Support Local LLM on React Agent

ldp/graph/modules/llm_call.py

@@ -17,14 +17,26 @@ def __init__(
         self, llm_model: dict[str, Any], parser: Callable[..., TParsedMessage]
     ):
         self.config_op = ConfigOp[dict](config=llm_model)
+        self.llm_model = llm_model
         self.llm_call_op = LLMCallOp()
         self.parse_msg_op = FxnOp(parser)
 
     @compute_graph()
     async def __call__(
         self, messages: Iterable[Message], *parse_args, **parse_kwargs
     ) -> tuple[OpResult[TParsedMessage], Message]:
-        raw_result = await self.llm_call_op(await self.config_op(), msgs=messages)
+        if "LocalLLMCallOp" in self.llm_call_op.__class__.__name__:
+            print(f"STARTING A CALL TO MODEL ======================= with {len(messages.value)} messages")
+            for i, message in enumerate(messages.value[1:], start=1):
+                print(f"message{i}: {message.content}")
+            print(f"END OF MESSAGES =======================")
+            raw_result = await self.llm_call_op(
+                xi=messages,
+                temperature=self.llm_model["temperature"],
+                max_new_tokens=self.llm_model["max_new_tokens"],
+            )
+        else:
+            raw_result = await self.llm_call_op(await self.config_op(), msgs=messages)
         return await self.parse_msg_op(
             raw_result, *parse_args, **parse_kwargs
         ), raw_result.value

ldp/graph/modules/react.py

@@ -82,6 +82,8 @@ def parse_message(m: Message, tools: list[Tool]) -> ToolRequestMessage:  # noqa:
         message_content = message_content[: loc if loc > 0 else None]
     # we need to override the message too - don't want the model to hallucinate
     m.content = message_content
+
+    print("Received back!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n" + m.content)
 
     action_args: tuple[Any, ...] = ()
     # https://regex101.com/r/qmqZ7Z/1
@@ -141,6 +143,8 @@ def is_number(s: str) -> bool:
     action = re.search(r"Action:[ \t]*(\S*)", m.content)
     if not action:
         raise MalformedMessageError("Action not emitted.")
+    if "Observation:" in m.content:
+        raise MalformedMessageError("Observation found in message content and not expected.")
     tool_name = action.group(1).strip()
     # have to match up name to tool to line up args in order
     try: