Chore/final website updates

langtest/modelhandler/transformers_modelhandler.py

@@ -810,6 +810,9 @@ def predict(self, text: Union[str, dict], prompt: dict, **kwargs) -> str:
                     text = prompt_template.format(**text)
                     messages = [*examples, {"role": "user", "content": text}]
                 else:
+                    if isinstance(text, dict):
+                        prompt_template = SimplePromptTemplate(**prompt)
+                        text = prompt_template.format(**text)
                     messages = [{"role": "user", "content": text}]
                 output = self.model._generate([messages])
                 return output[0].strip()

langtest/prompts.py

@@ -131,7 +131,7 @@ def get_input_variables(self):
 
     def prompt_style(self):
         """Generate a prompt based on the prompt type."""
-        if self.prompt_type == "chat":
+        if self.prompt_type in ["chat", "instruct"]:
             from langchain.prompts import (
                 ChatPromptTemplate,
                 FewShotChatMessagePromptTemplate,
@@ -154,7 +154,7 @@ def prompt_style(self):
             )
             return final_prompt
 
-        elif self.prompt_type == "instruct":
+        elif self.prompt_type == "completion":
             from langchain.prompts import FewShotPromptTemplate, PromptTemplate
 
             template = "".join(v for _, v in self.get_template)

pyproject.toml

@@ -99,7 +99,8 @@ metaflow = ["metaflow"]
 mlflow = ["mlflow"]
 datasets = ["datasets"]
 matplotlib = ["matplotlib"]
-databricks = ["langchain", "langchain-databricks", "langchain-community"]
+databricks = ["langchain", "langchain-databricks", "langchain-community", "langchain-openai"]
+llms = ["langchain", "langchain-community", "langchain-openai", "langchain-databricks"]
 
 [tool.poetry.group.dev.dependencies]
 ipdb = "^0.13.13"