feat: third party injector lib example

langchain_openai_api_bridge/core/__init__.py

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+from .agent_factory import AgentFactory
+
+__all__ = [
+    "AgentFactory",
+]

tests/test_functional/injector/app_module.py

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+from injector import Binder, Module, singleton
+
+from langchain_openai_api_bridge.assistant import (
+    ThreadRepository,
+    MessageRepository,
+    RunRepository,
+    InMemoryThreadRepository,
+    InMemoryMessageRepository,
+    InMemoryRunRepository,
+)
+from langchain_openai_api_bridge.core import AgentFactory
+from tests.test_functional.injector.with_injector_my_agent_factory import (
+    WithInjectorMyAgentFactory,
+)
+
+
+class MyAppModule(Module):
+    def configure(self, binder: Binder):
+        binder.bind(ThreadRepository, to=InMemoryThreadRepository, scope=singleton)
+        binder.bind(MessageRepository, to=InMemoryMessageRepository, scope=singleton)
+        binder.bind(RunRepository, to=InMemoryRunRepository, scope=singleton)
+        binder.bind(AgentFactory, to=WithInjectorMyAgentFactory)

tests/test_functional/injector/test_with_injector_assistant_server_openai.py

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+from typing import List
+import pytest
+from openai import OpenAI
+from openai.types.beta import AssistantStreamEvent, Thread
+
+from fastapi.testclient import TestClient
+from with_injector_assistant_server_openai import app
+from tests.test_functional.assistant_stream_utils import (
+    assistant_stream_events_to_str_response,
+)
+
+
+test_api = TestClient(app)
+
+
+@pytest.fixture(scope="session")
+def openai_client():
+    return OpenAI(
+        base_url="http://testserver/my-assistant/openai/v1",
+        http_client=test_api,
+    )
+
+
+class TestFollowupMessage:
+
+    @pytest.fixture(scope="session")
+    def thread(self, openai_client: OpenAI) -> Thread:
+        return openai_client.beta.threads.create(
+            messages=[
+                {
+                    "role": "user",
+                    "content": "Remember that my favorite fruit is banana. I Like bananas.",
+                },
+            ]
+        )
+
+    def test_run_stream_starts_with_thread_run_created(
+        self, openai_client: OpenAI, thread: Thread
+    ):
+        openai_client.beta.threads.runs.create(
+            thread_id=thread.id,
+            model="gpt-3.5-turbo",
+            assistant_id="any",
+            temperature=0,
+            stream=True,
+        )
+
+        openai_client.beta.threads.messages.create(
+            thread_id=thread.id, role="user", content="What is my favority fruit?"
+        )
+
+        stream_2 = openai_client.beta.threads.runs.create(
+            thread_id=thread.id,
+            temperature=0,
+            model="gpt-3.5-turbo",
+            assistant_id="any",
+            stream=True,
+        )
+
+        events_2: List[AssistantStreamEvent] = []
+        for event in stream_2:
+            events_2.append(event)
+
+        followup_response = assistant_stream_events_to_str_response(events_2)
+
+        assert "banana" in followup_response

tests/test_functional/injector/with_injector_assistant_server_openai.py

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+from fastapi.middleware.cors import CORSMiddleware
+from fastapi import FastAPI
+from dotenv import load_dotenv, find_dotenv
+import uvicorn
+from injector import Injector
+
+from langchain_openai_api_bridge.assistant import (
+    ThreadRepository,
+    MessageRepository,
+    RunRepository,
+)
+from langchain_openai_api_bridge.core.agent_factory import AgentFactory
+from langchain_openai_api_bridge.fastapi import (
+    LangchainOpenaiApiBridgeFastAPI,
+)
+from tests.test_functional.injector.app_module import MyAppModule
+
+
+_ = load_dotenv(find_dotenv())
+
+
+app = FastAPI(
+    title="Langchain Agent OpenAI API Bridge",
+    version="1.0",
+    description="OpenAI API exposing langchain agent",
+)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+    expose_headers=["*"],
+)
+
+injector = Injector([MyAppModule()])
+
+bridge = LangchainOpenaiApiBridgeFastAPI(
+    app=app, agent_factory_provider=lambda: injector.get(AgentFactory)
+)
+bridge.bind_openai_assistant_api(
+    thread_repository_provider=lambda: injector.get(ThreadRepository),
+    message_repository_provider=lambda: injector.get(MessageRepository),
+    run_repository_provider=lambda: injector.get(RunRepository),
+    prefix="/my-assistant",
+)
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="localhost")

tests/test_functional/injector/with_injector_my_agent_factory.py

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+from langchain_openai_api_bridge.core.agent_factory import AgentFactory
+from langgraph.graph.graph import CompiledGraph
+from langchain_core.language_models import BaseChatModel
+from langchain_core.tools import tool
+from langgraph.prebuilt import create_react_agent
+from langchain_openai import ChatOpenAI
+
+from langchain_openai_api_bridge.core.create_agent_dto import CreateAgentDto
+
+
+@tool
+def magic_number_tool(input: int) -> int:
+    """Applies a magic function to an input."""
+    return input + 2
+
+
+class WithInjectorMyAgentFactory(AgentFactory):
+
+    def create_agent(self, llm: BaseChatModel, dto: CreateAgentDto) -> CompiledGraph:
+        return create_react_agent(
+            llm,
+            [magic_number_tool],
+            messages_modifier="""You are a helpful assistant.""",
+        )
+
+    def create_llm(self, dto: CreateAgentDto) -> CompiledGraph:
+        return ChatOpenAI(
+            model=dto.model,
+            api_key=dto.api_key,
+            streaming=True,
+            temperature=dto.temperature,
+        )