v2.4.3

cookbook/assistants/multiply.py

@@ -17,4 +17,6 @@ def exponentiate(base: int, exponent: int) -> str:
 
 
 assistant = Assistant(tools=[multiply, add, exponentiate])
-assistant.print_response("Take 3 to the fifth power and multiply that by the sum of twelve and three, then square the whole result. Only show the result.")
+assistant.print_response(
+    "Take 3 to the fifth power and multiply that by the sum of twelve and three, then square the whole result. Only show the result."
+)

cookbook/knowledge/llamaindex.py

@@ -1,32 +1,31 @@
-# Import necessary modules
-# pip install llama-index-core llama-index-readers-file llama-index-embeddings-openai
+"""
+Import necessary modules
+pip install llama-index-core llama-index-readers-file llama-index-embeddings-openai phidata
+"""
 
+from pathlib import Path
+from shutil import rmtree
+
+import httpx
 from phi.assistant import Assistant
 from phi.knowledge.llamaindex import LlamaIndexKnowledgeBase
-
 from llama_index.core import (
     SimpleDirectoryReader,
     StorageContext,
     VectorStoreIndex,
 )
-
 from llama_index.core.retrievers import VectorIndexRetriever
-
 from llama_index.core.node_parser import SentenceSplitter
 
-import os
-
-import requests
-
-os.makedirs("data\paul_graham", exist_ok=True)
 
+data_dir = Path(__file__).parent.parent.parent.joinpath("wip", "data", "paul_graham")
+if data_dir.is_dir():
+    rmtree(path=data_dir, ignore_errors=True)
+data_dir.mkdir(parents=True, exist_ok=True)
 
 url = "https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt"
-
-file_path = "cookbook\knowledge\data\paul_graham\paul_graham_essay.txt"
-
-response = requests.get(url)
-
+file_path = data_dir.joinpath("paul_graham_essay.txt")
+response = httpx.get(url)
 if response.status_code == 200:
     with open(file_path, "wb") as file:
         file.write(response.content)
@@ -35,7 +34,7 @@
     print("Failed to download the file")
 
 
-documents = SimpleDirectoryReader("cookbook\knowledge\data\paul_graham").load_data()
+documents = SimpleDirectoryReader(str(data_dir)).load_data()
 
 splitter = SentenceSplitter(chunk_size=1024)
 
@@ -47,11 +46,11 @@
 
 retriever = VectorIndexRetriever(index)
 
-# # Create a knowledge base from the vector store
+# Create a knowledge base from the vector store
 knowledge_base = LlamaIndexKnowledgeBase(retriever=retriever)
 
-# # Create an assistant with the knowledge base
+# Create an assistant with the knowledge base
 assistant = Assistant(knowledge_base=knowledge_base, search_knowledge=True, debug_mode=True, show_tool_calls=True)
 
-# # Use the assistant to ask a question and print a response.
+# Use the assistant to ask a question and print a response.
 assistant.print_response("Explain what this text means: low end eats the high end", markdown=True)

cookbook/workflows/investment.py

@@ -13,7 +13,7 @@
 
 
 reports_dir = Path(__file__).parent.parent.parent.joinpath("wip", "reports")
-if reports_dir.exists():
+if reports_dir.is_dir():
     rmtree(path=reports_dir, ignore_errors=True)
 reports_dir.mkdir(parents=True, exist_ok=True)
 

phi/knowledge/llamaindex.py

@@ -5,11 +5,8 @@
 from phi.utils.log import logger
 
 try:
-    # I am aadding this to assert that the retreiver we receive is of the correct type.
-    from llama_index.core.retrievers import BaseRetriever
-
     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 langchain`.")
 
@@ -30,7 +27,6 @@ def search(self, query: str, num_documents: Optional[int] = None) -> List[Docume
             List[Document]: A list of relevant documents matching the query.
         Raises:
             ValueError: If the retriever is not of type BaseRetriever.
-
         """
         if not isinstance(self.retriever, BaseRetriever):
             raise ValueError(f"Retriever is not of type BaseRetriever: {self.retriever}")

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "phidata"
-version = "2.4.2"
+version = "2.4.3"
 description = "Memory, knowledge and tools for LLMs."
 requires-python = ">=3.7"
 readme = "README.md"
@@ -94,8 +94,8 @@ module = [
   "kubernetes.*",
   "lancedb.*",
   "langchain.*",
-  "langchain.*",
   "langchain_core.*",
+  "llama_index.*",
   "mistralai.*",
   "newspaper.*",
   "nest_asyncio.*",