fix: 修复工厂模式问题并增加chat-template设置

astrai/inference/generator.py

@@ -2,6 +2,7 @@ from dataclasses import dataclass
 from typing import Dict, Generator, List, Optional, Tuple, Union
 
 import torch
+from jinja2 import Template
 from torch import Tensor
 
 from astrai.config.param_config import ModelParameter
@@ -9,39 +10,69 @@ from astrai.core.factory import BaseFactory
 from astrai.inference.core import EmbeddingEncoderCore, GeneratorCore, KVCacheManager
 
 HistoryType = List[Tuple[str, str]]
+MessageType = Dict[str, str]
+
+# Predefined chat templates using jinja2
+CHAT_TEMPLATES: Dict[str, str] = {
+    "chatml": """{%- if system_prompt -%}
+<｜im▁start｜>system
+{{ system_prompt }}<｜im▁end｜>
+{%- endif -%}
+{%- for message in messages -%}
+<｜im▁start｜>{{ message['role'] }}
+{{ message['content'] }}<｜im▁end｜>
+{%- endfor -%}
+<｜im▁start｜>assistant
+""",
+}
 
 
 def build_prompt(
     query: str,
     system_prompt: Optional[str] = None,
     history: Optional[HistoryType] = None,
+    template: Optional[str] = None,
 ) -> str:
-    """
+    """Build prompt using jinja2 template for query and history.
-    Build prompt in ChatML format for query and history.
 
     Args:
         query (str): query string.
         system_prompt (Optional[str]): system prompt string.
         history (Optional[HistoryType]): history list of query and response.
+        template (Optional[str]): jinja2 template string. If None, uses default chatml template.
 
     Returns:
-        str: prompt string in ChatML format.
+        str: prompt string formatted according to the template.
+
+    Example:
+        # Use default template
+        prompt = build_prompt(query="Hello", history=[...])
+
+        # Use custom template
+        custom_template = '''
+        {%- for msg in messages -%}
+        {{ msg['role'] }}: {{ msg['content'] }}
+        {%- endfor -%}
+        '''
+        prompt = build_prompt(query="Hello", template=custom_template)
     """
-    result = ""
+    # Convert history to message format
-
+    messages: List[MessageType] = []
-    if system_prompt:
-        result += f"<｜im▁start｜>system\n{system_prompt}<｜im▁end｜>\n"
-
-    # (convert tuple format to ChatML)
     if history:
         for user_msg, assistant_msg in history:
-            result += f"<｜im▁start｜>user\n{user_msg}<｜im▁end｜>\n"
+            messages.append({"role": "user", "content": user_msg})
-            result += f"<｜im▁start｜>assistant\n{assistant_msg}<｜im▁end｜>\n"
+            messages.append({"role": "assistant", "content": assistant_msg})
+    messages.append({"role": "user", "content": query})
 
-    result += f"<｜im▁start｜>user\n{query}<｜im▁end｜>\n"
+    # Use provided template or default chatml template
-    result += "<｜im▁start｜>assistant\n"
+    template_str = template if template is not None else CHAT_TEMPLATES["chatml"]
 
-    return result
+    # Render template
+    jinja_template = Template(template_str)
+    return jinja_template.render(
+        messages=messages,
+        system_prompt=system_prompt,
+    )
 
 
 def pad_sequence(ids_list: List[List[int]], pad_id: int) -> Tuple[List[List[int]], int]:
@@ -303,18 +334,3 @@ class GeneratorFactory(BaseFactory[GeneratorCore]):
             EmbeddingEncoderCore instance
         """
         return EmbeddingEncoder(parameter)
-
-    @classmethod
-    def create(
-        cls, parameter: ModelParameter, request: GenerationRequest
-    ) -> GeneratorCore:
-        """Convenience method that delegates to create_generator.
-
-        Args:
-            parameter: Model parameters
-            request: Generation request
-
-        Returns:
-            Generator instance
-        """
-        return cls.create_generator(parameter, request)

pyproject.toml

@@ -15,6 +15,7 @@ dependencies = [
     "tqdm==4.67.1",
     "safetensors==0.5.3",
     "huggingface-hub==0.34.3",
+    "jinja2>=3.0.0",
     "fastapi",
     "uvicorn[standard]",
     "httpx",