Bug fixes (#10971)

docs/module_guides/models/llms/modules.md

@@ -158,6 +158,15 @@ maxdepth: 1
 /examples/llm/monsterapi.ipynb
 ```
 
+## MyMagic
+
+```{toctree}
+---
+maxdepth: 1
+---
+/examples/llm/mymagic.ipynb
+```
+
 ## NeutrinoAI
 
 ```{toctree}

llama-index-core/llama_index/core/node_parser/text/sentence_window.py

@@ -1,4 +1,5 @@
 """Simple node parser."""
+
 from typing import Any, Callable, List, Optional, Sequence
 
 from llama_index.core.bridge.pydantic import Field
@@ -115,7 +116,9 @@ def build_window_nodes_from_documents(
             # add window to each node
             for i, node in enumerate(nodes):
                 window_nodes = nodes[
-                    max(0, i - self.window_size) : min(i + self.window_size, len(nodes))
+                    max(0, i - self.window_size) : min(
+                        i + self.window_size + 1, len(nodes)
+                    )
                 ]
 
                 node.metadata[self.window_metadata_key] = " ".join(

llama-index-core/llama_index/core/postprocessor/rankGPT_rerank.py

@@ -2,7 +2,7 @@
 from typing import Any, Dict, List, Optional, Sequence
 
 from llama_index.core.bridge.pydantic import Field
-from llama_index.core.llms import LLM, ChatMessage, ChatResponse, OpenAI
+from llama_index.core.llms import LLM, ChatMessage, ChatResponse
 from llama_index.core.postprocessor.types import BaseNodePostprocessor
 from llama_index.core.prompts import BasePromptTemplate
 from llama_index.core.prompts.default_prompts import RANKGPT_RERANK_PROMPT
@@ -14,12 +14,18 @@
 logger.setLevel(logging.WARNING)
 
 
+def get_default_llm() -> LLM:
+    from llama_index.llms.openai import OpenAI
+
+    return OpenAI(model="gpt-3.5-turbo-16k")
+
+
 class RankGPTRerank(BaseNodePostprocessor):
     """RankGPT-based reranker."""
 
     top_n: int = Field(default=5, description="Top N nodes to return from reranking.")
     llm: LLM = Field(
-        default_factory=lambda: OpenAI(model="gpt-3.5-turbo-16k"),
+        default_factory=get_default_llm,
         description="LLM to use for rankGPT",
     )
     verbose: bool = Field(

llama-index-core/llama_index/core/query_engine/knowledge_graph_query_engine.py

@@ -6,9 +6,6 @@
 from llama_index.core.base.base_query_engine import BaseQueryEngine
 from llama_index.core.base.response.schema import RESPONSE_TYPE
 from llama_index.core.callbacks.schema import CBEventType, EventPayload
-from llama_index.core.graph_stores.registry import (
-    GRAPH_STORE_CLASS_TO_GRAPH_STORE_TYPE,
-)
 from llama_index.core.llms.llm import LLM
 from llama_index.core.prompts.base import (
     BasePromptTemplate,
@@ -89,11 +86,6 @@ def __init__(
 
         self._llm = llm or llm_from_settings_or_context(Settings, service_context)
 
-        # Get Graph Store Type
-        self._graph_store_type = GRAPH_STORE_CLASS_TO_GRAPH_STORE_TYPE[
-            self.graph_store.__class__
-        ]
-
         # Get Graph schema
         self._graph_schema = self.graph_store.get_schema(refresh=refresh_schema)
 

llama-index-core/llama_index/core/response_synthesizers/factory.py

@@ -156,6 +156,7 @@ def get_response_synthesizer(
         )
     elif response_mode == ResponseMode.NO_TEXT:
         return NoText(
+            llm=llm,
             streaming=streaming,
             callback_manager=callback_manager,
             prompt_helper=prompt_helper,

llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/pyproject.toml

@@ -24,13 +24,13 @@ description = "llama-index embeddings azure openai integration"
 license = "MIT"
 name = "llama-index-embeddings-azure-openai"
 readme = "README.md"
-version = "0.1.2"
+version = "0.1.3"
 
 [tool.poetry.dependencies]
 python = ">=3.8.1,<3.12"
 llama-index-core = "^0.10.1"
 llama-index-llms-azure-openai = "^0.1.1"
-llama-index-llms-openai = "^0.1.1"
+llama-index-embeddings-openai = "^0.1.3"
 
 [tool.poetry.group.dev.dependencies]
 ipython = "8.10.0"

llama-index-integrations/embeddings/llama-index-embeddings-openai/llama_index/embeddings/openai/base.py

@@ -211,12 +211,12 @@ def get_engine(
     mode: str,
     model: str,
     mode_model_dict: Dict[Tuple[OpenAIEmbeddingMode, str], OpenAIEmbeddingModeModel],
-) -> OpenAIEmbeddingModeModel:
+) -> str:
     """Get engine."""
     key = (OpenAIEmbeddingMode(mode), OpenAIEmbeddingModelType(model))
     if key not in mode_model_dict:
         raise ValueError(f"Invalid mode, model combination: {key}")
-    return mode_model_dict[key]
+    return mode_model_dict[key].value
 
 
 class OpenAIEmbedding(BaseEmbedding):
@@ -275,8 +275,8 @@ class OpenAIEmbedding(BaseEmbedding):
         ),
     )
 
-    _query_engine: OpenAIEmbeddingModeModel = PrivateAttr()
-    _text_engine: OpenAIEmbeddingModeModel = PrivateAttr()
+    _query_engine: str = PrivateAttr()
+    _text_engine: str = PrivateAttr()
     _client: Optional[OpenAI] = PrivateAttr()
     _aclient: Optional[AsyncOpenAI] = PrivateAttr()
     _http_client: Optional[httpx.Client] = PrivateAttr()

llama-index-integrations/embeddings/llama-index-embeddings-openai/pyproject.toml

@@ -24,7 +24,7 @@ description = "llama-index embeddings openai integration"
 license = "MIT"
 name = "llama-index-embeddings-openai"
 readme = "README.md"
-version = "0.1.2"
+version = "0.1.3"
 
 [tool.poetry.dependencies]
 python = ">=3.8.1,<3.12"