Metadata-Version: 2.4
Name: llm-api-adapter-mistral
Version: 0.1.1
Summary: Official Mistral API package for llm-api-adapter
Author: Sergey Inozemtsev
License: MIT License
        
        Copyright (c) 2025 Sergey Inozemtsev
        
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Project-URL: Repository, https://github.com/Inozem/llm_api_adapter/
Keywords: llm,mistral,adapter,api
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Typing :: Typed
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: llm-api-adapter<1.0.0,>=0.9.2
Provides-Extra: async
Requires-Dist: llm-api-adapter[async]<1.0.0,>=0.9.2; extra == "async"
Provides-Extra: httpx
Requires-Dist: llm-api-adapter[httpx]<1.0.0,>=0.9.2; extra == "httpx"
Dynamic: license-file

# llm-api-adapter-mistral

Official direct-API support for Mistral in
[llm-api-adapter](https://github.com/Inozem/llm_api_adapter/).

## Installation

Install through the core package extra (recommended):

```bash
pip install "llm-api-adapter[mistral]"
```

Direct installation remains supported when the core package is already managed
separately:

```bash
pip install llm-api-adapter-mistral
```

## Quick start

```python
import os

from llm_api_adapter.models.messages.chat_message import UserMessage
from llm_api_adapter.universal_adapter import UniversalLLMAPIAdapter

adapter = UniversalLLMAPIAdapter(
    organization="mistral",
    model="mistral-large-2512",
    api_key=os.environ["MISTRAL_API_KEY"],
)

response = adapter.chat(messages=[UserMessage("Explain retrieval-augmented generation.")])
print(response.content)
```

## Capabilities

- Chat, tool calling, structured JSON output, and image input.
- Synchronous and asynchronous chat and streaming.
- PDF URLs and bytes through Mistral OCR.
- Tool loops use explicit message history: append the assistant tool calls and
  `ToolMessage` results before the next request. `previous_response` is
  accepted for the shared API contract but is not sent to Mistral, whose Chat
  Completions API is stateless.

See the main [llm-api-adapter README](https://github.com/Inozem/llm_api_adapter/#readme)
for the shared API contract and examples.

## Structured-output portability

This package requires `llm-api-adapter>=0.9.2,<1.0.0` and enforces the same
Core portable JSON Schema profile as OpenAI, Anthropic, Google, and xAI. The
profile guarantees that every object is strict, every property is required,
optional values are nullable, and only direct,
non-recursive local `#/$defs/...` references are resolved before the request.

Use `json_schema` for parsed JSON only. Use a Pydantic `response_model` when
the final result must also be locally validated and returned as
`ChatResponse.parsed_model`; each nested Pydantic model must use
`ConfigDict(extra="forbid")`. Refusal and incomplete terminal responses set
`ChatResponse.refusal` or `ChatResponse.incomplete_reason` and leave parsed
fields unset. Invalid completed JSON or failed Pydantic validation raises
`JSONSchemaError`.

The complete schema vocabulary and examples are in the main
[Structured Output guide](https://github.com/Inozem/llm_api_adapter/#structured-output).

## Supported models

- `mistral-small-2603`
- `mistral-medium-3-5`
- `mistral-large-2512`

## PDF input

`DocumentPart` supports PDF URLs and bytes. Before the chat request, the
adapter sends each PDF to Mistral OCR 4.1 (`mistral-ocr-4-1`) and supplies the resulting Markdown to
the selected chat model. This creates a separate OCR API request, subject to
Mistral's OCR limits and pricing; `ChatResponse` usage and cost cover only the
chat completion.
