th-neu
diff --git a/‎examples/low_level_api/low_level_api_chat_cpp.py
Copy file name to clipboardExpand all lines: examples/low_level_api/low_level_api_chat_cpp.py
+14-14Lines changed: 14 additions & 14 deletions b/‎examples/low_level_api/low_level_api_chat_cpp.py
Copy file name to clipboardExpand all lines: examples/low_level_api/low_level_api_chat_cpp.py
+14-14Lines changed: 14 additions & 14 deletions
@@ -112,16 +112,17 @@ def __init__(self, params: GptParams) -> None:
 
 			if (path.exists(self.params.path_session)):
 				_session_tokens = (llama_cpp.llama_token * (self.params.n_ctx))()
-				_n_token_count_out = llama_cpp.c_int()
+				_n_token_count_out = llama_cpp.c_size_t()
 				if (llama_cpp.llama_load_session_file(
 					self.ctx, 
 					self.params.path_session.encode("utf8"),
 					_session_tokens,
 					self.params.n_ctx,
 					ctypes.byref(_n_token_count_out)
-				) != 0):
+				) != 1):
 					print(f"error: failed to load session file '{self.params.path_session}'", file=sys.stderr)
 					return
+				_n_token_count_out = _n_token_count_out.value
 				self.session_tokens = _session_tokens[:_n_token_count_out]
 				print(f"loaded a session with prompt size of {_n_token_count_out} tokens", file=sys.stderr)
 			else:
@@ -135,19 +136,21 @@ def __init__(self, params: GptParams) -> None:
 			raise RuntimeError(f"error: prompt is too long ({len(self.embd_inp)} tokens, max {self.params.n_ctx - 4})")
 
 		# debug message about similarity of saved session, if applicable
-		n_matching_session_tokens = 0
+		self.n_matching_session_tokens = 0
 		if len(self.session_tokens) > 0:
 			for id in self.session_tokens:
-				if n_matching_session_tokens >= len(self.embd_inp) or id != self.embd_inp[n_matching_session_tokens]:
+				if self.n_matching_session_tokens >= len(self.embd_inp) or id != self.embd_inp[self.n_matching_session_tokens]:
 					break
-				n_matching_session_tokens += 1
+				self.n_matching_session_tokens += 1
 
-			if n_matching_session_tokens >= len(self.embd_inp):
+			if self.n_matching_session_tokens >= len(self.embd_inp):
 				print(f"session file has exact match for prompt!")
-			elif n_matching_session_tokens < (len(self.embd_inp) / 2):
-				print(f"warning: session file has low similarity to prompt ({n_matching_session_tokens} / {len(self.embd_inp)} tokens); will mostly be reevaluated")
+			elif self.n_matching_session_tokens < (len(self.embd_inp) / 2):
+				print(f"warning: session file has low similarity to prompt ({self.n_matching_session_tokens} / {len(self.embd_inp)} tokens); will mostly be reevaluated")
 			else:
-				print(f"session file matches {n_matching_session_tokens} / {len(self.embd_inp)} tokens of prompt")
+				print(f"session file matches {self.n_matching_session_tokens} / {len(self.embd_inp)} tokens of prompt")
+
+		self.need_to_save_session = len(self.params.path_session) > 0 and self.n_matching_session_tokens < (len(self.embd_inp) * 3 / 4)
 
 		# number of tokens to keep when resetting context
 		if (self.params.n_keep < 0 or self.params.n_keep > len(self.embd_inp) or self.params.instruct):
@@ -232,9 +235,6 @@ def __init__(self, params: GptParams) -> None:
 """, file=sys.stderr)
 		self.set_color(util.CONSOLE_COLOR_PROMPT)
 
-		self.need_to_save_session = len(self.params.path_session) > 0 and n_matching_session_tokens < (len(self.embd_inp) * 3 / 4)
-
-
 	# tokenize a prompt
 	def _tokenize(self, prompt, bos=True):
 		_arr = (llama_cpp.llama_token * ((len(prompt) + 1) * 4))()
@@ -302,7 +302,7 @@ def generate(self):
 				) != 0):
 					raise Exception("Failed to llama_eval!")
 
-				if len(self.embd) > 0 and not len(self.params.path_session) > 0:
+				if len(self.embd) > 0 and len(self.params.path_session) > 0:
 					self.session_tokens.extend(self.embd)
 					self.n_session_consumed = len(self.session_tokens)
 
@@ -319,7 +319,7 @@ def generate(self):
 					llama_cpp.llama_save_session_file(
 						self.ctx,
 						self.params.path_session.encode("utf8"),
-						self.session_tokens,
+						(llama_cpp.llama_token * len(self.session_tokens))(*self.session_tokens),
 						len(self.session_tokens)
 					)