davsclaus commented on code in PR #27439:
URL: https://github.com/apache/camel/pull/27439#discussion_r4195014238
##########
components/camel-ai/camel-a2a/src/main/docs/a2a-producer.adoc:
##########
@@ -111,10 +113,15 @@ YAML::
steps:
- setHeader:
name: CamelA2AOperation
- constant: MESSAGE_STREAM
- - to: a2a:https://agent.example.com
+ expression:
+ constant:
+ expression: MESSAGE_STREAM
+ - to:
+ uri: a2a:https://agent.example.com
- split:
- simple: "${body}"
+ expression:
+ simple:
+ expression: "${body}"
streaming: true
steps:
- choice:
Review Comment:
Thanks, converted both `when` branches to the canonical `expression: simple:
expression:` form in 4a85ef367b (catalog copy in step).
_Claude Code on behalf of davsclaus_
##########
components/camel-ai/src/main/docs/ai-llm-integration-guide.adoc:
##########
@@ -203,13 +208,17 @@ Load prompts from the classpath or file system and pass
them as the body or via
[source,yaml]
----
-- from:
- uri: file:prompts/extract-resume.txt?noop=true
- steps:
- - setHeader:
- name: CamelOpenAIUserMessage
- simple: "${body}\n\nDocument to
parse:\n${exchangeProperty.documentText}"
- - to:
openai:chat-completion?jsonSchema=resource:classpath:schemas/resume.schema.json
+- route:
+ from:
+ uri: file:prompts/extract-resume.txt?noop=true
Review Comment:
Good catch, and the empty `documentText` was the bigger problem. Rather than
only fixing the URI, I restructured the example in 4a85ef367b. The prompt is
now a Simple template file (`prompts/extract-resume.txt` on the classpath,
shown on the page) with `${body}` where the document goes. The route reads the
resumes with `file:inbox/resumes` and sets `CamelOpenAIUserMessage` with
`simple: resource:classpath:prompts/extract-resume.txt`. Simple loads a static
`resource:` template once and evaluates it per exchange
(`LanguageSupport.loadResource`), so each resume fills in the prompt. No
`pollEnrich` is needed. The `jsonSchema` option is in the canonical
`parameters:` form too.
_Claude Code on behalf of davsclaus_
##########
core/camel-core-engine/src/main/docs/modules/eips/pages/ai-patterns.adoc:
##########
@@ -212,6 +212,44 @@ See also the full
xref:enterprise-integration-patterns.adoc[Enterprise Integrati
|xref:languages:semantic-language.adoc[Semantic], xref:switch-eip.adoc[Switch]
|Evaluate a Semantic choice question once and dispatch its category string
through literal Switch cases.
+|Guardrail / Guard decision
+|xref:languages:semantic-language.adoc[Semantic],
xref:ROOT:typesafe-ai-component.adoc[TypeSafe AI],
+xref:filter-eip.adoc[Filter], xref:validate-eip.adoc[Validate]
+|Ask a yes/no question about the message (is this request actionable, does
this action fit the task) and filter or
+validate on the answer. A System One model such as Jev answers with a fast,
structured decision instead of
+generated text.
+
+|Tool / Function calling
+|xref:ROOT:ai-tool-component.adoc[AI Tool]
+|Expose a route as a tool an AI agent can call. The same route works with the
LangChain4j, Spring AI and OpenAI
+agents.
+
+|MCP server
+|xref:others:mcp-server.adoc[MCP Server],
xref:ROOT:ai-resource-component.adoc[AI Resource]
+|Expose `ai-tool` routes as MCP tools and `ai-resource` routes as MCP
resources to any MCP client.
+
+|MCP client
+|xref:others:langchain4j-agent-mcp.adoc[LangChain4j Agent MCP],
xref:others:openai-mcp.adoc[OpenAI MCP]
+|Let an agent in a route call the tools of remote MCP servers.
+
+|Tool authorization / Agent permissions
+|xref:ROOT:ai-tool-component.adoc#_authorizing_tool_calls[AI Tool
authorization],
+xref:ROOT:opa-component.adoc[OPA], xref:ROOT:openfga-component.adoc[OpenFGA]
+|Authorize every tool call before it runs, on the caller identity and the tool
name, never on model output.
+
+|Agent identity / Workload identity
+|xref:ROOT:spiffe-component.adoc[SPIFFE]
+|Give each workload a cryptographic identity and mutual TLS, so a tool call
can be authorized on who is calling.
+
+|LLM observability
+|xref:others:ai-observability.adoc[AI Observability]
+|Record an OpenTelemetry span and Micrometer metrics (model, tokens, duration)
for every LLM call, inside the route's
Review Comment:
Applied your wording in 4a85ef367b: the row now names the LangChain4j,
OpenAI and Spring AI chat producers instead of every LLM call.
_Claude Code on behalf of davsclaus_
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