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config.py
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| import os | |
| from qdrant_client.http.models import Distance | |
| from typing import Any | |
| thread_id = "thread_demo" | |
| user_id = "user_demo" | |
| session_id = "session_demo" | |
| collection_name = "agent_ollama_demo" | |
| neo4j_auth: dict[str, Any] = { | |
| "url": "neo4j://localhost:7687", | |
| "username": None, | |
| "password": None, | |
| "database": None, | |
| } | |
| aws_config = { | |
| "access_key_id": os.environ.get("AWS_ACCESS_KEY_ID"), | |
| "secret_access_key": os.environ.get("AWS_SECRET_ACCESS_KEY"), | |
| "bucket": os.environ.get("AWS_BUCKET_NAME"), | |
| "region": os.environ.get("AWS_REGION") | |
| } | |
| model_ollama = { | |
| "model": "llama3.1", | |
| "model_provider": "ollama", | |
| "api_key": None, | |
| "base_url": "http://localhost:11434", | |
| "temperature": 0.5, | |
| } | |
| redis_config = { | |
| "host": "localhost", | |
| "port": 6379, | |
| "db": 0, | |
| } | |
| model_embedding_vs_config = { | |
| "path": None, | |
| "type": "hf", | |
| "name": "BAAI/bge-large-en-v1.5" | |
| } | |
| collection_config = { | |
| "collection_name": collection_name, | |
| "vectors_config": { | |
| "size": 768, | |
| # COSINE = "Cosine" | |
| # EUCLID = "Euclid" | |
| # DOT = "Dot" | |
| # MANHATTAN = "Manhattan" | |
| "distance": Distance.COSINE | |
| } | |
| } | |
| qdrant_config = { | |
| "url": "http://localhost:6333", | |
| } | |
| model_embedding_config = { | |
| "name": "nomic-embed-text", | |
| "url": "http://localhost:11434" | |
| } |
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