LangChain tools

The official fluentc-langchain-tool Python package. Install it, translate in real time or batch, detect languages, and give a LangChain agent FluentC as tools.

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fluentc-langchain-tool is the official Python package for using FluentC from LangChain. Each capability is a LangChain tool (a BaseTool subclass), so you can call it directly or hand it to an agent.

Requires: Python 3.8 or newer and LangChain.
Authentication: your FluentC API key, passed to each tool's constructor. See Authentication.
Source of truth: the package's page on PyPI.

Install

bash

pip install fluentc-langchain-tool

python

import os

API_KEY = os.environ["FLUENTC_KEY"]

The tools

Class	Tool name	What it does
`FluentCTranslationTool`	`fluentc_translation`	Translate in real-time or batch mode
`FluentCBatchTranslationTool`	`fluentc_batch_translation`	Submit a batch job and wait for the result
`FluentCLanguageDetectorTool`	`fluentc_language_detector`	Detect the language of some text
`FluentCTranslationStatusTool`	`fluentc_translation_status`	Check a batch job by `job_id`
`FluentCSupportedLanguagesTool`	`fluentc_supported_languages`	List the languages enabled for your key
`FluentCResultsTool`	`fluentc_results`	Legacy. Use `fluentc_translation_status` instead

All tools take the API key as their only constructor argument: FluentCTranslationTool(api_key=API_KEY). Tools return a string, which is what an agent reads back.

Translate in real time

python

from fluentc_langchain_tool import FluentCTranslationTool

tool = FluentCTranslationTool(api_key=API_KEY)

result = tool.run({
    "text": "Hello, world!",
    "target_language": "fr",
    "source_language": "en",
    "mode": "realtime",
})
print(result)  # Bonjour, le monde !

Input fields for fluentc_translation:

Field	Type	Required	Description
`text`	string or list of strings	Yes	What to translate.
`target_language`	string	Yes	Target language code, such as `fr`.
`source_language`	string	Yes	Source language code, such as `en`.
`mode`	string	No	`realtime` (default) or `batch`.
`callback_url`	string	No	For batch mode: a URL to notify when the job completes.

Real-time mode needs the Real-time plan. See Concepts.

Translate in batch

FluentCBatchTranslationTool submits the job and polls until it finishes or max_wait_time runs out:

python

from fluentc_langchain_tool import FluentCBatchTranslationTool

tool = FluentCBatchTranslationTool(api_key=API_KEY)

result = tool.run({
    "text": "<html>Hello, batch world!</html>",
    "target_language": "de",
    "source_language": "en",
})
print(result)  # the translated output, once the job completes

Input fields for fluentc_batch_translation:

Field	Type	Default	Description
`text`	string or list of strings	required	What to translate.
`target_language`	string	required	Target language code.
`source_language`	string	required	Source language code.
`wait_for_completion`	boolean	`true`	Set `false` to return the job ID immediately.
`max_wait_time`	integer	`300`	Seconds to wait before giving up.
`callback_url`	string	none	A URL to notify when the job completes.

To control the loop yourself, set wait_for_completion to false and check the job with FluentCTranslationStatusTool:

python

from fluentc_langchain_tool import FluentCTranslationStatusTool

status = FluentCTranslationStatusTool(api_key=API_KEY)
print(status.run({"job_id": "abc123def456"}))

Detect a language

python

from fluentc_langchain_tool import FluentCLanguageDetectorTool

detector = FluentCLanguageDetectorTool(api_key=API_KEY)
print(detector.run({"text": "Hola, ¿cómo estás?"}))
# Detected language: es (confidence: 0.99)

List supported languages

python

from fluentc_langchain_tool import FluentCSupportedLanguagesTool

languages = FluentCSupportedLanguagesTool(api_key=API_KEY)
print(languages.run({}))

Use the tools in an agent

Pass the tools to any LangChain agent. The tool names and descriptions tell the model when to use each one.

python

from langchain.agents import initialize_agent
from langchain.llms import OpenAI
from fluentc_langchain_tool import (
    FluentCTranslationTool,
    FluentCLanguageDetectorTool,
)

agent = initialize_agent(
    tools=[
        FluentCTranslationTool(API_KEY),
        FluentCLanguageDetectorTool(API_KEY),
    ],
    llm=OpenAI(temperature=0),
    agent="zero-shot-react-description",
)

agent.run("Translate 'Hello world' from English to German using FluentC.")

This example uses LangChain's classic initialize_agent interface. The tools are standard BaseTool objects, so they work with newer LangChain agent constructors too.

Errors

The tools catch API errors and return them as a readable string, for example Translation error: ..., instead of raising. An agent can read that and recover or report it. If you need exceptions, call the REST API directly.

The usual causes are on the Errors page: a language that isn't enabled for your key, a real-time request on a Batch plan key, or a key problem.

Something unclear, or missing? Tell us.