Added vLLM_example.py

playground/demos/vLLM/vLLM_example.py

@@ -0,0 +1,56 @@
+import os
+import asyncio
+from swarms import Agent, OpenAIChat
+from swarms.prompts.finance_agent_sys_prompt import (
+    FINANCIAL_AGENT_SYS_PROMPT,
+)
+
+# Set the OpenAI environment to use vLLM
+api_key = os.getenv("OPENAI_API_KEY") or "EMPTY" # for vllm
+api_base = os.getenv("OPENAI_API_BASE") or "http://localhost:8000/v1" # for vllm
+
+# Create an instance of the OpenAIChat class
+model = OpenAIChat(
+    base_url=api_base, api_key=api_key, model="NousResearch/Meta-Llama-3-8B-Instruct", temperature=0.5, streaming=True, verbose=True
+)
+
+# Initialize the agent
+agent = Agent(
+    agent_name="Financial-Analysis-Agent",
+    system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
+    llm=model,
+    max_loops=2,
+    autosave=True,
+    # dynamic_temperature_enabled=True,
+    dashboard=False,
+    verbose=True,
+    streaming_on=True,
+    # interactive=True, # Set to False to disable interactive mode
+    dynamic_temperature_enabled=False,
+    saved_state_path="finance_agent.json",
+    # tools=[#Add your functions here# ],
+    # stopping_token="Stop!",
+    # interactive=True,
+    # docs_folder="docs", # Enter your folder name
+    # pdf_path="docs/finance_agent.pdf",
+    # sop="Calculate the profit for a company.",
+    # sop_list=["Calculate the profit for a company."],
+    user_name="RAH@EntangleIT.com",
+    # # docs=
+    # # docs_folder="docs",
+    retry_attempts=3,
+    # context_length=1000,
+    # tool_schema = dict
+    context_length=200000,
+    # tool_schema=
+    # tools
+    # agent_ops_on=True,
+)
+
+async def startup_event():
+    agent.streaming(
+        "What are the components of a startups stock incentive equity plan"
+    )
+
+if __name__ == "__main__":
+    asyncio.run(startup_event())