Python Vercel LLM API

This is a reverse engineered API wrapper for the Vercel AI Playground, which allows for free access to many LLMs, including OpenAI's ChatGPT, Cohere's Command Nightly, as well as some open source models.

Features:

Download the available models
Generate text
Generate chat messages
Set custom parameters
Stream the responses

Limitations:

User-agent is hardcoded
No auth support
Can't use "pro" or "hobby" models

Installation:

You can install this library by running the following command:

pip3 install vercel-llm-api

Documentation:

Examples can be found in the /examples directory. To run these examples, simply execute the included Python files from your terminal.

python3 examples/generate.py

Using the Client:

To use this library, simply import vercel_ai and create a vercel_ai.Client instance. You can specify a proxy using the proxy keyword argument.

Normal example:

import vercel_ai
client = vercel_ai.Client()

Proxied example:

import vercel_ai
client = vercel_ai.Client(proxy="socks5h://193.29.62.48:11003")

Note that the following examples assume client is the name of your vercel_ai.Client instance.

Downloading the Available Models:

The client downloads the available models upon initialization, and stores them in client.models.

>>> print(json.dumps(client.models, indent=2))

{
  "anthropic:claude-instant-v1": { 
    "id": "anthropic:claude-instant-v1", #the model's id
    "provider": "anthropic",             #the model's provider
    "providerHumanName": "Anthropic",    #the provider's display name
    "makerHumanName": "Anthropic",       #the maker of the model
    "minBillingTier": "hobby",           #the minimum billing tier needed to use the model
    "parameters": {                      #a dict of optional parameters that can be passed to the generate function
      "temperature": {                   #the name of the parameter
        "value": 1,                      #the default value for the parameter
        "range": [0, 1]                  #a range of possible values for the parameter
      },
      ...
    }
    ...
  }
}

Note that, since there is no auth yet, if a model has the "minBillingTier" property present, it can't be used.

A list of model IDs is also available in client.model_ids.

>>> print(json.dumps(client.model_ids, indent=2))
[
  "anthropic:claude-instant-v1", #locked to hobby tier; unusable
  "anthropic:claude-v1",         #locked to hobby tier; unusable
  "replicate:replicate/alpaca-7b",
  "replicate:stability-ai/stablelm-tuned-alpha-7b",
  "huggingface:bigscience/bloom",
  "huggingface:bigscience/bloomz",
  "huggingface:google/flan-t5-xxl",
  "huggingface:google/flan-ul2",
  "huggingface:EleutherAI/gpt-neox-20b",
  "huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5",
  "huggingface:bigcode/santacoder",
  "cohere:command-medium-nightly",
  "cohere:command-xlarge-nightly",
  "openai:gpt-4",                #locked to pro tier; unusable
  "openai:code-cushman-001",
  "openai:code-davinci-002",
  "openai:gpt-3.5-turbo",
  "openai:text-ada-001",
  "openai:text-babbage-001",
  "openai:text-curie-001",
  "openai:text-davinci-002",
  "openai:text-davinci-003"
]

A dict of default parameters for each model can be found at client.model_params.

>>> print(json.dumps(client.model_defaults, indent=2))
{
  "anthropic:claude-instant-v1": {
    "temperature": 1,
    "maximumLength": 200,
    "topP": 1,
    "topK": 1,
    "presencePenalty": 1,
    "frequencyPenalty": 1,
    "stopSequences": [
      "\n\nHuman:"
    ]
  },
  ...
}

Generating Text:

To generate some text, use the client.generate function, which accepts the following arguments:

model - The ID of the model you want to use.
prompt - Your prompt.
params = {} - A dict of optional parameters. See the previous section for how to find these.

The function is a generator which returns the newly generated text as a string.

Streamed Example:

for chunk in client.generate("openai:gpt-3.5-turbo", "Summarize the GNU GPL v3"):
  print(chunk, end="", flush=True)

Non-Streamed Example:

result = ""
for chunk in client.generate("openai:gpt-3.5-turbo", "Summarize the GNU GPL v3"):
  result += chunk
print(result)

Generating Chat Messages:

To generate chat messages, use the client.chat function, which accepts the following arguments:

model - The ID of the model you want to use.
messages - A list of messages. The format for this is identical to how you would use the official OpenAI API.
params = {} - A dict of optional parameters. See the "Downloading the Available Models" section for how to find these.

The function is a generator which returns the newly generated text as a string.

messages = [
  {"role": "system", "content": "You are a helpful assistant."},
  {"role": "user", "content": "Who won the world series in 2020?"},
  {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
  {"role": "user", "content": "Where was it played?"}
]
for chunk in client.chat("openai:gpt-3.5-turbo", messages):
  print(chunk, end="", flush=True)
print()

Misc:

Changing the Logging Level:

If you want to show the debug messages, simply call vercel_ai.logger.setLevel.

import vercel_ai
import logging
vercel_ai.logger.setLevel(logging.INFO)

Copyright:

This program is licensed under the GNU GPL v3. All code has been written by me, ading2210.

Copyright Notice:

ading2210/vercel-llm-api: a reverse engineered API wrapper for the Vercel AI Playground
Copyright (C) 2023 ading2210

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.

ading2210/vercel-llm-api

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