Added GCP tokenizer for gemini models

README.md

@@ -26,13 +26,13 @@ ___
 
 ## Supported Models
 
-| LLM Family  | Hosting             | Supported LLMs                          |
-|-------------|---------------------|-----------------------------------------|
-| GPT(s)      | OpenAI endpoint     | `gpt-3.5-turbo`, `gpt-4`, `gpt-4-turbo` |
-| Google LLMs | VertexAI deployment | `text-bison@001`, `gemini-pro`          |
-| Llama2      | Azure deployment    | `llama2-7b`, `llama2-13b`, `llama2-70b` |
-| Mistral     | Azure deployment    | `Mistral-7b`, `Mixtral-7bx8`            |
-| Gemma       | GCP deployment      | `gemma`                                 |
+| LLM Family  | Hosting             | Supported LLMs                                                   |
+|-------------|---------------------|------------------------------------------------------------------|
+| GPT(s)      | OpenAI endpoint     | `gpt-3.5-turbo`, `gpt-4`, `gpt-4-turbo`, `gpt4-o`, `gpt4-o mini` |
+| Google LLMs | VertexAI deployment | `text-bison@001`, `gemini-pro`, `gemini-flash`                   |
+| Llama2      | Azure deployment    | `llama2-7b`, `llama2-13b`, `llama2-70b`                          |
+| Mistral     | Azure deployment    | `Mistral-7b`, `Mixtral-7bx8`                                     |
+| Gemma       | GCP deployment      | `gemma`                                                          |
 
 * Do you already have a subscription to a Cloud Provider for any the models above? Configure
 the model using your credentials and start querying!

allms/defaults/vertex_ai.py

@@ -10,7 +10,7 @@ class PalmModelDefaults:
 
 
 class GeminiModelDefaults:
-    GCP_MODEL_NAME = "gemini-pro"
+    GCP_MODEL_NAME = "gemini-1.5-flash-001"
     MODEL_TOTAL_MAX_TOKENS = 30720
     MAX_OUTPUT_TOKENS = 2048
     TEMPERATURE = 0.0

allms/models/vertexai_gemini.py

@@ -1,10 +1,15 @@
+import typing
 from asyncio import AbstractEventLoop
+
+from langchain_core.prompts import ChatPromptTemplate
 from langchain_google_vertexai import VertexAI
+from vertexai.preview import tokenization
 from typing import Optional
 
 from allms.defaults.general_defaults import GeneralDefaults
 from allms.defaults.vertex_ai import GeminiModelDefaults
 from allms.domain.configuration import VertexAIConfiguration
+from allms.domain.input_data import InputData
 from allms.models.vertexai_base import CustomVertexAI
 from allms.models.abstract import AbstractModel
 
@@ -28,6 +33,8 @@ def __init__(
         self._verbose = verbose
         self._config = config
 
+        self._gcp_tokenizer = tokenization.get_tokenizer_for_model(self._config.gemini_model_name)
+
         super().__init__(
             temperature=temperature,
             model_total_max_tokens=model_total_max_tokens,
@@ -48,4 +55,15 @@ def _create_llm(self) -> VertexAI:
             verbose=self._verbose,
             project=self._config.cloud_project,
             location=self._config.cloud_location
-        )
+        )
+
+    def _get_prompt_tokens_number(self, prompt: ChatPromptTemplate, input_data: InputData) -> int:
+        return self._gcp_tokenizer.count_tokens(
+            prompt.format_prompt(**input_data.input_mappings).to_string()
+        ).total_tokens
+
+    def _get_model_response_tokens_number(self, model_response: typing.Optional[str]) -> int:
+        if model_response:
+            return self._gcp_tokenizer.count_tokens(model_response).total_tokens
+        return 0
+