2.2 验证安装包: import llama_index print(llama_index.__package__) pip list | grep llama > llama-index-core 0.10.13> llama-index-readers-file 0.1.6> llamaindex-py-client 0.1.13编辑于 2024-02-29 12:43・IP 属地上海 内容所属专栏 大模型实践 记录大模型的实践 订阅专栏 ...
prometheus-client==0.17.1 prompt-toolkit==3.0.39 protobuf==4.23.4 psutil==5.9.5 ptyprocess==0.7.0 pulsar-client==3.4.0 pure-eval==0.2.2 pyasn1==0.5.0 pyasn1-modules==0.3.0 pycosat @ file:///croot/pycosat_1666805502580/work pycparser @ file:///tmp/build/80754af9/pycparser_163...
client = qdrant_client.QdrantClient( path="./qdrant_data" ) vector_store = QdrantVectorStore(client=client, collection_name="tweets") storage_context = StorageContext.from_defaults(vector_store=vector_store) 现在设置我们的StorageContext。我们将把它作为LLM传递给Mixtral,这样我们就可以在完成索引后测试...
# 重新初始化向量存储库client = qdrant_client.QdrantClient( path="./qdrant_data")vector_store = QdrantVectorStore(client=client, collection_name="tweets")# 再次获取LLMllm = Ollama(model="mixtral")service_context = ServiceContext.from_defaults(llm=llm, embed_model="local")# 从向量存储库加...
打开 tetsite/members/views.py 视图文件，新增一个方法视图：import chromadbfrom llama_index.core importVectorStoreIndexfrom llama_index.core importStorageContextdefsearchIndexVectory(): db = chromadb.PersistentClient(path="./chroma_db") chroma_collection = db.get_or_create_collection("quickstar...
2 changes: 1 addition & 1 deletion 2 gpt_index/indices/base.py Original file line numberDiff line numberDiff line change @@ -40,7 +40,7 @@ class BaseGPTIndex(Generic[IS]): """Base GPT Index. """Base LlamaIndex. Args: documents (Optional[Sequence[BaseDocument]]): List of ...
import weaviate # Connect to your Weaviate instance client = weaviate.Client( embedded_optio...
Use saved searches to filter your results more quickly Cancel Create saved search Sign in Sign up Reseting focus {{ message }} dgon-jd / llama_index Public forked from run-llama/llama_index Notifications You must be signed in to change notification settings Fork 0 Star 0 ...
打开tetsite/members/views.py视图文件,新增一个方法视图: importchromadbfromllama_index.coreimportVectorStoreIndexfromllama_index.coreimportStorageContextdefsearchIndexVectory():db=chromadb.PersistentClient(path="./chroma_db")chroma_collection=db.get_or_create_collection("quickstart")storage_context=Storage...
在6_qdrant.py中，我们引入了Qdrant，一个开源的本地向量数据库，它将这些事实存储在磁盘上。这样，如果我们重新启动机器人，它就记得以前说过的话。使用pip install qdrant-client并引入一些新的依赖项：import qdrant_clientfrom llama_index.vector_stores.qdrant import QdrantVectorStore 现在我们将初始化Qdrant客户...