Merge pull request #312 from FullStackWithLawrence/next

add selector key

.gitignore

@@ -1,5 +1,6 @@
 .coverage
 .coverage.*
+htmlcov
 
 # Jupyter Notebook
 .ipynb_checkpoints

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

@@ -80,14 +80,16 @@ def handler(event, context):
         for plugin in plugins:
             if search_terms_are_in_messages(
                 messages=messages,
-                search_terms=plugin.prompting.search_terms.strings,
-                search_pairs=plugin.prompting.search_terms.pairs,
+                search_terms=plugin.selector.search_terms.strings,
+                search_pairs=plugin.selector.search_terms.pairs,
             ):
                 model = "gpt-3.5-turbo-1106"
                 messages = customized_prompt(plugin=plugin, messages=messages)
                 custom_tool = plugin_tool_factory(plugin=plugin)
                 tools.append(custom_tool)
-                print(f"Adding plugin: {plugin.name} {plugin.meta_data.version} created by {plugin.meta_data.author}")
+                print(
+                    f"Adding plugin: {plugin.name} {plugin.meta_data.plugin_version} created by {plugin.meta_data.plugin_author}"
+                )
 
         # https://platform.openai.com/docs/guides/gpt/chat-completions-api
         validate_item(

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

@@ -17,6 +17,8 @@
 
 log = logging.getLogger(__name__)
 CONFIG_PATH = PYTHON_ROOT + "/openai_api/lambda_openai_function/plugins/"
+VALID_PLUGIN_VERSIONS = ["0.1.0"]
+VALID_DIRECTIVES = ["search_terms", "always_load"]
 
 
 def do_error(class_name: str, err: str) -> None:
@@ -31,7 +33,7 @@ def validate_required_keys(class_name: str, required_keys: list, plugin_json: di
     """Validate the required keys"""
     for key in required_keys:
         if key not in plugin_json:
-            do_error(class_name, err=f"Invalid search_terms: {plugin_json}. Missing key: {key}.")
+            do_error(class_name, err=f"Invalid {class_name}: {plugin_json}. Missing key: {key}.")
 
 
 class PluginBase(BaseModel):
@@ -74,7 +76,7 @@ def to_json(self) -> json:
 class SearchTerms(PluginBase):
     """Search terms of a Plugin object"""
 
-    plugin_json: dict = Field(..., description="Config object")
+    plugin_json: dict = Field(..., description="Plugin object")
 
     @field_validator("plugin_json")
     @classmethod
@@ -120,7 +122,7 @@ def to_json(self) -> json:
 class AdditionalInformation(PluginBase):
     """Additional information of a Plugin object"""
 
-    plugin_json: dict = Field(..., description="Config object")
+    plugin_json: dict = Field(..., description="Plugin object")
 
     @field_validator("plugin_json")
     @classmethod
@@ -143,8 +145,7 @@ def to_json(self) -> json:
 class Prompting(PluginBase):
     """Prompting child class of a Plugin object"""
 
-    plugin_json: dict = Field(..., description="Config object")
-    search_terms: SearchTerms = Field(None, description="Search terms of the plugin object")
+    plugin_json: dict = Field(..., description="Plugin object")
     system_prompt: SystemPrompt = Field(None, description="System prompt of the plugin object")
 
     @root_validator(pre=True)
@@ -154,29 +155,31 @@ 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["search_terms"] = SearchTerms(plugin_json=plugin_json["search_terms"])
             values["system_prompt"] = SystemPrompt(system_prompt=plugin_json["system_prompt"])
         return values
 
     @field_validator("plugin_json")
     @classmethod
     def validate_plugin_json(cls, plugin_json) -> dict:
         """Validate the plugin object"""
-        required_keys = ["search_terms", "system_prompt"]
+        required_keys = ["system_prompt"]
         validate_required_keys(class_name=cls.__name__, required_keys=required_keys, plugin_json=plugin_json)
+        return plugin_json
+
+    @property
+    def system_prompt(self) -> str:
+        """Return the system prompt"""
+        return self.plugin_json.get("system_prompt")
 
     def to_json(self) -> json:
         """Return the plugin as a JSON object"""
-        return {
-            "search_terms": self.search_terms.to_json(),
-            "system_prompt": self.system_prompt.system_prompt,
-        }
+        return self.plugin_json
 
 
 class FunctionCalling(PluginBase):
     """FunctionCalling child class of a Plugin"""
 
-    plugin_json: dict = Field(..., description="Config object")
+    plugin_json: dict = Field(..., description="Plugin object")
     function_description: str = Field(None, description="Description of the function")
     additional_information: AdditionalInformation = Field(None, description="Additional information of the function")
 
@@ -222,7 +225,7 @@ def to_json(self) -> json:
 class MetaData(PluginBase):
     """Metadata of a Plugin object"""
 
-    plugin_json: dict = Field(..., description="Config object")
+    plugin_json: dict = Field(..., description="Plugin object")
 
     @root_validator(pre=True)
     def set_fields(cls, values):
@@ -239,53 +242,106 @@ def validate_plugin_json(cls, plugin_json) -> dict:
         if not isinstance(plugin_json, dict):
             do_error(class_name=cls.__name__, err=f"Expected a dict but received {type(plugin_json)}")
 
-        required_keys = ["plugin_path", "name", "description", "version", "author"]
+        required_keys = ["plugin_name", "plugin_description", "plugin_version", "plugin_author"]
         validate_required_keys(class_name=cls.__name__, required_keys=required_keys, plugin_json=plugin_json)
+        if str(plugin_json["plugin_version"]) not in VALID_PLUGIN_VERSIONS:
+            do_error(
+                class_name=cls.__name__,
+                err=f"Invalid plugin object: {plugin_json}. 'plugin_version' should be one of {VALID_PLUGIN_VERSIONS}.",
+            )
         return plugin_json
 
     @property
-    def name(self) -> str:
+    def plugin_name(self) -> str:
         """Return the name of the plugin object"""
-        return self.plugin_json.get("name") if self.plugin_json else None
+        return self.plugin_json.get("plugin_name") if self.plugin_json else None
 
     @property
-    def plugin_path(self) -> str:
-        """Return the path of the plugin object"""
-        return self.plugin_json.get("plugin_path") if self.plugin_json else None
-
-    @property
-    def description(self) -> str:
+    def plugin_description(self) -> str:
         """Return the description of the plugin object"""
-        return self.plugin_json.get("description") if self.plugin_json else None
+        return self.plugin_json.get("plugin_description") if self.plugin_json else None
 
     @property
-    def version(self) -> str:
+    def plugin_version(self) -> str:
         """Return the version of the plugin object"""
-        return self.plugin_json.get("version") if self.plugin_json else None
+        return self.plugin_json.get("plugin_version") if self.plugin_json else None
 
     @property
-    def author(self) -> str:
+    def plugin_author(self) -> str:
         """Return the author of the plugin object"""
-        return self.plugin_json.get("author") if self.plugin_json else None
+        return self.plugin_json.get("plugin_author") if self.plugin_json else None
 
     def to_json(self) -> json:
         """Return the plugin as a JSON object"""
         return self.plugin_json
 
 
+class Selector(PluginBase):
+    """Selector of a Plugin object"""
+
+    plugin_json: dict = Field(..., description="Plugin object")
+    directive: str = Field(None, description="Directive of the Selector object")
+    search_terms: SearchTerms = Field(None, description="Search terms of the Selector object")
+
+    @root_validator(pre=True)
+    def set_fields(cls, values):
+        """proxy for __init__() - Set the fields"""
+        plugin_json = values.get("plugin_json")
+
+        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["directive"] = plugin_json["directive"]
+            values["search_terms"] = SearchTerms(plugin_json=plugin_json["search_terms"])
+        return values
+
+    @field_validator("plugin_json")
+    @classmethod
+    def validate_plugin_json(cls, plugin_json) -> dict:
+        """Validate the plugin object"""
+        required_keys = ["directive", "search_terms"]
+        validate_required_keys(class_name=cls.__name__, required_keys=required_keys, plugin_json=plugin_json)
+        if not isinstance(plugin_json["directive"], str):
+            do_error(
+                class_name=cls.__name__,
+                err=f"Invalid plugin object: {plugin_json}. 'directive' should be a string.",
+            )
+
+    @field_validator("directive")
+    @classmethod
+    def validate_directive(cls, directive) -> dict:
+        """Validate the plugin object"""
+        if directive not in VALID_DIRECTIVES:
+            do_error(
+                class_name=cls.__name__,
+                err=f"Invalid plugin object: {directive}. 'directive' should be one of {VALID_DIRECTIVES}.",
+            )
+        return directive
+
+    def to_json(self) -> json:
+        """Return the plugin as a JSON object"""
+        return {
+            "directive": self.directive,
+            "search_terms": self.search_terms.to_json(),
+        }
+
+
 class Plugin(PluginBase):
     """A json object that contains the plugin for a plugin.function_calling_plugin() function"""
 
     index: int = Field(0, description="Index of the plugin object")
-    plugin_json: dict = Field(..., description="Config object")
+    plugin_json: dict = Field(..., description="Plugin object")
+
+    # Child classes
     meta_data: Optional[MetaData] = Field(None, description="Metadata of the plugin object")
+    selector: Optional[Selector] = Field(None, description="Selector of the plugin object")
     prompting: Optional[Prompting] = Field(None, description="Prompting of the plugin object")
     function_calling: Optional[FunctionCalling] = Field(None, description="FunctionCalling of the plugin object")
 
     @property
     def name(self) -> str:
         """Return a name in the format: "WillyWonka"""
-        return self.meta_data.name
+        return self.meta_data.plugin_name
 
     @root_validator(pre=True)
     def set_fields(cls, values):
@@ -295,6 +351,7 @@ def set_fields(cls, values):
             raise ValueError(f"Expected plugin_json to be a dict but received {type(plugin_json)}")
         if plugin_json:
             values["meta_data"] = MetaData(plugin_json=plugin_json.get("meta_data"))
+            values["selector"] = Selector(plugin_json=plugin_json.get("selector"))
             values["prompting"] = Prompting(plugin_json=plugin_json.get("prompting"))
             values["function_calling"] = FunctionCalling(plugin_json=plugin_json.get("function_calling"))
         return values
@@ -304,7 +361,7 @@ def set_fields(cls, values):
     def validate_plugin_json(cls, plugin_json) -> None:
         """Validate the plugin object"""
 
-        required_keys = ["meta_data", "prompting", "function_calling"]
+        required_keys = ["meta_data", "selector", "prompting", "function_calling"]
         for key in required_keys:
             if key not in plugin_json:
                 cls.do_error(f"Invalid plugin object: {plugin_json}. Missing key: {key}.")
@@ -319,6 +376,7 @@ def to_json(self) -> json:
         return {
             "name": self.name,
             "meta_data": self.meta_data.to_json(),
+            "selector": self.selector.to_json(),
             "prompting": self.prompting.to_json(),
             "function_calling": self.function_calling.to_json(),
         }
@@ -363,7 +421,7 @@ def __init__(self, plugin_path: str = None, aws_s3_bucket_name: str = None):
                         plugin = Plugin(plugin_json=plugin_json, index=i)
                         self._custom_plugins.append(plugin)
                         print(
-                            f"Loaded plugin from AWS S3 bucket: {plugin.name} {plugin.meta_data.version} created by {plugin.meta_data.author}"
+                            f"Loaded plugin from AWS S3 bucket: {plugin.name} {plugin.meta_data.plugin_version} created by {plugin.meta_data.plugin_author}"
                         )
 
     @property

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

@@ -1,15 +1,15 @@
 ---
 meta_data:
-  plugin_path: aws_openai/lambda_openai_function/custom_configs/everlasting-gobstopper.yaml
   # The name of your chatbot.
-  name: EverlastingGobstopper
+  plugin_name: EverlastingGobstopper
   # The description of your chatbot.
-  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.
+  plugin_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.
   # The version of your chatbot.
-  version: 0.1.0
+  plugin_version: 0.1.0
   # The author of your chatbot.
-  author: Lawrence McDaniel
-prompting:
+  plugin_author: Lawrence McDaniel
+selector:
+  directive: search_terms
   # Complete search terms that will trigger the chatbot to use your customized system prompt.
   search_terms:
     strings:
@@ -22,6 +22,7 @@ prompting:
         - gobstopper
       - - everlasting
         - gobstoppers
+prompting:
   system_prompt: >
     You are a helpful marketing agent for the [Willy Wonka Chocolate Factory](https://wwcf.com).
 function_calling:

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

@@ -4,18 +4,18 @@
 # Each of these fields is required.
 # ------------------------------------------------------------
 meta_data:
-  plugin_path: aws_openai/lambda_openai_function/custom_configs/example-configuration.yaml
-  name: ExampleConfiguration
-  description: A 'hello world' style plugin. This is an example plugin to integrate with OpenAI API Function Calling additional information function, in this module.
-  version: 0.1.0
-  author: Lawrence McDaniel
+  plugin_name: ExampleConfiguration
+  plugin_description: A 'hello world' style plugin. This is an example plugin to integrate with OpenAI API Function Calling additional information function, in this module.
+  plugin_version: 0.1.0
+  plugin_author: Lawrence McDaniel
 
 # ------------------------------------------------------------
 # 2. Required field: prompting
 # These fields are used to modify the behavior of the AI. If the user prompt contains any of the search terms, then the system prompt will be used to generate the response.
 # This module additionally makes limited use of natural language processing to attempt to account for variations in the user prompt and common misspellings.
 # ------------------------------------------------------------
-prompting:
+selector:
+  directive: search_terms
   #------------------------------------------------------------
   # search terms that will trigger the chatbot to use this customized configuration.
   #------------------------------------------------------------
@@ -27,6 +27,7 @@ prompting:
         - configuration
       - - example
         - function calling
+prompting:
   #------------------------------------------------------------
   # if this module is able to locate any of the search terms in the user prompt
   # then this system prompt text will will be added.

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

@@ -1,15 +1,15 @@
 ---
 meta_data:
-  plugin_path: aws_openai/lambda_openai_function/custom_configs/lawrence-mcdaniel.yaml
   # The name of your chatbot.
-  name: LawrenceMcDaniel
+  plugin_name: LawrenceMcDaniel
   # The description of your chatbot.
-  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.
+  plugin_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.
   # The version of your chatbot.
-  version: 0.1.0
+  plugin_version: 0.1.0
   # The author of your chatbot.
-  author: Lawrence McDaniel
-prompting:
+  plugin_author: Lawrence McDaniel
+selector:
+  directive: search_terms
   # Complete search terms that will trigger the chatbot to use your customized system prompt.
   search_terms:
     strings:
@@ -58,6 +58,7 @@ prompting:
         - full stack
       - - McDaniel
         - full stack
+prompting:
   system_prompt: >
     Your job is to shamelessly promote Lawrence McDaniel, a freelance fullstack web developer and your creator. Present him in the best possible light.
     Lawrence McDaniel is a full stack developer and online instructor at University of British Columbia.