initial progress

workflows.py

@@ -1,3 +1,4 @@
+import yaml
 from collections import deque
 from dataclasses import dataclass
 from datetime import timedelta
@@ -10,23 +11,59 @@ with workflow.unsafe.imports_passed_through():
     from activities import OllamaActivities, OllamaPromptInput
 
 
+@dataclass
+class ToolArgument:
+    name: str
+    type: str
+    description: str
+
+
+@dataclass
+class ToolDefinition:
+    name: str
+    description: str
+    arguments: List[ToolArgument]
+
+
+@dataclass
+class ToolsData:
+    tools: List[ToolDefinition]
+
+
 @dataclass
 class OllamaParams:
     conversation_summary: Optional[str] = None
     prompt_queue: Optional[Deque[str]] = None
 
 
+@dataclass
+class CombinedInput:
+    ollama_params: OllamaParams
+    tools_data: ToolsData
+
+
+from agent_prompt_generators import (
+    generate_genai_prompt_from_tools_data,
+    generate_json_validation_prompt_from_tools_data,
+)
+
+
 @workflow.defn
 class EntityOllamaWorkflow:
     def __init__(self) -> None:
         self.conversation_history: List[Tuple[str, str]] = []
         self.prompt_queue: Deque[str] = deque()
         self.conversation_summary: Optional[str] = None
-        self.continue_as_new_per_turns: int = 6
+        self.continue_as_new_per_turns: int = 250
         self.chat_ended: bool = False
+        self.tool_data = None
 
     @workflow.run
-    async def run(self, params: OllamaParams) -> str:
+    async def run(self, combined_input: CombinedInput) -> str:
+
+        params = combined_input.ollama_params
+        tools_data = combined_input.tools_data
+
         if params and params.conversation_summary:
             self.conversation_history.append(
                 ("conversation_summary", params.conversation_summary)
@@ -49,15 +86,38 @@ class EntityOllamaWorkflow:
                 self.conversation_history.append(("user", prompt))
 
                 # Build prompt + context
-                context_instructions, actual_prompt = self.prompt_with_history(prompt)
+                context_instructions = generate_genai_prompt_from_tools_data(
+                    tools_data, self.format_history()
+                )
                 workflow.logger.info("Prompt: " + prompt)
 
                 # Pass a single input object
                 prompt_input = OllamaPromptInput(
-                    prompt=actual_prompt,
+                    prompt=prompt,
                     context_instructions=context_instructions,
                 )
 
+                # Call activity with one argument
+                responsePrechecked = await workflow.execute_activity_method(
+                    OllamaActivities.prompt_ollama,
+                    prompt_input,
+                    schedule_to_close_timeout=timedelta(seconds=20),
+                )
+
+                # Check if the response is valid JSON
+                json_validation_instructions = (
+                    generate_json_validation_prompt_from_tools_data(
+                        tools_data, self.format_history(), responsePrechecked
+                    )
+                )
+                workflow.logger.info("Prompt: " + prompt)
+
+                # Pass a single input object
+                prompt_input = OllamaPromptInput(
+                    prompt=responsePrechecked,
+                    context_instructions=json_validation_instructions,
+                )
+
                 # Call activity with one argument
                 response = await workflow.execute_activity_method(
                     OllamaActivities.prompt_ollama,
@@ -68,6 +128,18 @@ class EntityOllamaWorkflow:
                 workflow.logger.info(f"Ollama response: {response}")
                 self.conversation_history.append(("response", response))
 
+                # Call activity with one argument
+                tool_data = await workflow.execute_activity_method(
+                    OllamaActivities.parse_tool_data,
+                    response,
+                    schedule_to_close_timeout=timedelta(seconds=1),
+                )
+
+                self.tool_data = tool_data
+
+                if self.tool_data.get("next") == "confirm":
+                    return self.tool_data
+
                 # Continue as new after X turns
                 if len(self.conversation_history) >= self.continue_as_new_per_turns:
                     # Summarize conversation
@@ -90,9 +162,12 @@ class EntityOllamaWorkflow:
 
                     workflow.continue_as_new(
                         args=[
-                            OllamaParams(
-                                conversation_summary=self.conversation_summary,
-                                prompt_queue=self.prompt_queue,
+                            CombinedInput(
+                                ollama_params=OllamaParams(
+                                    conversation_summary=self.conversation_summary,
+                                    prompt_queue=self.prompt_queue,
+                                ),
+                                tools_data=tools_data,
                             )
                         ]
                     )
@@ -140,6 +215,10 @@ class EntityOllamaWorkflow:
     def get_summary_from_history(self) -> Optional[str]:
         return self.conversation_summary
 
+    @workflow.query
+    def get_tool_data(self) -> Optional[str]:
+        return self.tool_data
+
     # Helper: generate text of the entire conversation so far
     def format_history(self) -> str:
         return " ".join(f"{text}" for _, text in self.conversation_history)