Mirrors/open-webui
1
0
Fork 0
mirror of https://github.com/open-webui/open-webui.git synced 2025-12-16 03:47:49 +01:00
Code Issues Packages Projects Releases Wiki Activity

feat: hybrid search and reranking support

Browse Source
This commit is contained in:
Steven Kreitzer
2024-04-22 18:36:46 -05:00
parent db801aee79
commit c0259aad67
10 changed files with 262 additions and 131 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
backend/config.py
View File

@@ -420,6 +420,9 @@ if WEBUI_AUTH and WEBUI_SECRET_KEY == "":
CHROMA_DATA_PATH = f"{DATA_DIR}/vector_db"
# this uses the model defined in the Dockerfile ENV variable. If you dont use docker or docker based deployments such as k8s, the default embedding model will be used (sentence-transformers/all-MiniLM-L6-v2)
RAG_TOP_K = int(os.environ.get("RAG_TOP_K", "5"))
RAG_RELEVANCE_THRESHOLD = float(os.environ.get("RAG_RELEVANCE_THRESHOLD", "0.0"))
RAG_EMBEDDING_ENGINE = os.environ.get("RAG_EMBEDDING_ENGINE", "")
RAG_EMBEDDING_MODEL = os.environ.get(
@@ -431,10 +434,9 @@ RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE = (
os.environ.get("RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
)
RAG_RERANKING_MODEL = os.environ.get(
"RAG_RERANKING_MODEL", "BAAI/bge-reranker-v2-m3"
)
log.info(f"Reranking model set: {RAG_RERANKING_MODEL}"),
RAG_RERANKING_MODEL = os.environ.get("RAG_RERANKING_MODEL", "")
if not RAG_RERANKING_MODEL == "":
log.info(f"Reranking model set: {RAG_RERANKING_MODEL}"),
RAG_RERANKING_MODEL_TRUST_REMOTE_CODE = (
os.environ.get("RAG_RERANKING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
@@ -448,16 +450,15 @@ if USE_CUDA.lower() == "true":
else:
DEVICE_TYPE = "cpu"
CHROMA_CLIENT = chromadb.PersistentClient(
path=CHROMA_DATA_PATH,
settings=Settings(allow_reset=True, anonymized_telemetry=False),
)
CHUNK_SIZE = 1500
CHUNK_OVERLAP = 100
CHUNK_SIZE = int(os.environ.get("CHUNK_SIZE", "1500"))
CHUNK_OVERLAP = int(os.environ.get("CHUNK_OVERLAP", "100"))
RAG_TEMPLATE = """Use the following context as your learned knowledge, inside <context></context> XML tags.
DEFAULT_RAG_TEMPLATE = """Use the following context as your learned knowledge, inside <context></context> XML tags.
<context>
[context]
</context>
@@ -471,6 +472,8 @@ And answer according to the language of the user's question.
Given the context information, answer the query.
Query: [query]"""
RAG_TEMPLATE = os.environ.get("RAG_TEMPLATE", DEFAULT_RAG_TEMPLATE)
RAG_OPENAI_API_BASE_URL = os.getenv("RAG_OPENAI_API_BASE_URL", OPENAI_API_BASE_URL)
RAG_OPENAI_API_KEY = os.getenv("RAG_OPENAI_API_KEY", OPENAI_API_KEY)