Merge pull request #12 from KeithLin724/KY-docker-compose-linux

KY-docker-compose-linux

.gitignore

@@ -11,4 +11,5 @@ gui_venv_linux
 *.log
 .vscode/
 **.env
-onnx-stable-diffusion-v1-5/
+onnx-stable-diffusion-v1-5/
+test/

api/Dockerfile

@@ -47,4 +47,5 @@ COPY . .
 EXPOSE 5000
 
 # Run the application.
-CMD uvicorn api_server:app --reload --port 5000 --host 0.0.0.0
+# CMD uvicorn api_server:app --reload --port 5000 --host 0.0.0.0
+CMD uvicorn api_server:app --port 5000 --host 0.0.0.0

api/api_server.py

@@ -10,8 +10,6 @@
 # import uvicorn
 import router
 from base import (
-    SERVER_IP,
-    SERVER_PORT,
     SERVER_URL,
     # redis queue
     TASK_IMAGE_QUEUE,
@@ -28,6 +26,7 @@
     server_close,
     monitor_micro_server,
     chat_to_ai_fast_function,
+    cut_prompt_with_fast_function,
 )
 from api_task_func import generate_image_queue
 from contextlib import asynccontextmanager
@@ -104,6 +103,7 @@ async def generate_request_to_micro_service(generate_service: GenerateServiceIte
         "prompt": generate_service.prompt,
     }
 
+    # TODO: chat with ai service
     if generate_service.type_service == "chat":
         provider, result = await chat_to_ai_fast_function(
             prompt=generate_service.prompt
@@ -114,6 +114,11 @@ async def generate_request_to_micro_service(generate_service: GenerateServiceIte
             "message": result,
         }
 
+    # TODO: cut prompt service
+    elif generate_service.type_service == "cut_prompt":
+        return await cut_prompt_with_fast_function(prompt=generate_service.prompt)
+
+    # TODO: other service
     if generate_service.type_service in monitor_micro_server:
         response = await handle_request_function(generate_service, json_data)
         return response

api/base/__init__.py

@@ -70,6 +70,25 @@ async def chat_to_ai_fast_function(prompt: str):
     return provider, reply_message
 
 
+async def cut_prompt_with_fast_function(prompt: str):
+    """The function `cut_prompt_with_fast_function` takes a prompt as input and uses a text generator model
+    to cut the prompt.
+
+    Parameters
+    ----------
+    prompt : str
+        The `prompt` parameter is a string that represents the text you want to use as a prompt for the
+    text generation model. It is the input that the model will use to generate the desired output.
+
+    Returns
+    -------
+        The function `cut_prompt_with_fast_function` returns the result of calling the `cut_prompt` method
+    of the `text_generator_model` object with the provided `prompt` as an argument.
+
+    """
+    return await text_generator_model.cut_prompt(prompt=prompt)
+
+
 from .message_item import (
     GenerateImageItem,
     ChatItem,

api/model/text_generator_g4f.py

@@ -22,9 +22,16 @@ def __init__(self) -> None:
             g4f.Provider.ChatBase,
             g4f.Provider.GptGo,
             g4f.Provider.You,
+            g4f.Provider.Raycast,
             # g4f.Provider.Yqcloud,
         ]
 
+        self._cut_prompt_provider = [
+            g4f.Provider.You,
+            # g4f.Provider.GptGo,
+            g4f.Provider.GeekGpt,
+        ]
+
     async def run_provider(self, provider: g4f.Provider.BaseProvider, prompt: str):
         """
         The function `run_provider` takes a provider and a prompt as input, and uses the provider to
@@ -142,3 +149,41 @@ async def generate(self, prompt):
 
         provider, msg = await self.get_generate(prompt=prompt)
         return provider, msg
+
+    async def cut_prompt(self, prompt: str) -> dict:
+        """The `cut_prompt` function takes a prompt string and runs it through multiple providers
+        asynchronously, returning a list of dictionaries containing the state, provider, and response for
+        each provider.
+
+        Parameters
+        ----------
+        prompt : str
+            The `prompt` parameter is a string that represents the text or question that you want to send to
+        each provider for processing.
+
+        Returns
+        -------
+            The `cut_prompt` function returns a list of dictionaries. Each dictionary contains three key-value
+        pairs: "state", "provider", and "response". The "state" key represents the state of the provider,
+        the "provider" key represents the provider itself, and the "response" key represents the response
+        received from the provider.
+
+        """
+        pending_tasks = [
+            self.run_provider(
+                provider=provider,
+                prompt=prompt,
+            )
+            for provider in self._cut_prompt_provider
+        ]
+
+        result = await asyncio.gather(*pending_tasks)
+
+        return [
+            {
+                "state": state,
+                "provider": provider,
+                "response": response,
+            }
+            for state, provider, response in result
+        ]