AI Agent

The Vadalog AI Agent is a streaming conversational interface that can autonomously plan and execute data workflows — generating Vadalog programs, running concepts, inspecting results, and iterating based on outcomes.

Chat

Send a message to the agent and receive a streaming NDJSON response. The agent maintains conversation history within a session, so follow-up messages have full context. HTTP Request:

POST /api/v1/agent/{ontology_id}/chat

Path Parameters:

Parameter	Type	Required	Description
`ontology_id`	string	Yes	The ID of the ontology to work within

Request Body:

Field	Type	Required	Description
`message`	string	Yes	The user’s message
`session_id`	string	No	Conversation session identifier. Default: `"default"`
`model`	string	No	Override the LLM model for this session

Example:

curl -X POST "https://api.prometheux.ai/jarvispy/my-org/my-user/api/v1/agent/my-project-id/chat" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -d '{
    "message": "Create a concept that finds all transitive suppliers and run it",
    "session_id": "session-1"
  }'

Response (NDJSON stream): The response is a stream of newline-delimited JSON objects. Each line has a type and data field:

Type	Description
`metadata`	Session metadata (project, model, context loaded)
`tool_start`	Agent is invoking a tool (tool name and input)
`proposal`	Agent proposes a concept (definition, name, description)
`tool_result`	Result from a tool invocation
`content`	Text chunk from the agent’s response
`done`	Stream complete
`error`	An error occurred

Example stream:

{"type": "metadata", "data": {"ontology_id": "my-ontology-id", "model": "gpt-4o", "context_loaded": true}}
{"type": "tool_start", "data": {"tool": "create_concept", "input": {"definition": "..."}}}
{"type": "proposal", "data": {"tool": "create_concept", "concept_name": "transitive_suppliers", "definition": "...", "description": "..."}}
{"type": "tool_result", "data": {"tool": "create_concept", "result": {"id": "concept-uuid"}}}
{"type": "tool_start", "data": {"tool": "run_concept", "input": {"concept_name": "transitive_suppliers"}}}
{"type": "tool_result", "data": {"tool": "run_concept", "result": {"total_records": 42}}}
{"type": "content", "data": {"chunk": "I created and ran the transitive_suppliers concept. It derived 42 records..."}}
{"type": "done", "data": {"ontology_id": "my-ontology-id"}}

Reset Session

Clear the conversation history for a session. HTTP Request:

POST /api/v1/agent/{ontology_id}/reset

Path Parameters:

Parameter	Type	Required	Description
`ontology_id`	string	Yes	The ID of the ontology

Request Body:

Field	Type	Required	Description
`session_id`	string	No	Session to reset. Default: `"default"`

Example:

curl -X POST "https://api.prometheux.ai/jarvispy/my-org/my-user/api/v1/agent/my-project-id/reset" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -d '{"session_id": "session-1"}'

Session ManagementSessions are maintained server-side and keyed by username + session ID. Use different session_id values to run parallel conversations. Sessions are automatically evicted (LRU) when the server reaches capacity.

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Chat

Reset Session

​Chat

​Reset Session

Chat

Reset Session