I have the same problem with French in DSPY, I rewrote the dspy.Anyscale this way but with no very good results:
import os
import random
import re
import shutil
import subprocess
from typing import Literal

from dsp.modules.adapter import TurboAdapter, DavinciAdapter, LlamaAdapter

import backoff
import requests

class Anyscale(dspy.HFModel):
def init(self, model, **kwargs):
super().init(model=model, is_client=True)
self.session = requests.Session()
self.api_base = os.getenv("ANYSCALE_API_BASE")
self.token = os.getenv("ANYSCALE_API_KEY")
self.model = model
self.kwargs = {
"temperature": 0.0,
"n": 1,
**kwargs,
}

def _generate(self, prompt, use_chat_api=True, **kwargs):
    url = f"{self.api_base}/completions"
    
    kwargs = {**self.kwargs, **kwargs}

    temperature = kwargs.get("temperature")
    max_tokens = kwargs.get("max_tokens", 150) 
    system_prompt = kwargs.get("system_prompt","Vous êtes un robot de discussion générale. Vous vous exprimez uniquement en français. Vos réponses sont concises, elles ne dépassent pas 50 mots, mais restent informatives.")

    if use_chat_api:
        url = f"{self.api_base}/chat/completions"
        #print(f"**** {url} {system_prompt}")
        messages = [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": prompt},
        ]
        body = {
            "model": self.model,
            "messages": messages,
            "temperature": temperature,
            "max_tokens": max_tokens,
        }
    else:
        body = {
            "model": self.model,
            "prompt": f"[INST]{system_prompt}[/INST]{prompt}",
            "temperature": temperature,
            "max_tokens": max_tokens,
        }

    headers = {"Authorization": f"Bearer {self.token}"}

    try:
        completions = []
        for i in range(kwargs.get('n', 1)):
            with self.session.post(url, headers=headers, json=body) as resp:
                resp_json = resp.json()
                if use_chat_api:
                    completions.extend([resp_json.get('choices', [])[0].get('message', {}).get('content', "")])
                else:
                    completions.extend([resp_json.get('choices', [])[0].get('text', "")])
        response = {"prompt": prompt, "choices": [{"text": c} for c in completions]}
        return response
    except Exception as e:
        print(f"Failed to parse JSON response: {e}")
        raise Exception("Received invalid JSON response from server")

me too problem with French. On some other project I worked on, it transpired the embedding was causing the problem as opposed the LLM itself.

My bad, I mixed DSPy and more specific problem of Mistral, but the given class answers the question and the results are usually correct as long as I don't use the DSPy compiler, for example:

model = Anyscale(model='mistralai/Mixtral-8x7B-Instruct-v0.1',max_tokens=1024)
model( "Qui sont Adam et Ève ?") # How are Adam and Eve

[" Adam et Ève sont les premiers êtres humains mentionnés dans la Genèse, le premier livre de la Bible. Ils sont considérés comme les ancêtres de toute l'humanité."] # Adam and Eve are etc.
But when I use this instance inside a DSPy compiler results come in English.

Using the OpenAI interface, it works too :

import openai
client = openai.OpenAI(
base_url = "https://api.endpoints.anyscale.com/v1",
api_key = "esecret_*******"
)

Note: not all arguments are currently supported and will be ignored by the backend.

chat_completion = client.chat.completions.create(
model="mistralai/Mixtral-8x7B-Instruct-v0.1",
messages=[{"role": "system", "content": "Vous êtes un assistant efficace, vos réponses sont courtes et précises"},
{"role": "user", "content": "Qui était d'Alembert ?"}],
temperature=0.7
)
print(chat_completion.choices[0].message.content)

I get the good answer :

Jean le Rond d'Alembert (1717-1783) était un philosophe, mathématicien et encyclopédiste français, célèbre pour ses contributions en mécanique et en équations différentielles. Il a travaillé en étroite collaboration avec Denis Diderot sur l'Encyclopédie, servant de co-rédacteur en chef et rédigeant de nombreux articles.

Hi there, if you ever have issues to get a model adhere to a language you want, try playing around with prefixes, basically appending something to the final string before its sent for completion.

The idea is something like this: [INST] Answer always in spanish to the user.\n\nHi there! [/INST] Aquí está la respuesta en español:

This might be able to help make it more consistent and adhere to the language better. <3

Thanks will try