Merge branch 'rag_scoring_fn_1' into rag_scoring_fn_2

llama_stack/providers/utils/inference/openai_compat.py

@@ -4,17 +4,28 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from typing import AsyncGenerator, Optional
+from typing import AsyncGenerator, List, Optional
 
 from llama_models.llama3.api.chat_format import ChatFormat
 
-from llama_models.llama3.api.datatypes import StopReason
-
-from llama_stack.apis.inference import *  # noqa: F403
+from llama_models.llama3.api.datatypes import SamplingParams, StopReason
 from pydantic import BaseModel
 
 from llama_stack.apis.common.content_types import ImageContentItem, TextContentItem
 
+from llama_stack.apis.inference import (
+    ChatCompletionResponse,
+    ChatCompletionResponseEvent,
+    ChatCompletionResponseEventType,
+    ChatCompletionResponseStreamChunk,
+    CompletionMessage,
+    CompletionResponse,
+    CompletionResponseStreamChunk,
+    Message,
+    ToolCallDelta,
+    ToolCallParseStatus,
+)
+
 from llama_stack.providers.utils.inference.prompt_adapter import (
     convert_image_content_to_url,
 )

llama_stack/providers/utils/inference/prompt_adapter.py

@@ -40,7 +40,6 @@ from llama_stack.apis.common.content_types import (
     InterleavedContent,
     InterleavedContentItem,
     TextContentItem,
-    URL,
 )
 
 from llama_stack.apis.inference import (
@@ -94,9 +93,14 @@ async def convert_request_to_raw(
             d = m.model_dump()
             d["content"] = content
             messages.append(RawMessage(**d))
-        request.messages = messages
+
+        d = request.model_dump()
+        d["messages"] = messages
+        request = ChatCompletionRequestWithRawContent(**d)
     else:
-        request.content = await interleaved_content_convert_to_raw(request.content)
+        d = request.model_dump()
+        d["content"] = await interleaved_content_convert_to_raw(request.content)
+        request = CompletionRequestWithRawContent(**d)
 
     return request
 
@@ -112,27 +116,31 @@ async def interleaved_content_convert_to_raw(
         elif isinstance(c, TextContentItem):
             return RawTextItem(text=c.text)
         elif isinstance(c, ImageContentItem):
-            # load image and return PIL version
-            img = c.data
-            if isinstance(img, URL):
-                if img.uri.startswith("data"):
-                    match = re.match(r"data:image/(\w+);base64,(.+)", img.uri)
+            if c.url:
+                # Load image bytes from URL
+                if c.url.uri.startswith("data"):
+                    match = re.match(r"data:image/(\w+);base64,(.+)", c.url.uri)
                     if not match:
-                        raise ValueError("Invalid data URL format")
+                        raise ValueError(
+                            f"Invalid data URL format, {c.url.uri[:40]}..."
+                        )
                     _, image_data = match.groups()
                     data = base64.b64decode(image_data)
-                elif img.uri.startswith("file://"):
-                    path = img.uri[len("file://") :]
+                elif c.url.uri.startswith("file://"):
+                    path = c.url.uri[len("file://") :]
                     with open(path, "rb") as f:
                         data = f.read()  # type: ignore
-                elif img.uri.startswith("http"):
+                elif c.url.uri.startswith("http"):
                     async with httpx.AsyncClient() as client:
-                        response = await client.get(img.uri)
+                        response = await client.get(c.url.uri)
                         data = response.content
                 else:
                     raise ValueError("Unsupported URL type")
-            else:
+            elif c.data:
                 data = c.data
+            else:
+                raise ValueError("No data or URL provided")
+
             return RawMediaItem(data=data)
         else:
             raise ValueError(f"Unsupported content type: {type(c)}")
@@ -277,7 +285,8 @@ def chat_completion_request_to_messages(
     ):
         # llama3.1 and llama3.2 multimodal models follow the same tool prompt format
         messages = augment_messages_for_tools_llama_3_1(request)
-    elif model.model_family == ModelFamily.llama3_2:
+    elif model.model_family in (ModelFamily.llama3_2, ModelFamily.llama3_3):
+        # llama3.2 and llama3.3 models follow the same tool prompt format
         messages = augment_messages_for_tools_llama_3_2(request)
     else:
         messages = request.messages

llama_stack/providers/utils/kvstore/kvstore.py

@@ -4,8 +4,10 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from .api import *  # noqa: F403
-from .config import *  # noqa: F403
+from typing import List, Optional
+
+from .api import KVStore
+from .config import KVStoreConfig, KVStoreType
 
 
 def kvstore_dependencies():

llama_stack/providers/utils/kvstore/redis/redis.py

@@ -9,7 +9,7 @@ from typing import List, Optional
 
 from redis.asyncio import Redis
 
-from ..api import *  # noqa: F403
+from ..api import KVStore
 from ..config import RedisKVStoreConfig
 
 

llama_stack/providers/utils/kvstore/sqlite/sqlite.py

@@ -11,7 +11,7 @@ from typing import List, Optional
 
 import aiosqlite
 
-from ..api import *  # noqa: F403
+from ..api import KVStore
 from ..config import SqliteKVStoreConfig
 
 

llama_stack/providers/utils/memory/vector_store.py

@@ -15,14 +15,17 @@ from urllib.parse import unquote
 import chardet
 import httpx
 import numpy as np
+
+from llama_models.llama3.api.tokenizer import Tokenizer
 from numpy.typing import NDArray
 from pypdf import PdfReader
 
-from llama_models.llama3.api.datatypes import *  # noqa: F403
-from llama_models.llama3.api.tokenizer import Tokenizer
-
-from llama_stack.apis.common.content_types import InterleavedContent, TextContentItem
-from llama_stack.apis.memory import *  # noqa: F403
+from llama_stack.apis.common.content_types import (
+    InterleavedContent,
+    TextContentItem,
+    URL,
+)
+from llama_stack.apis.memory import Chunk, MemoryBankDocument, QueryDocumentsResponse
 from llama_stack.apis.memory_banks import VectorMemoryBank
 from llama_stack.providers.datatypes import Api
 from llama_stack.providers.utils.inference.prompt_adapter import (

llama_stack/providers/utils/scoring/aggregation_utils.py

@@ -6,7 +6,8 @@
 import statistics
 from typing import Any, Dict, List
 
-from llama_stack.apis.scoring import AggregationFunctionType, ScoringResultRow
+from llama_stack.apis.scoring import ScoringResultRow
+from llama_stack.apis.scoring_functions import AggregationFunctionType
 
 
 def aggregate_accuracy(scoring_results: List[ScoringResultRow]) -> Dict[str, Any]:

llama_stack/providers/utils/telemetry/tracing.py

@@ -12,10 +12,18 @@ import threading
 import uuid
 from datetime import datetime
 from functools import wraps
-from typing import Any, Callable, Dict, List
+from typing import Any, Callable, Dict, List, Optional
 
-
-from llama_stack.apis.telemetry import *  # noqa: F403
+from llama_stack.apis.telemetry import (
+    LogSeverity,
+    Span,
+    SpanEndPayload,
+    SpanStartPayload,
+    SpanStatus,
+    StructuredLogEvent,
+    Telemetry,
+    UnstructuredLogEvent,
+)
 from llama_stack.providers.utils.telemetry.trace_protocol import serialize_value
 
 log = logging.getLogger(__name__)