106 lines
3.9 KiB
Markdown
106 lines
3.9 KiB
Markdown
<div align="center">
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<h1>ChatMock</h1>
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<p><b>OpenAI & Ollama compatible API powered by your ChatGPT plan.</b></p>
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<p>Use your ChatGPT Plus/Pro account to call OpenAI models from code or alternate chat UIs.</p>
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<br>
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</div>
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## What It Does
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ChatMock runs a local server that creates an OpenAI/Ollama compatible API, and requests are then fulfilled using your authenticated ChatGPT login with the oauth client of Codex, OpenAI's coding CLI tool. This allows you to use GPT-5 and other models right through your OpenAI account, without requiring an api key.
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This does require a paid ChatGPT account.
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## Quickstart
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*If you use MacOS, you can currently try out the GUI application in the Github releases and disregard the following instructions*
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Clone or download this repository, then cd into the project directory. Then follow the instrunctions listed below.
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1. Sign in with your ChatGPT account and follow the prompts
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```bash
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python chatmock.py login
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```
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You can make sure this worked by running `python chatmock.py info`
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2. After the login completes successfully, you can just simply start the local server
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```bash
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python chatmock.py serve
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```
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Then, you can simply use the address and port as the baseURL as you require (http://127.0.0.1:8000 by default)
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**Reminder:** When setting a baseURL, make you sure you include /v1/ at the end of the URL if you're using this as a OpenAI compatible endpoint (e.g http://127.0.0.1:8000/v1)
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# Examples
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### Python
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```python
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from openai import OpenAI
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client = OpenAI(
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base_url="http://127.0.0.1:8000/v1",
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api_key="key" # ignored
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)
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resp = client.chat.completions.create(
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model="gpt-5",
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messages=[{"role": "user", "content": "hello world"}]
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)
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print(resp.choices[0].message.content)
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```
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### curl
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```bash
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curl http://127.0.0.1:8000/v1/chat/completions \
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-H "Authorization: Bearer key" \
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-H "Content-Type: application/json" \
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-d '{
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"model": "gpt-5",
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"messages": [{"role":"user","content":"hello world"}]
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}'
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```
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# What's supported
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- Tool calling
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- Vision/Image understanding
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- Thinking summaries (through thinking tags)
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## Notes & Limits
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- Requires an active, paid ChatGPT account.
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- Expect lower rate limits than what you may recieve in the ChatGPT app.
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- Instrunctions in the system prompt (prompt.md) cannot be modified
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- Use responsibly and at your own risk. This project is not affiliated with OpenAI, and is a educational exercise.
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# Supported models
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- `gpt-5`
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- `codex-mini`
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# Customisation / Configuration
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### Thinking effort
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- `--reasoning-effort` (choice of low,medium,high)<br>
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GPT-5 has a configurable amount of "effort" it can put into thinking, which may cause it to take more time for a response to return, but may overall give a smarter answer. Applying this parameter after `serve` forces the server to use this reasoning effort by default, unless overrided by the API request with a different effort set. The default reasoning effort without setting this parameter is `medium`.
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### Thinking summaries
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- `--reasoning-summary` (choice of auto,concise,detailed,none)<br>
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Models like GPT-5 do not return raw thinking content, but instead return thinking summaries. These can also be customised by you.
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## Notes
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If you wish to have the fastest responses, I'd recommend setting `--reasoning-effort` to low, and `--reasoning-summary` to none.
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All parameters and choices can be seen by sending `python chatmock.py serve --h`<br>
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The context size of this route is also larger than what you get access to in the regular ChatGPT app.
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**When the model returns a thinking summary, the model will send back thinking tags to make it compatible with chat apps. If you don't like this behavior, you can instead set `--reasoning-compat` to legacy, and reasoning will be set in the reasoning tag instead of being returned in the actual response text.**
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# TODO
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- ~~Implement Ollama support~~ ✅
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- Explore to see if we can make more model settings accessible
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- Implement analytics (token counting, etc, to track usage)
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