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‎.gitignore‎

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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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#.idea/

‎README.md‎

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# client-python
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Python client library for Mistral AI platform
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# Mistral Python Client
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This client uses poetry as a depedency and virtual environment manager.
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you can install poetry with@
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```bash
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pip install poetry
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```
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## Installing
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poetry will set up a virtual environment and install dependencies with the following command:
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```bash
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poetry install
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```
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## Run examples
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You can run the examples using `poetry run` or by entering the virtual environment using `poetry shell`.
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### Using poetry run
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```bash
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cd examples
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poetry run python async_chat.py
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```
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### Using poetry shell
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```bash
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cd examples
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poetry shell
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>> python async_chat.py
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```

‎examples/async_examples.py‎

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import asyncio
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import os
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from mistral_client.async_client import MistralAsyncClient
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from mistral_client.models.chat_completion import ChatMessage
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async def main():
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api_key = os.environ["MISTRAL_API_KEY"]
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client = MistralAsyncClient(api_key=api_key)
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### LIST MODELS
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list_models_response = await client.list_models()
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print(list_models_response)
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### CHAT NO STREAMING
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chat_response = await client.chat(
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model="le-tiny",
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messages=[ChatMessage(role="user", content="Hello, how are you?")],
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)
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print(chat_response)
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### CHAT STREAMING
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async for chunk in client.chat_stream(
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model="le-tiny",
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messages=[ChatMessage(role="user", content="Hello, how are you?")],
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):
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print(chunk)
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### EMBEDDINGS
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embeddings_response = await client.embeddings(
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model="le-embed",
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input="Hello, how are you?",
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)
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print(embeddings_response)
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### EMBEDDINGS BATCH
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embeddings_batch_response = await client.embeddings(
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model="le-embed",
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input=["Hello, how are you?"] * 10,
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)
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print(embeddings_batch_response)
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if __name__ == "__main__":
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asyncio.run(main())

‎examples/examples.py‎

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import os
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from mistral_client.client import MistralClient
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from mistral_client.models.chat_completion import ChatMessage
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def main():
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api_key = os.environ["MISTRAL_API_KEY"]
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client = MistralClient(api_key=api_key)
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### LIST MODELS
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list_models_response = client.list_models()
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print(list_models_response)
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### CHAT NO STREAMING
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chat_response = client.chat(
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model="le-tiny",
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messages=[ChatMessage(role="user", content="Hello, how are you?")],
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)
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print(chat_response)
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### CHAT STREAMING
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for chunk in client.chat_stream(
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model="le-tiny",
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messages=[ChatMessage(role="user", content="Hello, how are you?")],
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):
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print(chunk)
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### EMBEDDINGS
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embeddings_response = client.embeddings(
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model="le-embed",
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input="Hello, how are you?",
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)
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print(embeddings_response)
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### EMBEDDINGS BATCH
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embeddings_batch_response = client.embeddings(
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model="le-embed",
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input=["Hello, how are you?"] * 10,
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)
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print(embeddings_batch_response)
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if __name__ == "__main__":
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main()

‎poetry.lock‎

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‎pyproject.toml‎

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[tool.poetry]
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name = "mistral_client"
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version = "0.1.0"
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description = ""
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authors = ["Bam4d <bam4d@mistral.ai>"]
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readme = "README.md"
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[tool.ruff]
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select = ["E", "F", "W", "Q", "I"]
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ignore = ["E203"]
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fixable = ["ALL"]
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unfixable = []
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line-length = 120
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[tool.mypy]
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disallow_untyped_defs = true
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show_error_codes = true
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no_implicit_optional = true
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warn_return_any = true
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warn_unused_ignores = true
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exclude = ["docs", "tests", "examples", "tools", "build"]
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[tool.poetry.dependencies]
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python = "^3.8"
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aiohttp = "^3.9.1"
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backoff = "^2.2.1"
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orjson = "^3.9.10"
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requests = "^2.31.0"
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pydantic = "^2.5.2"
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[tool.poetry.group.dev.dependencies]
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ruff = "^0.1.6"
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mypy = "^1.7.1"
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types-requests = "^2.31.0.10"
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[build-system]
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requires = ["poetry-core"]
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build-backend = "poetry.core.masonry.api"
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‎src/mistral_client/__init__.py‎

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