chore: mv examples out of pipelines

examples/llama_cpp_pipeline.py

@@ -0,0 +1,51 @@
+from typing import List, Union, Generator, Iterator
+from schemas import OpenAIChatMessage
+
+
+class Pipeline:
+    def __init__(self):
+        # Optionally, you can set the id and name of the pipeline.
+        # Assign a unique identifier to the pipeline.
+        # The identifier must be unique across all pipelines.
+        # The identifier must be an alphanumeric string that can include underscores or hyphens. It cannot contain spaces, special characters, slashes, or backslashes.
+        self.id = "llama_cpp_pipeline"
+
+        self.name = "Llama C++ Pipeline"
+        self.llm = None
+        pass
+
+    async def on_startup(self):
+        # This function is called when the server is started.
+        print(f"on_startup:{__name__}")
+        from llama_cpp import Llama
+
+        self.llm = Llama(
+            model_path="./models/llama3.gguf",
+            # n_gpu_layers=-1, # Uncomment to use GPU acceleration
+            # seed=1337, # Uncomment to set a specific seed
+            # n_ctx=2048, # Uncomment to increase the context window
+        )
+
+        pass
+
+    async def on_shutdown(self):
+        # This function is called when the server is stopped.
+        print(f"on_shutdown:{__name__}")
+        pass
+
+    def pipe(
+        self, user_message: str, model_id: str, messages: List[dict], body: dict
+    ) -> Union[str, Generator, Iterator]:
+        # This is where you can add your custom pipelines like RAG.'
+        print(f"pipe:{__name__}")
+
+        print(messages)
+        print(user_message)
+        print(body)
+
+        response = self.llm.create_chat_completion_openai_v1(
+            messages=messages,
+            stream=body["stream"],
+        )
+
+        return response