50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
import json
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import sys
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from pathlib import Path
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import requests
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root_path = Path(__file__).parent.parent.parent
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sys.path.append(str(root_path))
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from chatchat.server.utils import api_address
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api_base_url = api_address()
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kb = "samples"
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file_name = "/media/gpt4-pdf-chatbot-langchain/langchain-ChatGLM/knowledge_base/samples/content/llm/大模型技术栈-实战与应用.md"
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doc_ids = [
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"357d580f-fdf7-495c-b58b-595a398284e8",
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"c7338773-2e83-4671-b237-1ad20335b0f0",
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"6da613d1-327d-466f-8c1a-b32e6f461f47",
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]
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def test_summary_file_to_vector_store(
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api="/knowledge_base/kb_summary_api/summary_file_to_vector_store",
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):
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url = api_base_url + api
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print("\n文件摘要：")
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r = requests.post(
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url, json={"knowledge_base_name": kb, "file_name": file_name}, stream=True
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)
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for chunk in r.iter_content(None):
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data = json.loads(chunk[6:])
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assert isinstance(data, dict)
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assert data["code"] == 200
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print(data["msg"])
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def test_summary_doc_ids_to_vector_store(
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api="/knowledge_base/kb_summary_api/summary_doc_ids_to_vector_store",
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):
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url = api_base_url + api
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print("\n文件摘要：")
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r = requests.post(
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url, json={"knowledge_base_name": kb, "doc_ids": doc_ids}, stream=True
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)
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for chunk in r.iter_content(None):
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data = json.loads(chunk[6:])
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assert isinstance(data, dict)
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assert data["code"] == 200
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print(data)
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