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LangChainRust framework implementation introduction
LangChainRust is a Rust implementation of the LangChain framework.
It provides core components for building LLM-powered applications.
The framework includes support for multiple LLM providers.
OpenAI and Ollama are the primary supported language models.
The framework supports function calling and structured outputs.
LangChainRust provides a complete memory system.
ConversationBufferMemory stores the full conversation history.
ConversationSummaryMemory uses LLM to summarize conversations.
ConversationSummaryBufferMemory combines both approaches.
ChatMessageHistory provides persistent message storage.
LangChainRust implements various chain patterns.
LLMChain is the basic single-step chain.
SequentialChain executes multiple chains in sequence.
RouterChain routes inputs to different chains.
RetrievalQA combines retrieval with question answering.
LangChainRust has a complete agent framework.
ReActAgent uses the ReAct pattern for reasoning.
FunctionCallingAgent uses native function calling.
AgentExecutor manages the agent execution loop.
Agents can use multiple tools simultaneously.
LangChainRust provides RAG retrieval capabilities.
TextSplitter splits documents into chunks.
PDFLoader and CSVLoader load various document formats.
SimilarityRetriever performs vector similarity search.
BM25Retriever performs keyword-based retrieval.
LangChainRust supports LangGraph workflows.
StateGraph builds graph-based agent workflows.
ConditionalEdge enables dynamic routing.
Human-in-the-loop allows manual intervention.
Subgraph supports nested workflow structures.
Parallel enables concurrent node execution.
LangChainRust includes callback and tracing support.
CallbackManager orchestrates callback handlers.
LangSmithHandler integrates with LangSmith tracing.
FileCallbackHandler logs to file in various formats.
RunTree tracks execution hierarchy.
LangChainRust provides vector store integrations.
InMemoryVectorStore provides in-memory storage.
QdrantVectorStore integrates with Qdrant database.
VectorStoreBuilder creates stores from configuration.
OpenAIEmbeddings generates document embeddings.