dev sync

- main system prompt split
- history rework in progress

python/extensions/message_loop_prompts/_10_system_prompt.py

@@ -0,0 +1,37 @@
+from datetime import datetime
+from python.helpers.extension import Extension
+from agent import Agent, LoopData
+
+
+class SystemPrompt(Extension):
+
+    async def execute(self, loop_data: LoopData = LoopData(), **kwargs):
+        # collect and concatenate main prompts
+        main = concat_main_prompts(self.agent)
+        # collect and concatenate tool instructions
+        tools = concat_tool_prompts(self.agent)
+        # append to system message
+        loop_data.system.append(main)
+        loop_data.system.append(tools)
+
+
+def concat_main_prompts(agent: Agent):
+    # variables for prompts
+    vars = {
+        "date_time": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+        "agent_name": agent.agent_name,
+    }
+
+    # prompt files
+    mains = agent.read_prompts("agent.system.main.*.md", **vars)
+    mains = "\n\n".join(mains)
+    return mains
+
+
+def concat_tool_prompts(agent: Agent):
+    # prompt files
+    tools = agent.read_prompts("agent.system.tool.*.md")
+    tools = "\n\n".join(tools)
+    # tools template
+    sys = agent.read_prompt("agent.system.tools.md", tools=tools)
+    return sys

python/extensions/message_loop_prompts/_10_tool_instructions.py

@@ -1,23 +0,0 @@
-from python.helpers.extension import Extension
-from agent import Agent, LoopData
-
-
-class RecallMemories(Extension):
-
-    INTERVAL = 3
-    HISTORY = 5
-    RESULTS = 3
-    THRESHOLD = 0.1
-
-    async def execute(self, loop_data: LoopData = LoopData(), **kwargs):
-        # collect and concatenate tool instructions
-        sys = concat_tool_prompts(self.agent)
-        # append to system message
-        loop_data.system.append(sys)
-
-
-def concat_tool_prompts(agent: Agent):
-    tools = agent.read_prompts("agent.system.tool.*.md")
-    tools = "\n\n".join(tools)
-    sys = agent.read_prompt("agent.system.tools.md", tools=tools)
-    return sys

python/helpers/log.py

@@ -4,7 +4,7 @@ from typing import Literal, Optional, Dict
 import uuid
 
 
-type Type = Literal[
+Type = Literal[
     "agent",
     "code_exe",
     "error",

python/helpers/memory.py

@@ -1,5 +1,5 @@
 from datetime import datetime
-from typing import Any
+from typing import Any, List, Sequence
 from langchain.storage import InMemoryByteStore, LocalFileStore
 from langchain.embeddings import CacheBackedEmbeddings
 
@@ -21,6 +21,14 @@ from python.helpers.log import Log, LogItem
 from enum import Enum
 from agent import Agent
 
+class MyFaiss(FAISS):
+    #override aget_by_ids
+    def get_by_ids(self, ids: Sequence[str], /) -> List[Document]:
+        # return all self.docstore._dict[id] in ids
+        return [self.docstore._dict[id] for id in ids if id in self.docstore._dict] #type: ignore
+
+    async def aget_by_ids(self, ids: Sequence[str], /) -> List[Document]:
+        return self.get_by_ids(ids)
 
 class Memory:
 
@@ -28,7 +36,7 @@ class Memory:
         MAIN = "main"
         SOLUTIONS = "solutions"
 
-    index: dict[str, "FAISS"] = {}
+    index: dict[str, "MyFaiss"] = {}
 
     @staticmethod
     async def get(agent: Agent):
@@ -64,7 +72,7 @@ class Memory:
         embeddings_model,
         memory_subdir: str,
         in_memory=False,
-    ):
+    ) -> MyFaiss:
 
         print("Initializing VectorDB...")
 
@@ -102,7 +110,7 @@ class Memory:
 
         # if db folder exists and is not empty:
         if os.path.exists(db_dir) and files.exists(db_dir, "index.faiss"):
-            db = FAISS.load_local(
+            db = MyFaiss.load_local(
                 folder_path=db_dir,
                 embeddings=embedder,
                 allow_dangerous_deserialization=True,
@@ -113,7 +121,7 @@ class Memory:
         else:
             index = faiss.IndexFlatIP(len(embedder.embed_query("example")))
 
-            db = FAISS(
+            db = MyFaiss(
                 embedding_function=embedder,
                 index=index,
                 docstore=InMemoryDocstore(),
@@ -122,12 +130,12 @@ class Memory:
                 # normalize_L2=True,
                 relevance_score_fn=Memory._cosine_normalizer,
             )
-        return db
+        return db # type: ignore
 
     def __init__(
         self,
         agent: Agent,
-        db: FAISS,
+        db: MyFaiss,
         memory_subdir: str,
     ):
         self.agent = agent
@@ -226,13 +234,15 @@ class Memory:
         return removed
 
     async def delete_documents_by_ids(self, ids: list[str]):
-        # pre = self.db.get(ids=ids)["ids"]
-        self.db.delete(ids=ids)
-        # post = self.db.get(ids=ids)["ids"]
-        # TODO? compare pre and post
-        if ids:
+        # aget_by_ids is not yet implemented in faiss, need to do a workaround
+        rem_docs =self.db.get_by_ids(ids) # existing docs to remove (prevents error)
+        if rem_docs:
+            rem_ids = [doc.metadata["id"] for doc in rem_docs] # ids to remove
+            await self.db.adelete(ids=rem_ids)
+
+        if rem_docs:
             self._save_db()  # persist
-        return len(ids)
+        return rem_docs
 
     def insert_text(self, text, metadata: dict = {}):
         id = str(uuid.uuid4())

python/tools/memory_delete.py

@@ -7,5 +7,5 @@ class MemoryForget(Tool):
         db = await Memory.get(self.agent)
         dels = await db.delete_documents_by_ids(ids=ids)
 
-        result =  self.agent.read_prompt("fw.memories_deleted.md", memory_count=dels)
+        result =  self.agent.read_prompt("fw.memories_deleted.md", memory_count=len(dels))
         return Response(message=result, break_loop=False)

python/tools/memory_tool.py.txt

@@ -1,92 +0,0 @@
-import re
-from agent import Agent
-from python.helpers.vector_db import get_or_create_db, Area
-import os
-from python.helpers.tool import Tool, Response
-from python.helpers.print_style import PrintStyle
-from python.helpers.errors import handle_error
-from python.helpers import files
-
-DEFAULT_THRESHOLD = 0.5
-
-
-class Memory(Tool):
-
-    async def execute(self, **kwargs):
-        result = ""
-
-        try:
-            if "query" in kwargs:
-                threshold = float(kwargs.get("threshold", DEFAULT_THRESHOLD))
-                count = int(kwargs.get("limit", 5))
-                result = search(self.agent, kwargs["query"], count, threshold)
-            elif "memorize" in kwargs:
-                meta = {"area": Area.MAIN.value}
-                result = save(self.agent, kwargs["memorize"])
-            elif "forget" in kwargs:
-                result = forget(self.agent, kwargs["forget"])
-                # elif "delete" in kwargs
-                result = delete(self.agent, kwargs["delete"])
-        except Exception as e:
-            handle_error(e)
-            # hint about embedding change with existing database
-            PrintStyle.hint(
-                "If you changed your embedding model, you will need to remove contents of /memory directory."
-            )
-            self.agent.context.log.log(
-                type="hint",
-                content="If you changed your embedding model, you will need to remove contents of /memory directory.",
-            )
-            raise
-
-        # result = process_query(self.agent, self.args["memory"],self.args["action"], result_count=self.agent.config.auto_memory_count)
-        return Response(message=result, break_loop=False)
-
-
-def search(
-    agent: Agent, query: str, count: int = 5, threshold: float = DEFAULT_THRESHOLD
-):
-    db = get_db(agent)
-    # docs = db.search_similarity(query,count) # type: ignore
-    docs = db.search_similarity_threshold(query=query, limit=count, threshold=threshold)  # type: ignore
-    if len(docs) == 0:
-        return agent.read_prompt("fw.memories_not_found.md", query=query)
-    else:
-        return str(docs)
-
-
-def save(agent: Agent, text: str, metadata: dict = {}):
-    db = get_db(agent)
-    id = db.insert_text(text, metadata)  # type: ignore
-    return agent.read_prompt("fw.memory_saved.md", memory_id=id)
-
-
-def delete(agent: Agent, ids_str: str):
-    db = get_db(agent)
-    ids = extract_guids(ids_str)
-    deleted = db.delete_documents_by_ids(ids)  # type: ignore
-    return agent.read_prompt("fw.memories_deleted.md", memory_count=deleted)
-
-
-def forget(agent: Agent, query: str):
-    db = get_db(agent)
-    deleted = db.delete_documents_by_query(query)  # type: ignore
-    return agent.read_prompt("fw.memories_deleted.md", memory_count=deleted)
-
-
-def get_db(agent: Agent):
-    mem_dir = files.get_abs_path("memory", agent.config.memory_subdir or "default")
-    kn_dirs = [
-        files.get_abs_path("knowledge", d) for d in agent.config.knowledge_subdirs or []
-    ]
-
-    db = get_or_create_db(
-        agent=agent,
-    )
-
-    return db
-
-
-def extract_guids(text):
-    pattern = r"\b[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-5][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}\b"
-    return re.findall(pattern, text)

python/tools/unknown.py

@@ -1,5 +1,5 @@
 from python.helpers.tool import Tool, Response
-from python.extensions.message_loop_prompts._10_tool_instructions import (
+from python.extensions.message_loop_prompts._10_system_prompt import (
     concat_tool_prompts,
 )