POST
/
mistral
/
{region}
/
v1
/
fim
/
completions
Fim Completion
curl --request POST \
  --url https://api.langdock.com/mistral/{region}/v1/fim/completions \
  --header 'Authorization: <authorization>' \
  --header 'Content-Type: application/json' \
  --data '{
  "model": "codestral-2405",
  "prompt": "function removeSpecialCharactersWithRegex(str: string) {",
  "max_tokens": 64
}'
{
  "data": "asd",
  "id": "245c52bc936f53ba90327800c73d1c3e",
  "object": "chat.completion",
  "model": "codestral",
  "usage": {
    "prompt_tokens": 16,
    "completion_tokens": 102,
    "total_tokens": 118
  },
  "created": 1732902806,
  "choices": [
    {
      "index": 0,
      "message": {
        "content": "\n  // Use a regular expression to match any non-alphanumeric character and replace it with an empty string\n  return str.replace(/[^a-zA-Z0-9]/g, '');\n}\n\n// Test the function\nconst inputString = \"Hello, World! 123\";\nconst outputString = removeSpecialCharactersWithRegex(inputString);\nconsole.log(outputString); // Output: \"HelloWorld123\"",
        "prefix": false,
        "role": "assistant"
      },
      "finish_reason": "stop"
    }
  ]
}
Erstellt eine Code-Vervollständigung mit dem Codestral-Modell von Mistral. Alle Parameter des Mistral Fill-in-the-Middle Completion Endpunkts werden gemäß den Mistral-Spezifikationen unterstützt.

​
Rate Limits

Die Rate Limit für den FIM Completion Endpunkt beträgt 500 RPM (Anfragen pro Minute) und 60.000 TPM (Token pro Minute). Rate Limits werden auf Workspace-Ebene definiert - und nicht auf API-Schlüssel-Ebene. Jedes Modell hat seine eigene Rate Limit. Wenn du deine Rate Limit überschreitest, erhältst du eine 429 Too Many Requests Antwort. Bitte beachte, dass die Rate Limits Änderungen unterliegen. Beziehe dich auf diese Dokumentation für die aktuellsten Informationen. Falls du eine höhere Rate Limit benötigst, kontaktiere uns bitte unter support@langdock.com.

​
Verwendung des Continue AI Code Assistants

Die Verwendung des Codestral-Modells in Kombination mit Chat-Completion-Modellen der Langdock API ermöglicht es, den Open-Source-KI-Code-Assistenten Continue (continue.dev) vollständig über die Langdock API zu nutzen. Continue ist als VS Code-Erweiterung und als JetBrains-Erweiterung verfügbar. Um die von Continue verwendeten Modelle anzupassen, kannst du die Konfigurationsdatei unter ~/.continue/config.json (MacOS / Linux) oder %USERPROFILE%\.continue\config.json (Windows) bearbeiten. Nachfolgend findest du ein Beispiel-Setup für die Verwendung von Continue mit dem Codestral-Modell für Autovervollständigung und Claude 3.5 Sonnet und GPT-4o-Modellen für Chats und Bearbeitungen, die alle über die Langdock API bereitgestellt werden. 
{
  "models": [
    {
      "title": "GPT-4o",
      "provider": "openai",
      "model": "gpt-4o",
      "apiKey": "<YOUR_LANGDOCK_API_KEY>",
      "apiBase": "https://api.langdock.com/openai/eu/v1"
    },
    {
      "title": "Claude 3.5 Sonnet",
      "provider": "anthropic",
      "model": "claude-3-5-sonnet-20240620",
      "apiKey": "<YOUR_LANGDOCK_API_KEY>",
      "apiBase": "https://api.langdock.com/anthropic/eu/v1"
    }
  ],
  "tabAutocompleteModel": {
    "title": "Codestral",
    "provider": "mistral",
    "model": "codestral-2405",
    "apiKey": "<YOUR_LANGDOCK_API_KEY>",
    "apiBase": "https://api.langdock.com/mistral/eu/v1"
  }
  /* ... other configuration ... */
}

Headers

​
Authorization
string
required

API key as Bearer token. Format "Bearer YOUR_API_KEY"

Path Parameters

​
region
enum<string>
required

The region of the API to use.

Available options:
eu

Body

application/json
​
model
string
default:codestral-2405
required

ID of the model to use. Only compatible for now with:

  • codestral-2405
​
prompt
string
required

The text/code to complete.

​
temperature
number

What sampling temperature to use, we recommend between 0.0 and 0.7. Higher values like 0.7 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both. The default value varies depending on the model you are targeting. Call the /models endpoint to retrieve the appropriate value.

Required range: 0 <= x <= 1.5
​
top_p
number
default:1

Nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.

Required range: 0 <= x <= 1
​
max_tokens
integer

The maximum number of tokens to generate in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length.

Required range: x >= 0
​
stream
boolean
default:false

Whether to stream back partial progress. If set, tokens will be sent as data-only server-side events as they become available, with the stream terminated by a data: [DONE] message. Otherwise, the server will hold the request open until the timeout or until completion, with the response containing the full result as JSON.

​
stop

Stop generation if this token is detected. Or if one of these tokens is detected when providing an array

​
random_seed
integer

The seed to use for random sampling. If set, different calls will generate deterministic results.

Required range: x >= 0
​
suffix
string
default:""

Optional text/code that adds more context for the model. When given a prompt and a suffix the model will fill what is between them. When suffix is not provided, the model will simply execute completion starting with prompt.

​
min_tokens
integer

The minimum number of tokens to generate in the completion.

Required range: x >= 0

Response

Successful Response

​
model
string
required
Example:

"mistral-small-latest"

​
id
string
required
Example:

"cmpl-e5cc70bb28c444948073e77776eb30ef"

​
object
string
required
Example:

"chat.completion"

​
usage
object
required
​
choices
ChatCompletionChoice · object[]
​
created
integer
Example:

1702256327