diff --git a/agents-api/agents_api/activities/embed_docs.py b/agents-api/agents_api/activities/embed_docs.py index 0fad43d92..924424881 100644 --- a/agents-api/agents_api/activities/embed_docs.py +++ b/agents-api/agents_api/activities/embed_docs.py @@ -1,8 +1,7 @@ from beartype import beartype from temporalio import activity -from ..clients import cozo -from ..clients import vertexai as embedder +from ..clients import cozo, litellm from ..env import testing from ..models.docs.embed_snippets import embed_snippets as embed_snippets_query from .types import EmbedDocsPayload @@ -14,8 +13,8 @@ async def embed_docs(payload: EmbedDocsPayload, cozo_client=None) -> None: embed_instruction: str = payload.embed_instruction or "" title: str = payload.title or "" - embeddings = await embedder.embed( - [ + embeddings = await litellm.aembedding( + inputs=[ ( embed_instruction + (title + "\n\n" + snippet) if title else snippet ).strip() diff --git a/agents-api/agents_api/clients/litellm.py b/agents-api/agents_api/clients/litellm.py index bb996576f..865db58db 100644 --- a/agents-api/agents_api/clients/litellm.py +++ b/agents-api/agents_api/clients/litellm.py @@ -1,21 +1,31 @@ from functools import wraps -from typing import List +from typing import List, Literal from beartype import beartype -from litellm import acompletion as _acompletion -from litellm import get_supported_openai_params +from litellm import ( + acompletion as _acompletion, + aembedding as _aembedding, + get_supported_openai_params, +) +import litellm from litellm.utils import CustomStreamWrapper, ModelResponse -from ..env import litellm_master_key, litellm_url +from ..env import embedding_model_id, embedding_dimensions, litellm_master_key, litellm_url __all__: List[str] = ["acompletion"] +# TODO: Should check if this is really needed +litellm.drop_params = True + @wraps(_acompletion) @beartype async def acompletion( *, model: str, messages: list[dict], custom_api_key: None | str = None, **kwargs ) -> ModelResponse | CustomStreamWrapper: + if not custom_api_key: + model = f"openai/{model}" # FIXME: This is for litellm + supported_params = get_supported_openai_params(model) settings = {k: v for k, v in kwargs.items() if k in supported_params} @@ -26,3 +36,40 @@ async def acompletion( base_url=None if custom_api_key else litellm_url, api_key=custom_api_key or litellm_master_key, ) + + +@wraps(_aembedding) +@beartype +async def aembedding( + *, + inputs: str |list[str], + model: str = embedding_model_id, + dimensions: int = embedding_dimensions, + join_inputs: bool = False, + custom_api_key: None | str = None, + **settings, +) -> list[list[float]]: + if not custom_api_key: + model = f"openai/{model}" # FIXME: This is for litellm + + if isinstance(inputs, str): + input = [inputs] + else: + input = ["\n\n".join(inputs)] if join_inputs else inputs + + response = await _aembedding( + model=model, + input=input, + # dimensions=dimensions, # FIXME: litellm doesn't support dimensions correctly + api_base=None if custom_api_key else litellm_url, + api_key=custom_api_key or litellm_master_key, + drop_params=True, + **settings, + ) + + embedding_list: list[dict[Literal["embedding"], list[float]]] = response.data + + # FIXME: Truncation should be handled by litellm + result = [embedding["embedding"][:dimensions] for embedding in embedding_list] + + return result diff --git a/agents-api/agents_api/clients/embed.py b/agents-api/agents_api/clients/old_embed.py similarity index 100% rename from agents-api/agents_api/clients/embed.py rename to agents-api/agents_api/clients/old_embed.py diff --git a/agents-api/agents_api/clients/vertexai.py b/agents-api/agents_api/clients/vertexai.py deleted file mode 100644 index eaaee0182..000000000 --- a/agents-api/agents_api/clients/vertexai.py +++ /dev/null @@ -1,18 +0,0 @@ -import litellm -from litellm import aembedding - -from ..env import google_project_id, vertex_location - -litellm.vertex_project = google_project_id -litellm.vertex_location = vertex_location - - -async def embed( - inputs: list[str], dimensions: int = 1024, join_inputs: bool = True -) -> list[list[float]]: - input = ["\n\n".join(inputs)] if join_inputs else inputs - response = await aembedding( - model="vertex_ai/text-embedding-004", input=input, dimensions=dimensions - ) - - return response.data or [] diff --git a/agents-api/agents_api/env.py b/agents-api/agents_api/env.py index b5253788f..daee79172 100644 --- a/agents-api/agents_api/env.py +++ b/agents-api/agents_api/env.py @@ -25,6 +25,7 @@ # ----- task_max_parallelism: int = env.int("AGENTS_API_TASK_MAX_PARALLELISM", default=100) + # Debug # ----- debug: bool = env.bool("AGENTS_API_DEBUG", default=False) @@ -51,6 +52,7 @@ api_key_header_name: str = env.str("AGENTS_API_KEY_HEADER_NAME", default="X-Auth-Key") + # Litellm API # ----------- litellm_url: str = env.str("LITELLM_URL", default="http://0.0.0.0:4000") @@ -59,13 +61,11 @@ # Embedding service # ----------------- -embedding_service_base: str = env.str( - "EMBEDDING_SERVICE_BASE", default="http://0.0.0.0:8082" -) embedding_model_id: str = env.str( "EMBEDDING_MODEL_ID", default="Alibaba-NLP/gte-large-en-v1.5" ) -truncate_embed_text: bool = env.bool("TRUNCATE_EMBED_TEXT", default=True) + +embedding_dimensions: int = env.int("EMBEDDING_DIMENSIONS", default=1024) # Temporal @@ -77,9 +77,6 @@ temporal_endpoint: Any = env.str("TEMPORAL_ENDPOINT", default="localhost:7233") temporal_task_queue: Any = env.str("TEMPORAL_TASK_QUEUE", default="julep-task-queue") -# Google cloud -google_project_id: str = env.str("GOOGLE_PROJECT_ID") -vertex_location: str = env.str("VERTEX_LOCATION", default="us-central1") # Consolidate environment variables environment: Dict[str, Any] = dict( @@ -94,13 +91,10 @@ api_key_header_name=api_key_header_name, hostname=hostname, api_prefix=api_prefix, - embedding_service_base=embedding_service_base, - truncate_embed_text=truncate_embed_text, temporal_worker_url=temporal_worker_url, temporal_namespace=temporal_namespace, embedding_model_id=embedding_model_id, testing=testing, - google_project_id=google_project_id, ) if debug or testing: diff --git a/agents-api/agents_api/models/chat/gather_messages.py b/agents-api/agents_api/models/chat/gather_messages.py index f1b64d05d..3712a9137 100644 --- a/agents-api/agents_api/models/chat/gather_messages.py +++ b/agents-api/agents_api/models/chat/gather_messages.py @@ -9,7 +9,7 @@ from agents_api.autogen.Chat import ChatInput from ...autogen.openapi_model import DocReference, History -from ...clients import vertexai as embed +from ...clients import litellm from ...common.protocol.developers import Developer from ...common.protocol.sessions import ChatContext from ..docs.search_docs_hybrid import search_docs_hybrid @@ -61,12 +61,11 @@ async def gather_messages( return past_messages, [] # Search matching docs - query_embedding = await embed.embed( - inputs=[ + [query_embedding, *_] = await litellm.aembedding( + inputs="\n\n".join([ f"{msg.get('name') or msg['role']}: {msg['content']}" for msg in new_raw_messages - ], - join_inputs=True, + ]), ) query_text = new_raw_messages[-1]["content"] diff --git a/agents-api/agents_api/routers/docs/embed.py b/agents-api/agents_api/routers/docs/embed.py index 932fcbf6c..3e880fa74 100644 --- a/agents-api/agents_api/routers/docs/embed.py +++ b/agents-api/agents_api/routers/docs/embed.py @@ -3,12 +3,11 @@ from fastapi import Depends -import agents_api.clients.vertexai as embedder - from ...autogen.openapi_model import ( EmbedQueryRequest, EmbedQueryResponse, ) +from ...clients import litellm from ...dependencies.developer_id import get_developer_id from .router import router @@ -23,6 +22,6 @@ async def embed( [text_to_embed] if isinstance(text_to_embed, str) else text_to_embed ) - vectors = await embedder.embed(inputs=text_to_embed) + vectors = await litellm.aembedding(inputs=text_to_embed) return EmbedQueryResponse(vectors=vectors) diff --git a/agents-api/agents_api/routers/sessions/chat.py b/agents-api/agents_api/routers/sessions/chat.py index 27199c58d..1963db316 100644 --- a/agents-api/agents_api/routers/sessions/chat.py +++ b/agents-api/agents_api/routers/sessions/chat.py @@ -47,7 +47,6 @@ async def chat( # Merge the settings and prepare environment chat_context.merge_settings(chat_input) settings: dict = chat_context.settings.model_dump() - settings["model"] = f"openai/{settings['model']}" # litellm proxy idiosyncracy # Get the past messages and doc references past_messages, doc_references = await gather_messages( diff --git a/agents-api/poetry.lock b/agents-api/poetry.lock index 050f2516f..e3882e93d 100644 --- a/agents-api/poetry.lock +++ b/agents-api/poetry.lock @@ -149,13 +149,13 @@ files = [ [[package]] name = "anyio" -version = "4.4.0" +version = "4.5.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.8" files = [ - {file = 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-4624,4 +4652,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.11,<3.12" -content-hash = "67ea5d319a5e733137e06c3d576f7e606f31b3237760ff1360821d2ca9db570c" +content-hash = "0f44caacfcff3c513b0374bd9e4d787576700184247c2572a31f1033083b21b9" diff --git a/agents-api/pyproject.toml b/agents-api/pyproject.toml index dd2963440..3d7a7c925 100644 --- a/agents-api/pyproject.toml +++ b/agents-api/pyproject.toml @@ -23,7 +23,7 @@ arrow = "^1.3.0" jinja2 = "^3.1.4" jinja2schema = "^0.1.4" jsonschema = "^4.21.1" -litellm = "^1.43.18" +litellm = "^1.46.7" numpy = "^2.1.0" tiktoken = "^0.7.0" tenacity = "^9.0.0" diff --git a/embedding-service/docker-compose.yml b/embedding-service/docker-compose.yml index b6b96c6b3..2ee619f8f 100644 --- a/embedding-service/docker-compose.yml +++ b/embedding-service/docker-compose.yml @@ -7,8 +7,6 @@ x--text-embeddings-inference: &text-embeddings-inference - MODEL_ID=${EMBEDDING_MODEL_ID:-Alibaba-NLP/gte-large-en-v1.5} image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 - ports: - - "8082:80" volumes: - ~/.cache/huggingface/hub:/data diff --git a/llm-proxy/docker-compose.yml b/llm-proxy/docker-compose.yml index bbcb184ee..ca75164c9 100644 --- a/llm-proxy/docker-compose.yml +++ b/llm-proxy/docker-compose.yml @@ -3,11 +3,10 @@ name: julep-llm-proxy services: litellm: image: ghcr.io/berriai/litellm-database:main-v1.46.6 + restart: unless-stopped volumes: - ./litellm-config.yaml:/app/config.yaml - - .keys:/app/.keys - ports: - - "4000:4000" + - .keys:/app/.keys:ro environment: - LITELLM_MASTER_KEY=${LITELLM_MASTER_KEY} - LITELLM_POSTGRES_DB=${LITELLM_POSTGRES_DB:-litellm} @@ -26,6 +25,7 @@ services: - GITHUB_API_KEY=${GITHUB_API_KEY} - VOYAGE_API_KEY=${VOYAGE_API_KEY} - GOOGLE_APPLICATION_CREDENTIALS=${GOOGLE_APPLICATION_CREDENTIALS} + - EMBEDDING_SERVICE_BASE=${EMBEDDING_SERVICE_BASE:-http://text-embeddings-inference-gpu} command: [ "--config", @@ -41,9 +41,15 @@ services: - litellm-db - litellm-redis + develop: + watch: + - action: sync+restart + path: ./litellm-config.yaml + target: /app/config.yaml + litellm-db: image: postgres:16 - restart: always + restart: unless-stopped volumes: - litellm-db-data:/var/lib/postgresql/data ports: @@ -61,13 +67,11 @@ services: litellm-redis: image: redis/redis-stack-server - restart: always + restart: unless-stopped environment: REDIS_ARGS: --requirepass ${LITELLM_REDIS_PASSWORD} volumes: - litellm-redis-data:/data - ports: - - "16379:6379" volumes: litellm-db-data: diff --git a/llm-proxy/litellm-config.yaml b/llm-proxy/litellm-config.yaml index 0e2cf0254..226a814ab 100644 --- a/llm-proxy/litellm-config.yaml +++ b/llm-proxy/litellm-config.yaml @@ -85,25 +85,25 @@ model_list: api_key: os.environ/VOYAGE_API_KEY tags: ["paid"] -- model_name: voyage-large-2 +- model_name: voyage-3 litellm_params: model: "voyage/voyage-large-2" api_key: os.environ/VOYAGE_API_KEY tags: ["paid"] -- model_name: gte-large-en-v1.5 +- model_name: Alibaba-NLP/gte-large-en-v1.5 litellm_params: model: openai/Alibaba-NLP/gte-large-en-v1.5 api_base: os.environ/EMBEDDING_SERVICE_BASE tags: ["free"] -- model_name: bge-m3 +- model_name: BAAI/bge-m3 litellm_params: model: openai/BAAI/bge-m3 api_base: os.environ/EMBEDDING_SERVICE_BASE tags: ["free"] -- model_name: text-embedding-004 +- model_name: vertex_ai/text-embedding-004 litellm_params: model: vertex_ai/text-embedding-004 vertex_project: os.environ/GOOGLE_PROJECT_ID diff --git a/memory-store/docker-compose.yml b/memory-store/docker-compose.yml index 303677e94..3ed06f1de 100644 --- a/memory-store/docker-compose.yml +++ b/memory-store/docker-compose.yml @@ -24,6 +24,7 @@ services: memory-store-backup-cron: image: mcuadros/ofelia:latest + restart: unless-stopped depends_on: - memory-store command: daemon --docker -f label=com.docker.compose.project=${COMPOSE_PROJECT_NAME} diff --git a/monitoring/docker-compose.yml b/monitoring/docker-compose.yml index d13bd3bb6..51cb60f67 100644 --- a/monitoring/docker-compose.yml +++ b/monitoring/docker-compose.yml @@ -4,6 +4,7 @@ services: portainer: image: portainer/portainer-ce:latest container_name: portainer + restart: unless-stopped ports: - "9000:8000" - "9443:9443" @@ -16,8 +17,6 @@ services: container_name: prometheus command: - "--config.file=/etc/prometheus/prometheus.yml" - ports: - - 9090:9090 restart: unless-stopped volumes: - ./prometheus:/etc/prometheus diff --git a/scheduler/docker-compose.yml b/scheduler/docker-compose.yml index 6e452eb8d..21cd5fab9 100644 --- a/scheduler/docker-compose.yml +++ b/scheduler/docker-compose.yml @@ -14,8 +14,6 @@ services: - POSTGRES_SEEDS=temporal-db - DYNAMIC_CONFIG_FILE_PATH=config/dynamicconfig/development-sql.yaml image: temporalio/auto-setup:1.24 - ports: - - 7233:7233 volumes: - ./dynamicconfig:/etc/temporal/config/dynamicconfig @@ -35,8 +33,6 @@ services: - POSTGRES_DB=${TEMPORAL_POSTGRES_DB:-temporal} - POSTGRES_USER=${TEMPORAL_POSTGRES_USER:-temporal} - POSTGRES_PASSWORD=${TEMPORAL_POSTGRES_PASSWORD} - ports: - - 25432:5432 volumes: - temporal-db-data:/var/lib/postgresql/data healthcheck: