v2.2.0

README.md

@@ -187,6 +187,7 @@ duckdb_assistant = DuckDbAssistant(
             }
         ]
     }),
+    show_tool_calls=True,
 )
 
 duckdb_assistant.print_response("What is the average rating of movies? Show me the SQL.")
@@ -231,7 +232,7 @@ INFO     Running: SELECT AVG(Rating) AS average_rating
 <summary><h3>Structured output from a Movie Assistant</h3></summary>
 
 One of our favorite features is generating structured data (i.e. a pydantic model) from sparse information.
-Meaning we can use LLMs to return pydantic models and generate content which previously could not be possible.
+Meaning we can use Assistants to return pydantic models and generate content which previously could not be possible.
 In this example, our movie assistant generates an object of the `MovieScript` class.
 
 - Create a file `movie_assistant.py`

phi/assistant/__init__.py

@@ -1 +1 @@
-from phi.assistant.assistant import Assistant, AssistantRow
+from phi.assistant.assistant import Assistant, AssistantRow, AssistantMemory, AssistantStorage, KnowledgeBase

phi/llm/openai/chat.py

@@ -31,7 +31,7 @@
 
 class OpenAIChat(LLM):
     name: str = "OpenAIChat"
-    model: str = "gpt-3.5-turbo-1106"
+    model: str = "gpt-4-1106-preview"
     seed: Optional[int] = None
     max_tokens: Optional[int] = None
     temperature: Optional[float] = None

phi/task/llm/llm_task.py

@@ -240,11 +240,13 @@ def get_system_prompt(self) -> Optional[str]:
             _instructions.append("Search the knowledge base for information")
         if self.knowledge_base is not None:
             _instructions.append("Always prefer information from the knowledge base over your own knowledge.")
-            _instructions.extend([
-                "Do not use phrases like 'based on the information provided'.",
-                "Never mention about your knowledge base or the tools you have access to.",
-                "If you don't know the answer, say 'I don't know'.",
-            ])
+            _instructions.extend(
+                [
+                    "Do not use phrases like 'based on the information provided'.",
+                    "Never mention about your knowledge base or the tools you have access to.",
+                    "If you don't know the answer, say 'I don't know'.",
+                ]
+            )
 
         # Add instructions for using tools
         if self.tool_calls or self.tools is not None:

phi/tools/python.py

@@ -53,6 +53,8 @@ def save_to_file_and_run(
         If successful, returns the value of `variable_to_return` if provided otherwise returns a success message.
         If failed, returns an error message.
 
+        Make sure the file_name ends with `.py`
+
         :param file_name: The name of the file the code will be saved to.
         :param code: The code to save and run.
         :param variable_to_return: The variable to return.

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "phidata"
-version = "2.2.0.dev5"
-description = "AI Toolkit for Engineers"
+version = "2.2.0"
+description = "Build AI Assistants using language models"
 requires-python = ">=3.7"
 readme = "README.md"
 authors = [