chore: Updated the structure

ai_agent_tutorials/ai_reasoning_agent/reasoning_agent.py

@@ -0,0 +1,19 @@
+from phi.agent import Agent
+from phi.model.openai import OpenAIChat
+from phi.cli.console import console
+
+regular_agent = Agent(model=OpenAIChat(id="gpt-4o-mini"), markdown=True)
+
+reasoning_agent = Agent(
+    model=OpenAIChat(id="gpt-4o"),
+    reasoning=True,
+    markdown=True,
+    structured_outputs=True,
+)
+
+task = "How many 'r' are in the word 'supercalifragilisticexpialidocious'?"
+
+console.rule("[bold green]Regular Agent[/bold green]")
+regular_agent.print_response(task, stream=True)
+console.rule("[bold yellow]Reasoning Agent[/bold yellow]")
+reasoning_agent.print_response(task, stream=True, show_full_reasoning=True)

ai_agent_tutorials/legal_ai_agent/legal_agent.py

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+from phi.agent import Agent
+from phi.model.openai import OpenAIChat
+from phi.knowledge.pdf import PDFKnowledgeBase, PDFReader
+from phi.vectordb.lancedb import LanceDb, SearchType
+from phi.playground import Playground, serve_playground_app
+from phi.tools.duckduckgo import DuckDuckGo
+
+# Set up configurations
+DB_URI = "tmp/legal_docs_db"
+
+# Create a knowledge base for legal documents
+knowledge_base = PDFKnowledgeBase(
+    path="tmp/legal_docs",
+    vector_db=LanceDb(
+        table_name="legal_documents",
+        uri=DB_URI,
+        search_type=SearchType.vector
+    ),
+    reader=PDFReader(chunk=True),
+    num_documents=5
+)
+
+# Create the agent
+agent = Agent(
+    model=OpenAIChat(id="gpt-4"),
+    agent_id="legal-analysis-agent",
+    knowledge=knowledge_base,
+    tools=[DuckDuckGo()],
+    show_tool_calls=True,
+    markdown=True,
+)
+
+app = Playground(agents=[agent]).get_app()
+
+if __name__ == "__main__":
+    serve_playground_app("legal_agent:app", reload=True)

ai_agent_tutorials/legal_ai_agent/requirements.txt

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+streamlit
+phidata
+openai
+lancedb
+tantivy
+pypdf
+duckduckgo-search