Show details for query tokens (#1392)

embedchain/llm/together.py

@@ -1,8 +1,13 @@
 import importlib
 import os
-from typing import Optional
+from typing import Any, Optional
 
-from langchain_community.llms import Together
+try:
+    from langchain_together import ChatTogether
+except ImportError:
+    raise ImportError(
+        "Please install the langchain_together package by running `pip install langchain_together==0.1.3`."
+    )
 
 from embedchain.config import BaseLlmConfig
 from embedchain.helpers.json_serializable import register_deserializable
@@ -24,20 +29,43 @@ class TogetherLlm(BaseLlm):
         if not self.config.api_key and "TOGETHER_API_KEY" not in os.environ:
             raise ValueError("Please set the TOGETHER_API_KEY environment variable or pass it in the config.")
 
-    def get_llm_model_answer(self, prompt):
+    def get_llm_model_answer(self, prompt) -> tuple[str, Optional[dict[str, Any]]]:
         if self.config.system_prompt:
             raise ValueError("TogetherLlm does not support `system_prompt`")
-        return TogetherLlm._get_answer(prompt=prompt, config=self.config)
+
+        if self.config.token_usage:
+            response, token_info = self._get_answer(prompt, self.config)
+            model_name = "together/" + 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) -> str:
-        api_key = config.api_key or os.getenv("TOGETHER_API_KEY")
-        llm = Together(
-            together_api_key=api_key,
-            model=config.model,
-            max_tokens=config.max_tokens,
-            temperature=config.temperature,
-            top_p=config.top_p,
-        )
+        api_key = config.api_key or os.environ["TOGETHER_API_KEY"]
+        kwargs = {
+            "model_name": config.model or "mixtral-8x7b-32768",
+            "temperature": config.temperature,
+            "max_tokens": config.max_tokens,
+            "together_api_key": api_key,
+        }
 
-        return llm.invoke(prompt)
+        chat = ChatTogether(**kwargs)
+        chat_response = chat.invoke(prompt)
+        if config.token_usage:
+            return chat_response.content, chat_response.response_metadata["token_usage"]
+        return chat_response.content