderr=asyncio.subprocess.PIPE,
+ cwd=os.path.dirname(__file__),
+ )
+ input_json = json.dumps(vmind_params, ensure_ascii=False).encode("utf-8")
+ try:
+ stdout, stderr = await process.communicate(input_json)
+ stdout_str = stdout.decode("utf-8")
+ stderr_str = stderr.decode("utf-8")
+ if process.returncode == 0:
+ return json.loads(stdout_str)
+ else:
+ return {"error": f"Node.js Error: {stderr_str}"}
+ except Exception as e:
+ return {"error": f"Subprocess Error: {str(e)}"}
+
diff --git a/app/tool/chart_visualization/chart_prepare.py b/app/tool/chart_visualization/chart_prepare.py
index 1eed35e4d..d9898d709 100644
--- a/app/tool/chart_visualization/chart_prepare.py
+++ b/app/tool/chart_visualization/chart_prepare.py
@@ -1,36 +1,36 @@
from app.tool.chart_visualization.python_execute import NormalPythonExecute
-
-
class VisualizationPrepare(NormalPythonExecute):
"""A tool for Chart Generation Preparation"""
name: str = "visualization_preparation"
- description: str = "Using Python code to generates metadata of data_visualization tool. Outputs: 1) JSON Information. 2) Cleaned CSV data files (Optional)."
+ description: str = """
+ You need some charts to replace initial report's placeholders. So you need to use this tool first to prepare metadata for data_visualization tool.
+ Using Python code to generates metadata of data_visualization tool. Outputs: 1) JSON Information. 2) Cleaned CSV data files (Optional).
+ """
parameters: dict = {
"type": "object",
"properties": {
"code_type": {
- "description": "code type, visualization: csv -> chart; insight: choose insight into chart",
+ "description": "code type, visualization: csv -> chart",
"type": "string",
- "default": "visualization",
- "enum": ["visualization", "insight"],
+ "default": "visualization"
},
"code": {
"type": "string",
"description": """Python code for data_visualization prepare.
-## Visualization Type
+
+## Visualization Type (Initial Step)
1. Data loading logic
2. Csv Data and chart description generate
-2.1 Csv data (The data you want to visulazation, cleaning / transform from origin data, saved in .csv)
-2.2 Chart description of csv data (The chart title or description should be concise and clear. Examples: 'Product sales distribution', 'Monthly revenue trend'.)
+ 2.1 Csv data (The data you want to visulazation, cleaning / transform from origin data, saved in .csv)
+ 2.2 Chart description of csv data (The chart title or description should be concise and clear. Examples: 'Product sales distribution', 'Monthly revenue trend'.)
3. Save information in json file.( format: {"csvFilePath": string, "chartTitle": string}[])
-## Insight Type
-1. Select the insights from the data_visualization results that you want to add to the chart.
-2. Save information in json file.( format: {"chartPath": string, "insights_id": number[]}[])
-# Note
-1. You can generate one or multiple csv data with different visualization needs.
-2. Make each chart data esay, clean and different.
-3. Json file saving in utf-8 with path print: print(json_path)
+
+
+# Best Practices
+1. Generate one or multiple csv data with different visualization needs based on the initial report
+2. Make each chart data simple, clean and distinct
+4. Json file saving in utf-8 with path print: print(json_path)
""",
},
},
diff --git a/app/tool/chart_visualization/data_visualization.py b/app/tool/chart_visualization/data_visualization.py
index 26dfaa985..a75b62aa0 100644
--- a/app/tool/chart_visualization/data_visualization.py
+++ b/app/tool/chart_visualization/data_visualization.py
@@ -14,12 +14,8 @@
class DataVisualization(BaseTool):
name: str = "data_visualization"
- description: str = """Visualize statistical chart or Add insights in chart with JSON info from visualization_preparation tool. You can do steps as follows:
-1. Visualize statistical chart
-2. Choose insights into chart based on step 1 (Optional)
-Outputs:
-1. Charts (png/html)
-2. Charts Insights (.md)(Optional)"""
+ description: str = """Visualize statistical chart with JSON info from visualization_preparation tool.
+Outputs: Charts (png/html)"""
parameters: dict = {
"type": "object",
"properties": {
@@ -34,10 +30,9 @@ class DataVisualization(BaseTool):
"enum": ["png", "html"],
},
"tool_type": {
- "description": "visualize chart or add insights",
+ "description": "visualize",
"type": "string",
"default": "visualization",
- "enum": ["visualization", "insight"],
},
"language": {
"description": "english(en) / chinese(zh)",
@@ -79,11 +74,43 @@ def get_file_path(
raise Exception(f"No such file or directory: {item[path_str]}")
return res
+ def load_chart_with_css(self, chart_path):
+ # 读取 HTML 文件
+ with open(chart_path, 'r', encoding='utf-8') as f:
+ html_content = f.read()
+
+ # 在 里插入 CSS
+ css = """
+
+ """
+
+ # 如果原文件没有 ，直接插入到最前面
+ if "" in html_content:
+ html_content = html_content.replace("", "" + css)
+ else:
+ html_content = css + html_content
+
+ with open(chart_path, 'w', encoding='utf-8') as f:
+ f.write(html_content)
+
def success_output_template(self, result: list[dict[str, str]]) -> str:
content = ""
if len(result) == 0:
return "Is EMPTY!"
for item in result:
+ chart_path=item['chart_path']
+ self.load_chart_with_css(chart_path)
content += f"""## {item['title']}\nChart saved in: {item['chart_path']}"""
if "insight_path" in item and item["insight_path"] and "insight_md" in item:
content += "\n" + item["insight_md"]
@@ -145,7 +172,7 @@ async def data_visualization(
else:
return {"observation": f"{self.success_output_template(success_list)}"}
- async def add_insighs(
+ async def add_insights(
self, json_info: list[dict[str, str]], output_type: str
) -> str:
data_list = []
@@ -207,7 +234,7 @@ async def execute(
if tool_type == "visualization":
return await self.data_visualization(json_info, output_type, language)
else:
- return await self.add_insighs(json_info, output_type)
+ return await self.add_insights(json_info, output_type)
except Exception as e:
return {
"observation": f"Error: {e}",
diff --git a/app/tool/chart_visualization/package-lock.json b/app/tool/chart_visualization/package-lock.json
index 19dae01ea..7365da31e 100644
--- a/app/tool/chart_visualization/package-lock.json
+++ b/app/tool/chart_visualization/package-lock.json
@@ -10,7 +10,7 @@
"license": "ISC",
"dependencies": {
"@visactor/vchart": "^1.13.7",
- "@visactor/vmind": "2.0.5",
+ "@visactor/vmind": "2.0.6-alpha.2",
"get-stdin": "^9.0.0",
"puppeteer": "^24.9.0"
},
@@ -6319,9 +6319,9 @@
}
},
"node_modules/@visactor/calculator": {
- "version": "2.0.5",
- "resolved": "https://registry.npmjs.org/@visactor/calculator/-/calculator-2.0.5.tgz",
- "integrity": "sha512-/NBDB/wBQLeQuSspDBuiEAbbyfJS/xPX6mubVsLGhfy65UwUBojAQgmX25FcRJnUsRXooK5heshni19DBBf8xA==",
+ "version": "2.0.6-alpha.2",
+ "resolved": "https://registry.npmjs.org/@visactor/calculator/-/calculator-2.0.6-alpha.2.tgz",
+ "integrity": "sha512-eSihYc5cTOeH3gFIW5lBBSWk1PDPDrO/dhaz3G6ZfRRx/wLNf5K1W1jCUaKeNcfcLyydB+6JH7u1k8vm2oIznw==",
"dependencies": {
"@visactor/vutils": "~0.19.3",
"node-sql-parser": "~4.17.0",
@@ -6329,13 +6329,26 @@
}
},
"node_modules/@visactor/chart-advisor": {
- "version": "2.0.5",
- "resolved": "https://registry.npmjs.org/@visactor/chart-advisor/-/chart-advisor-2.0.5.tgz",
- "integrity": "sha512-pvHceRlworB7kDSmbWXUtherLLXh5nMj0aEGuxtzKQyHmeO0sjuu9gGXBFIgscGliSZM4tmeNrFU9eBLGJ8dxw==",
+ "version": "2.0.6-alpha.2",
+ "resolved": "https://registry.npmjs.org/@visactor/chart-advisor/-/chart-advisor-2.0.6-alpha.2.tgz",
+ "integrity": "sha512-QlhM5s3o48QtUDn0VmJB6xwYwBPgUh2SfxYosGKrbmajRFUb8e6I6LDKTNOda2dQ3/e0a04+zZIiDTpViMxkCw==",
+ "license": "MIT",
"dependencies": {
"@visactor/vutils": "~0.19.3"
}
},
+ "node_modules/@visactor/generate-vchart": {
+ "version": "2.0.6-alpha.2",
+ "resolved": "https://registry.npmjs.org/@visactor/generate-vchart/-/generate-vchart-2.0.6-alpha.2.tgz",
+ "integrity": "sha512-Md62wBLtAwIZ/a04xRyCfgeFDy0sgwUiBei6vD6FoE+vgEkpp9+Vf0jpMXK1sTuxFa3nxi8GxcUsDmiNwEZJ9w==",
+ "dependencies": {
+ "@visactor/vchart-theme": "~1.12.2",
+ "@visactor/vutils": "~0.19.3",
+ "dayjs": "~1.11.10",
+ "node-sql-parser": "~4.17.0",
+ "ts-pattern": "~4.1.4"
+ }
+ },
"node_modules/@visactor/vchart": {
"version": "1.13.8",
"resolved": "https://registry.npmjs.org/@visactor/vchart/-/vchart-1.13.8.tgz",
@@ -6496,14 +6509,16 @@
}
},
"node_modules/@visactor/vmind": {
- "version": "2.0.5",
- "resolved": "https://registry.npmjs.org/@visactor/vmind/-/vmind-2.0.5.tgz",
- "integrity": "sha512-QztQaeSkdeRZYOUlB4qaBpx3/swyO3JzFH8eYvSgvptS/rf8aQDZiufAUasafDLkcME5N6RpBGkcGYIDkmt74Q==",
+ "version": "2.0.6-alpha.2",
+ "resolved": "https://registry.npmjs.org/@visactor/vmind/-/vmind-2.0.6-alpha.2.tgz",
+ "integrity": "sha512-bPuZ4U7dIxHbYnu1oSuddJc5HvRN194Yair9kYqlx4fBqNukHAqWAUEyCdir9YzyJVDvSdEJ7xqmvXecW5W3WQ==",
+ "license": "MIT",
"dependencies": {
"@stdlib/stats-base-dists-t-quantile": "0.2.1",
- "@visactor/calculator": "2.0.5",
- "@visactor/chart-advisor": "2.0.5",
- "@visactor/vchart-theme": "^1.11.2",
+ "@visactor/calculator": "2.0.6-alpha.2",
+ "@visactor/chart-advisor": "2.0.6-alpha.2",
+ "@visactor/generate-vchart": "2.0.6-alpha.2",
+ "@visactor/vchart-theme": "~1.12.2",
"@visactor/vdataset": "~0.19.3",
"@visactor/vutils": "~0.19.3",
"alasql": "~4.3.2",
diff --git a/app/tool/chart_visualization/package.json b/app/tool/chart_visualization/package.json
index 1e9189dcb..4de31476e 100644
--- a/app/tool/chart_visualization/package.json
+++ b/app/tool/chart_visualization/package.json
@@ -9,7 +9,7 @@
},
"dependencies": {
"@visactor/vchart": "^1.13.7",
- "@visactor/vmind": "2.0.5",
+ "@visactor/vmind": "2.0.6-alpha.2",
"get-stdin": "^9.0.0",
"puppeteer": "^24.9.0"
},
diff --git a/app/tool/chart_visualization/select_insights.py b/app/tool/chart_visualization/select_insights.py
new file mode 100644
index 000000000..fb56a305b
--- /dev/null
+++ b/app/tool/chart_visualization/select_insights.py
@@ -0,0 +1,54 @@
+from app.tool.chart_visualization.python_execute import NormalPythonExecute
+class SelectInsights(NormalPythonExecute):
+ name: str = "insights_selection"
+ description: str = (
+ "This tool analyzes data_visualization tool's outputs and identifies key data insights for each chart."
+ "based on their importance ranking. Insights are prioritized in three tiers:\n"
+ "1 **Critical Insights**: 'abnormal_trend', 'abnormal_band', 'turning_point', 'overall_trend'\n"
+ "2 **Important Insights**: 'outlier', 'extreme_value', 'majority_value', 'avg'\n"
+ "3 **Basic Insights**: 'min', 'max'\n\n"
+ "**!Must be called immediately after data_visualization completes!**"
+ "**!All insights_id must come from the data_visualization analysis results!**"
+
+ )
+ parameters: dict = {
+ "type": "object",
+ "properties": {
+ "code": {
+ "type": "string",
+ "description": """Python code to analyze visualized charts and extract insights.
+
+# PRIORITY REQUIREMENTS
+Insights must be selected and ranked according to these importance tiers:
+1. **First Priority**: Always include 'abnormal_trend', 'abnormal_band', 'turning_point', 'overall_trend' when present
+2. **Second Priority**: Include 'outlier', 'extreme_value', 'majority_value', 'avg' if no first-tier insights exist
+3. **Third Priority**: Fall back to 'min', 'max' only when no higher-priority insights are available
+
+# EXECUTION REQUIREMENTS
+1. **Timing**: MUST be called immediately after data_visualization completes
+2. **Dependency**: MUST use insights from data_visualization output as the only source for insights_id
+
+
+# CODE REQUIREMENTS
+Your Python code must:
+1. Analyze the data_visualization results to identify significant insights for each chart.
+2. Save the findings in JSON format:
+ ```json
+ [
+ {
+ "chartPath": "string", // Path to the generated chart
+ "insights_id": number[] // Array of key insight IDs FROM DATA_VISUALIZATION RESULTS
+ },
+ {
+ "chartPath": "string", // Path to the generated chart
+ "insights_id": number[] // Array of key insight IDs FROM DATA_VISUALIZATION RESULTS
+ },
+ ...
+ ]
+ ```
+Json file saving in utf-8 with path print: print(json_path)
+""",
+ },
+ },
+ "required": ["code"],
+ }
diff --git a/app/tool/chart_visualization/src/chartVisualize.ts b/app/tool/chart_visualization/src/chartVisualize.ts
index c5091a373..784b6cba2 100644
--- a/app/tool/chart_visualization/src/chartVisualize.ts
+++ b/app/tool/chart_visualization/src/chartVisualize.ts
@@ -1,7 +1,8 @@
import path from "path";
import fs from "fs";
import puppeteer from "puppeteer";
-import VMind, { ChartType, DataTable } from "@visactor/vmind";
+import VMind, { ChartType } from "@visactor/vmind";
+import type { DataTable } from '@visactor/generate-vchart';
import { isString } from "@visactor/vutils";
enum AlgorithmType {
@@ -63,8 +64,7 @@ function getHtmlVChart(spec: any, width?: number, height?: number) {
-