refactor: cleanup agent class objects (#384)

This PR represents an attempt to cleanup, document, and rationalize the
existing set of classes in `agent` hierarchy. I also wanted to remove as
much vestigial and unused surface (primarily related to async execution)
in an attempt to simplify and reduce surface area for implementors.

As part of this PR, I updated the example assistant to show how
synchronous agent responses could be done using `emitFns`. This then led
to an update of the REPL to allow flexible identification of
`AgentService` methods. I think we need more thought there.

Because we've introduced an `LLM` class, I took the `get_llm()` method
that created ad-hoc ones from context off of the context and added
helpers to create contexts with LLM instances. This was an attempt to
rationalize usage within Tools, etc. I'm open to other approaches there.

---------

Co-authored-by: Douglas Reid <doug@steamship.com>
Co-authored-by: Ted Benson <ted@steamship.com>

Author: 3 people

src/steamship/agents/base.py

@@ -0,0 +1,47 @@
+import uuid
+from typing import List
+
+from steamship import Block
+from steamship.agents.llms.openai import OpenAI
+from steamship.agents.react import ReACTAgent
+from steamship.agents.schema import AgentContext
+from steamship.agents.schema.context import Metadata
+from steamship.agents.service.agent_service import AgentService
+from steamship.agents.tools.image_generation.dalle import DalleTool
+from steamship.agents.tools.search.search import SearchTool
+from steamship.invocable import post
+from steamship.utils.repl import AgentREPL
+
+
+class MyAssistant(AgentService):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self._agent = ReACTAgent(
+            tools=[
+                SearchTool(),
+                DalleTool(),
+            ],
+            llm=OpenAI(self.client),
+        )
+
+    @post("prompt")
+    def prompt(self, prompt: str) -> str:
+        context_id = uuid.uuid4()
+        context = AgentContext.get_or_create(self.client, {"id": f"{context_id}"})
+        context.chat_history.append_user_message(prompt)
+
+        # TODO: is this preferred over taking the last step in completed step?
+        output = ""
+
+        def sync_emit(blocks: List[Block], meta: Metadata):
+            nonlocal output
+            block_text = "\n".join([b.text for b in blocks if b.is_text()])
+            output += block_text
+
+        context.emit_funcs.append(sync_emit)
+        self.run_agent(self._agent, context)
+        return output
+
+
+if __name__ == "__main__":
+    AgentREPL(MyAssistant, "prompt").run()

src/steamship/agents/context/context.py

@@ -0,0 +1,3 @@
+from .openai import OpenAI
+
+__all__ = ["OpenAI"]

src/steamship/agents/example_agents/my_assistant.py

@@ -1,12 +1,18 @@
-from typing import List
+from typing import List, Optional
 
 from steamship import Block, PluginInstance, Steamship
-from steamship.agents.base import LLM
+from steamship.agents.schema import LLM
 
 PLUGIN_HANDLE = "gpt-4"
 
 
 class OpenAI(LLM):
+    """LLM that uses Steamship's OpenAI plugin to generate completions.
+
+    NOTE: By default, this LLM uses the `gpt-3.5-turbo` model. Valid model
+    choices are `gpt-3.5-turbo` and `gpt-4`.
+    """
+
     generator: PluginInstance
     client: Steamship
 
@@ -21,7 +27,10 @@ def __init__(self, client, model_name: str = "gpt-3.5-turbo", *args, **kwargs):
         generator = client.use_plugin(PLUGIN_HANDLE, config={"model": model_name})
         super().__init__(client=client, generator=generator, *args, **kwargs)
 
-    def complete(self, prompt: str, stop: str) -> List[Block]:
-        action_task = self.generator.generate(text=prompt, options={"stop": stop})
+    def complete(self, prompt: str, stop: Optional[str] = None) -> List[Block]:
+        options = {}
+        if stop:
+            options["stop"] = stop
+        action_task = self.generator.generate(text=prompt, options=options)
         action_task.wait()
         return action_task.output.blocks

…amship/agents/example_agents/__init__.py src/steamship/agents/examples/__init__.pysrc/steamship/agents/example_agents/__init__.py renamed to src/steamship/agents/examples/__init__.py src/steamship/agents/example_agents/__init__.py renamed to src/steamship/agents/examples/__init__.py

@@ -0,0 +1,3 @@
+from .chathistory import ChatHistory
+
+__all__ = ["ChatHistory"]

src/steamship/agents/examples/my_assistant.py

@@ -21,7 +21,7 @@ def __init__(self, file: File):
 
     @staticmethod
     def _get_existing_file(client: Client, context_keys: Dict[str, str]) -> Optional[File]:
-        """Find an existing File object whose context Tag matches the passed context keys"""
+        """Find an existing File object whose memory Tag matches the passed memory keys"""
         file_query = " and ".join(
             [f'value("{key}") = "{value}"' for key, value in context_keys.items()]
         )
@@ -32,7 +32,7 @@ def _get_existing_file(client: Client, context_keys: Dict[str, str]) -> Optional
             return None
         else:
             raise SteamshipError(
-                "Multiple ChatHistory objects have been created in this workspace with these context keys."
+                "Multiple ChatHistory objects have been created in this workspace with these memory keys."
             )
 
     @staticmethod
@@ -48,6 +48,7 @@ def get_or_create(
             tags = tags or []
             tags.append(Tag(kind=TagKind.DOCUMENT, name=DocTag.CHAT))
             tags.append(Tag(kind=TagKind.CHAT, name=ChatTag.CONTEXT_KEYS, value=context_keys))
+
             blocks = []
             file = File.create(
                 client=client,