stackexchange-...
StackExchange Q Count – A lightweight helper to quickly obtain the monthly volume of questions asked on any Stack Exchange site.
Features
- Fast execution – Uses an LLM to parse the user’s natural‑language query and return a precise count.
- Zero‑config – If you have an environment variable
LLM7_API_KEY, the package will automatically pick it up. - Extensible – Pass your own
BaseChatModelinstance (OpenAI, Anthropic, Google GenAI, etc.) to use an alternative LLM. - Easy error handling – The function returns a list of strings containing the extracted answers or throws an informative exception.
Installation
pip install stackexchange-...
Quick start
from stackexchange_... import stackexchange_...
# Simple call using the default ChatLLM7
result = stackexchange_(...user_input="How many questions were asked on Stack Overflow in the last 6 months?")
print(result)
Tip: In the examples below, replace
stackexchange_...andstackexchange_...with the real package and function names once you publish it (e.g.stackexchange_q).
Parameters
| Parameter | Type | Description |
|---|---|---|
user_input |
str |
The query to be processed. |
llm |
Optional[BaseChatModel] |
A LangChain LLM instance to use. If omitted, the default ChatLLM7 is instantiated. |
api_key |
Optional[str] |
LLM7 API key. If omitted, the package will look for LLM7_API_KEY in the environment. |
Using a Custom LLM
| LLM | Example |
|---|---|
| OpenAI | python<br>from langchain_openai import ChatOpenAI<br>from stackexchange_... import stackexchange_...<br>llm = ChatOpenAI()<br>response = stackexchange_(..., llm=llm)<br> |
| Anthropic | python<br>from langchain_anthropic import ChatAnthropic<br>from stackexchange_... import stackexchange_...<br>llm = ChatAnthropic()<br>response = stackexchange_(..., llm=llm)<br> |
| Google Generative AI | python<br>from langchain_google_genai import ChatGoogleGenerativeAI<br>from stackexchange_... import stackexchange_...<br>llm = ChatGoogleGenerativeAI()<br>response = stackexchange_(..., llm=llm)<br> |
Rate Limits and API Key
- LLM7 free tier is sufficient for most use‑cases.
- For higher limits, provide your own key:
stackexchange_(..., api_key="YOUR_KEY"). - You can also set the key via the environment variable
LLM7_API_KEY. - Obtain a free API key by registering at https://token.llm7.io/.
Author
Eugene Evstafev
Email: hi@euegne.plus
GitHub: chigwell
Issues
If you encounter any bugs or have feature requests, open an issue on GitHub:
https://github.com/chigwell/stackexchange-.../issues
License
MIT License – see the LICENSE file for details.
Metadata
Release files for stackexchange-question-analyzer 2025.12.21142930
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| stackexchange_question_analyzer-2025.12.21142930.tar.gz | 4.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| stackexchange_question_analyzer-2025.12.21142930-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.0 kB
Release files / stackexchange_question_analyzer-2025.12.21142930.tar.gz
| Download URL | stackexchange_question_analyzer-2025.12.21142930.tar.gz |
|---|---|
| Size | 4.6 kB |
| Tags | Source |
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Release files / stackexchange_question_analyzer-2025.12.21142930-py3-none-any.whl
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