Update README.md

README.md

@@ -28,8 +28,8 @@ We provide custom code for both converting tool definitions into the system prom
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("meetkai/functionary-small-v2.5", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("meetkai/functionary-small-v2.5", device_map="auto", trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("meetkai/functionary-medium-v3.1", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("meetkai/functionary-medium-v3.1", device_map="auto", trust_remote_code=True)
 
 tools = [
     {
@@ -61,9 +61,9 @@ print(tokenizer.decode(pred.cpu()[0]))
 
 ## Prompt Template
 
-We convert function definitions to a similar text to TypeScript definitions. Then we inject these definitions as system prompts. After that, we inject the default system prompt. Then we start the conversation messages.
+We convert function definitions to a similar text to Meta's Llama 3.1 definitions. Then we inject these definitions as system prompts. After that, we inject the default system prompt. Then we start the conversation messages.
 
-This formatting is also available via our vLLM server which we process the functions into Typescript definitions encapsulated in a system message and use a pre-defined Transformers chat template. This means that lists of messages can be formatted for you with the apply_chat_template() method within our server:
+This formatting is also available via our vLLM server which we process the functions into definitions encapsulated in a system message and use a pre-defined Transformers chat template. This means that lists of messages can be formatted for you with the apply_chat_template() method within our server:
 
 ```python
 from openai import OpenAI
@@ -101,21 +101,42 @@ will yield:
 ```
 <|start_header_id|>system<|end_header_id|>
 
-// Supported function definitions that should be called when necessary.
-namespace functions {
+Environment: ipython
 
-// Get the current weather
-type get_current_weather = (_: {
-// The city and state, e.g. San Francisco, CA
-location: string,
-}) => any;
+Cutting Knowledge Date: December 2023
 
-} // namespace functions<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+You have access to the following functions:
+
+Use the function 'get_current_weather' to 'Get the current weather'
+{"name": "get_current_weather", "description": "Get the current weather", "parameters": {"type": "object", "properties": {"location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}},"required": ["location"]}}
+
+
+Think very carefully before calling functions.
+If a you choose to call a function ONLY reply in the following format:
+<{start_tag}={function_name}>{parameters}{end_tag}
+where
+
+start_tag => `<function`
+parameters => a JSON dict with the function argument name as key and function argument value as value.
+end_tag => `</function>`
+
+Here is an example,
+<function=example_function_name>{"example_name": "example_value"}</function>
+
+Reminder:
+- If looking for real time information use relevant functions before falling back to brave_search
+- Function calls MUST follow the specified format, start with <function= and end with </function>
+- Required parameters MUST be specified
+- Only call one function at a time
+- Put the entire function call reply on one line
+
+<|eot_id|><|start_header_id|>user<|end_header_id|>
 
 What is the weather for Istanbul?
 ```
 
-A more detailed example is provided [here](https://github.com/MeetKai/functionary/blob/main/tests/prompt_test_v2.llama3.txt). 
+A more detailed example is provided [here](https://github.com/MeetKai/functionary/blob/main/tests/prompt_test_v3-llama3.1.txt).
 
 ## Run the model