AI Search Engine

Overview

AI Web Search Engine is designed to retrieve real-time information from the internet. This solution processes user queries and return relevant data from various online sources, making them useful for tasks that require up-to-date knowledge beyond static datasets. It supports two usage options:

1

Using six specialized API endpoints, each designed to search for only one specific type of information. These endpoints return structured responses, making them more suitable for integration into specialized services (e.g., a weather widget). Here are the types of information you can retrieve this way:

• Links

• Images

• Videos

• Weather details for a specified location

• Locations

• Knowledge about a topic, structured as a small knowledge base

See API references and examples on the subpages.

2

As a general chat completion solution (but searching on the internet): enter a query in the prompt and receive an internet-sourced answer, similar to asking a question on a search engine through a browser. See the API Schema below or check how this call is made in the Python example on the bottom of this page.

API Schema

Generate a conversational response using a language model.

Creates a chat completion using a language model, allowing interactive conversation by predicting the next response based on the given chat history. This is useful for AI-driven dialogue systems and virtual assistants.

post

/v1/chat/completions

Authorizations

Body

modelundefined · enumrequired

Options: bagoodex/bagoodex-search-v1

messagesobject[]required

frequency_penaltynumber | nullable

logit_biasobject | nullable

logprobsboolean | nullable

top_logprobsnumber | nullable

max_tokensnumber · min: 1 · default: 512

ninteger | nullable

presence_penaltynumber | nullable

response_formatone of

seedinteger · min: 1

stopany of

streamboolean · default: false

temperaturenumber · max: 2

top_pnumber · min: 0.1 · max: 1

toolsobject[]Deprecated

tool_choiceany ofDeprecated

userstring

best_ofinteger | nullable

use_beam_searchboolean | nullable

top_kinteger | nullable

min_pnumber | nullable

repetition_penaltynumber | nullable

length_penaltynumber | nullable

early_stoppingboolean | nullable

ignore_eosboolean | nullable

min_tokensinteger | nullable

stop_token_idsinteger[] | nullable

skip_special_tokensboolean | nullable

spaces_between_special_tokensany | nullable

echoboolean | nullable

If true, the new message will be prepended with the last message if they belong to the same role.

add_generation_promptboolean | nullable

If true, the generation prompt will be added to the chat template. This is a parameter used by chat template in tokenizer config of the model.

add_special_tokensboolean | nullable

If true, special tokens (e.g. BOS) will be added to the prompt on top of what is added by the chat template. For most models, the chat template takes care of adding the special tokens so this should be set to False (as is the default).

documentsobject[] | nullable

A list of dicts representing documents that will be accessible to the model if it is performing RAG (retrieval-augmented generation). If the template does not support RAG, this argument will have no effect. We recommend that each document should be a dict containing "title" and "text" keys.

chat_templatestring | nullable

A Jinja template to use for this conversion. If this is not passed, the model's default chat template will be used instead.

chat_template_kwargsobject | nullable

Additional kwargs to pass to the template renderer. Will be accessible by the chat template

include_stop_str_in_outputboolean | nullable

Whether to include the stop string in the output. This is only applied when the stop or stop_token_ids is set

guided_jsonany of

If specified, the output will follow the JSON schema.

guided_regexstring | nullable

If specified, the output will follow the regex pattern.

guided_choicestring[] | nullable

If specified, the output will be exactly one of the choices.

guided_grammarstring | nullable

If specified, the output will follow the context free grammar.

guided_decoding_backendstring · enum | nullable

If specified, will override the default guided decoding backend of the server for this specific request. If set, must be either 'outlines' / 'lm-format-enforcer'

Options: outlines, lm-format-enforcer

guided_whitespace_patternstring | nullable

If specified, will override the default whitespace pattern for guided json decoding.

Responses

cURL

JavaScript

Python

HTTP

cURL

curl -L \
  --request POST \
  --url 'https://api.aimlapi.com/v1/chat/completions' \
  --header 'Authorization: Bearer <YOUR_AIMLAPI_KEY>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "bagoodex/bagoodex-search-v1",
    "messages": [
      {
        "role": "user",
        "content": "text"
      }
    ],
    "frequency_penalty": 1,
    "logit_bias": {
      "ANY_ADDITIONAL_PROPERTY": 1
    },
    "logprobs": true,
    "top_logprobs": 1,
    "max_tokens": 512,
    "n": 1,
    "presence_penalty": 1,
    "response_format": {
      "type": "text"
    },
    "seed": 1,
    "stop": "text",
    "stream": false,
    "temperature": 1,
    "top_p": 1,
    "tools": [
      {
        "type": "function",
        "function": {
          "description": "text",
          "name": "text",
          "parameters": null,
          "required": [
            "text"
          ]
        }
      }
    ],
    "tool_choice": "none",
    "user": "text",
    "best_of": 1,
    "use_beam_search": true,
    "top_k": 1,
    "min_p": 1,
    "repetition_penalty": 1,
    "length_penalty": 1,
    "early_stopping": true,
    "ignore_eos": true,
    "min_tokens": 1,
    "stop_token_ids": [
      1
    ],
    "skip_special_tokens": true,
    "spaces_between_special_tokens": null,
    "echo": true,
    "add_generation_prompt": true,
    "add_special_tokens": true,
    "documents": [
      {
        "ANY_ADDITIONAL_PROPERTY": "text"
      }
    ],
    "chat_template": "text",
    "chat_template_kwargs": {
      "ANY_ADDITIONAL_PROPERTY": null
    },
    "include_stop_str_in_output": true,
    "guided_json": "text",
    "guided_regex": "text",
    "guided_choice": [
      "text"
    ],
    "guided_grammar": "text",
    "guided_decoding_backend": "outlines",
    "guided_whitespace_pattern": "text"
  }'

201

201

No body

Example

import requests
from openai import OpenAI

# Insert your AIML API Key instead of <YOUR_API_KEY>:
API_KEY = '<YOUR_API_KEY>'
API_URL = 'https://api.aimlapi.com'

def complete_chat():
    client = OpenAI(
        base_url=API_URL,
        api_key=API_KEY,
    )    

    response = client.chat.completions.create(
        model="bagoodex/bagoodex-search-v1",
        messages=[
            {
                "role": "user",
                
                # Enter your query here
                "content": 'how to make a slingshot',
            },
        ],
    )
    
    
    print(response.choices[0].message.content)


# Run the function
complete_chat()

Response:

To make a slingshot, you can follow the instructions provided in the two sources:

**Option 1: Make a Giant Slingshot**

* Start by cutting two 2x4's to a length of 40 inches each, which will be the main arms of the slingshot.
* Attach the arms to a base made of plywood using screws, and then add side braces to support the arms.
* Install an exercise band as the launching mechanism, making sure to tighten it to achieve the desired distance.
* Add a cross brace to keep the arms rigid and prevent them from spreading or caving in.

**Option 2: Make a Stick Slingshot**

* Find a sturdy, Y-shaped stick and break it down to the desired shape.
* Cut notches on the ends of the stick to hold the rubber bands in place.
* Create a pouch by folding a piece of fabric in half and then half again, and then cutting small holes for the rubber bands.        
* Thread the rubber bands through the holes and tie them securely to the stick using thread.
* Decorate the slingshot with coloured yarn or twine if desired.

You can choose to make either a giant slingshot or a stick slingshot, depending on your preference and the materials available.