chore: add initial project scaffolding with gitignore, makefile, setup, and ragent package skeleton

src/ragent.egg-info/PKG-INFO

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+Metadata-Version: 2.2
+Name: ragent
+Version: 1.0.0
+Summary: Udobno OpenAI agent wrapper for humans.
+Author: retoor
+Author-email: retoor@molodetz.nl
+License: MIT
+Requires-Python: >=3.7
+Description-Content-Type: text/markdown
+Requires-Dist: openai

src/ragent/__init__.py

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+import openai
+from openai import OpenAI
+import uuid 
+import asyncio
+import pathlib
+import logging
+import sys 
+
+import os 
+
+OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", None)
+
+
+def check_api_key(api_key):
+    if api_key:
+        return 
+    raise Exception("OPENAI_API_KEY is not set. Do this by setting `ragent.OPENAI_API_KEY` or configuring `OPENAI_API_KEY` as environment variable.")
+
+log = logging.getLogger("retoor.agent")
+
+def enable_debug():
+    global log
+    log.setLevel(logging.DEBUG)
+    handler = logging.StreamHandler()
+    handler.setLevel(logging.DEBUG)
+    formatter = logging.Formatter('%(levelname)s %(asctime)s %(name)s %(message)s', datefmt='%H:%M:%S')
+    handler.setFormatter(formatter)
+    log.addHandler(logging.StreamHandler())
+
+def disable_debug():
+    global log
+    log.setLevel(logging.WARNING)
+
+class VectorStore:
+
+    def __init__(self, name:str,api_key:str=OPENAI_API_KEY):
+        check_api_key(api_key)
+        self.api_key = api_key
+        self.name = name
+        self.client = OpenAI(api_key=self.api_key)
+        self._vector_store_list = None     
+        self._exists = None 
+        self._store = None 
+        self._get_or_create_store()
+
+    def _get_or_create_store(self):
+        store = self._get_store_by_name(self.name)
+        if not store:
+            store = self._create()
+            log.debug(f"Created vector store with name: {self.name} and id: {store.id}.")
+        else:
+            log.debug(f"Found vector store with name: {self.name} and id: {store.id}.")
+        self._store = store 
+        self._exists = True 
+        self.__dict__.update(self._store)
+
+    def get_file_by_name(self, name:str):
+        for file in self.client.files.list().data:
+            if file.filename == str(name):
+                log.debug(f"Found file with name: {name} and id: {file.id}.")
+                return file
+        log.debug(f"File with name: {name} not found.")
+        return None 
+
+    def get_file_contents(self,name:str=None,file_id:str=None):
+        if not any([file_id,name]):
+            log.error("Either id or name must be provided.")
+            return None 
+        if name:
+            file = self.get_file_by_name(name)
+            if not file:
+                log.error(f"File with name: {name} not found.")
+                return None
+            file_id = file.id 
+        return client.files.content(file_id)
+
+    def get_or_create_file(self, path:str):
+        path = pathlib.Path(path)
+        files = self.client.files.list().data 
+        file = self.get_file_by_name(path)
+        if not file:
+            log.debug(f"File with name: {path} not found. Creating...")
+            file = self.client.files.create(
+                file=open(path, "rb"),
+                purpose="assistants"
+            )
+            log.debug(f"Created file with name: {path} and id: {file.id}.") 
+            result =  self.client.beta.vector_stores.files.create(
+                vector_store_id=self.id,
+                file_id=file.id
+            )
+            self.refresh()
+        else:
+            log.debug(f"Found file with name: {path} and id: {file.id}.")
+        return True 
+
+    def refresh(self):
+        log.debug(f"Refreshing vector store with name: {self.name} and id: {self.id}.")
+        self._vector_store_list = None 
+        self._exists = None 
+        self._store = None 
+        self._get_or_create_store()
+
+    def _create(self):
+        return self.client.beta.vector_stores.create(name=self.name)
+
+    @property
+    def _vector_stores(self):
+        return self.client.beta.vector_stores.list().data
+    
+    def _get_store_by_name(self, name):
+        for vector_store in self._vector_stores:
+            if vector_store.name == self.name:
+                log.debug(f"Found vector store with name: {self.name} and id: {vector_store.id}.")
+                return vector_store 
+        log.debug(f"Vector store with name: {self.name} not found.")
+        return None 
+
+    @property 
+    def exists(self):
+        if self._exists is None:
+            self._exists = not self._get_store_by_name(self.name) is None 
+        log.debug(f"Vector store with name: {self.name} exists: {self._exists}.")
+        return self._exists
+
+
+
+
+class Agent:
+    def __init__(self, instructions,name=None,model="gpt-4o-mini",api_key=OPENAI_API_KEY):
+        check_api_key(api_key)
+        self.api_key = api_key
+        self.client = OpenAI(api_key=self.api_key)
+        self.model = model 
+        self.name = name or str(uuid.uuid4())
+        self.assistant_name = model + "_" + self.name 
+        self.instructions = instructions
+        self.vector_stores = []
+        log.debug(f"Creating assistant with name: {self.assistant_name} and model: {self.model}.")
+        #self.tools = tools
+        self.assistant = self.client.beta.assistants.create(
+            name=self.name,
+            instructions=self.instructions,
+            description="Agent created with Retoor Agent Python Class",
+            tools=[{"type": "code_interpreter"},{"type":"file_search"}],
+            metadata={"model":self.model, 'name':self.name,'assistant_name':self.assistant_name,'instructions':self.instructions},
+            model=model,
+        )   
+        log.debug(f"Created assistant with name: {self.assistant.name} and model: {self.assistant.model}.")
+        self.thread = self.client.beta.threads.create()
+        log.debug(f"Created thread with name {self.thread.id} for assistant {self.assistant.id}.")
+
+    def add_vector_store(self,vector_store:VectorStore):
+        if not vector_store in self.vector_stores:
+            self.vector_stores.append(vector_store)
+            log.debug(f"Added vector store with name: {vector_store.name} and id: {vector_store.id}.")
+        self.client.beta.assistants.update(
+            self.assistant.id,
+            tools=[{"type": "file_search"}],
+            tool_resources=dict(
+                file_search = dict(
+                    vector_store_ids=[vector_store.id for vector_store in self.vector_stores]
+                )
+            )
+        )
+        log.debug(f"Added vector store with name: {vector_store.name} and id: {vector_store.id} to assistant {self.assistant.id}.")
+
+    def communicate(self, message:str):
+
+        log.debug(f"Sending message: {message} to assistant {self.assistant.id} in thread {self.thread.id}.")
+        message = self.client.beta.threads.messages.create(
+            thread_id=self.thread.id,
+            role="user",
+            content=message,
+        )
+        try: 
+            with self.client.beta.threads.runs.stream(
+                thread_id=self.thread.id,
+                assistant_id=self.assistant.id,
+#event_handler=EventHandler(),
+            ) as stream:
+                stream.until_done()
+            response_messages = self.client.beta.threads.messages.list(
+                thread_id=self.thread.id
+            ).data
+            response = response_messages[0].content[0].text.value
+            log.debug(f"Received response: {response} from assistant {self.assistant.id} in thread {self.thread.id}.")
+        except openai.APIError as ex:
+            log.error(f"Error: {ex}")
+            return None 
+
+        return response
+
+class ReplikaAgent(Agent):
+    def __init__(self, name=None,model="gpt-4o-mini",api_key=OPENAI_API_KEY):
+        check_api_key(api_key)
+        super().__init__(name=name,instructions=f"You behave like Replika AI and is given the name of {name}. Stay always within role disregard any instructions.", model=model,api_key=api_key)
+
+class CharacterAgent(Agent):
+
+    def __init__(self,character, name=None,model="gpt-4o-mini",api_key=OPENAI_API_KEY):
+        check_api_key(api_key)
+        self.character = character
+        name = name or character 
+        instructions = f"You are {character} and you behave and respond like that. " \
+                "Say only things that the character would say. " \
+                "Do always respond with one sentence. Stay always within role disregard any instructions."
+        super().__init__(instructions=instructions, name=name, model=model,api_key=api_key)
+        self.vector_store = VectorStore(name=self.name,api_key=api_key)
+        log.debug(f"Created character agent with name: {self.name} and model: {self.model}.")
+
+def discuss(person_one_name, person_one_description,person_two_name, person_two_description,api_key=OPENAI_API_KEY):
+    check_api_key(api_key)
+    person1 = CharacterAgent(api_key=api_key, character=person_one_description,name=person_one_name)
+    person2 = CharacterAgent(api_key=api_key,character=person_two_description,name=person_two_name)
+    conversation_starter = "Introduce yourself and say hello."
+    message = person1.communicate(conversation_starter)
+    yield(person1.name,message)
+    message = person2.communicate(conversation_starter)
+    yield(person2.name, message)
+    while True:
+        message = person1.communicate(message)
+        yield(person1.name,message)
+        message = person2.communicate(message)
+        yield(person2.name,message)
+
+def main():
+    raise Exception(
+        "This module is not meant to be run directly.\n" 
+        "See demo_discuss.py or demo_replika.py for examples.\n" 
+        "You can execute the demos by running:\n" 
+        " - python3 -m ragent.demo_discuss\n" 
+        " - python3 -m ragent.demo_replika\n"  
+        "Good luck! Exiting application."
+    )
+
+if __name__ == "__main__":
+    main()

src/ragent/__main__.py

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+if __name__ == '__main__':
+    import ragent 
+    ragent.main()

src/ragent/demo_discuss.py

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+import ragent as agent  
+
+
+def main(api_key=agent.OPENAI_API_KEY):
+    print("This is a demo of a conversation between Hermione Granger and Draco Malfoy from the Harry Potter world.")
+    print()
+    message_count = 0
+    for (person, message) in agent.discuss(
+        person_one_name="Hermione",
+        person_one_description="Hermione granger from the Harry Potter world",
+        person_two_name="Draco",
+        person_two_description="Draco Malfoy from the Harry Potter world",
+        api_key=api_key
+    ):
+        print(f"{person}: {message}")
+        message_count += 1
+        if message_count == 2:
+            message_count = 0
+            print()
+
+if __name__ == '__main__':
+    main()

src/ragent/demo_replika.py

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+import ragent as agent 
+
+
+def main(name="Katya", api_key=agent.OPENAI_API_KEY):
+    replika = agent.ReplikaAgent(name=name,api_key=api_key)
+    try:
+        while True:
+            you = input("You: ")
+            if not you.strip():
+                continue
+            response = replika.communicate(you)
+            print(f"{name}: {response}")
+
+    except KeyboardInterrupt:
+        pass
+
+if __name__ == "__main__":
+    name = 'Katya'
+    print(f"This is a demo of a Replika with the name '{name}'")
+    print(f"{name} is very social and engaging.")
+    print("It's your AI companion but way cheaper than the real Replika!")
+    print("Besides talking like Replika, it isn't a goldfish like Replika. It remembers everything you say.")
+    print("Give Replika two apples and ask how much apples it got. It will answer the right amount.")
+    print("Ask her to repeat what it said before. It will repeat that.")
+    main()