Mistral

Use the Mistral API through Portkey for:

Enhanced Logging: Track API usage with detailed insights and custom segmentation.
Production Reliability: Automated fallbacks, load balancing, retries, time outs, and caching.
Continuous Improvement: Collect and apply user feedback.

1.1 Setup & Logging

Obtain your Portkey API Key.
Set $ export PORTKEY_API_KEY=PORTKEY_API_KEY
Set $ export MISTRAL_API_KEY=MISTRAL_API_KEY
pip install portkey-ai or npm i portkey-ai

""" OPENAI PYTHON SDK """

from portkey_ai import Portkey

portkey = Portkey(

    api_key="PORTKEY_API_KEY",

    # ************************************

    provider="mistral-ai",

    Authorization="Bearer MISTRAL_API_KEY"

    # ************************************

)

response = portkey.chat.completions.create(

    model="mistral-tiny",

    messages = [{ "role": "user", "content": "c'est la vie" }]

)

import Portkey from 'portkey-ai';

const portkey = new Portkey({

    apiKey: "PORTKEY_API_KEY",

    // ***********************************

    provider: "mistral-ai",

    Authorization: "Bearer MISTRAL_API_KEH"

    // ***********************************

})

async function main(){

  const response = await portkey.chat.completions.create({

      model: "mistral-tiny",

      messages: [{ role: 'user', content: "c'est la vie" }]

  });

}

main()

1.2. Enhanced Observability

Trace requests with single id.
Append custom tags for request segmenting & in-depth analysis.

Just add their relevant headers to your request:

from portkey_ai import Portkey

portkey = Portkey(

    api_key="PORTKEY_API_KEY",

    provider="mistral-ai",

    Authorization="Bearer MISTRAL_API_KEY"

)

response = portkey.with_options(

    # ************************************

    trace_id="ux5a7",

    metadata={"user": "john_doe"}

    # ************************************

).chat.completions.create(

    model="mistral-tiny",

    messages = [{ "role": "user", "content": "c'est la vie" }]

)

import Portkey from 'portkey-ai';

const portkey = new Portkey({

    apiKey: "PORTKEY_API_KEY",

    provider: "mistral-ai",

    Authorization: "Bearer MISTRAL_API_KEH"

})

async function main(){

  const response = await portkey.chat.completions.create({

      model: "mistral-tiny",

      messages: [{ role: 'user', content: "c'est la vie" }]

  },{

    // ***********************************

    traceID: "ux5a7",

    metadata: {"user": "john_doe"}

});

}

main()

Here’s how your logs will appear on your Portkey dashboard:

2. Caching, Fallbacks, Load Balancing

Fallbacks: Ensure your application remains functional even if a primary service fails.
Load Balancing: Efficiently distribute incoming requests among multiple models.
Semantic Caching: Reduce costs and latency by intelligently caching results.

Toggle these features by saving Configs (from the Portkey dashboard > Configs tab). If we want to enable semantic caching + fallback from Mistral-Medium to Mistral-Tiny, your Portkey config would look like this:

{

	"cache": {"mode": "semantic"},

	"strategy": {"mode": "fallback"},

	"targets": [

		{

			"provider": "mistral-ai", "api_key": "...",

			"override_params": {"model": "mistral-medium"}

		},

		{

			"provider": "mistral-ai", "api_key": "...",

			"override_params": {"model": "mistral-tiny"}

		}

	]

}

Now, just set the Config ID while instantiating Portkey:

""" OPENAI PYTHON SDK """

from portkey_ai import Portkey

portkey = Portkey(

    api_key="PORTKEY_API_KEY",

    # ************************************

    config="pp-mistral-cache-xx"

    # ************************************

)

response = portkey.chat.completions.create(

    model="mistral-tiny",

    messages = [{ "role": "user", "content": "c'est la vie" }]

)

import Portkey from 'portkey-ai';

const portkey = new Portkey({

    apiKey: "PORTKEY_API_KEY",

    // ***********************************

    config: "pp-mistral-cache-xx"

    // ***********************************

})

async function main(){

  const response = await portkey.chat.completions.create({

      model: "mistral-tiny",

      messages: [{ role: 'user', content: "c'est la vie" }]

  });

}

main()

For more on Configs and other gateway feature like Load Balancing, check out the docs.

3. Collect Feedback

Gather weighted feedback from users and improve your app:

from portkey import Portkey

portkey = Portkey(

    api_key="PORTKEY_API_KEY"

)

def send_feedback():

    portkey.feedback.create(

        'trace_id'= 'REQUEST_TRACE_ID',

        'value'= 0  # For thumbs down

    )

send_feedback()

import Portkey from 'portkey-ai';

const portkey = new Portkey({

    apiKey: "PORTKEY_API_KEY"

});

const sendFeedback = async () => {

    await portkey.feedback.create({

        traceID: "REQUEST_TRACE_ID",

        value: 1  // For thumbs up

    });

}

await sendFeedback();

Conclusion

Integrating Portkey with Mistral helps you build resilient LLM apps from the get-go. With features like semantic caching, observability, load balancing, feedback, and fallbacks, you can ensure optimal performance and continuous improvement. Read full Portkey docs here. | Reach out to the Portkey team.

Evals

Prompt Engineering

Whitepapers

Getting Started

Integrations

Use Cases

1.1 Setup & Logging

1.2. Enhanced Observability

2. Caching, Fallbacks, Load Balancing

3. Collect Feedback

Conclusion

Portkey is now PRISMA AIRS AI Gateway. See it in action.

​1.1 Setup & Logging

​1.2. Enhanced Observability

​2. Caching, Fallbacks, Load Balancing

​3. Collect Feedback

​Conclusion

Portkey is now PRISMA AIRS AI Gateway. See it in action.

1.1 Setup & Logging

1.2. Enhanced Observability

2. Caching, Fallbacks, Load Balancing

3. Collect Feedback

Conclusion