wiseflow

wiseflow is an open-source information mining and intelligence aggregation tool that extracts useful information from web pages and other sources based on your focus areas. It calls large language models through the native OpenAI SDK, so you can connect wiseflow to ScitiX Model Inference. This guide uses glm-5.2 as an example. For the full model list and pricing, see Models.

Configure

Create an API Key on the API Keys page. In the project root, edit .env:

LLM_API_BASE="https://api.scitix.ai/model-api/v1"
LLM_API_KEY="<YOUR_API_KEY>"
PRIMARY_MODEL="glm-5.2"
SECONDARY_MODEL="glm-5.2"

Field	Description
`LLM_API_BASE`	ScitiX OpenAI-compatible base URL with `/v1`: `https://api.scitix.ai/model-api/v1`
`LLM_API_KEY`	Your API Key created on the API Keys page
`PRIMARY_MODEL`	Primary model ID, such as `glm-5.2`
`SECONDARY_MODEL`	Secondary model for initial filtering. It can be the same as the primary model.

Verify

wiseflow reads the configuration above in core/llms/openai_wrapper.py and calls the model through the native OpenAI SDK. After you start a task, model requests are sent to the ScitiX endpoint. You can also run a minimal check:

import asyncio
from core.llms.openai_wrapper import openai_llm

print(asyncio.run(openai_llm(
    [{"role": "user", "content": "Reply with exactly: OK"}],
    model="glm-5.2",
)))

For normal operation, run python core/run_task.py. Extracted information is written to PocketBase by default at http://127.0.0.1:8090/_/.

FAQ

Version: Use a 0.3.x release, such as tag v0.3.8. The repository’s master branch has moved to a different product, while the classic Python + PocketBase implementation is available in versioned tags.
LLM_API_BASE: Use the base URL with /v1: https://api.scitix.ai/model-api/v1. wiseflow uses the native OpenAI SDK and does not require a dedicated provider.
Model IDs: Use model IDs from the Models page.

Get Started

Models

Usage

API Guides

Tool Integrations

Configure

Verify

FAQ

​Configure

​Verify

​FAQ

Configure

Verify

FAQ