feat(api): Runs endpoints

packages/api/chart/values.yaml

@@ -10,7 +10,7 @@ image:
     fsGroup: 65532
 
 supabase:
-  url: "https://supabase-kong.###ZARF_VAR_HOSTED_DOMAIN###"
+  url: "http://supabase-kong.leapfrogai.svc.cluster.local:80"
 
 api:
   replicas: 1

packages/api/supabase/migrations/20240611111500_runs.sql

@@ -0,0 +1,52 @@
+-- Create a table to store the OpenAI Run Objects
+create table
+  run_objects (
+    id uuid primary key default uuid_generate_v4(),
+    user_id uuid references auth.users not null,
+    object text check (object in ('thread.run')),
+    created_at bigint default extract(epoch FROM NOW()) not null,
+    thread_id uuid references thread_objects (id) on delete cascade not null,
+    assistant_id uuid references assistant_objects (id) on delete cascade not null,
+    status text,
+    required_action jsonb,
+    last_error jsonb,
+    expires_at bigint,
+    started_at bigint,
+    cancelled_at bigint,
+    failed_at bigint,
+    completed_at bigint,
+    model text,
+    instructions text,
+    tools jsonb,
+    metadata jsonb,
+    parallel_tool_calls boolean,
+    stream boolean,
+    file_ids uuid[],
+    incomplete_details jsonb,
+    usage jsonb,
+    temperature float,
+    top_p float,
+    max_prompt_tokens int,
+    max_completion_tokens int,
+    truncation_strategy jsonb,
+    tool_choice jsonb,
+    response_format jsonb
+  );
+
+-- RLS policies
+alter table run_objects enable row level security;
+
+-- Policies for run_objects
+create policy "Individuals can view their own run_objects." on run_objects for
+    select using (auth.uid() = user_id);
+create policy "Individuals can create run_objects." on run_objects for
+    insert with check (auth.uid() = user_id);
+create policy "Individuals can update their own run_objects." on run_objects for
+    update using (auth.uid() = user_id);
+create policy "Individuals can delete their own run_objects." on run_objects for
+    delete using (auth.uid() = user_id);
+
+-- Indexes for common filtering and sorting for run_objects
+CREATE INDEX run_objects_id ON run_objects (id);
+CREATE INDEX run_objects_user_id ON run_objects (user_id);
+CREATE INDEX run_objects_created_at ON run_objects (created_at);

src/leapfrogai_api/Makefile

@@ -36,4 +36,4 @@ env:
 	$(call get_jwt_token,"${SUPABASE_URL}/auth/v1/token?grant_type=password")
 
 test-integration:
-	cd ../../ && python -m pytest tests/integration/api
+	cd ../../ && python -m pytest tests/integration/api/ -vv -s

src/leapfrogai_api/backend/converters.py

@@ -0,0 +1,107 @@
+"""Converters for the LeapfrogAI API"""
+
+from typing import Iterable
+from openai.types.beta import AssistantStreamEvent
+from openai.types.beta.assistant_stream_event import ThreadMessageDelta
+from openai.types.beta.threads.file_citation_annotation import FileCitation
+from openai.types.beta.threads import (
+    MessageContentPartParam,
+    MessageContent,
+    TextContentBlock,
+    Text,
+    Message,
+    MessageDeltaEvent,
+    MessageDelta,
+    TextDeltaBlock,
+    TextDelta,
+    FileCitationAnnotation,
+)
+
+
+def from_assistant_stream_event_to_str(stream_event: AssistantStreamEvent):
+    return f"event: {stream_event.event}\ndata: {stream_event.data.model_dump_json()}"
+
+
+def from_content_param_to_content(
+    thread_message_content: str | Iterable[MessageContentPartParam],
+) -> MessageContent:
+    """Converts messages from MessageContentPartParam to MessageContent"""
+    if isinstance(thread_message_content, str):
+        return TextContentBlock(
+            text=Text(annotations=[], value=thread_message_content),
+            type="text",
+        )
+    else:
+        result: str = ""
+
+        for message_content_part in thread_message_content:
+            if isinstance(text := message_content_part.get("text"), str):
+                result += text
+
+        return TextContentBlock(
+            text=Text(annotations=[], value=result),
+            type="text",
+        )
+
+
+def from_text_to_message(text: str, file_ids: list[str]) -> Message:
+    all_file_ids: str = ""
+
+    for file_id in file_ids:
+        all_file_ids += f" [{file_id}]"
+
+    message_content: TextContentBlock = TextContentBlock(
+        text=Text(
+            annotations=[
+                FileCitationAnnotation(
+                    text=f"[{file_id}]",
+                    file_citation=FileCitation(file_id=file_id, quote=""),
+                    start_index=0,
+                    end_index=0,
+                    type="file_citation",
+                )
+                for file_id in file_ids
+            ],
+            value=text + all_file_ids,
+        ),
+        type="text",
+    )
+
+    new_message = Message(
+        id="",
+        created_at=0,
+        object="thread.message",
+        status="in_progress",
+        thread_id="",
+        content=[message_content],
+        role="assistant",
+        metadata=None,
+    )
+
+    return new_message
+
+
+async def from_chat_completion_choice_to_thread_message_delta(
+    index, random_uuid, streaming_response
+) -> ThreadMessageDelta:
+    thread_message_event: ThreadMessageDelta = ThreadMessageDelta(
+        data=MessageDeltaEvent(
+            id=str(random_uuid),
+            delta=MessageDelta(
+                content=[
+                    TextDeltaBlock(
+                        index=index,
+                        type="text",
+                        text=TextDelta(
+                            annotations=[],
+                            value=streaming_response.choices[0].chat_item.content,
+                        ),
+                    )
+                ],
+                role="assistant",
+            ),
+            object="thread.message.delta",
+        ),
+        event="thread.message.delta",
+    )
+    return thread_message_event

src/leapfrogai_api/backend/grpc_client.py

@@ -1,6 +1,6 @@
 """gRPC client for OpenAI models."""
 
-from typing import Iterator
+from typing import Iterator, AsyncGenerator, Any
 import grpc
 from fastapi.responses import StreamingResponse
 import leapfrogai_sdk as lfai
@@ -16,6 +16,9 @@
     EmbeddingResponseData,
     Usage,
 )
+from leapfrogai_sdk.chat.chat_pb2 import (
+    ChatCompletionResponse as ProtobufChatCompletionResponse,
+)
 from leapfrogai_api.utils.config import Model
 
 
@@ -66,6 +69,22 @@ async def stream_chat_completion(model: Model, request: lfai.ChatCompletionReque
         return StreamingResponse(recv_chat(stream), media_type="text/event-stream")
 
 
+async def stream_chat_completion_raw(
+    model: Model, request: lfai.ChatCompletionRequest
+) -> AsyncGenerator[ProtobufChatCompletionResponse, Any]:
+    """Stream chat completion using the specified model."""
+    async with grpc.aio.insecure_channel(model.backend) as channel:
+        stub = lfai.ChatCompletionStreamServiceStub(channel)
+        stream: grpc.aio.UnaryStreamCall[
+            lfai.ChatCompletionRequest, lfai.ChatCompletionResponse
+        ] = stub.ChatCompleteStream(request)
+
+        await stream.wait_for_connection()
+
+        async for response in stream:
+            yield response
+
+
 # TODO: Clean up completion() and stream_completion() to reduce code duplication
 async def chat_completion(model: Model, request: lfai.ChatCompletionRequest):
     """Complete chat using the specified model."""

src/leapfrogai_api/backend/helpers.py

@@ -1,6 +1,6 @@
 """Helper functions for the OpenAI backend."""
 
-from typing import BinaryIO, Iterator
+from typing import BinaryIO, Iterator, AsyncGenerator, Any
 import grpc
 import leapfrogai_sdk as lfai
 from leapfrogai_api.backend.types import (
@@ -48,7 +48,7 @@ async def recv_chat(
     stream: grpc.aio.UnaryStreamCall[
         lfai.ChatCompletionRequest, lfai.ChatCompletionResponse
     ],
-):
+) -> AsyncGenerator[str, Any]:
     """Generator that yields chat completion responses as Server-Sent Events."""
     async for c in stream:
         yield (

src/leapfrogai_api/backend/rag/query.py

@@ -2,6 +2,7 @@
 
 from supabase_py_async import AsyncClient
 from leapfrogai_api.backend.rag.index import IndexingService
+from postgrest.base_request_builder import SingleAPIResponse
 
 
 class QueryService:
@@ -11,7 +12,9 @@ def __init__(self, db: AsyncClient) -> None:
         """Initializes the QueryService."""
         self.db = db
 
-    async def query_rag(self, query: str, vector_store_id: str, k: int = 5):
+    async def query_rag(
+        self, query: str, vector_store_id: str, k: int = 5
+    ) -> SingleAPIResponse:
         """
         Query the Vector Store.
 

src/leapfrogai_api/backend/types.py

@@ -5,15 +5,24 @@
 import datetime
 from enum import Enum
 from typing import Literal
-from pydantic import BaseModel, Field
+
 from fastapi import UploadFile, Form, File
-from openai.types.beta.vector_store import ExpiresAfter
 from openai.types import FileObject
-from openai.types.beta import VectorStore
 from openai.types.beta import Assistant, AssistantTool
-from openai.types.beta.threads import Message, MessageContent, TextContentBlock, Text
-from openai.types.beta.threads.message import Attachment
-from openai.types.beta.assistant import ToolResources
+from openai.types.beta import VectorStore
+from openai.types.beta.assistant import (
+    ToolResources as BetaAssistantToolResources,
+    ToolResourcesFileSearch,
+)
+from openai.types.beta.assistant_tool import FileSearchTool
+from openai.types.beta.thread import ToolResources as BetaThreadToolResources
+from openai.types.beta.thread_create_params import (
+    ToolResourcesFileSearchVectorStoreChunkingStrategy,
+    ToolResourcesFileSearchVectorStoreChunkingStrategyAuto,
+)
+from openai.types.beta.threads.text_content_block_param import TextContentBlockParam
+from openai.types.beta.vector_store import ExpiresAfter
+from pydantic import BaseModel, Field
 
 
 ##########
@@ -101,8 +110,8 @@ class ChatFunction(BaseModel):
 class ChatMessage(BaseModel):
     """Message object for chat completion."""
 
-    role: str
-    content: str
+    role: Literal["user", "assistant", "system", "function"]
+    content: str | list[TextContentBlockParam]
 
 
 class ChatDelta(BaseModel):
@@ -259,16 +268,29 @@ class ListFilesResponse(BaseModel):
 class CreateAssistantRequest(BaseModel):
     """Request object for creating an assistant."""
 
-    model: str = "mistral"
-    name: str | None = "Froggy Assistant"
-    description: str | None = "A helpful assistant."
-    instructions: str | None = "You are a helpful assistant."
-    tools: list[AssistantTool] | None = []  # This is all we support right now
-    tool_resources: ToolResources | None = ToolResources()
-    metadata: dict | None = Field(default=None, examples=[{}])
-    temperature: float | None = 1.0
-    top_p: float | None = 1.0
-    response_format: Literal["auto"] | None = "auto"  # This is all we support right now
+    model: str = Field(default="llama-cpp-python", examples=["llama-cpp-python"])
+    name: str | None = Field(default=None, examples=["Froggy Assistant"])
+    description: str | None = Field(default=None, examples=["A helpful assistant."])
+    instructions: str | None = Field(
+        default=None, examples=["You are a helpful assistant."]
+    )
+    tools: list[AssistantTool] | None = Field(
+        default=None, examples=[[FileSearchTool(type="file_search")]]
+    )
+    tool_resources: BetaAssistantToolResources | None = Field(
+        default=None,
+        examples=[
+            BetaAssistantToolResources(
+                file_search=ToolResourcesFileSearch(vector_store_ids=[])
+            )
+        ],
+    )
+    metadata: dict | None = Field(default={}, examples=[{}])
+    temperature: float | None = Field(default=None, examples=[1.0])
+    top_p: float | None = Field(default=None, examples=[1.0])
+    response_format: Literal["auto"] | None = Field(
+        default=None, examples=["auto"]
+    )  # This is all we support right now
 
 
 class ModifyAssistantRequest(CreateAssistantRequest):
@@ -304,6 +326,21 @@ class VectorStoreStatus(Enum):
     COMPLETED = "completed"
 
 
+class CreateVectorStoreFileRequest(BaseModel):
+    """Request object for creating a vector store file."""
+
+    chunking_strategy: ToolResourcesFileSearchVectorStoreChunkingStrategy | None = (
+        Field(
+            default=None,
+            examples=[
+                ToolResourcesFileSearchVectorStoreChunkingStrategyAuto(type="auto")
+            ],
+        )
+    )
+
+    file_id: str = Field(default="", examples=[""])
+
+
 class CreateVectorStoreRequest(BaseModel):
     """Request object for creating a vector store."""
 
@@ -371,30 +408,18 @@ class ListVectorStoresResponse(BaseModel):
 ################
 
 
-class CreateThreadRequest(BaseModel):
-    """Request object for creating a thread."""
+class ModifyRunRequest(BaseModel):
+    """Request object for modifying a run."""
 
-    messages: list[Message] | None = Field(default=None, examples=[None])
-    tool_resources: ToolResources | None = Field(default=None, examples=[None])
-    metadata: dict | None = Field(default=None, examples=[{}])
+    metadata: dict[str, str] | None = Field(default=None, examples=[{}])
 
 
 class ModifyThreadRequest(BaseModel):
     """Request object for modifying a thread."""
 
-    tool_resources: ToolResources | None = Field(default=None, examples=[None])
-    metadata: dict | None = Field(default=None, examples=[{}])
-
-
-class CreateMessageRequest(BaseModel):
-    """Request object for creating a message."""
-
-    role: Literal["user", "assistant"] = Field(default="user")
-    content: list[MessageContent] = Field(
-        default=[TextContentBlock(text=Text(value="", annotations=[]), type="text")],
-        examples=[[TextContentBlock(text=Text(value="", annotations=[]), type="text")]],
+    tool_resources: BetaThreadToolResources | None = Field(
+        default=None, examples=[None]
     )
-    attachments: list[Attachment] | None = Field(default=None, examples=[None])
     metadata: dict | None = Field(default=None, examples=[{}])