Disable chunking (temporary), fix llama-cpp tools

Might break openai? Can't test it right now, but I hope I can make both
happy with a unified sollution instead of patching everything for each
model

r2ai/r2clippy/functions.py

@@ -40,12 +40,12 @@ def result(self) -> str:
         print("Running %s" % self.command)
         res = r2.cmd(self.command)
         print(res)
-        add_chunk(res)
-        res = get_chunk()
-        chunk_size = size()
-        if chunk_size > 0:
-            res+= f"\nChunked message. Remaining chunks: {chunk_size}. Use RetriveChunk to retrive the next chunk."
-        LOGGER.getChild("auto").info("Response has been chunked. Nr of chunks: %s", chunk_size)
+        # add_chunk(res)
+        # r        # res = get_chunk()es = get_chunk()
+        # chunk_size = size()
+        # if chunk_size > 0:
+        #     res+= f"\nChunked message. Remaining chunks: {chunk_size}. Use RetriveChunk to retrive the next chunk."
+        # LOGGER.getChild("auto").info("Response has been chunked. Nr of chunks: %s", chunk_size)
         return res
 
 
@@ -62,27 +62,29 @@ def result(self) -> str:
             print(self.snippet)
             r2lang.cmd('#!python r2ai_tmp.py > $tmp')
             res = r2lang.cmd('cat $tmp')
-            add_chunk(res)
-            res = get_chunk()
-            chunk_size = size()
-            if chunk_size > 0:
-                res+= f"\nChunked message. Remaining chunks: {chunk_size}. Use RetriveChunk to retrive the next chunk."
+            # add_chunk(res)
+            # res = get_chunk()
+            # chunk_size = size()
+            # if chunk_size > 0:
+            #     res+= f"\nChunked message. Remaining chunks: {chunk_size}. Use RetriveChunk to retrive the next chunk."
             r2lang.cmd('rm r2ai_tmp.py')
             print(res)
             return res
 
-@FunctionStorage.store()
-class RetriveChunk(OpenAISchema):
-    """gets a chunk of a chunked message."""
-
-    @computed_field
-    def result(self) -> str:
-        res = get_chunk()
-        chunk_size = size()
-        if chunk_size > 0:
-            res+=f"\nChunked message. Remaining chunks: {chunk_size}. Use RetriveChunk to retrive the next chunk."
-        LOGGER.getChild("auto").info("Remaining chunks: %s", chunk_size)
-        return res
+#TODO: better choice is to make it so it replaces the previous chunk with a summary
+# from the ai. disabled for now
+# @FunctionStorage.store()
+# class RetriveChunk(OpenAISchema):
+#     """gets a chunk of a chunked message."""
+
+#     @computed_field
+#     def result(self) -> str:
+#         res = get_chunk()
+#         chunk_size = size()
+#         if chunk_size > 0:
+#             res+=f"\nChunked message. Remaining chunks: {chunk_size}. Use RetriveChunk to retrive the next chunk."
+#         LOGGER.getChild("auto").info("Remaining chunks: %s", chunk_size)
+#         return res
 
 @FunctionStorage.store()
 class SaveMemory(OpenAISchema):

r2ai/r2clippy/processors.py

@@ -66,13 +66,13 @@ def process_streaming_response(interpreter, response) -> bool:
 def process_tool_calls(interpreter, tool_calls):
     interpreter.messages.append(
         {
-            "content": "Continue with task",
+            "content": None,
             "tool_calls": tool_calls,
             "role": "assistant"
         }
     )
-    content = ""
     for tool in tool_calls:
+        content = ""
         args = tool["function"]["arguments"]
         tool_name = tool["function"]["name"]
         tool_id = tool["id"] if "id" in tool else None
@@ -81,7 +81,7 @@ def process_tool_calls(interpreter, tool_calls):
                 args = json.loads(args)
             except json.JSONDecodeError:
                 print(f"Error parsing json: {args}", file=sys.stderr)
-        content = validate_ai_tool(args).result
+        content = validate_ai_tool(args).result or "Continue with task"
         if not tool_name:
             raise ValueError("Tool name must not be null")
         if not tool_id: