chore: bump version

.github/workflows/CI.yml

@@ -4,6 +4,9 @@ on:
   workflow_dispatch:
   pull_request:
     branches: ["main"]
+  push:
+    branches:
+      - main
 
 permissions:
   contents: read

examples/langchain_variable.py

@@ -32,7 +32,7 @@
 cb = lai.langchain_callback()
 
 # Returns a langchain_openai.ChatOpenAI instance.
-gpt_4o = init_chat_model(
+gpt_4o = init_chat_model(  # type: ignore
     model_provider=prompt.provider,
     **prompt.settings,
 )

literalai/instrumentation/llamaindex/event_handler.py

@@ -100,7 +100,7 @@ def extract_document_info(nodes: List[NodeWithScore]):
 
 
 def build_message_dict(message: ChatMessage):
-    message_dict = {
+    message_dict: GenerationMessage = {
         "role": convert_message_role(message.role),
         "content": message.content,
     }
@@ -144,8 +144,8 @@ def extract_query(x: Union[str, QueryBundle]):
 class LiteralEventHandler(BaseEventHandler):
     """This class handles events coming from LlamaIndex."""
 
-    _client: "LiteralClient" = PrivateAttr(...)
-    _span_handler: "LiteralSpanHandler" = PrivateAttr(...)
+    _client: "LiteralClient" = PrivateAttr()
+    _span_handler: "LiteralSpanHandler" = PrivateAttr()
     runs: Dict[str, List[Step]] = {}
     streaming_run_ids: List[str] = []
     _standalone_step_id: Optional[str] = None
@@ -163,21 +163,18 @@ def __init__(
         object.__setattr__(self, "_client", literal_client)
         object.__setattr__(self, "_span_handler", llama_index_span_handler)
 
-    def _convert_message(
-        self,
-        message: ChatMessage,
-    ):
+    def _convert_message(self, message: ChatMessage):
         tool_calls = message.additional_kwargs.get("tool_calls")
-        msg = GenerationMessage(
-            name=getattr(message, "name", None),
-            role=convert_message_role(message.role),
-            content="",
-        )
-
-        msg["content"] = message.content
-
-        if tool_calls:
-            msg["tool_calls"] = [tool_call.to_dict() for tool_call in tool_calls]
+        msg: GenerationMessage = {
+            "name": getattr(message, "name", None),
+            "role": convert_message_role(message.role),
+            "content": message.content,
+            "tool_calls": (
+                [tool_call.to_dict() for tool_call in tool_calls]
+                if tool_calls
+                else None
+            ),
+        }
 
         return msg
 
@@ -238,7 +235,7 @@ def handle(self, event: BaseEvent, **kwargs) -> None:
                     thread_id=thread_id,
                     content=query,
                 )
-            
+
             # Retrieval wraps the Embedding step in LlamaIndex
             if isinstance(event, RetrievalStartEvent):
                 run = self._client.start_step(

literalai/observability/generation.py

@@ -67,15 +67,16 @@ class BaseGeneration(Utils):
         to_dict(self) -> Dict:
             Converts the generation object to a dictionary.
     """
+
     id: Optional[str] = None
     prompt_id: Optional[str] = None
     provider: Optional[str] = None
     model: Optional[str] = None
     error: Optional[str] = None
-    settings: Optional[Dict] = Field(default_factory=dict)
-    variables: Optional[Dict] = Field(default_factory=dict)
-    tags: Optional[List[str]] = Field(default_factory=list)
-    metadata: Optional[Dict] = Field(default_factory=dict)
+    settings: Optional[Dict] = Field(default_factory=lambda: {})
+    variables: Optional[Dict] = Field(default_factory=lambda: {})
+    tags: Optional[List[str]] = Field(default_factory=lambda: [])
+    metadata: Optional[Dict] = Field(default_factory=lambda: {})
     tools: Optional[List[Dict]] = None
     token_count: Optional[int] = None
     input_token_count: Optional[int] = None
@@ -129,6 +130,7 @@ class CompletionGeneration(BaseGeneration, Utils):
         completion (Optional[str]): The generated completion text.
         type (GenerationType): The type of generation, which is set to GenerationType.COMPLETION.
     """
+
     prompt: Optional[str] = None
     completion: Optional[str] = None
     type = GenerationType.COMPLETION
@@ -177,8 +179,9 @@ class ChatGeneration(BaseGeneration, Utils):
         message_completion (Optional[GenerationMessage]): The completion message of the chat generation.
         type (GenerationType): The type of generation, which is set to GenerationType.CHAT.
     """
+
     type = GenerationType.CHAT
-    messages: Optional[List[GenerationMessage]] = Field(default_factory=list)
+    messages: Optional[List[GenerationMessage]] = Field(default_factory=lambda: [])
     message_completion: Optional[GenerationMessage] = None
 
     def to_dict(self):
@@ -213,4 +216,3 @@ def from_dict(self, generation_dict: Dict):
             messages=generation_dict.get("messages", []),
             message_completion=generation_dict.get("messageCompletion"),
         )
-

literalai/prompt_engineering/prompt.py

@@ -67,7 +67,7 @@ class Prompt(Utils):
 
     Attributes
     ----------
-        template_messages : List[GenerationMessage] 
+        template_messages : List[GenerationMessage]
             The messages that make up the prompt. Messages can be of type `text` or `image`.
             Messages can reference variables.
         variables : List[PromptVariable]
@@ -214,9 +214,9 @@ def to_langchain_chat_prompt_template(self, additional_messages=[]):
 
         class CustomChatPromptTemplate(ChatPromptTemplate):
             orig_messages: Optional[List[GenerationMessage]] = Field(
-                default_factory=list
+                default_factory=lambda: []
             )
-            default_vars: Optional[Dict] = Field(default_factory=dict)
+            default_vars: Optional[Dict] = Field(default_factory=lambda: {})
             prompt_id: Optional[str] = None
 
             def format_messages(self, **kwargs: Any) -> List[BaseMessage]:

literalai/version.py

@@ -1 +1 @@
-__version__ = "0.1.102"
+__version__ = "0.1.103"

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name="literalai",
-    version="0.1.102",  # update version in literalai/version.py
+    version="0.1.103",  # update version in literalai/version.py
     description="An SDK for observability in Python applications",
     long_description=open("README.md").read(),
     long_description_content_type="text/markdown",