release

.github/workflows/build.yaml

@@ -25,9 +25,59 @@ jobs:
         run: |
           sudo apt-get update
           sudo apt-get install -y build-essential cmake libpython3-dev
+          pip3 install torch --index-url https://download.pytorch.org/whl/cpu
+          pip3 install transformers tiktoken pyinstaller
 
-      - name: Build
-        id: cmake_build
+      - name: Build backend server
+        id: cmake_build_backend_server
         run: |
-          cmake -B build -S .
-          cmake --build build --config Release
+          cmake -B build_backend_server -S .
+          cmake --build build_backend_server --config Release
+
+      - name: Build lsp server
+        id: pyinstaller_build_lsp_server
+        run: |
+          pyinstaller flatline_lsp.py \
+            --copy-metadata tqdm \
+            --copy-metadata regex \
+            --copy-metadata requests \
+            --copy-metadata packaging \
+            --copy-metadata filelock \
+            --copy-metadata numpy \
+            --copy-metadata tokenizers \
+            --copy-metadata huggingface-hub \
+            --copy-metadata safetensors \
+            --copy-metadata pyyaml \
+            --copy-metadata torch \
+            --hidden-import=tiktoken_ext.openai_public \
+            --hidden-import=tiktoken_ext \
+            --add-binary build_backend_server/bin/flatline-server:flatline/backend_server \
+            ;
+          mkdir -p ./dist/flatline/license
+          find build_backend_server/bin -name \*.LICENSE.txt | xargs -I{} cp {} ./dist/flatline/license/
+          zip -r flatline_lsp.zip dist/flatline_lsp
+
+      - name: Create release
+        id: create_release
+        uses: actions/create-release@v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          tag_name: ${{ github.ref }}
+          release_name: Release ${{ github.ref }}
+          body: |
+            Release test
+          draft: true
+          prerelease: true
+
+      - name: Upload Release Asset
+        id: upload_release_asset
+        uses: actions/upload-release-asset@v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          upload_url: ${{ steps.create_release.outputs.upload_url }}
+          asset_path: ./flatline_lsp.zip
+          asset_name: flatline_lsp.zip
+          asset_content_type: application/zip
+

flatline_lsp.py

@@ -1,4 +1,6 @@
 import argparse
+import sys
+import os
 import requests
 from typing import Any, Dict, Optional, List
 import threading
@@ -27,6 +29,7 @@ class LlamaCppCausalLM(PreTrainedModel):
     def __init__(
         self,
         config: LlamaCppConfig,
+        backend_server_bin: str,
         backend_server_host: str,
         backend_server_port: int,
         model_name: str,
@@ -35,6 +38,7 @@ def __init__(
     ):
         super().__init__(config)
 
+        self.baseckend_server_bin = backend_server_bin
         self.baseckend_server_host = backend_server_host
         self.baseckend_server_port = backend_server_port
         try:
@@ -43,7 +47,7 @@ def __init__(
             )
         except Exception:
             subprocess.Popen(
-                f"/home/okada/flatline2/build/bin/flatline-server --model-path {model_name} --n-gpu_layers {n_gpu_layers}".split()
+                f"{self.baseckend_server_bin} --model-path {model_name} --n-gpu_layers {n_gpu_layers}".split()
             )
 
     @property
@@ -123,27 +127,29 @@ def __init__(
         self,
         lang_server: LanguageServer,
         max_new_tokens: int,
+        backend_server_bin: str,
         backend_server_host: str,
         backend_server_port: int,
         model_name: str,
         n_threads: int,
         n_gpu_layers: int,
     ):
         self.lang_server = lang_server
+        self.max_new_tokens = max_new_tokens
 
         assert model_name.endswith(".gguf")
         self.tokenizer = AutoTokenizer.from_pretrained(
             "Salesforce/codegen25-7b-multi", trust_remote_code=True
         )
         self.model = LlamaCppCausalLM(
             config=LlamaCppConfig(),
+            backend_server_bin=backend_server_bin,
             backend_server_host=backend_server_host,
             backend_server_port=backend_server_port,
             model_name=model_name,
             n_threads=n_threads,
             n_gpu_layers=n_gpu_layers,
         )
-        self.max_new_tokens = max_new_tokens
 
         self.latest_completion_id_lock = threading.Lock()
         self.computing_resource_lock = threading.Lock()
@@ -221,14 +227,23 @@ def completions(
     )
 
 
+def resource_path(relative_path: str):
+    try:
+        base_path = sys._MEIPASS
+    except Exception:
+        base_path = os.path.dirname(__file__)
+    return os.path.join(base_path, relative_path)
+
+
 def main() -> None:
     parser = argparse.ArgumentParser()
+    parser.add_argument("--backend-server-bin", type=str, default=resource_path("./flatline/backend_server/flatline-server"))
     parser.add_argument("--backend-server-host", type=str, default="localhost")
     parser.add_argument("--backend-server-port", type=int, default=5000)
     parser.add_argument(
         "--model-name",
         type=str,
-        default="/home/okada/flatline2/codegen25-7b-multi/ggml-model-Q4_K.gguf",
+        default=resource_path("./flatline/model_data/codegen25-7b-multi/ggml-model-Q4_K.gguf"),
     )
     parser.add_argument("--max-new-tokens", type=int, default=256)
     parser.add_argument("--n-threads", type=int, default=8)
@@ -239,6 +254,7 @@ def main() -> None:
     lm_for_completion = LanguageModelForCompletion(
         lang_server=server,
         max_new_tokens=args.max_new_tokens,
+        backend_server_bin=args.backend_server_bin,
         backend_server_host=args.backend_server_host,
         backend_server_port=args.backend_server_port,
         model_name=args.model_name,

prepare_codegen25_model.sh

@@ -1,3 +1,3 @@
 #!/usr/bin/bash
 head -c 30M </dev/urandom >dummy_file
-python3 make_dummy_tokenizer.py 2>&1 | grep -v 'The corpus must be encoded in utf-8.'
+python3 make_dummy_tokenizer.py