fix merge bugs.

build_all_in_one.sh

@@ -1,5 +1,3 @@
 #!/usr/bin/bash
-
-pipreqs ./src --force
 # Build the docker image
 docker build -t aios .

src/aios_kernel/compute_task.py

@@ -12,12 +12,13 @@ class ComputeTaskState(Enum):
     PENDING = 4
 
 class ComputeTaskType(Enum):
-    NONE = -1
+    NONE = "None"
-    LLM_COMPLETION = 0
+    LLM_COMPLETION = "llm_completion"
-    TEXT_2_IMAGE = 1
+    TEXT_2_IMAGE = "text_2_image"
-    IMAGE_2_IMAGE = 2
+    IMAGE_2_IMAGE = "image_2_image"
-    VOICE_2_TEXT = 3
+    VOICE_2_TEXT = "voice_2_text"
-    TEXT_2_VOICE = 4
+    TEXT_2_VOICE = "text_2_voice"
+    TEXT_EMBEDDING ="text_embedding"
 
 
 class ComputeTask:
@@ -54,7 +55,7 @@ class ComputeTask:
             self.params["inner_functions"] = inner_functions
 
     def set_text_embedding_params(self, input, model_name=None, callchain_id = None):
-        self.task_type = "text_embedding"
+        self.task_type = ComputeTaskType.TEXT_EMBEDDING
         self.create_time = time.time()
         self.task_id = uuid.uuid4().hex
         self.callchain_id = callchain_id

src/aios_kernel/open_ai_node.py

@@ -59,7 +59,8 @@ class OpenAI_ComputeNode(ComputeNode):
 
     def _run_task(self, task: ComputeTask):
         task.state = ComputeTaskState.RUNNING
-        if task.task_type == "text_embedding":
+        match task.task_type:
+            case ComputeTaskType.TEXT_EMBEDDING:
                 model_name = task.params["model_name"]
                 input = task.params["input"]
                 logger.info(f"call openai {model_name} input: {input}")
@@ -90,29 +91,26 @@ class OpenAI_ComputeNode(ComputeNode):
                 result.result = resp["data"][0]["embedding"]
 
                 return result
-          
+            case ComputeTaskType.LLM_COMPLETION:
-        if task.task_type == "llm_completion":
                 mode_name = task.params["model_name"]
-            # max_token_size = task.params["max_token_size"]
                 prompts = task.params["prompts"]
-
+                max_token_size = task.params.get("max_token_size")
-            mode_name = task.params["model_name"]
+                llm_inner_functions = task.params["inner_functions"]
-	        # max_token_size = task.params["max_token_size"]
+                if max_token_size is None:
-            prompts = task.params["prompts"]          
+                    max_token_size = 4000
-       
                     
                 logger.info(f"call openai {mode_name} prompts: {prompts}")
 
-            if task.params.get("inner_functions") is None:
+                if llm_inner_functions is None:
                     resp = openai.ChatCompletion.create(model=mode_name,
                                                     messages=prompts,
-                                                max_tokens=task.params["max_token_size"],
+                                                    max_tokens=max_token_size,
                                                     temperature=0.7)
                 else:
                     resp = openai.ChatCompletion.create(model=mode_name,
                                                         messages=prompts,
-                                                    functions=task.params["inner_functions"],
+                                                        functions=llm_inner_functions,
-                                                    max_tokens=task.params["max_token_size"],
+                                                        max_tokens=max_token_size,
                                                         temperature=0.7) # TODO: add temperature to task params?
 
             
@@ -135,9 +133,10 @@ class OpenAI_ComputeNode(ComputeNode):
                 result.worker_id = self.node_id
                 result.result_str = resp["choices"][0]["message"]["content"]
                 result.result_message = resp["choices"][0]["message"]
-
                 return result
-
+            case _:
+                task.state = ComputeTaskState.ERROR
+                return None
 
     def start(self):
         if self.is_start is True:
@@ -167,9 +166,9 @@ class OpenAI_ComputeNode(ComputeNode):
 
     def is_support(self, task: ComputeTask) -> bool:
         if task.task_type == ComputeTaskType.LLM_COMPLETION: 
-            if (not task.params["model_name"] or task.params["model_name"] == "gpt-4-0613")
+            if not task.params["model_name"] or task.params["model_name"] == "gpt-4-0613":
                 return True
-        if task.task_type == "text_embedding":
+        if task.task_type == ComputeTaskType.TEXT_EMBEDDING:
             if task.params["model_name"] == "text-embedding-ada-002":
                 return True
         return False

src/requirements.txt

@@ -1,7 +1,4 @@
-
 chromadb==0.4
-openai==0.28
-toml==0.10
 moviepy==1.0
 base58==2.1
 base36==0.1
@@ -11,14 +8,14 @@ aioimaplib==1.0.1
 aiosmtplib==2.0.2
 beautifulsoup4==4.12.2
 mail_parser==3.15.0
-openai==0.27.10
-Pillow
 prompt_toolkit==3.0.39
-protobuf
 pydantic==1.10.11
 python-telegram-bot==20.5
 Requests==2.31.0
+protobuf
 stability_sdk
-toml==0.10.2
+toml
-
+base58
 google-cloud-texttospeech
+openai
+Pillow

src/service/aios_shell/aios_shell.py

@@ -102,7 +102,7 @@ class AIOS_Shell:
         EmailTunnel.register_to_loader()
 
         user_data_dir = AIStorage.get_instance().get_myai_dir()
-        tunnels_config_path = os.path.abspath(f"{user_data_dir}/tunnels.cfg.toml")
+        tunnels_config_path = os.path.abspath(f"{user_data_dir}/etc/tunnels.cfg.toml")
         tunnel_config = None
         try: 
             tunnel_config = toml.load(tunnels_config_path)