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Superagent Python SDK

Home Page: https://docs.superagent.sh

License: MIT License

Python 100.00%

ai assistants gpt superagent transformers

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API definition mismatch

I've created an agent using the admin interface and tried using it with the SDK.
It seems there's an entity definition mismatch.

SDK version 0.1.36

Traceback (most recent call last):
  File ".../main.py", line 5, in <module>
    agent = client.agent.get("XXXXXX")
  File ".../lib/python3.10/site-packages/superagent/resources/agent/client.py", line 89, in get
    return pydantic.parse_obj_as(AppModelsResponseAgent, _response.json())  # type: ignore
  File ".../lib/python3.10/site-packages/pydantic/v1/tools.py", line 38, in parse_obj_as
    return model_type(__root__=obj).__root__
  File ".../lib/python3.10/site-packages/pydantic/v1/main.py", line 341, in __init__
    raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for ParsingModel[AppModelsResponseAgent]
__root__ -> data -> llms -> 0 -> llm -> options

`gpt-4-1106-preview`missing from LLM enums

I've created an agent using the admin interface and tried using it with the SDK.

It seems that gpt-4-1106-preview is missing.

Traceback (most recent call last):
  File "main.py", line 5, in <module>
    agent = client.agent.get("f60830db-8cd2-47c3-98ea-671ef4e0ee4c")
  File ".../lib/python3.10/site-packages/superagent/resources/agent/client.py", line 89, in get
    return pydantic.parse_obj_as(AppModelsResponseAgent, _response.json())  # type: ignore
  File ".../lib/python3.10/site-packages/pydantic/v1/tools.py", line 38, in parse_obj_as
    return model_type(__root__=obj).__root__
  File ".../lib/python3.10/site-packages/pydantic/v1/main.py", line 341, in __init__
    raise validation_error
pydantic.v1.error_wrappers.ValidationError: 2 validation errors for ParsingModel[AppModelsResponseAgent]
__root__ -> data -> llms -> 0 -> llm -> options
  str type expected (type=type_error.str)
__root__ -> data -> llmModel
  value is not a valid enumeration member; permitted: 'GPT_3_5_TURBO_16K_0613', 'GPT_3_5_TURBO_0613', 'GPT_4_0613', 'GPT_4_32K_0613' (type=type_error.enum; enum_values=[<LlmModel.GPT_3_5_TURBO_16_K_0613: 'GPT_3_5_TURBO_16K_0613'>, <LlmModel.GPT_3_5_TURBO_0613: 'GPT_3_5_TURBO_0613'>, <LlmModel.GPT_4_0613: 'GPT_4_0613'>, <LlmModel.GPT_4_32_K_0613: 'GPT_4_32K_0613'>])

I need your help creating an example with superagent-py and MiniAutoGen: Lightweight and Flexible Agents for Multi-Agent Chats

🌐 Hello, amazing community!

I'm exploring the integration of two powerful libraries: MiniAutoGen and superagent-py, and I would greatly appreciate your help and insights!

MiniAutoGen is an innovative open-source library designed to take applications with Large Language Models (LLMs) to the next level. Its differentiators are its lightweight and flexible approach, which allows for a high degree of customization.

Here are some notable features of MiniAutoGen:

Multi-Agent Dialogues: The ability to create complex and nuanced interactions with multiple intelligent agents operating together.
Agent Coordination: A mechanism that ensures harmony and efficient management among the agents.
Customizable Agents: Total freedom to shape agent behaviors according to project needs.
Action Pipeline: Simplifies and automates agent operations, facilitating scalability and maintenance.
Integration with +100 LLMs: Expanding conversational capabilities with over 100 LLMs for intelligent and contextualized responses.

My Challenge: I'm seeking help from the community to develop new integrations and modules.

I Seek Your Help: Do you have examples, tips, or guidance on how I can accomplish this integration? Any insight or shared experience would be extremely valuable!

Check out MiniAutoGen on Google Colab: MiniAutoGen on Google Colab
And here is the GitHub repository for more information: GitHub - brunocapelao/miniAutoGen

I'm looking forward to your ideas and suggestions. Let's shape the future of AI conversations together! 🌟

AttributeError: 'Superagent' object has no attribute 'agents'

AttributeError                            Traceback (most recent call last)
[/Users/dekahalane/superagent-py/test.ipynb](https://file+.vscode-resource.vscode-cdn.net/Users/dekahalane/superagent-py/test.ipynb) Cell 1 line 6
      [2](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=1) from superagent.client import Superagent
      [4](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=3) client = Superagent(token="REMOVED FOR DEBUGGING", base_url="https://api.beta.superagent.sh/")
----> [6](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=5) agent = client.agents.create(request={
      [7](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=6)     "name": "My Agent",
      [8](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=7)     "description": "My awesome agent",
      [9](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=8)     "isActive": True,
     [10](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=9)     "llmModel": "GPT_4_0613"
     [11](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=10) })
     [13](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=12) output = client.agent.invoke(
     [14](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=13)     agent_id=agent.data.id,
     [15](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=14)     input="Hi there!",
     [16](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=15)     enable_streaming=False,
     [17](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=16)     session_id="123"
     [18](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=17) )
     [20](vscode-notebook-cell:/Users/dekahalane/superagent-py/test.ipynb#W0sZmlsZQ%3D%3D?line=19) print("Received response from superagent", agent.data)

AttributeError: 'Superagent' object has no attribute 'agents'

I can't find the documentation to fix this error, I've tried both removing the agents from client.agents.create and just the s as I thought it might be a typo but then it throws an InternalServerError

Typo on README.md

Hi,

This is just a small thing I saw when reading about the tool. There's a typo on README.md. It is written Flase instead of False.

Chat History of agents based on the session

To Add: Chat history of agents and the ability to retrieve past conversation of any session just like list conversation for threads in OpenAI Assistants API

Hi Alan and Ismail ,How can I access my custom gpt aavaible on chat gpt using super agent .

Hi Alan and ismail , I have created many custom gpt on chat gpt for various use cases like available on this screen shot , I want to access this custom gpt using super agent how can I do it . Please note I do not want gpt -3.5 or gpt 4 . I want that particular custom gpt

Unable To Use SDK With API Tokens

Problem Statement / Overview

Hi there, I'm unable to use the SDK with API Tokens. I keep getting {'detail': 'Not authenticated'}. I think it's most likely because the API doesn't seem to accept API Tokens, only bearer auth (https://github.com/homanp/superagent/blob/7e73c21cde43c39c4e83d7ec069e4e0f7ec816c2/app/api/agents.py#L70C50-L70C59)

Expected Output

I would expect the GET request to return my agent successfully. But, let me know if I'm initializing it incorrectly in my code snippet below.

Code Snippet

I included a code snippet with how I'm initializing the client

class WrappedSuperagent(object):
    def __init__(self, api_token: str, environment="https://api.superagent.sh"):
        self._client = Superagent(environment=environment, api_key=api_token)

    # Begin Public Methods
    def get_agent(self, agent_id: str) -> typing.Any:
        return self._get_agent(agent_id)        
    # End Public Methods

    # Begin Private Methods
    def _get_agent(self, agent_id: str) -> typing.Any:
        agent = self._client.agent.get_agent(agent_id) #### ---- Error starts here
        return agent
    # End Private Methods

Let me know if you need anymore info and I'm happy to add that as well!

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