KJ24 commited on
Commit
037a839
·
verified ·
1 Parent(s): e4d3035

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +19 -7
app.py CHANGED
@@ -2,9 +2,10 @@ from fastapi import FastAPI
2
  from pydantic import BaseModel
3
  from typing import Optional
4
 
5
- from llama_index.core import Document, ServiceContext
6
- from llama_index.llms.llama_cpp import LlamaCPP
7
  from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 
8
  from llama_index.core.node_parser import SemanticSplitterNodeParser
9
 
10
  app = FastAPI()
@@ -33,14 +34,25 @@ async def chunk_text(data: ChunkRequest):
33
  embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")
34
 
35
  # ✅ Configuration du service IA
36
- service_context = ServiceContext.from_defaults(
37
- llm=llm,
38
- embed_model=embed_model
39
- )
 
 
 
 
 
 
40
 
 
41
  try:
42
  # ✅ Découpage sémantique intelligent
43
- parser = SemanticSplitterNodeParser.from_defaults(service_context=service_context)
 
 
 
 
44
  nodes = parser.get_nodes_from_documents([Document(text=data.text)])
45
 
46
  return {
 
2
  from pydantic import BaseModel
3
  from typing import Optional
4
 
5
+ from llama_index.core.settings import Settings
6
+ from llama_index.core import Document
7
  from llama_index.embeddings.huggingface import HuggingFaceEmbedding
8
+ from llama_index.llms.llama_cpp import LlamaCPP
9
  from llama_index.core.node_parser import SemanticSplitterNodeParser
10
 
11
  app = FastAPI()
 
34
  embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en-v1.5")
35
 
36
  # ✅ Configuration du service IA
37
+ # service_context = ServiceContext.from_defaults(
38
+ # llm=llm,
39
+ # embed_model=embed_model
40
+ # )
41
+
42
+
43
+ # ✅ Nouvelle méthode recommandée : paramétrer Settings globalement
44
+ Settings.llm = llm
45
+ Settings.embed_model = embed_model
46
+
47
 
48
+
49
  try:
50
  # ✅ Découpage sémantique intelligent
51
+ # parser = SemanticSplitterNodeParser.from_defaults(service_context=service_context)
52
+
53
+ # ✅ Appel du parser sans service_context
54
+
55
+ parser = SemanticSplitterNodeParser.from_defaults()
56
  nodes = parser.get_nodes_from_documents([Document(text=data.text)])
57
 
58
  return {