Rename embedchain to mem0 and open sourcing code for long term memory (#1474)

Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>

embedchain/embedchain/llm/mistralai.py

@@ -0,0 +1,72 @@
+import os
+from typing import Any, Optional
+
+from embedchain.config import BaseLlmConfig
+from embedchain.helpers.json_serializable import register_deserializable
+from embedchain.llm.base import BaseLlm
+
+
+@register_deserializable
+class MistralAILlm(BaseLlm):
+    def __init__(self, config: Optional[BaseLlmConfig] = None):
+        super().__init__(config)
+        if not self.config.api_key and "MISTRAL_API_KEY" not in os.environ:
+            raise ValueError("Please set the MISTRAL_API_KEY environment variable or pass it in the config.")
+
+    def get_llm_model_answer(self, prompt) -> tuple[str, Optional[dict[str, Any]]]:
+        if self.config.token_usage:
+            response, token_info = self._get_answer(prompt, self.config)
+            model_name = "mistralai/" + self.config.model
+            if model_name not in self.config.model_pricing_map:
+                raise ValueError(
+                    f"Model {model_name} not found in `model_prices_and_context_window.json`. \
+                    You can disable token usage by setting `token_usage` to False."
+                )
+            total_cost = (
+                self.config.model_pricing_map[model_name]["input_cost_per_token"] * token_info["prompt_tokens"]
+            ) + self.config.model_pricing_map[model_name]["output_cost_per_token"] * token_info["completion_tokens"]
+            response_token_info = {
+                "prompt_tokens": token_info["prompt_tokens"],
+                "completion_tokens": token_info["completion_tokens"],
+                "total_tokens": token_info["prompt_tokens"] + token_info["completion_tokens"],
+                "total_cost": round(total_cost, 10),
+                "cost_currency": "USD",
+            }
+            return response, response_token_info
+        return self._get_answer(prompt, self.config)
+
+    @staticmethod
+    def _get_answer(prompt: str, config: BaseLlmConfig):
+        try:
+            from langchain_core.messages import HumanMessage, SystemMessage
+            from langchain_mistralai.chat_models import ChatMistralAI
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "The required dependencies for MistralAI are not installed."
+                'Please install with `pip install --upgrade "embedchain[mistralai]"`'
+            ) from None
+
+        api_key = config.api_key or os.getenv("MISTRAL_API_KEY")
+        client = ChatMistralAI(mistral_api_key=api_key)
+        messages = []
+        if config.system_prompt:
+            messages.append(SystemMessage(content=config.system_prompt))
+        messages.append(HumanMessage(content=prompt))
+        kwargs = {
+            "model": config.model or "mistral-tiny",
+            "temperature": config.temperature,
+            "max_tokens": config.max_tokens,
+            "top_p": config.top_p,
+        }
+
+        # TODO: Add support for streaming
+        if config.stream:
+            answer = ""
+            for chunk in client.stream(**kwargs, input=messages):
+                answer += chunk.content
+            return answer
+        else:
+            chat_response = client.invoke(**kwargs, input=messages)
+            if config.token_usage:
+                return chat_response.content, chat_response.response_metadata["token_usage"]
+            return chat_response.content