Unofficial open APIs for popular LLMs with self-hosted redirect capability
Project description
๐๏ธ LLM-API-Open (LMAO)
Unofficial open APIs for popular LLMs with self-hosted redirect capability |
---|
โ WAT
๐๏ธ LLM-API-Open (LMAO) allows for the free and universal utilization of popular Large Language Models (LLM). This is achieved using browser automation. LLM-API-Open (LMAO) launches a browser in headless mode and controls a website as if a real user were using it. This enables the use of popular LLMs that usually don't offer easy and free access to their official APIs
๐ฅ Additionally, LLM-API-Open (LMAO) is capable of creating its own API server to which any other apps can send requests. In other words, you can utilize LLM-API-Open (LMAO) both as a Python package and as an API proxy for any of your apps!
๐ง LLM-API-Open is development
Due to my studies, I don't have much time to work on the project ๐
Currently, LLM-API-Open has only 2 modules: ChatGPT and Microsoft Copilot
๐ But it is possible to add other popular online LLMs (You can wait, or make a pull-request yourself)
๐ Documentation is also under development! Consider reading docstring for now
๐ Support project
-
BTC:
bc1qd2j53p9nplxcx4uyrv322t3mg0t93pz6m5lnft
-
ETH:
0x284E6121362ea1C69528eDEdc309fC8b90fA5578
-
ZEC:
t1Jb5tH61zcSTy2QyfsxftUEWHikdSYpPoz
-
Or by my music on ๐ฆ bandcamp
๐๏ธ Getting started
โ ๏ธ Will not work with Python 3.13 or later due to
imghdr
โ๏ธ 1. Download / build / install LLM-API-Open
There is 4 general ways to get LLM-API-Open
โ๏ธ Install via pip
-
Install from PyPi
pip install llm-api-open
-
Or install from GitHub directly
pip install git+https://github.com/F33RNI/LLM-API-Open.git
-
Or clone repo and install
git clone https://github.com/F33RNI/LLM-API-Open.git cd LLM-API-Open python -m venv venv source venv/bin/activate pip install .
โฌ๏ธ Download cli version from releases
https://github.com/F33RNI/LLM-API-Open/releases/latest
๐จ Build cli version from source using PyInstaller
git clone https://github.com/F33RNI/LLM-API-Open.git
cd LLM-API-Open
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
pyinstaller lmao.spec
dist/lmao --help
๐ป Use source as is
git clone https://github.com/F33RNI/LLM-API-Open.git
cd LLM-API-Open
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
export PYTHONPATH=./src:$PYTHONPATH
export PYTHONPATH=./src/lmao:$PYTHONPATH
python -m main --help
๐ง 2. Configure LLM-API-Open
- Download
configs
directory from this repo - Open
.json
files of modules you need in any editor and change it as you need - Specify path to
configs
directory with-c path/to/configs
argument
๐ฆ Python package example
import logging
import json
from lmao.module_wrapper import ModuleWrapper
# Initialize logging in a simplest way
logging.basicConfig(level=logging.INFO)
# Load config
with open("path/to/configs/chatgpt.json", "r", encoding="utf-8") as file:
module_config = json.loads(file.read())
# Initialize module
module = ModuleWrapper("chatgpt", module_config)
module.initialize(blocking=True)
# Ask smth
conversation_id = None
for response in module.ask({"prompt": "Hi! Who are you?", "convert_to_markdown": True}):
conversation_id = response.get("conversation_id")
response_text = response.get("response")
print(response_text, end="\n\n")
# Delete conversation
module.delete_conversation({"conversation_id": conversation_id})
# Close (unload) module
module.close(blocking=True)
๐ป CLI example
$ lmao --help
usage: lmao [-h] [-v] [-c CONFIG] [-t TEST] [-i IP] [-p PORT] [--no-logging-init]
Unofficial open APIs for popular LLMs with self-hosted redirect capability
options:
-h, --help show this help message and exit
-v, --version show program's version number and exit
-c CONFIGS, --configs CONFIGS
path to configs directory with each module config file (Default: configs)
-t TEST, --test TEST module name to test in cli instead of starting API server (eg. --test=chatgpt)
-i IP, --ip IP API server Host (IP) (Default: localhost)
-p PORT, --port PORT API server port (Default: 1312)
--no-logging-init specify to bypass logging initialization (will be set automatically when using --test)
examples:
lmao --test=chatgpt
lmao --ip="0.0.0.0" --port=1312
lmao --ip="0.0.0.0" --port=1312 --no-logging-init
$ lmao --test=chatgpt
WARNING:root:Error adding cookie oai-did
WARNING:root:Error adding cookie ajs_anonymous_id
WARNING:root:Error adding cookie oai-allow-ne
User > Hi!
chatgpt > Hello! How can I assist you today?
๐ API example
Start server
$ lmao --configs "configs" --ip "0.0.0.0" --port "1312"
2024-03-30 23:14:50 INFO Logging setup is complete
2024-03-30 23:14:50 INFO Loading config files from configs directory
2024-03-30 23:14:50 INFO Adding config of ms_copilot module
2024-03-30 23:14:50 INFO Adding config of chatgpt module
* Serving Flask app 'lmao.external_api'
* Debug mode: off
2024-03-30 23:14:50 INFO WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:1312
* Running on http://192.168.0.3:1312
2024-03-30 23:14:50 INFO Press CTRL+C to quit
...
๐ Python (requests)
import logging
import time
from typing import Dict
import requests
# API URL
BASE_URL = "http://localhost:1312/api"
# Timeout for each request
TIMEOUT = 60
# Initialize logging in a simplest way
logging.basicConfig(level=logging.INFO)
def post(endpoint: str, data: Dict):
"""POST request wrapper"""
response_ = requests.post(f"{BASE_URL}/{endpoint}", json=data, timeout=TIMEOUT, stream=endpoint == "ask")
if endpoint != "ask":
try:
logging.info(f"{endpoint.capitalize()} Response: {response_.status_code}. Data: {response_.json()}")
except Exception:
logging.info(f"{endpoint.capitalize()} Response: {response_.status_code}")
else:
logging.info(f"{endpoint.capitalize()} Response: {response_.status_code}")
return response_
def get(endpoint: str):
"""GET request wrapper"""
response_ = requests.get(f"{BASE_URL}/{endpoint}", timeout=TIMEOUT)
logging.info(f"{endpoint.capitalize()} Response: {response_.status_code}. Data: {response_.json()}")
return response_
# Initialize module
response = post("init", {"module": "chatgpt"})
# Read module's status and wait until it's initialized (in Idle)
logging.info("Waiting for module initialization")
while True:
response = get("status")
chatgpt_status_code = response.json()[0].get("status_code")
if chatgpt_status_code == 2:
break
time.sleep(1)
# Ask and read stream response
response = post("ask", {"chatgpt": {"prompt": "Hi! Please write a long text about AI", "convert_to_markdown": True}})
logging.info("Stream Response:")
for line in response.iter_lines():
if line:
logging.info(line.decode("utf-8"))
# Delete last conversation
response = post("delete", {"chatgpt": {"conversation_id": ""}})
# Close module (uninitialize it)
response = post("close", {"module": "chatgpt"})
๐ CURL
For CURL examples please read ๐ API docs
section
๐ API docs
โ ๏ธ Documentation is still under development!
๐ Module initialization /api/init
Begins module initialization (in a separate, non-blocking thread)
Please call
/api/status
to check if the module is initialized BEFORE calling/api/init
.After calling
/api/init
, please call/api/status
to check if the module's initialization finished.
Request (POST):
{
"module": "name of module from MODULES"
}
Returns:
- โ๏ธ If everything is ok: status code
200
and{}
body - โ In case of an error: status code
400
or500
and{"error": "Error message"}
body
Example:
$ curl --request POST --header "Content-Type: application/json" --data '{"module": "chatgpt"}' http://localhost:1312/api/init
{}
๐ Status /api/status
Retrieves the current status of all modules
Request (GET or POST):
{}
Returns:
- โ๏ธ If no errors during modules iteration: status code
200
and
[
{
"module": "Name of the module from MODULES",
"status_code": "Module's status code as an integer",
"status_name": "Module's status as a string",
"error": "Empty or module's error message"
},
]
- โ In case of an modules iteration error: status code
500
and{"error": "Error message"}
body
Example:
$ curl --request GET http://localhost:1312/api/status
[{"error":"","module":"chatgpt","status_code":2,"status_name":"Idle"}]
๐ Send request and get stream response /api/ask
Initiates a request to the specified module and streams responses back
Please call
/api/status
to check if the module is initialized and not busy BEFORE calling/api/ask
To stop the stream, please call
/api/stop
Request (POST):
For ChatGPT:
{
"chatgpt": {
"prompt": "Text request to send to the module",
"conversation_id": "Optional conversation ID (to continue existing chat) or empty for a new conversation",
"convert_to_markdown": true or false //(Optional flag for converting response to Markdown)
}
}
For Microsoft Copilot:
{
"ms_copilot": {
"prompt": "Text request",
"image": image as base64 to include into request,
"conversation_id": "empty string or existing conversation ID",
"style": "creative" / "balanced" / "precise",
"convert_to_markdown": True or False
}
}
Yields:
- โ๏ธ A stream of JSON objects containing module responses
For ChatGPT, each JSON object has the following structure:
{
"finished": "True if it's the last response, False if not",
"message_id": "ID of the current message (from assistant)",
"response": "Actual response as text"
}
For Microsoft Copilot, each JSON object has the following structure:
{
"finished": True if it's the last response, False if not,
"response": "response as text (or meta response)",
"images": ["array of image URL's"],
"caption": "images caption",
"attributions": [
{
"name": "name of attribution",
"url": "URL of attribution"
},
...
],
"suggestions": ["array of suggestions of the requests"]
}
Returns:
- โ In case of error: status code
500
and{"error": "Error message"}
body
Example:
$ curl --request POST --header "Content-Type: application/json" --data '{"chatgpt": {"prompt": "Hi! Who are you?", "convert_to_markdown": true}}' http://localhost:1312/api/ask
{"finished": false, "conversation_id": "1033be5b-d37d-46b3-b47c-9548da5b192c", "message_id": "00d9cc0d-c4d9-484d-a8e5-9c78eaf2a0e1", "response": "Hello! I'm ChatGPT, an AI developed by O"}
...
{"finished": true, "conversation_id": "1033be5b-d37d-46b3-b47c-9548da5b192c", "message_id": "00d9cc0d-c4d9-484d-a8e5-9c78eaf2a0e1", "response": "Hello! I'm ChatGPT, an AI developed by OpenAI. I'm here to help answer your questions, engage in conversation, provide information, or assist you with anything else you might need. How can I assist you today?"}
๐ Stop stream response /api/stop
Stops the specified module's streaming response (stops yielding from /api/ask
)
Request (POST):
{
"module": "Name of the module from MODULES"
}
Returns:
- โ๏ธ If the stream stopped successfully: status code
200
and{}
body - โ In case of an error: status code
400
or500
and{"error": "Error message"}
body
Example:
$ curl --request POST --header "Content-Type: application/json" --data '{"module": "chatgpt"}' http://localhost:1312/api/stop
{}
๐ Delete conversation /api/delete
Clears the module's conversation history
Please call
/api/status
to check if the module is initialized and not busy BEFORE calling/api/delete
Request:
For ChatGPT:
{
"chatgpt": {
"conversation_id": "ID of conversation to delete or empty to delete the top one"
}
}
Returns:
- โ๏ธ If conversation deleted successfully: status code
200
and{}
body - โ In case of an error: status code
400
or500
and{"error": "Error message"}
body
Example:
$ curl --request POST --header "Content-Type: application/json" --data '{"chatgpt": {"conversation_id": "1033be5b-d37d-46b3-b47c-9548da5b192c"}}' http://localhost:1312/api/delete
{}
๐ Close module /api/close
Requests the module's session to close (in a separate, non-blocking thread)
Please call
/api/status
to check if the module is initialized and its status is Idle or Failed BEFORE calling/api/close
After calling
/api/close
, please call/api/status
to check if the module's closing finished
Request:
{
"module": "Name of the module from MODULES"
}
Returns:
- โ๏ธ If requested successfully: status code
200
and{}
body - โ In case of an error: status code
400
or500
and{"error": "Error message"}
body
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