Merge branch 'master' into swiftyos/secrt-871-monitor-page-crashing-o…

…n-due-to-number-of-requests

.dockerignore

@@ -0,0 +1,40 @@
+# Ignore everything by default, selectively add things to context
+classic/run
+
+# AutoGPT
+!classic/original_autogpt/autogpt/
+!classic/original_autogpt/pyproject.toml
+!classic/original_autogpt/poetry.lock
+!classic/original_autogpt/README.md
+!classic/original_autogpt/tests/
+
+# Benchmark
+!classic/benchmark/agbenchmark/
+!classic/benchmark/pyproject.toml
+!classic/benchmark/poetry.lock
+!classic/benchmark/README.md
+
+# Forge
+!classic/forge/
+!classic/forge/pyproject.toml
+!classic/forge/poetry.lock
+!classic/forge/README.md
+
+# Frontend
+!classic/frontend/build/web/
+
+# Platform
+!autogpt_platform/
+
+# Explicitly re-ignore some folders
+.*
+**/__pycache__
+
+autogpt_platform/frontend/.next/
+autogpt_platform/frontend/node_modules
+autogpt_platform/frontend/.env.example
+autogpt_platform/frontend/.env.local
+autogpt_platform/backend/.env
+autogpt_platform/backend/.venv/
+
+autogpt_platform/market/.env

autogpt_platform/README.md

@@ -27,7 +27,7 @@ To run the AutoGPT Platform, follow these steps:
 6. Run the following command:
 
    ```
-   docker compose -f docker-compose.combined.yml up -d
+   docker compose up -d
 
    ```
 
@@ -46,8 +46,8 @@ To run the AutoGPT Platform, follow these steps:
 
 Here are some useful Docker Compose commands for managing your AutoGPT Platform:
 
-- `docker compose -f docker-compose.combined.yml up -d`: Start the services in detached mode.
-- `docker compose -f docker-compose.combined.yml stop`: Stop the running services without removing them.
+- `docker compose up -d`: Start the services in detached mode.
+- `docker compose stop`: Stop the running services without removing them.
 - `docker compose rm`: Remove stopped service containers.
 - `docker compose build`: Build or rebuild services.
 - `docker compose down`: Stop and remove containers, networks, and volumes.

autogpt_platform/backend/backend/blocks/llm.py

@@ -320,7 +320,7 @@ def llm_call(input_data: AIStructuredResponseGeneratorBlock.Input) -> str:
             if output_name == "response":
                 return output_data["response"]
             else:
-                raise output_data
+                raise RuntimeError(output_data)
         raise ValueError("Failed to get a response from the LLM.")
 
     def run(self, input_data: Input) -> BlockOutput:

autogpt_platform/backend/backend/blocks/time_blocks.py

@@ -23,7 +23,7 @@ def __init__(self):
                 {"trigger": "Hello", "format": "{time}"},
             ],
             test_output=[
-                ("time", time.strftime("%H:%M:%S")),
+                ("time", lambda _: time.strftime("%H:%M:%S")),
             ],
         )
 

autogpt_platform/backend/backend/data/execution.py

@@ -396,19 +396,19 @@ def merge_execution_input(data: BlockInput) -> BlockInput:
 
     # Merge all input with <input_name>_$_<index> into a single list.
     items = list(data.items())
-    list_input: list[Any] = []
+
     for key, value in items:
         if LIST_SPLIT not in key:
             continue
         name, index = key.split(LIST_SPLIT)
         if not index.isdigit():
-            list_input.append((name, value, 0))
-        else:
-            list_input.append((name, value, int(index)))
+            raise ValueError(f"Invalid key: {key}, #{index} index must be an integer.")
 
-    for name, value, _ in sorted(list_input, key=lambda x: x[2]):
         data[name] = data.get(name, [])
-        data[name].append(value)
+        if int(index) >= len(data[name]):
+            # Pad list with empty string on missing indices.
+            data[name].extend([""] * (int(index) - len(data[name]) + 1))
+        data[name][int(index)] = value
 
     # Merge all input with <input_name>_#_<index> into a single dict.
     for key, value in items:

autogpt_platform/backend/backend/executor/manager.py

@@ -69,20 +69,28 @@ def __init__(
         self.prefix = f"[ExecutionManager|uid:{user_id}|gid:{graph_id}|nid:{node_id}]|geid:{graph_eid}|nid:{node_eid}|{block_name}]"
 
     def info(self, msg: str, **extra):
+        msg = self._wrap(msg, **extra)
         logger.info(msg, extra={"json_fields": {**self.metadata, **extra}})
 
     def warning(self, msg: str, **extra):
+        msg = self._wrap(msg, **extra)
         logger.warning(msg, extra={"json_fields": {**self.metadata, **extra}})
 
     def error(self, msg: str, **extra):
+        msg = self._wrap(msg, **extra)
         logger.error(msg, extra={"json_fields": {**self.metadata, **extra}})
 
     def debug(self, msg: str, **extra):
+        msg = self._wrap(msg, **extra)
         logger.debug(msg, extra={"json_fields": {**self.metadata, **extra}})
 
     def exception(self, msg: str, **extra):
+        msg = self._wrap(msg, **extra)
         logger.exception(msg, extra={"json_fields": {**self.metadata, **extra}})
 
+    def _wrap(self, msg: str, **extra):
+        return f"{self.prefix} {msg} {extra}"
+
 
 T = TypeVar("T")
 ExecutionStream = Generator[NodeExecution, None, None]