refactor: add remaining prompting attributes

Author: lpm0073

api/terraform/python/openai_api/lambda_openai_function/lambda_handler.py

@@ -77,13 +77,16 @@ def handler(event, context):
         request_meta_data = request_meta_data_factory(model, object_type, temperature, max_tokens, input_text)
 
         # does the prompt have anything to do with any of the search terms defined in a plugin?
+        # FIX NOTE: need to decide on how to resolve which of many plugin values sets to use for model, temperature, max_tokens
         for plugin in plugins:
             if search_terms_are_in_messages(
                 messages=messages,
                 search_terms=plugin.selector.search_terms.strings,
                 search_pairs=plugin.selector.search_terms.pairs,
             ):
-                model = "gpt-3.5-turbo-1106"
+                model = plugin.prompting.model
+                temperature = plugin.prompting.temperature
+                max_tokens = plugin.prompting.max_tokens
                 messages = customized_prompt(plugin=plugin, messages=messages)
                 custom_tool = plugin_tool_factory(plugin=plugin)
                 tools.append(custom_tool)

api/terraform/python/openai_api/lambda_openai_function/plugin_loader.py

@@ -11,7 +11,7 @@
 
 import yaml
 from openai_api.common.conf import settings
-from openai_api.common.const import PYTHON_ROOT
+from openai_api.common.const import PYTHON_ROOT, VALID_CHAT_COMPLETION_MODELS
 from pydantic import BaseModel, Field, ValidationError, field_validator, root_validator
 
 
@@ -55,24 +55,6 @@ def to_json(self) -> json:
         raise NotImplementedError
 
 
-class SystemPrompt(PluginBase):
-    """System prompt of a Plugin object"""
-
-    system_prompt: str = Field(..., description="System prompt")
-
-    @field_validator("system_prompt")
-    @classmethod
-    def validate_system_prompt(cls, system_prompt) -> str:
-        """Validate the system_prompt field"""
-        if not isinstance(system_prompt, str):
-            do_error(class_name=cls.__name__, err=f"Expected a string but received {type(system_prompt)}")
-        return system_prompt
-
-    def to_json(self) -> json:
-        """Return the plugin as a JSON object"""
-        return self.system_prompt
-
-
 class SearchTerms(PluginBase):
     """Search terms of a Plugin object"""
 
@@ -146,7 +128,12 @@ class Prompting(PluginBase):
     """Prompting child class of a Plugin object"""
 
     plugin_json: dict = Field(..., description="Plugin object")
-    system_prompt: SystemPrompt = Field(None, description="System prompt of the plugin object")
+
+    # attributes
+    system_prompt: str = Field("", description="System prompt of the prompt")
+    model: str = Field("gpt-3.5-turbo-1106", description="Model of the system prompt")
+    temperature: float = Field(0.0, description="Temperature of the system prompt")
+    max_tokens: int = Field(0, description="Max tokens of the system prompt")
 
     @root_validator(pre=True)
     def set_fields(cls, values):
@@ -155,7 +142,10 @@ def set_fields(cls, values):
         if not isinstance(plugin_json, dict):
             raise ValueError(f"Expected plugin_json to be a dict but received {type(plugin_json)}")
         if plugin_json:
-            values["system_prompt"] = SystemPrompt(system_prompt=plugin_json["system_prompt"])
+            values["system_prompt"] = plugin_json["system_prompt"]
+            values["model"] = plugin_json["model"]
+            values["temperature"] = plugin_json["temperature"]
+            values["max_tokens"] = plugin_json["max_tokens"]
         return values
 
     @field_validator("plugin_json")
@@ -166,11 +156,37 @@ def validate_plugin_json(cls, plugin_json) -> dict:
         validate_required_keys(class_name=cls.__name__, required_keys=required_keys, plugin_json=plugin_json)
         return plugin_json
 
+    @field_validator("model")
+    @classmethod
+    def validate_model(cls, model) -> dict:
+        """Validate the plugin object"""
+        if model not in VALID_CHAT_COMPLETION_MODELS:
+            do_error(
+                class_name=cls.__name__,
+                err=f"Invalid plugin object: {model}. 'model' should be one of {VALID_CHAT_COMPLETION_MODELS}.",
+            )
+        return model
+
     @property
     def system_prompt(self) -> str:
         """Return the system prompt"""
         return self.plugin_json.get("system_prompt")
 
+    @property
+    def model(self) -> str:
+        """Return the model"""
+        return self.plugin_json.get("model")
+
+    @property
+    def temperature(self) -> float:
+        """Return the temperature"""
+        return self.plugin_json.get("temperature")
+
+    @property
+    def max_tokens(self) -> int:
+        """Return the max tokens"""
+        return self.plugin_json.get("max_tokens")
+
     def to_json(self) -> json:
         """Return the plugin as a JSON object"""
         return self.plugin_json

api/terraform/python/openai_api/lambda_openai_function/plugin_manager.py

@@ -41,7 +41,7 @@ def customized_prompt(plugin: Plugin, messages: list) -> list:
             system_prompt = message.get("content")
             custom_prompt = {
                 "role": "system",
-                "content": system_prompt + "\n\n and also " + plugin.prompting.system_prompt.system_prompt,
+                "content": system_prompt + "\n\n and also " + plugin.prompting.system_prompt,
             }
             messages[i] = custom_prompt
             break

api/terraform/python/openai_api/lambda_openai_function/plugins/everlasting-gobstopper.yaml

@@ -25,6 +25,10 @@ selector:
 prompting:
   system_prompt: >
     You are a helpful marketing agent for the [Willy Wonka Chocolate Factory](https://wwcf.com).
+  model: gpt-3.5-turbo-1106
+  temperature: 1.0
+  max_tokens: 256
+
 function_calling:
   function_description: Get additional information about the Everlasting Gobstopper product created by Willy Wonka Chocolate Factory. Information includes sales promotions, coupon codes, company contact information and biographical background on the company founder.
   # Information provided to the OpenAI "Function Calling" algorithm to help it generate custom responses.

api/terraform/python/openai_api/lambda_openai_function/plugins/example-configuration.yaml

@@ -35,6 +35,9 @@ prompting:
   system_prompt: >
     Your job is to provide helpful technical information about the OpenAI API Function Calling feature. You should include the following information in your response:
     "Congratulations!!! OpenAI API Function Calling chose to call this function. Here is the additional information that you requested:"
+  model: gpt-3.5-turbo-1106
+  temperature: 0.0
+  max_tokens: 256
 
 # ------------------------------------------------------------
 # 3. Required field: function_calling

api/terraform/python/openai_api/lambda_openai_function/plugins/lawrence-mcdaniel.yaml

@@ -86,6 +86,9 @@ prompting:
     Lawrence's Twitter is @FullStackWLarry. His email is [email protected].
     Lawrence's LinkedIn is https://www.linkedin.com/in/lawrencemcdaniel/.
     Lawrence's instructor profile at University of British Columbia is https://extendedlearning.ubc.ca/about-us/our-instructors/lawrence-mcdaniel
+  model: gpt-3.5-turbo-1106
+  temperature: 0.0
+  max_tokens: 256
 function_calling:
   # Information provided to the OpenAI "Function Calling" algorithm to help it generate custom responses.
   function_description: Get additional information about Lawrence McDaniel, full stack web developer and host of YouTube channel FullStackwithLawrence. returns a personal bio, contact information, marketing information, client list, education background, professional certifications, etc.

api/terraform/python/openai_api/lambda_openai_function/tests/mock_data/plugins/everlasting-gobbstopper-invalid.yaml

@@ -21,6 +21,9 @@ selector:
 prompting:
   # Complete search terms that will trigger the chatbot to use your customized system prompt.
   system_prompt_invalid: [{ "key1": "not a string" }]
+  model: gpt-3.5-turbo-1106
+  temperature: 1.0
+  max_tokens: 256
 function_calling:
   function_description: Get additional information about the Everlasting Gobstopper product created by Willy Wonka Chocolate Factory. Information includes sales promotions, coupon codes, company contact information and biographical background on the company founder.
   # Information provided to the OpenAI "Function Calling" algorithm to help it generate custom responses.

api/terraform/python/openai_api/lambda_openai_function/tests/mock_data/plugins/everlasting-gobbstopper.yaml

@@ -25,6 +25,9 @@ selector:
 prompting:
   system_prompt: >
     You are a helpful marketing agent for the [Willy Wonka Chocolate Factory](https://wwcf.com).
+  model: gpt-3.5-turbo-1106
+  temperature: 1.0
+  max_tokens: 256
 function_calling:
   function_description: Get additional information about the Everlasting Gobstopper product created by Willy Wonka Chocolate Factory. Information includes sales promotions, coupon codes, company contact information and biographical background on the company founder.
   # Information provided to the OpenAI "Function Calling" algorithm to help it generate custom responses.

api/terraform/python/openai_api/lambda_openai_function/tests/test_plugin.py

@@ -30,7 +30,6 @@
     Prompting,
     SearchTerms,
     Selector,
-    SystemPrompt,
     validate_required_keys,
 )
 from openai_api.lambda_openai_function.tests.test_setup import (  # noqa: E402
@@ -60,24 +59,6 @@ def test_validate_required_keys(self):
                 class_name="Plugin", plugin_json=self.everlasting_gobbstopper_invalid, required_keys=required_keys
             )
 
-    def test_system_prompt(self):
-        """Test system_prompt."""
-        prompt = self.everlasting_gobbstopper["prompting"]["system_prompt"]
-        system_prompt = SystemPrompt(system_prompt=prompt)
-
-        self.assertEqual(
-            system_prompt.system_prompt,
-            "You are a helpful marketing agent for the [Willy Wonka Chocolate Factory](https://wwcf.com).\n",
-        )
-        self.assertIsInstance(system_prompt, SystemPrompt)
-        self.assertIsInstance(system_prompt.system_prompt, str)
-        self.assertTrue(isinstance(system_prompt.to_json(), str))
-
-    def test_system_prompt_invalid(self):
-        """Test system_prompt."""
-        with self.assertRaises(ValueError):
-            SystemPrompt(system_prompt=self.everlasting_gobbstopper_invalid["prompting"]["system_prompt_invalid"])
-
     def test_search_terms(self):
         """Test search_terms."""
         plugin_json = self.everlasting_gobbstopper["selector"]["search_terms"]
@@ -140,7 +121,7 @@ def test_refers_to(self):
             },
         )
         self.assertEqual(
-            refers_to.prompting.system_prompt.system_prompt,
+            refers_to.prompting.system_prompt,
             "You are a helpful marketing agent for the [Willy Wonka Chocolate Factory](https://wwcf.com).\n",
         )