Chat（Image analysis）

POST

/chat/completions

adds image recognition capabilities to all models, and there are two ways to enable it, you can choose either one:

Append -ocr to all model suffixes, for example gpt-3.5-turbo-ocr (convenient for third-party software)

Specify the OCR model when requesting the model: ocr_model:gpt-4o-mini, as shown in the example (convenient for API)

Note: If the suffix of the multimodal model has -ocr, it will also use the specified or default OCR model for image analysis, so try to avoid enabling this feature on multimodal models

The principle of this function is: before each request, the user's image is sent to the multimodal model for analysis, and then the analysis results are incorporated into the model context as reference information. The specific process can be viewed in the logs during the API call. The default OCR model currently in use is gpt-4o-mini.

Image analysis prompt words:

Price: On the basis of the original model + the cost of the multimodal model

Request

Header Params

Content-Type

string

required

Example:

application/json

string

required

Example:

application/json

Authorization

string

required

Fill the API KEY generated in the management backend - API KEYS after Bearer, for example Bearer sk-xxxx

Example:

Bearer {{YOUR_API_KEY}}

Body Params application/json

model

string

required

ID of the model to be used. For more details on which models are compatible with the chat API, see the model endpoint compatibility table.

messages

array [object {2}]

required

Generate chat completion messages in chat format.

role

string

optional

content

string

optional

temperature

integer

optional

What sampling temperature is used, between 0 and 2. A higher value (such as 0.8) will make the output more random, while a lower value (such as 0.2) will make the output more centralized and definite. We usually recommend changing this or top_p but not both.

top_p

integer

optional

An alternative to temperature sampling, called kernel sampling, in which the model considers the results of markers with top_p probability mass. So 0.1 means only considering marks that constitute the top 10% probability mass. We usually recommend changing this or temperature but not both.

integer

optional

How many chat completion options are generated for each input message.

stream

boolean

optional

If set, partial message increments will be sent, just like in ChatGPT. When tokens are available, tokens will be sent as raw data data: [DONE] through Server-Sent Events, and the stream is terminated by the message. For example code, please see OpenAI Cookbook.

stop

string

optional

API will stop generating a maximum of 4 tokens for more sequences.

max_tokens

integer

optional

The maximum number of tokens generated when the chat is complete. The total length of input tokens and generated tokens is limited by the model's context length.

presence_penalty

number

optional

Numbers between -2.0 and 2.0. Positive values punish new tags based on whether they appear in the text so far, thereby increasing the possibility that the model will talk about new topics. See more information about frequency and exists penalties.

frequency_penalty

number

optional

Numbers between -2.0 and 2.0. Positive values punish new tags based on their existing frequency in the text, reducing the possibility that the model will repeat the same line verbatim. See more information about frequency and exists penalties.

logit_bias

null

optional

Modify the possibility that the specified mark appears in completion. Accepts a json object that maps the tag (specified by the tag ID in the tagger) to the associated bias value from -100 to 100. Mathematically, bias is added to the model-generated logits before sampling. The exact effect varies by model, but values between -1 and 1 should reduce or increase the likelihood of selection; values like -100 or 100 should result in prohibited or exclusive selection of the relevant token.

user

string

optional

A unique identifier that represents your end user, which can help OpenAI monitor and detect abuse. Learn more.

Example

{
  "model": "gpt-3.5-turbo-ocr",
  "ocr_model": "gpt-4o-mini",
  "stream": false,
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "这张图片有什么"
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://s2.loli.net/2024/02/01/QSWVdw9bX56gj7O.jpg"
          }
        }
      ]
    }
  ]
}

Request samples

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

curl --location --request POST 'https://api.302.ai/v1/chat/completions' \
--header 'Accept: application/json' \
--header 'Authorization: Bearer sk-jls4AaVBGoe1GwZD64qZA1qyKTN1MPHa4NmvH1cT68z7K1Zz' \
--header 'Content-Type: application/json' \
--data-raw '{
  "model": "gpt-3.5-turbo-ocr",
  "ocr_model":"gpt-4o-mini",
  "stream": false,
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "这张图片有什么"
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://s2.loli.net/2024/02/01/QSWVdw9bX56gj7O.jpg"
          }
        }
      ]
    }
  ]
}'

Responses

🟢200OK

application/json

Body

string

required

object

string

required

created

integer

required

choices

array [object {3}]

required

index

integer

optional

message

object

optional

finish_reason

string

optional

usage

object

required

prompt_tokens

integer

required

completion_tokens

integer

required

total_tokens

integer

required

Example

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "\n\nHello there, how may I assist you today?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 12,
    "total_tokens": 21
  }
}

Chat（Depth-First Search）

Chat（Reasoning mode）