Merge pull request #9 from tech-envision/codex/add-robust-system-prompt-for-tool-chaining

README.md

@@ -10,6 +10,10 @@ conversations can be resumed with context. Two example tools are included:
   and allows importing safe modules like ``math``. The result is returned from a
   ``result`` variable or captured output.
 
+The application now injects a system prompt that instructs the model to chain
+multiple tools when required. This prompt ensures the assistant can orchestrate
+tool calls in sequence to satisfy the user's request.
+
 ## Usage
 
 ```bash

src/chat.py

@@ -5,7 +5,13 @@ import json
 
 from ollama import AsyncClient, ChatResponse, Message
 
-from .config import MAX_TOOL_CALL_DEPTH, MODEL_NAME, NUM_CTX, OLLAMA_HOST
+from .config import (
+    MAX_TOOL_CALL_DEPTH,
+    MODEL_NAME,
+    NUM_CTX,
+    OLLAMA_HOST,
+    SYSTEM_PROMPT,
+)
 from .db import Conversation, Message as DBMessage, User, _db, init_db
 from .log import get_logger
 from .schema import Msg
@@ -30,6 +36,7 @@ class ChatSession:
             user=self._user, session_name=session
         )
         self._messages: List[Msg] = self._load_history()
+        self._ensure_system_prompt()
 
     async def __aenter__(self) -> "ChatSession":
         return self
@@ -38,6 +45,15 @@ class ChatSession:
         if not _db.is_closed():
             _db.close()
 
+    def _ensure_system_prompt(self) -> None:
+        if any(m.get("role") == "system" for m in self._messages):
+            return
+
+        DBMessage.create(
+            conversation=self._conversation, role="system", content=SYSTEM_PROMPT
+        )
+        self._messages.insert(0, {"role": "system", "content": SYSTEM_PROMPT})
+
     def _load_history(self) -> List[Msg]:
         messages: List[Msg] = []
         for msg in self._conversation.messages.order_by(DBMessage.created_at):

src/config.py

@@ -7,3 +7,11 @@ MODEL_NAME: Final[str] = os.getenv("OLLAMA_MODEL", "qwen3")
 OLLAMA_HOST: Final[str] = os.getenv("OLLAMA_HOST", "http://localhost:11434")
 MAX_TOOL_CALL_DEPTH: Final[int] = 5
 NUM_CTX: Final[int] = int(os.getenv("OLLAMA_NUM_CTX", "32000"))
+
+SYSTEM_PROMPT: Final[str] = (
+    "You are a versatile AI assistant able to orchestrate several tools to "
+    "complete tasks. Plan your responses carefully and, when needed, call one "
+    "or more tools consecutively to gather data, compute answers, or transform "
+    "information. Continue chaining tools until the user's request is fully "
+    "addressed and then deliver a concise, coherent final reply."
+)