Remove LANGSMITH (hub) dependency

src/main/askai/core/askai_prompt.py

@@ -12,14 +12,14 @@
 
    Copyright (c) 2024, HomeSetup
 """
+from functools import lru_cache
+
+from hspylib.core.metaclass.singleton import Singleton
+
 from askai.__classpath__ import classpath
 from askai.core.askai_configs import configs
 from askai.core.support.platform import get_os, get_shell, get_user, SupportedPlatforms, SupportedShells
 from askai.core.support.utilities import read_resource
-from functools import lru_cache
-from hspylib.core.metaclass.singleton import Singleton
-from langchain import hub
-from langchain_core.prompts import ChatPromptTemplate
 
 
 class AskAiPrompt(metaclass=Singleton):
@@ -56,10 +56,6 @@ def read_prompt(self, template_file: str, prompt_dir: str = None) -> str:
         """Read a processor prompt template and set its persona."""
         return read_resource(prompt_dir or self.PROMPT_DIR, template_file)
 
-    def hub(self, owner_repo_commit) -> ChatPromptTemplate:
-        """Read a prompt from LangChain hub."""
-        return hub.pull(owner_repo_commit)
-
     def append_path(self, path: str) -> str:
         """Return the PROMPT_DIR with the extra path appended."""
         return f"{self.PROMPT_DIR}/{path}"

src/main/askai/core/askai_settings.py

@@ -30,9 +30,9 @@
 import re
 
 # AskAI config directory.
-ASKAI_DIR: Path = Path(f'{os.getenv("HHS_DIR", os.getenv("ASKAI_DIR", str(Path.home())))}/askai')
+ASKAI_DIR: Path = Path(f'{os.getenv("ASKAI_DIR", os.getenv("HHS_CACHE_DIR", str(Path.home())))}/askai')
 if not ASKAI_DIR.exists():
-    ASKAI_DIR: Path = classpath.resource_path()
+    ASKAI_DIR.mkdir(parents=True, exist_ok=True)
 
 # Make sure the AskAI directory is exported.
 os.environ["ASKAI_DIR"] = str(ASKAI_DIR)

src/main/askai/core/features/router/task_agent.py

@@ -74,7 +74,7 @@ def __init__(self):
     @property
     def agent_template(self) -> ChatPromptTemplate:
         """Retrieve the Structured Agent Template."""
-        return prompt.hub("hwchase17/structured-chat-agent")
+        return prompt.read_prompt("langchain/structured-agent")
 
     @property
     def lc_agent(self) -> Runnable:

src/main/askai/resources/prompts/langchain/structured-agent.txt

@@ -0,0 +1,36 @@
+Respond to the human as helpfully and accurately as possible. You have access to the following tools:
+
+{tools}
+
+Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
+
+Valid "action" values: "Final Answer" or {tool_names}
+
+Provide only ONE action per $JSON_BLOB, as shown:
+
+```
+{{
+  "action": $TOOL_NAME,
+  "action_input": $INPUT
+}}
+```
+
+Follow this format:
+
+Question: input question to answer
+Thought: consider previous and subsequent steps
+Action:
+```
+$JSON_BLOB
+```
+Observation: action result
+... (repeat Thought/Action/Observation N times)
+Thought: I know what to respond
+Action:
+```
+{{
+  "action": "Final Answer",
+  "action_input": "Final response to human"
+}}
+
+Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation