| |
| |
| |
| from openai import OpenAI |
|
|
| openai_api_key = "EMPTY" |
| openai_api_base = "http://localhost:8000/v1" |
|
|
| client = OpenAI( |
| api_key=openai_api_key, |
| base_url=openai_api_base, |
| ) |
|
|
| chat_response = client.chat.completions.create( |
| model="/root/llama_3.1_8b_function_calling/checkpoint-669", |
| messages=[ |
| {"role": "system", "content": """You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows: |
| <tool_call> |
| {"name": <function-name>,"arguments": <args-dict>} |
| </tool_call> |
| |
| Here are the available tools: |
| <tools> { |
| "name": "create_new_user", |
| "description": "Creates a new user in the database with the provided username, email, and encrypted password.", |
| "parameters": { |
| "properties": { |
| "username": { |
| "type": "string", |
| "description": "The username for the new user." |
| }, |
| "email": { |
| "type": "string", |
| "description": "The email address for the new user.", |
| "format": "email" |
| }, |
| "password": { |
| "type": "string", |
| "description": "The password for the new user which will be encrypted before storage." |
| } |
| }, |
| "required": [ |
| "username", |
| "email", |
| "password" |
| ] |
| }, |
| "required": [ |
| "username", |
| "email", |
| "password" |
| ] |
| } </tools>"""}, |
| {"role": "user", "content": "Hey, I need to create a new account for our project management system. Can you help me with that?"}] |
| |
| |
| ) |
|
|
| print("Chat response:", chat_response) |