Skip to main content

Unofficial open APIs for popular LLMs with self-hosted redirect capability

Project description

๐Ÿ•Š๏ธ LLM-API-Open (LMAO)

LLM-API-Open logo

Unofficial open APIs for popular LLMs with self-hosted redirect capability


โ“ WAT

๐Ÿ•Š๏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

๐Ÿ”ฅ 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!


๐Ÿšง LLM-API-Open is development

Due to my studies, I don't have much time to work on the project ๐Ÿ˜”

Currently, LLM-API-Open has only 2 modules: ChatGPT and Microsoft Copilot

๐Ÿ“ˆ But it is possible to add other popular online LLMs (You can wait, or make a pull-request yourself)

๐Ÿ“„ Documentation is also under development! Consider reading docstring for now


๐Ÿ˜‹ Support project

  • BTC: bc1qd2j53p9nplxcx4uyrv322t3mg0t93pz6m5lnft

  • ETH: 0x284E6121362ea1C69528eDEdc309fC8b90fA5578

  • ZEC: t1Jb5tH61zcSTy2QyfsxftUEWHikdSYpPoz

  • Or by my music on ๐ŸŸฆ bandcamp


๐Ÿ—๏ธ Getting started

โš ๏ธ Will not work with Python 3.13 or later due to imghdr

โš™๏ธ 1. Download / build / install LLM-API-Open

There is 4 general ways to get LLM-API-Open

โš™๏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

๐Ÿ”จ 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

๐Ÿ’ป 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

๐Ÿ”ง 2. Configure LLM-API-Open

  1. Download configs directory from this repo
  2. Open .json files of modules you need in any editor and change it as you need
  3. Specify path to configs directory with -c path/to/configs argument

๐Ÿ“ฆ 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)

๐Ÿ’ป 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?

๐ŸŒ 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
...

๐Ÿ 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"})

๐ŸŒ CURL

For CURL examples please read ๐Ÿ“„ API docs section


๐Ÿ“„ API docs

โš ๏ธ Documentation is still under development!

๐ŸŒ 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:

  • โœ”๏ธ If everything is ok: status code 200 and {} body
  • โŒ In case of an error: status code 400 or 500 and {"error": "Error message"} body

Example:

$ curl --request POST --header "Content-Type: application/json" --data '{"module": "chatgpt"}' http://localhost:1312/api/init
{}

๐ŸŒ Status /api/status

Retrieves the current status of all modules

Request (GET or POST):

{}

Returns:

  • โœ”๏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Œ 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"}]

๐ŸŒ 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:

  • โœ”๏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Œ 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?"}

๐ŸŒ 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:

  • โœ”๏ธ If the stream stopped successfully: status code 200 and {} body
  • โŒ In case of an error: status code 400 or 500 and {"error": "Error message"} body

Example:

$ curl --request POST --header "Content-Type: application/json" --data '{"module": "chatgpt"}' http://localhost:1312/api/stop
{}

๐ŸŒ 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:

  • โœ”๏ธ If conversation deleted successfully: status code 200 and {} body
  • โŒ In case of an error: status code 400 or 500 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
{}

๐ŸŒ 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:

  • โœ”๏ธ If requested successfully: status code 200 and {} body
  • โŒ In case of an error: status code 400 or 500 and {"error": "Error message"} body

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llm-api-open-2.1.24.tar.gz (49.0 kB view details)

Uploaded Source

Built Distribution

llm_api_open-2.1.24-py3-none-any.whl (93.6 kB view details)

Uploaded Python 3

File details

Details for the file llm-api-open-2.1.24.tar.gz.

File metadata

  • Download URL: llm-api-open-2.1.24.tar.gz
  • Upload date:
  • Size: 49.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for llm-api-open-2.1.24.tar.gz
Algorithm Hash digest
SHA256 412f15593373195215e06b848f38541c0ab6874620b3461f75930cb036272357
MD5 0cd2f29648d549b94d60bfb327ca26b5
BLAKE2b-256 7ae7194ef109ecd5a99382eb557e949fb3001413a19cbeb9a92ca422db205dc7

See more details on using hashes here.

File details

Details for the file llm_api_open-2.1.24-py3-none-any.whl.

File metadata

File hashes

Hashes for llm_api_open-2.1.24-py3-none-any.whl
Algorithm Hash digest
SHA256 3311ee54f12920ab90e24626c6ea1ff8bdbeb32f58e097d297bb06ce1075ff2a
MD5 a085548cff419ee122bc82ed0d87da04
BLAKE2b-256 7e21ab0d580c8e6904fe25037bb79f53cb3292746633401991c515534b95531f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page