change-knowledge_base-to-knowledge-phi-2000

cookbook/integrations/chromadb/agent.py

@@ -1,44 +1,22 @@
-import typer
-from rich.prompt import Prompt
-from typing import Optional
-
 from phi.agent import Agent
 from phi.knowledge.pdf import PDFUrlKnowledgeBase
 from phi.vectordb.chroma import ChromaDb
 
-
 knowledge_base = PDFUrlKnowledgeBase(
     urls=["https://phi-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
     vector_db=ChromaDb(collection="recipes"),
 )
-
 # Comment out after first run
 knowledge_base.load(recreate=False)
 
+agent = Agent(
+    knowledge=knowledge_base,
+    # Show tool calls in the response
+    show_tool_calls=True,
+    # Enable the agent to search the knowledge base
+    search_knowledge=True,
+    # Enable the agent to read the chat history
+    read_chat_history=True,
+)
 
-def pdf_agent(user: str = "user"):
-    run_id: Optional[str] = None
-
-    agent = Agent(
-        run_id=run_id,
-        user_id=user,
-        knowledge_base=knowledge_base,
-        use_tools=True,
-        show_tool_calls=True,
-        debug_mode=True,
-    )
-    if run_id is None:
-        run_id = agent.run_id
-        print(f"Started Run: {run_id}\n")
-    else:
-        print(f"Continuing Run: {run_id}\n")
-
-    while True:
-        message = Prompt.ask(f"[bold] :sunglasses: {user} [/bold]")
-        if message in ("exit", "bye"):
-            break
-        agent.print_response(message)
-
-
-if __name__ == "__main__":
-    typer.run(pdf_agent)
+agent.print_response("How do I make pad thai?", markdown=True)

cookbook/integrations/lancedb/agent.py

@@ -1,12 +1,7 @@
-import typer
-from rich.prompt import Prompt
-from typing import Optional
-
 from phi.agent import Agent
 from phi.knowledge.pdf import PDFUrlKnowledgeBase
 from phi.vectordb.lancedb import LanceDb
 
-# type: ignore
 db_url = "/tmp/lancedb"
 
 knowledge_base = PDFUrlKnowledgeBase(
@@ -17,31 +12,14 @@
 # Comment out after first run
 knowledge_base.load(recreate=False)
 
+agent = Agent(
+    knowledge=knowledge_base,
+    # Show tool calls in the response
+    show_tool_calls=True,
+    # Enable the agent to search the knowledge base
+    search_knowledge=True,
+    # Enable the agent to read the chat history
+    read_chat_history=True,
+)
 
-def pdf_agent(user: str = "user"):
-    run_id: Optional[str] = None
-
-    agent = Agent(
-        run_id=run_id,
-        user_id=user,
-        knowledge_base=knowledge_base,
-        use_tools=True,
-        show_tool_calls=True,
-        # Uncomment the following line to use traditional RAG
-        # add_references_to_prompt=True,
-    )
-    if run_id is None:
-        run_id = agent.run_id
-        print(f"Started Run: {run_id}\n")
-    else:
-        print(f"Continuing Run: {run_id}\n")
-
-    while True:
-        message = Prompt.ask(f"[bold] :sunglasses: {user} [/bold]")
-        if message in ("exit", "bye"):
-            break
-        agent.print_response(message)
-
-
-if __name__ == "__main__":
-    typer.run(pdf_agent)
+agent.print_response("How do I make pad thai?", markdown=True)

cookbook/integrations/pinecone/agent.py

@@ -1,13 +1,10 @@
-import os
-import typer
-from typing import Optional
-from rich.prompt import Prompt
+from os import getenv
 
 from phi.agent import Agent
 from phi.knowledge.pdf import PDFUrlKnowledgeBase
 from phi.vectordb.pineconedb import PineconeDB
 
-api_key = os.getenv("PINECONE_API_KEY")
+api_key = getenv("PINECONE_API_KEY")
 index_name = "thai-recipe-index"
 
 vector_db = PineconeDB(
@@ -24,35 +21,16 @@
 )
 
 # Comment out after first run
-knowledge_base.load(recreate=False, upsert=True)
-
-
-def pinecone_agent(user: str = "user"):
-    run_id: Optional[str] = None
-
-    agent = Agent(
-        run_id=run_id,
-        user_id=user,
-        knowledge_base=knowledge_base,
-        use_tools=True,
-        show_tool_calls=True,
-        debug_mode=True,
-        # Uncomment the following line to use traditional RAG
-        # add_references_to_prompt=True,
-    )
-
-    if run_id is None:
-        run_id = agent.run_id
-        print(f"Started Run: {run_id}\n")
-    else:
-        print(f"Continuing Run: {run_id}\n")
-
-    while True:
-        message = Prompt.ask(f"[bold] :sunglasses: {user} [/bold]")
-        if message in ("exit", "bye"):
-            break
-        agent.print_response(message)
-
+knowledge_base.load(recreate=False)
+
+agent = Agent(
+    knowledge=knowledge_base,
+    # Show tool calls in the response
+    show_tool_calls=True,
+    # Enable the agent to search the knowledge base
+    search_knowledge=True,
+    # Enable the agent to read the chat history
+    read_chat_history=True,
+)
 
-if __name__ == "__main__":
-    typer.run(pinecone_agent)
+agent.print_response("How do I make pad thai?", markdown=True)

cookbook/integrations/qdrant/agent.py

@@ -1,14 +1,11 @@
-import os
-import typer
-from typing import Optional
-from rich.prompt import Prompt
+from os import getenv
 
 from phi.agent import Agent
 from phi.knowledge.pdf import PDFUrlKnowledgeBase
 from phi.vectordb.qdrant import Qdrant
 
-api_key = os.getenv("QDRANT_API_KEY")
-qdrant_url = os.getenv("QDRANT_URL")
+api_key = getenv("QDRANT_API_KEY")
+qdrant_url = getenv("QDRANT_URL")
 collection_name = "thai-recipe-index"
 
 vector_db = Qdrant(
@@ -23,36 +20,16 @@
 )
 
 # Comment out after first run
-knowledge_base.load(recreate=True, upsert=True)
-
-
-def qdrant_agent(user: str = "user"):
-    run_id: Optional[str] = None
-
-    agent = Agent(
-        run_id=run_id,
-        user_id=user,
-        knowledge_base=knowledge_base,
-        tool_calls=True,
-        use_tools=True,
-        show_tool_calls=True,
-        debug_mode=True,
-        # Uncomment the following line to use traditional RAG
-        # add_references_to_prompt=True,
-    )
-
-    if run_id is None:
-        run_id = agent.run_id
-        print(f"Started Run: {run_id}\n")
-    else:
-        print(f"Continuing Run: {run_id}\n")
-
-    while True:
-        message = Prompt.ask(f"[bold] :sunglasses: {user} [/bold]")
-        if message in ("exit", "bye"):
-            break
-        agent.print_response(message)
-
+knowledge_base.load(recreate=False)
+
+agent = Agent(
+    knowledge=knowledge_base,
+    # Show tool calls in the response
+    show_tool_calls=True,
+    # Enable the agent to search the knowledge base
+    search_knowledge=True,
+    # Enable the agent to read the chat history
+    read_chat_history=True,
+)
 
-if __name__ == "__main__":
-    typer.run(qdrant_agent)
+agent.print_response("How do I make pad thai?", markdown=True)

cookbook/integrations/singlestore/agent.py

@@ -1,10 +1,8 @@
-import typer
-from typing import Optional
 from os import getenv
 
 from sqlalchemy.engine import create_engine
 
-from phi.assistant import Assistant
+from phi.agent import Agent
 from phi.knowledge.pdf import PDFUrlKnowledgeBase
 from phi.vectordb.singlestore import S2VectorDb
 
@@ -33,28 +31,12 @@
 # Comment out after first run
 knowledge_base.load(recreate=False)
 
-
-def pdf_assistant(user: str = "user"):
-    run_id: Optional[str] = None
-
-    assistant = Assistant(
-        run_id=run_id,
-        user_id=user,
-        knowledge_base=knowledge_base,
-        use_tools=True,
-        show_tool_calls=True,
-        # Uncomment the following line to use traditional RAG
-        # add_references_to_prompt=True,
-    )
-    if run_id is None:
-        run_id = assistant.run_id
-        print(f"Started Run: {run_id}\n")
-    else:
-        print(f"Continuing Run: {run_id}\n")
-
-    while True:
-        assistant.cli_app(markdown=True)
-
-
-if __name__ == "__main__":
-    typer.run(pdf_assistant)
+agent = Agent(
+    knowledge_base=knowledge_base,
+    # Show tool calls in the response
+    show_tool_calls=True,
+    # Enable the agent to search the knowledge base
+    search_knowledge=True,
+    # Enable the agent to read the chat history
+    read_chat_history=True,
+)

cookbook/knowledge/arxiv_kb.py

@@ -18,8 +18,8 @@
 
 # Create an agent with the knowledge base
 agent = Agent(
-    knowledge_base=knowledge_base,
-    add_references_to_prompt=True,
+    knowledge=knowledge_base,
+    add_context=True,
 )
 
 # Ask the agent about the knowledge base

cookbook/knowledge/combined_kb.py

@@ -62,8 +62,8 @@
 
 # Initialize the Agent with the combined knowledge base
 agent = Agent(
-    knowledge_base=knowledge_base,
-    add_references_to_prompt=True,
+    knowledge=knowledge_base,
+    add_context=True,
 )
 
 knowledge_base.load(recreate=False)

cookbook/knowledge/csv_kb.py

@@ -20,8 +20,8 @@
 
 # Initialize the Agent with the knowledge_base
 agent = Agent(
-    knowledge_base=knowledge_base,
-    add_references_to_prompt=True,
+    knowledge=knowledge_base,
+    add_context=True,
 )
 
 # Use the agent

cookbook/knowledge/docx_kb.py

@@ -19,8 +19,8 @@
 
 # Create an agent with the knowledge base
 agent = Agent(
-    knowledge_base=knowledge_base,
-    add_references_to_prompt=True,
+    knowledge=knowledge_base,
+    add_context=True,
 )
 
 # Ask the agent about the knowledge base

cookbook/knowledge/json_kb.py

@@ -20,8 +20,8 @@
 
 # Initialize the Agent with the knowledge_base
 agent = Agent(
-    knowledge_base=knowledge_base,
-    add_references_to_prompt=True,
+    knowledge=knowledge_base,
+    add_context=True,
 )
 
 # Use the agent