v2.4.17

cookbook/llms/groq/finance.py

@@ -7,7 +7,6 @@
  tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, stock_fundamentals=True, company_news=True)],
  show_tool_calls=True,
 )
-assistant.cli_app(markdown=True, stream=False, user="Groq")
-# assistant.print_response("What's the NVDA stock price", markdown=True, stream=False)
-# assistant.print_response("Share NVDA analyst recommendations", markdown=True, stream=False)
-# assistant.print_response("Summarize fundamentals for TSLA", markdown=True, stream=False)
+assistant.print_response("What's the NVDA stock price", markdown=True)
+assistant.print_response("Share NVDA analyst recommendations", markdown=True)
+assistant.print_response("Summarize fundamentals for TSLA", markdown=True)

phi/knowledge/llamaindex.py

@@ -8,7 +8,9 @@
  from llama_index.core.schema import NodeWithScore
  from llama_index.core.retrievers import BaseRetriever
 except ImportError:
- raise ImportError("The `llama-index-core` package is not installed. Please install it via `pip install llama-index-core`.")
+ raise ImportError(
+ "The `llama-index-core` package is not installed. Please install it via `pip install llama-index-core`."
+ )
 
 
 class LlamaIndexKnowledgeBase(AssistantKnowledge):

phi/llm/groq/groq.py

@@ -10,8 +10,6 @@
 
 try:
  from groq import Groq as GroqClient
- from groq.types.chat.chat_completion import ChatCompletion, ChoiceMessage
- from groq.lib.chat_completion_chunk import ChatCompletionChunk, ChoiceDelta, ChoiceDeltaToolCall
 except ImportError:
  logger.error("`groq` not installed")
  raise
@@ -148,14 +146,14 @@ def to_dict(self) -> Dict[str, Any]:
  _dict["tool_choice"] = self.tool_choice
  return _dict
 
- def invoke(self, messages: List[Message]) -> ChatCompletion:
+ def invoke(self, messages: List[Message]) -> Any:
  return self.client.chat.completions.create(
  model=self.model,
  messages=[m.to_dict() for m in messages], # type: ignore
  **self.api_kwargs,
  )
 
- def invoke_stream(self, messages: List[Message]) -> Iterator[ChatCompletionChunk]:
+ def invoke_stream(self, messages: List[Message]) -> Iterator[Any]:
  yield from self.client.chat.completions.create(
  model=self.model,
  messages=[m.to_dict() for m in messages], # type: ignore
@@ -171,14 +169,14 @@ def response(self, messages: List[Message]) -> str:
 
  response_timer = Timer()
  response_timer.start()
- response: ChatCompletion = self.invoke(messages=messages)
+ response = self.invoke(messages=messages)
  response_timer.stop()
  logger.debug(f"Time to generate response: {response_timer.elapsed:.4f}s")
  # logger.debug(f"Groq response type: {type(response)}")
  # logger.debug(f"Groq response: {response}")
 
  # -*- Parse response
- response_message: ChoiceMessage = response.choices[0].message
+ response_message = response.choices[0].message
 
  # -*- Create assistant message
  assistant_message = Message(
@@ -248,18 +246,18 @@ def response_stream(self, messages: List[Message]) -> Iterator[str]:
 
  assistant_message_role = None
  assistant_message_content = ""
- assistant_message_tool_calls: Optional[List[ChoiceDeltaToolCall]] = None
+ assistant_message_tool_calls: Optional[List[Any]] = None
  response_timer = Timer()
  response_timer.start()
  for response in self.invoke_stream(messages=messages):
  # logger.debug(f"Groq response type: {type(response)}")
  # logger.debug(f"Groq response: {response}")
  # -*- Parse response
- response_delta: ChoiceDelta = response.choices[0].delta
+ response_delta = response.choices[0].delta
  if assistant_message_role is None and response_delta.role is not None:
  assistant_message_role = response_delta.role
  response_content: Optional[str] = response_delta.content
- response_tool_calls: Optional[List[ChoiceDeltaToolCall]] = response_delta.tool_calls
+ response_tool_calls: Optional[List[Any]] = response_delta.tool_calls
 
  # -*- Return content if present, otherwise get tool call
  if response_content is not None:

phi/tools/pubmed.py

@@ -26,7 +26,7 @@ def fetch_pubmed_ids(self, query: str, max_results: int, email: str) -> List[str
  "email": email,
  "usehistory": "y",
  }
- response = httpx.get(url, params=params)
+ response = httpx.get(url, params=params) # type: ignore
  root = ElementTree.fromstring(response.content)
  return [id_elem.text for id_elem in root.findall(".//Id") if id_elem.text is not None]
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "phidata"
-version = "2.4.16"
+version = "2.4.17"
 description = "Memory, knowledge and tools for LLMs."
 requires-python = ">=3.7"
 readme = "README.md"