errors.New("EOF") creates a distinct error instance that doesn't match
io.EOF, causing processRawHTTPStream to silently ignore normal stream
termination without sending a done response.
- SSEReader: return io.EOF instead of errors.New("EOF")
- processRawHTTPStream: handle io.EOF as normal completion, send done
response with usage/toolCalls (aligned with processStream behavior)
Fixes#860
- Streamlined the handling of the temperature option in both OllamaChat and RemoteAPIChat by removing unnecessary conditional checks.
- Ensured that the temperature value is directly assigned when options are provided, improving code clarity and reducing complexity.
- guard against empty content completion in analyzeResponse/executeLoop
with retry (max 2), nudge message, and fallback response
- propagate actual finish_reason through streaming pipeline instead of
hardcoding "stop" in streamThinkingToEventBus
- add FinishReason field to StreamResponse and streamLLMResult
- add finish marker chunk in processStreamDelta for empty content scenarios
- propagate lastFinishReason through EOF handler in processStream
- strengthen PureAgent system prompt with MCP tool guidelines and
graceful fallback instructions for unanswerable questions
- add unit tests for empty response bug and finish_reason propagation
- Updated context template to include runtime metadata such as current time and week, improving contextual awareness in user queries.
- Enhanced rewrite template with critical instructions for intent classification, ensuring that rewritten questions preserve essential entities and keywords.
- Refined intent classification logic to prioritize user intents more effectively, improving the accuracy of responses based on user queries.
- Added examples to clarify expected input and output formats for intent classification, enhancing usability for developers.
- Replaced the default DialContext with SSRFSafeDialContext in the raw HTTP client to improve security against DNS rebinding attacks.
- Added SSRF validation for BaseURL and endpoint in NewRemoteAPIChat and chat methods, ensuring safer URL handling.
- Updated security utility functions to provide consistent SSRF checks across the application.
- Introduced a new ParallelToolCalls field in ChatOptions to control parallel execution of tool calls.
- Updated the BuildChatCompletionRequest method to handle the new ParallelToolCalls option, ensuring it is correctly propagated in requests.
- Enhanced the streamThinkingToEventBus function to utilize the ParallelToolCalls setting.
- Added comprehensive tests to validate the behavior of ParallelToolCalls in various scenarios, ensuring correct propagation and default handling.
- Added diagnostics for streaming events in the AgentEngine, including chunk counts and response type distributions.
- Implemented logging for emitted event types during the thinking process to aid in debugging and performance analysis.
- Updated the session handler to provide more informative warnings when fallback answers are emitted due to non-streaming behavior.
- Introduced a dedicated HTTP client for Ollama to improve connection handling and timeout management during streaming calls.
- Added token usage tracking to the AgentEngine, allowing for better estimation of current context token counts.
- Implemented a new method to estimate current tokens based on previous usage and newly appended messages, improving context management.
- Updated context window management to utilize estimated token counts for more efficient message consolidation.
- Enhanced streaming methods to include token usage information, providing better insights into LLM interactions.
- Refactored the token estimator to support BPE tokenization, ensuring accurate token counts for messages.
- Added unit tests to validate new token estimation and context management functionalities.
- Introduced a configurable LLM call timeout with a default value, allowing for better control over LLM call durations.
- Added logic to retry transient errors (e.g., timeouts, rate limits) up to a specified maximum number of retries, improving robustness in error handling.
- Implemented parameter casting for tool arguments to ensure correct types are used, addressing common LLM quirks.
- Enhanced tool execution error messages with guidance for retrying with different approaches.
- Added validation for configuration values to prevent runtime errors.
Two related fixes for thinking mode streaming:
1. chat_completion_stream.go: When the response channel closes
unexpectedly (context cancelled, upstream error) while thinking
is in progress, the <think> tag was left unclosed. This caused
the stored message to have an incomplete tag, making the frontend
show a perpetual "thinking..." state on history reload.
Now we emit a closing </think> tag when the channel ends with
thinkingStarted=true but thinkingEnded=false.
2. remote_api.go: The thinking Done=true event was only sent when
the first answer content chunk arrived. If the model produced
only reasoning with no answer (e.g., finish_reason set with
empty content), the thinking-done signal was never emitted.
Now we also check isDone && state.hasThinking at the end of
processStreamDelta to ensure the done event is always sent.
- Parse reasoning field together with standard stream response using local struct
- Unify reasoning content extraction from standard and vLLM response paths
- Adapt processStreamDelta to accept reasoning content as a separate parameter
- Send reasoning content as thinking response in the stream when available
- Ensure compatibility with existing SDK logic by constructing standard choice object
- Introduced MessageContentPart and ImageURL types to allow for multi-content messages that can include both text and images.
- Updated the Message struct to include a MultiContent field for handling multiple message parts.
- Modified the ConvertMessages function to prioritize processing of multi-content messages, improving the handling of user messages with images.
These changes enhance the flexibility and functionality of chat messages, enabling richer content delivery.
- Removed outdated instructions regarding the `skip_kb_search` field in the conversation configuration.
- Clarified requirements for `image_description` to ensure it is non-empty when images are present.
- Adjusted the handling of message parts in the chat pipeline to improve image processing.
- Deleted unused migration files related to image handling in the database schema.
These changes enhance the clarity and functionality of the conversation and image processing logic.
- Added functionality for image uploads in chat, allowing users to attach images for multimodal Q&A.
- Enhanced the input field to handle image selection via drag-and-drop and paste, with validation for file types and sizes.
- Updated the backend to process images alongside text queries, including support for image analysis.
- Introduced new UI components for image previews and management, improving user interaction with uploaded content.
- Added localization strings for image upload features and error messages, enhancing accessibility for users in multiple languages.
These changes significantly improve the chat experience by enabling users to incorporate images into their queries, facilitating richer interactions and responses.
- Introduced the final_answer tool to ensure agents submit their complete responses as the last action, improving response accuracy and consistency.
- Updated the agent engine to log detailed information about tool calls and responses, including the total duration of agent execution.
- Enhanced the chat message model to include agent_duration_ms, tracking the total execution time from query start to answer delivery.
- Implemented JSON field extraction for streaming responses, allowing for more efficient handling of tool call outputs.
These changes significantly improve the agent's response handling and ensure that final answers are consistently delivered, enhancing overall user experience.
Handle thinking models that return wrapped content even when
Thinking=false is configured. This is a fallback strategy for models
like MiniMax-M2.1 that do not fully support the Thinking parameter.
The thinking tags and their enclosed content are completely stripped.
ChatTemplateKwargs parameter is only supported by custom backends
like vLLM. OpenAI API does not support this parameter and returns
400 Bad Request error.
This change conditionally includes ChatTemplateKwargs only when
the provider is ProviderGeneric (custom deployment).
Fixes connection test failure for OpenAI models with error:
"Unrecognized request argument supplied: chat_template_kwargs"
- Added support for tracking the status of FAQ import tasks, including progress indicators for ongoing imports.
- Introduced new localization strings for processing tasks and batch operations in multiple languages.
- Updated the FAQ entry manager to display import progress and improved user feedback during the import process.
- Enhanced the KnowledgeBase component to reflect the processing state of knowledge items, improving user experience during document uploads.
- Implemented batch deletion functionality for chunks, streamlining the management of knowledge base content.
- Added functionality for manual knowledge entry, allowing users to create and edit Markdown content directly in the browser.
- Introduced new API endpoints for creating and updating manual knowledge entries.
- Enhanced UI components to support the new manual knowledge editor, including integration with existing knowledge base features.
- Updated knowledge retrieval logic to accommodate manual entries, ensuring seamless user experience across knowledge types.
- Improved agent configuration to support custom system prompts, enhancing flexibility in agent responses.
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