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Releases: mistralai/mistral-common

v1.11.4: Chat templates integration, fixes

25 Jun 06:41
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New Contributors

Full Changelog: v1.11.3...v1.11.4

v1.11.3: Fix continue_final_message, add reasoning format to to_openai

04 Jun 09:01
97267ee

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Full Changelog: v1.11.2...v1.11.3

v1.11.2: Improve from_openai method.

03 Jun 14:51
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Full Changelog: v1.11.1...v1.11.2

v1.11.1: Patch for agentic use

29 Apr 07:24
e5fe9b0

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This Patch allows usage of user message after tool message. It also makes from_openai less strict to make mistral-common integrations in other frameworks smoother.

Full Changelog: v1.11.0...v1.11.1

v1.11.0: Mistral Guidance

29 Apr 07:22
7843bc8

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Mistral Guidance is out !

Make use of lark grammar to guide your model in generating valid reasoning traces with or without tool calls !

Full Changelog: v1.10.0...v1.11.0

v1.10.0: Tokenizer v15, Reasoning Effort and Python 3.14

13 Mar 10:13
accfb26

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New Contributors

Full Changelog: v1.9.1...v1.10.0

v1.9.1 Patch Release

12 Feb 10:51
a54e57f

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Refactor online streaming processing and allow for dynamic streaming delay

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New Contributors

Full Changelog: v1.9.0...v1.9.1

v1.9.0 - Stream my audio 🎙️

03 Feb 16:17
e5f8f24

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Mistral-Common can now process streaming requests

import numpy as np

from mistral_common.audio import Audio
from mistral_common.protocol.instruct.chunk import RawAudio
from mistral_common.protocol.transcription.request import (
    StreamingMode,
    TranscriptionRequest,
)
from mistral_common.tokens.tokenizers.mistral import MistralTokenizer

# 1. Load the tokenizer with audio support
tokenizer = MistralTokenizer.from_hf_hub(
    "mistralai/Voxtral-Mini-4B-Realtime-2602"
)

# 2. Create sample audio data (or load from a file)
sampling_rate = 16_000
duration_s = 2.0
audio_array = np.random.uniform(-1, 1, size=int(duration_s * sampling_rate)).astype(np.float32)

audio = Audio(
    audio_array=audio_array,
    sampling_rate=sampling_rate,
    format="wav",
)

# 3. Create the streaming transcription request
request = TranscriptionRequest(
    audio=RawAudio(
        data=audio.to_base64("wav"),
        format="wav",
    ),
    streaming=StreamingMode.ONLINE,  # or StreamingMode.OFFLINE
    language=None,
)

# 4. Encode the request
tokenized = tokenizer.encode_transcription(request)

# 5. Access the results
print(f"Tokens: {tokenized.tokens}")
print(f"Number of tokens: {len(tokenized.tokens)}")
print(f"Number of audio segments: {len(tokenized.audios)}")

See https://huggingface.co/mistralai/Voxtral-Mini-4B-Realtime-2602 for more info.

What's Changed

New Contributors

Full Changelog: v1.8.7...v1.9.0

v1.8.8: Backward comp

22 Dec 10:52

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Full Changelog: v1.8.7...v1.8.8

v1.8.7: Refactoring and bug fixes.

22 Dec 09:41
bd80f0e

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New Contributors

Full Changelog: v1.8.6...v1.8.7