Fixes GH-3151
Follow-up of commit ca843e85887aa1da6300c77550c379c103500897,`includeCompletion` is renamed to `logCompletion`.
Signed-off-by: Yanming Zhou <zhouyanming@gmail.com>
Time-series each chat window in Cassandra, keeping past (and deleted) windows still in the db.
Add ability to store different MessageTypes.
Signed-off-by: mck <mck@apache.org>
- Rename the artifact ID of the chat memory repository artifacts:
- `spring-ai-model-chat-memory-jdbc` -> `spring-ai-model-chat-memory-repository-jdbc`
- `spring-ai-model-chat-memory-cassandra` -> `spring-ai-model-chat-memory-repository-cassandra`
- `spring-ai-model-chat-memory-neo4j` -> `spring-ai-model-chat-memory-repository-neo4j`
- Rename the package names to include "repository". Example: org.springframework.ai.chat.memory.repository.jdbc.JdbcChatMemoryRepository
- This package renaming also requires to change the default schema location for the jdbc repository to include "repository"
- Update the docs
- Update the artifact IDs in the parent POM, BOM, autoconfiguration and starters
- Update upgrade notes and docs to describe the changes
Fix JdbcChatMemoryRepositoryPostgresqlIT
- Make sure to set the dialect via datasource
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
Such as `BatchProperties.Jdbc`, `IntegrationProperties.Jdbc`, `JdbcSessionProperties` and `QuartzProperties.Jdbc`
1. Reuse Spring Boot's `DatabaseInitializationMode`
2. Allow to customize platform
3. add `OnJdbcChatMemoryRepositoryDatasourceInitializationCondition` for `JdbcChatMemoryRepositorySchemaInitializer`
Signed-off-by: Yanming Zhou <zhouyanming@gmail.com>
- Removed the CassandraChatMemory class and its usages, now using CassandraChatMemoryRepository.
- Updated configuration, repository, and test classes to rely on CassandraChatMemoryRepository.
- Cleaned up related configuration and integration tests.
- Minor doc update to reflect the removal.
Fixes#3090
Signed-off-by: Mark Pollack <mark.pollack@broadcom.com>
- Rename chat memory repository autoconfiguration modules to include the "repository" suffix:
- spring-ai-autoconfigure-model-chat-memory-cassandra -> spring-ai-autoconfigure-model-chat-memory-repository-cassandra
- spring-ai-autoconfigure-model-chat-memory-jdbc -> spring-ai-autoconfigure-model-chat-memory-repository-jdbc
- spring-ai-autoconfigure-model-chat-memory-neo4j -> spring-ai-autoconfigure-model-chat-memory-repository-neo4j
- Update Spring Boot starter modules to match the new naming convention.
- Rename packages to include `.repository.` for improved clarity and consistency.
- Rename configuration and related classes to use the `ChatMemoryRepository` suffix.
- Update Spring AI BOM and parent POM files to reference the new artifact names.
- Update all imports, references, and configuration to use the new package and class names.
BREAKING CHANGE:
These changes require users to update their dependencies, imports, and configuration to use the new artifact, package, and class names. See the upgrade notes for migration instructions.
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
This removes the possible large amount of data that was attached
to spans and it logs the data out. This change also removes the direct
dependency on the OTel SDK. approach for content in Spring AI.
Refactors the observability approach for content in Spring AI:
- Replace content observation filters with logging handlers
- Rename configuration properties to better reflect their purpose:
- `include-prompt` → `log-prompt`
- `include-completion` → `log-completion`
- `include-query-response` → `log-query-response`
- Add TracingAwareLoggingObservationHandler for trace-aware logging
- Replace micrometer-tracing-bridge-otel with micrometer-tracing
- Remove event-based tracing in favor of direct logging
- Update documentation to reflect these changes (add breaking-changes section)
- Rename includePrompt to logPrompt in observation properties. Updated in ChatClientBuilderProperties, ChatObservationProperties, and ImageObservationProperties.
Signed-off-by: Christian Tzolov <christian.tzolov@broadcom.com>
Add SQL Server dialect support with new SqlServerChatMemoryDialect class
Create schema-sqlserver.sql script for SQL Server table creation
Refactor database schema initialization with new JdbcChatMemorySchemaInitializer
Standardize table names across databases to SPRING_AI_CHAT_MEMORY
Implement ChatMemoryDialect abstraction for database-specific operations
Add dialect implementations for PostgreSQL, MySQL/MariaDB, HSQLDB
Update configuration properties with more flexible schema initialization options
Enhance documentation with detailed information about dialect support and configuration
Add integration tests for HSQLDB and SQL Server
Signed-off-by: Mark Pollack <247466+markpollack@users.noreply.github.com>
- Enhanced Neo4jChatMemoryRepository to correctly restore custom metadata for SystemMessage using SystemMessage.Builder.
- Refactored and clarified Neo4jChatMemoryRepository implementation code.
- Added comprehensive integration tests for Neo4jChatMemoryConfig and Neo4jChatMemoryRepository, including:
-- Index creation verification
-- Custom label support
-- Getter validation for all configuration properties
-- Tests for saving and retrieving SystemMessage metadata
-- Tests ensuring saveAll(conversationId, Collections.emptyList()) clears all messages and removes the conversation node
-- Tests for handling of messages with empty content and empty metadata
-- Improved overall test coverage for Neo4j persistence and configuration edge cases
- Fixed resource management bugs in test classes (ensured proper driver/session closure).
- Improved index creation logic in Neo4jChatMemoryConfig for reliability and logging.
- Updated documentation to include Neo4jChatMemoryRepository usage and configuration
Signed-off-by: enricorampazzo <enrico.rampazzo@live.com>
Signed-off-by: Mark Pollack <mark.pollack@broadcom.com>
* Update remaining Advisors and related classes to use the new APIs.
* In AbstractChatMemoryAdvisor, the “doNextWithProtectFromBlockingBefore()” protected method has been changed from accepting AdvisedRequest to ChatClientRequest. It’s a breaking change since the alternative was not part of M8.
* MessageAggregator has a new method to aggregate messages from ChatClientRequest. The previous method aggregating messages from AdvisedRequest has been removed. Warning since it wasn’t marked as deprecated in M8.
* In SimpleLoggerAdvisor, the “requestToString” input argument needs to be updated to use ChatClientRequest. It’s a breaking change since the alternative was not part of M8. Same thing about the constructor.
* The “getTemplateRenderer” method has been removed from BaseAdvisorChain. Each Advisor is encouraged to accept a PromptTemplate to achieve self-contained prompt augmentation operations.
* Remove deprecations in ChatClient and Advisors, and update tests accordingly.
* When building a Prompt from the ChatClient input, the SystemMessage passed via systemText() is placed first in the message list. Before, it was put last, resulting in errors with several model providers.
Relates to gh-2655
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
* Remove deprecated APIs for JdbcChatMemory.
* Improve documentation about chat memory vs. chat history.
* Fix mismatch between docs vs code for max messages in MessageWindowChatMemory.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Remove deprecated constructor method Media(MimeType mimeType, URL url) from Media
- Remove deprecated builder method data(URL url) from Media builder
- Update references to use the builder and the data(URI) methods
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
- set timestamp manually to prevent saving equal timestamps while batch insert
- return DESC order into get query (in `JdbcChatMemory`)
- Update similar changes for JdbcChatMemoryRepository
This PR solves some problems with message ordering:
JdbcChatMemory fetches rows in DESC order, and MessageChatMemoryAdvisor get and add all messages in that order - from last to first. So messages list needs to be reversed.
After batch insert without specifying timestamp manually all rows have the same timestamp (because database sets current_timestamp by default). Sooo after fetching rows from database the message order is unpredictable - they have same timestamp.
Signed-off-by: Linar Abzaltdinov <abzaltdinov@gmail.com>
* The new spring.ai.model.* properties introduced in M7 were missing Spring Boot configuration metadata.
* Furthermore, the breaking change was not documented as the previous properties have been completely removed. Documentation has been added in the upgrade notes for this change.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
* ChatClient observations now include the full prompt content instead of just the userText and systemText. Furthermore, they include consistent telemetry for the tools passed via the ChatClient and a first-class conversation ID when using memory advisors. Incomplete or unsafe attributes have been deprecated.
* Adopted the new robust Advisor APIs for BaseAdvisor and RetrievalAugmentationAdvisor.
* Improved the prompt augmentation facilities in ChatClientRequest and Prompt for performance and immutability.
* Fixed integration test racing condition.
* Updated the documentation for ChatClient and Observability accordingly.
* Documented changes in upgrade notes.
* Introduced `prompt.augmentUserMessage(String text)` to directly replace the user message content.
* Added `prompt.augmentUserMessage(Function<UserMessage, UserMessage> augmenter)` for more granular updates using the `userMessage.mutate()` pattern, allowing modification of text, media, and metadata.
Relates to gh-2655
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
* ChatMemory will become a generic interface to implement different memory management strategies. It’s been moved from the “”spring-ai-client-chat” package to “spring-ai-model” package while retaining the same package, so it’s transparent to users.
* A MessageWindowChatMemory has been introduced to provide support for a chat memory that keeps at most N messages in the memory.
* A ChatMemoryRepository interface has been introduced to support different storage strategies for the chat memory. It’s meant to be used as part of a ChatMemory implementation. This is different than before, where the storage-specific implementation was directly tied to the ChatMemory. This design is familiar to Spring users since it’s used already in the ecosystem. The goal was to use a programming model similar to Spring Session and Spring Data.
* The JdbcChatMemory has been supersed by JdbcChatMemoryRepository.
* A ChatMemory bean is auto-configured for you whenever using one of the Spring AI Model starters. By default, it uses the MessageWindowChatMemory implementation and stores the conversation history in memory. If a different repository is already configured (e.g., Cassandra, JDBC, or Neo4j), Spring AI will use that instead.
* First-class documentation has been introduced to describe the ChatMemory API and related features.
* All the changes introduced in this PR are backward-compatible.
Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
- Avoid overlapping package names
Changed in spring-ai-commons package from org.sf.ai.model to org.sf.ai.content
Refactor advisor module name to be spring-ai-advisors-vector-store
Moved advisors into org.springframework.ai.chat.client.advisor.vectorstore
- Created top level memory directory
- Create new module spring-ai-model-chat-memory-neo4j and moved neo4j memory classes out of the vectorstore module
Updated neo4j autoconfiguation
- Conditionally enable invidividual models within the provider
- Introduce top level properties to support conditional logic
- The properties will have the format like "spring.ai.model.<chat/embedding/image etc.,>=<provider>" to enable specific chat/embedding/image/audio/moderation models by the provider. By default, these will be enabled when no specific properties are set. To disable, set any value other than the provider name for example, "none"
- For the auto configurations where the provider has multiple models, split the autoconfiguration into per model auto-configuration classes. This will enable the isolated auto-configurations for each provider and its model.
- This PR addresses this for OpenAI and others will follow in subsequent PRs
Signed-off-by: Ilayaperumal Gopinathan <ilayaperumal.gopinathan@broadcom.com>
