revert: remove letta learning-sdk integration

examples/slackbot/pyproject.toml

@@ -42,7 +42,6 @@ dependencies = [
   "raggy[tpuf] @ git+https://github.com/zzstoatzz/raggy.git",
   "pretty-mod",
   "claude-agent-sdk",
-  "agentic-learning",
 ]
 
 

examples/slackbot/src/slackbot/_internal/templates.py

@@ -51,6 +51,7 @@
 - **Assume Prefect 3.x:** Unless the user specifies otherwise, assume the user is using Prefect 3.x. You can mention this assumption IF RELEVANT (e.g., "In Prefect 3.x, you would...").
 - **Code is King:** When providing code examples, ensure they are complete and correct. Use your `verify_import_statements` tool's output to guide you.
 - **Honesty Over Invention:** If your tools don't find a clear answer, say so. It's better to admit a knowledge gap than to provide incorrect information.
+- **Stay on Topic:** Only reference notes you've stored about the user if they are directly relevant to the current question.
 - **Proportionality:** If asked a simple question, you don't need to do a bunch of work. Just answer the question once you find it. However, feel free to dig into broad questions.
 
 ## CRITICAL - Removed/Deprecated Features
@@ -62,17 +63,18 @@
 If a user explicitly mentions using Prefect 2.x, that's fine, but recommend upgrading to 3.x or using workers in 2.x.
 
 ## Tool Usage Protocol
-You have a suite of tools to gather information. Use them methodically.
+You have a suite of tools to gather and store information. Use them methodically.
 
 1.  **For Technical/Conceptual Questions:** Use `research_prefect_topic`. It delegates to a specialized agent that will do comprehensive research for you.
 2.  **For Bugs or Error Reports:** Use `read_github_issues` to find existing discussions or solutions.
 3.  **For Community Discussions:** Use `search_github_discussions` to find existing GitHub discussions on topics.
-4. **For Checking the Work of the Research Agent:** Use `explore_module_offerings` and `display_callable_signature` to verify specific syntax recommendations.
-5. **For CLI Commands:** use `check_cli_command` with --help before suggesting any Prefect CLI command to verify it exists and has the correct syntax. This prevents suggesting non-existent commands.
+4.  **For Remembering User Details:** When a user shares information about their goals, environment, or preferences, use `store_facts_about_user` to save these details for future interactions.
+5. **For Checking the Work of the Research Agent:** Use `explore_module_offerings` and `display_callable_signature` to verify specific syntax recommendations.
+6. **For CLI Commands:** use `check_cli_command` with --help before suggesting any Prefect CLI command to verify it exists and has the correct syntax. This prevents suggesting non-existent commands.
    - **IMPORTANT:** When checking commands that require optional dependencies (e.g., AWS, Docker, Kubernetes integrations), use the `uv run --with 'prefect[<extra>]'` syntax.
    - Examples: `uv run --with 'prefect[aws]'`, `uv run --with 'prefect[docker]'`, `uv run --with 'prefect[kubernetes]'`
    - This ensures the command runs with the necessary dependencies installed.
-6. **For Creating GitHub Discussions (USE SPARINGLY):** Use `create_discussion_and_notify` only when:
+7. **For Creating GitHub Discussions (USE SPARINGLY):** Use `create_discussion_and_notify` only when:
    - The thread contains valuable insights, solutions, or patterns not documented elsewhere
    - You've searched both issues and discussions and found no existing coverage of the topic
    - The conversation would clearly benefit the broader Prefect community

examples/slackbot/src/slackbot/api.py

@@ -5,7 +5,6 @@
 from contextlib import asynccontextmanager
 from typing import Any
 
-from agentic_learning import learning
 from fastapi import FastAPI, HTTPException, Request
 from prefect import Flow, State, flow, get_run_logger, task
 from prefect.blocks.notifications import SlackWebhook
@@ -101,13 +100,11 @@ async def run_agent(
                 settings=decorator_settings,
                 max_tool_calls=settings.max_tool_calls_per_turn,
             ):
-                # wrap agent run with learning context for persistent memory
-                async with learning(agent=f"slackbot-{user_context['user_id']}"):
-                    result = await create_agent(model=settings.model_name).run(
-                        user_prompt=cleaned_message,
-                        message_history=conversation,
-                        deps=user_context,
-                    )
+                result = await create_agent(model=settings.model_name).run(
+                    user_prompt=cleaned_message,
+                    message_history=conversation,
+                    deps=user_context,
+                )
         finally:
             _progress_message.reset(token)
             _tool_usage_counts.reset(counts_token)
@@ -250,6 +247,7 @@ async def handle_message(payload: SlackPayload, db: Database):
 
         user_context = build_user_context(
             user_id=event.user,
+            user_question=cleaned_message,
             thread_ts=thread_ts,
             workspace_name=await get_workspace_domain(),
             channel_id=event.channel or "unknown",

examples/slackbot/src/slackbot/assets.py

@@ -4,9 +4,13 @@
 
 from prefect.assets import Asset, AssetProperties, add_asset_metadata, materialize
 from pydantic import BaseModel
+from pydantic_ai import RunContext
 from pydantic_ai.messages import ModelMessage, SystemPromptPart
+from raggy.documents import Document
+from raggy.vectorstores.tpuf import TurboPuffer
 
 from marvin import cast_async
+from slackbot.settings import settings
 from slackbot.slack import get_channel_name
 from slackbot.types import UserContext
 
@@ -70,6 +74,54 @@ def thread_summary_asset(
     )
 
 
+def user_facts_asset(user_context: UserContext) -> Asset:
+    user_id = user_context["user_id"]
+    workspace_name = user_context["workspace_name"]
+    bot_id = user_context["bot_id"]
+    return Asset(
+        key=f"slack://{workspace_name}/bot/{bot_id}/facts/{user_id}",
+        properties=AssetProperties(
+            name=f"User Facts {user_id}",
+            description=f"Facts learned about user {user_id} by bot {bot_id}",
+            owners=["slackbot"],
+        ),
+    )
+
+
+async def store_user_facts(ctx: RunContext[UserContext], facts: list[str]) -> str:
+    """Store facts extracted from a Slack thread using context for namespacing."""
+
+    with TurboPuffer(
+        namespace=f"{settings.user_facts_namespace_prefix}{ctx.deps['user_id']}"
+    ) as tpuf:
+        tpuf.upsert(documents=[Document(text=fact) for fact in facts])
+
+    user_facts = user_facts_asset(ctx.deps)
+
+    slack_thread = await slack_thread_asset(ctx.deps)
+    slackbot = slackbot_asset(ctx.deps)
+
+    @materialize(user_facts, asset_deps=[slack_thread, slackbot])
+    async def materialize_user_facts():
+        add_asset_metadata(
+            user_facts,
+            {
+                "user_id": ctx.deps["user_id"],
+                "fact_count": len(facts),
+                "timestamp": datetime.now().isoformat(),
+                "namespace": f"{settings.user_facts_namespace_prefix}{ctx.deps['user_id']}",
+                "thread_ts": ctx.deps["thread_ts"],
+                "workspace_name": ctx.deps["workspace_name"],
+                "channel_id": ctx.deps["channel_id"],
+                "bot_id": ctx.deps["bot_id"],
+                "facts": facts,
+            },
+        )
+        return f"Stored {len(facts)} facts about user {ctx.deps['user_id']} from thread {ctx.deps['thread_ts']}"
+
+    return await materialize_user_facts()
+
+
 async def summarize_thread(
     user_context: UserContext, conversation: list[ModelMessage]
 ) -> ThreadSummary:

examples/slackbot/src/slackbot/core.py

@@ -17,8 +17,11 @@
 from pydantic_ai.models.anthropic import AnthropicModel
 from pydantic_ai.providers import Provider
 from pydantic_ai.settings import ModelSettings
+from raggy.vectorstores.tpuf import TurboPuffer, query_namespace
+from turbopuffer import NotFoundError
 
 from slackbot._internal.templates import DEFAULT_SYSTEM_PROMPT
+from slackbot.assets import store_user_facts
 from slackbot.github import (
     GitHubAuthError,
     GitHubError,
@@ -133,13 +136,23 @@ def _insert():
 @task(task_run_name="build user context for {user_id}")
 def build_user_context(
     user_id: str,
+    user_question: str,
     thread_ts: str,
     workspace_name: str,
     channel_id: str,
     bot_id: str,
 ) -> UserContext:
+    try:
+        user_notes = query_namespace(
+            query_text=user_question,
+            namespace=f"{settings.user_facts_namespace_prefix}{user_id}",
+            top_k=5,
+        )
+    except NotFoundError:
+        user_notes = "<No notes found>"
     return UserContext(
         user_id=user_id,
+        user_notes=user_notes,
         thread_ts=thread_ts,
         workspace_name=workspace_name,
         channel_id=channel_id,
@@ -164,7 +177,6 @@ def create_agent(
         UserContext, str
     ](
         model=ai_model,
-        system_prompt=DEFAULT_SYSTEM_PROMPT,
         model_settings=ModelSettings(temperature=settings.temperature),
         tools=[
             research_prefect_topic,  # Tool for researching Prefect topics
@@ -177,6 +189,42 @@ def create_agent(
         deps_type=UserContext,
     )
 
+    @agent.system_prompt
+    def personality_and_maybe_notes(ctx: RunContext[UserContext]) -> str:
+        system_prompt = DEFAULT_SYSTEM_PROMPT + (
+            f"\n\nUser notes: {ctx.deps['user_notes']}"
+            if ctx.deps["user_notes"]
+            else ""
+        )
+        print(f"System prompt: {system_prompt}")
+        return system_prompt
+
+    @agent.tool
+    async def store_facts_about_user(
+        ctx: RunContext[UserContext], facts: list[str]
+    ) -> str:
+        """Store facts about the user that are useful for answering their questions."""
+        print(f"Storing {len(facts)} facts about user {ctx.deps['user_id']}")
+        # This creates an asset dependency: USER_FACTS depends on SLACK_MESSAGES
+        message = await store_user_facts(ctx, facts)
+        print(message)
+        return message
+
+    @agent.tool
+    def delete_facts_about_user(ctx: RunContext[UserContext], related_to: str) -> str:
+        """Delete facts about the user related to a specific topic."""
+        print(f"forgetting stuff about {ctx.deps['user_id']} related to {related_to}")
+        user_id = ctx.deps["user_id"]
+        with TurboPuffer(
+            namespace=f"{settings.user_facts_namespace_prefix}{user_id}"
+        ) as tpuf:
+            vector_result = tpuf.query(related_to)
+            ids = [str(v.id) for v in vector_result.rows or []]
+            tpuf.delete(ids)
+            message = f"Deleted {len(ids)} facts about user {user_id}"
+            print(message)
+            return message
+
     @agent.tool
     async def create_discussion_and_notify(
         ctx: RunContext[UserContext],

examples/slackbot/src/slackbot/prompts.py

@@ -30,6 +30,7 @@
 - **Assume Prefect 3.x:** Unless the user specifies otherwise, assume the user is using Prefect 3.x. You can mention this assumption IF RELEVANT (e.g., "In Prefect 3.x, you would...").
 - **Code is King:** When providing code examples, ensure they are complete and correct. Use your `verify_import_statements` tool's output to guide you.
 - **Honesty Over Invention:** If your tools don't find a clear answer, say so. It's better to admit a knowledge gap than to provide incorrect information.
+- **Stay on Topic:** Only reference notes you've stored about the user if they are directly relevant to the current question.
 - **Proportionality:** If asked a simple question, you don't need to do a bunch of work. Just answer the question once you find it. However, feel free to dig into broad questions.
 
 ## CRITICAL - Removed/Deprecated Features
@@ -41,17 +42,18 @@
 If a user explicitly mentions using Prefect 2.x, that's fine, but recommend upgrading to 3.x or using workers in 2.x.
 
 ## Tool Usage Protocol
-You have a suite of tools to gather information. Use them methodically.
+You have a suite of tools to gather and store information. Use them methodically.
 
 1.  **For Technical/Conceptual Questions:** Use `research_prefect_topic`. It delegates to a specialized agent that will do comprehensive research for you.
 2.  **For Bugs or Error Reports:** Use `read_github_issues` to find existing discussions or solutions.
 3.  **For Community Discussions:** Use `search_github_discussions` to find existing GitHub discussions on topics.
-4. **For Checking the Work of the Research Agent:** Use `explore_module_offerings` and `display_callable_signature` to verify specific syntax recommendations.
-5. **For CLI Commands:** use `check_cli_command` with --help before suggesting any Prefect CLI command to verify it exists and has the correct syntax. This prevents suggesting non-existent commands.
+4.  **For Remembering User Details:** When a user shares information about their goals, environment, or preferences, use `store_facts_about_user` to save these details for future interactions.
+5. **For Checking the Work of the Research Agent:** Use `explore_module_offerings` and `display_callable_signature` to verify specific syntax recommendations.
+6. **For CLI Commands:** use `check_cli_command` with --help before suggesting any Prefect CLI command to verify it exists and has the correct syntax. This prevents suggesting non-existent commands.
    - **IMPORTANT:** When checking commands that require optional dependencies (e.g., AWS, Docker, Kubernetes integrations), use the `uv run --with 'prefect[<extra>]'` syntax.
    - Examples: `uv run --with 'prefect[aws]'`, `uv run --with 'prefect[docker]'`, `uv run --with 'prefect[kubernetes]'`
    - This ensures the command runs with the necessary dependencies installed.
-6. **For Creating GitHub Discussions (USE SPARINGLY):** Use `create_discussion_and_notify` only when:
+7. **For Creating GitHub Discussions (USE SPARINGLY):** Use `create_discussion_and_notify` only when:
    - The thread contains valuable insights, solutions, or patterns not documented elsewhere
    - You've searched both issues and discussions and found no existing coverage of the topic
    - The conversation would clearly benefit the broader Prefect community

examples/slackbot/src/slackbot/settings.py

@@ -1,9 +1,8 @@
 import os
 from pathlib import Path
-from typing import ClassVar
+from typing import ClassVar, Literal
 
 from prefect.blocks.system import Secret
-from prefect.exceptions import ObjectNotFound
 from prefect.variables import Variable
 from pydantic import Field, field_validator, model_validator
 from pydantic_settings import BaseSettings, SettingsConfigDict
@@ -57,9 +56,13 @@ def validate_log_level(cls, v: str) -> str:
         default="anthropic-api-key",
         description="Name of the Prefect secret block containing Anthropic API key",
     )
-    letta_api_key_secret_name: str = Field(
-        default="letta-api-key",
-        description="Name of the Prefect secret block containing Letta API key",
+
+    vector_store_type: Literal["turbopuffer"] = Field(
+        default="turbopuffer", description="Type of vector store to use"
+    )
+    user_facts_namespace_prefix: str = Field(
+        default="user-facts-",
+        description="Prefix for user facts namespaces in vector store",
     )
 
     # Development settings
@@ -91,12 +94,6 @@ def _apply_post_validation_defaults(self) -> "SlackbotSettings":
                 os.environ["TURBOPUFFER_API_KEY"] = api_key
             except Exception:
                 pass  # If secret doesn't exist, turbopuffer will handle the error
-        if not os.getenv("LETTA_API_KEY"):
-            try:
-                api_key = Secret.load(self.letta_api_key_secret_name, _sync=True).get()  # type: ignore
-                os.environ["LETTA_API_KEY"] = api_key
-            except ObjectNotFound:
-                pass  # If secret doesn't exist, learning-sdk won't be used
         if not self.admin_slack_user_id:
             self.admin_slack_user_id = Variable.get("admin-slack-id", _sync=True)
         return self

examples/slackbot/src/slackbot/types.py

@@ -3,6 +3,7 @@
 
 class UserContext(TypedDict):
     user_id: str
+    user_notes: str
     thread_ts: str
     workspace_name: str
     channel_id: str

pyproject.toml

@@ -96,9 +96,6 @@ extend-select = ["I"]
 [tool.ruff.lint.per-file-ignores]
 "__init__.py" = ["F401", "I001", "RUF013"]
 
-[tool.uv]
-prerelease = "allow"
-
 [tool.uv.sources]
 slackbot = { workspace = true }