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https://github.com/open-webui/open-webui
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@ -923,24 +923,9 @@ TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = PersistentConfig(
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####################################
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####################################
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# RAG document content extraction
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# Vector Database
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####################################
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####################################
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CONTENT_EXTRACTION_ENGINE = PersistentConfig(
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"CONTENT_EXTRACTION_ENGINE",
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"rag.CONTENT_EXTRACTION_ENGINE",
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os.environ.get("CONTENT_EXTRACTION_ENGINE", "").lower(),
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)
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TIKA_SERVER_URL = PersistentConfig(
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"TIKA_SERVER_URL",
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"rag.tika_server_url",
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os.getenv("TIKA_SERVER_URL", "http://tika:9998"), # Default for sidecar deployment
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)
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####################################
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# RAG
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####################################
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CHROMA_DATA_PATH = f"{DATA_DIR}/vector_db"
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CHROMA_DATA_PATH = f"{DATA_DIR}/vector_db"
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CHROMA_TENANT = os.environ.get("CHROMA_TENANT", chromadb.DEFAULT_TENANT)
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CHROMA_TENANT = os.environ.get("CHROMA_TENANT", chromadb.DEFAULT_TENANT)
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@ -958,6 +943,43 @@ else:
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CHROMA_HTTP_SSL = os.environ.get("CHROMA_HTTP_SSL", "false").lower() == "true"
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CHROMA_HTTP_SSL = os.environ.get("CHROMA_HTTP_SSL", "false").lower() == "true"
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# 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)
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# 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)
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if CHROMA_HTTP_HOST != "":
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CHROMA_CLIENT = chromadb.HttpClient(
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host=CHROMA_HTTP_HOST,
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port=CHROMA_HTTP_PORT,
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headers=CHROMA_HTTP_HEADERS,
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ssl=CHROMA_HTTP_SSL,
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tenant=CHROMA_TENANT,
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database=CHROMA_DATABASE,
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settings=Settings(allow_reset=True, anonymized_telemetry=False),
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)
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else:
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CHROMA_CLIENT = chromadb.PersistentClient(
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path=CHROMA_DATA_PATH,
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settings=Settings(allow_reset=True, anonymized_telemetry=False),
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tenant=CHROMA_TENANT,
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database=CHROMA_DATABASE,
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)
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####################################
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# RAG
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####################################
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# RAG Content Extraction
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CONTENT_EXTRACTION_ENGINE = PersistentConfig(
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"CONTENT_EXTRACTION_ENGINE",
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"rag.CONTENT_EXTRACTION_ENGINE",
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os.environ.get("CONTENT_EXTRACTION_ENGINE", "").lower(),
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)
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TIKA_SERVER_URL = PersistentConfig(
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"TIKA_SERVER_URL",
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"rag.tika_server_url",
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os.getenv("TIKA_SERVER_URL", "http://tika:9998"), # Default for sidecar deployment
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)
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RAG_TOP_K = PersistentConfig(
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RAG_TOP_K = PersistentConfig(
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"RAG_TOP_K", "rag.top_k", int(os.environ.get("RAG_TOP_K", "5"))
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"RAG_TOP_K", "rag.top_k", int(os.environ.get("RAG_TOP_K", "5"))
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)
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)
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@ -1049,25 +1071,6 @@ RAG_RERANKING_MODEL_TRUST_REMOTE_CODE = (
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)
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)
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if CHROMA_HTTP_HOST != "":
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CHROMA_CLIENT = chromadb.HttpClient(
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host=CHROMA_HTTP_HOST,
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port=CHROMA_HTTP_PORT,
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headers=CHROMA_HTTP_HEADERS,
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ssl=CHROMA_HTTP_SSL,
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tenant=CHROMA_TENANT,
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database=CHROMA_DATABASE,
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settings=Settings(allow_reset=True, anonymized_telemetry=False),
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)
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else:
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CHROMA_CLIENT = chromadb.PersistentClient(
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path=CHROMA_DATA_PATH,
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settings=Settings(allow_reset=True, anonymized_telemetry=False),
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tenant=CHROMA_TENANT,
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database=CHROMA_DATABASE,
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)
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# device type embedding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
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# device type embedding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
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USE_CUDA = os.environ.get("USE_CUDA_DOCKER", "false")
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USE_CUDA = os.environ.get("USE_CUDA_DOCKER", "false")
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