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TestSpace / scribe_python_client /mcp_app /responseAPi.py

Ethanporath

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2568dca over 1 year ago

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from openai import OpenAI
from dotenv import load_dotenv
from pathlib import Path
import json

readPath = Path(__file__).parent / "toolsDescriptions/tool_docs.json"
load_dotenv()

def main(): 
    client = OpenAI()

    with open(readPath, "r") as f:
        tool_description = json.load(f)
    instructions = "Tool usage guidance:\n" + json.dumps(tool_description, indent=2)


    response = client.responses.create(
        model= "gpt-4o",
        tools= [{
                "type": "mcp",
                "server_label": "ScriScribeMCPHuggingFacebeMCP",
                "server_url": "https://eporath-scribe-mcp.hf.space/mcp",
                "require_approval": "never",
            }],
        input = "Query the vulnerabilities table for the top 5 risky CVEs - KEV vulnerabilities and vulnerabilities with highest EPSS scores."
        #+ "Take each risky CVES from the first query and then Query the vulnerabilities table of each of them to get a list of affected products."
        #+ "Create a report summarizing the findings."
        #+ "Query the lineage check if these products have assets of type pod; in that case these products are in production and are more risky."

        #instructions = instructions
    )
    print(response.output_text)


if __name__ == "__main__":
    main()

	from openai import OpenAI
	from dotenv import load_dotenv
	from pathlib import Path
	import json

	readPath = Path(__file__).parent / "toolsDescriptions/tool_docs.json"
	load_dotenv()

	def main():
	client = OpenAI()

	with open(readPath, "r") as f:
	tool_description = json.load(f)
	instructions = "Tool usage guidance:\n" + json.dumps(tool_description, indent=2)


	response = client.responses.create(
	model= "gpt-4o",
	tools= [{
	"type": "mcp",
	"server_label": "ScriScribeMCPHuggingFacebeMCP",
	"server_url": "https://eporath-scribe-mcp.hf.space/mcp",
	"require_approval": "never",
	}],
	input = "Query the vulnerabilities table for the top 5 risky CVEs - KEV vulnerabilities and vulnerabilities with highest EPSS scores."
	#+ "Take each risky CVES from the first query and then Query the vulnerabilities table of each of them to get a list of affected products."
	#+ "Create a report summarizing the findings."
	#+ "Query the lineage check if these products have assets of type pod; in that case these products are in production and are more risky."

	#instructions = instructions
	)
	print(response.output_text)


	if __name__ == "__main__":
	main()