added llama3 prompt (#1962)

* added llama3 prompt

* more fixes to pass tests; changed type VectorStore -> BasePydanticVectorStore, see https://github.com/run-llama/llama_index/blob/main/CHANGELOG.md#2024-05-14

* fix: new llama3 prompt

---------

Co-authored-by: Javier Martinez <javiermartinezalvarez98@gmail.com>

private_gpt/components/llm/prompt_helper.py

@@ -138,6 +138,73 @@ class Llama2PromptStyle(AbstractPromptStyle):
         )
 
 
+class Llama3PromptStyle(AbstractPromptStyle):
+    r"""Template for Meta's Llama 3.1.
+
+    The format follows this structure:
+    <|begin_of_text|>
+    <|start_header_id|>system<|end_header_id|>
+
+    [System message content]<|eot_id|>
+    <|start_header_id|>user<|end_header_id|>
+
+    [User message content]<|eot_id|>
+    <|start_header_id|>assistant<|end_header_id|>
+
+    [Assistant message content]<|eot_id|>
+    ...
+    (Repeat for each message, including possible 'ipython' role)
+    """
+
+    BOS, EOS = "<|begin_of_text|>", "<|end_of_text|>"
+    B_INST, E_INST = "<|start_header_id|>", "<|end_header_id|>"
+    EOT = "<|eot_id|>"
+    B_SYS, E_SYS = "<|start_header_id|>system<|end_header_id|>", "<|eot_id|>"
+    ASSISTANT_INST = "<|start_header_id|>assistant<|end_header_id|>"
+    DEFAULT_SYSTEM_PROMPT = """\
+    You are a helpful, respectful and honest assistant. \
+    Always answer as helpfully as possible and follow ALL given instructions. \
+    Do not speculate or make up information. \
+    Do not reference any given instructions or context. \
+    """
+
+    def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str:
+        prompt = self.BOS
+        has_system_message = False
+
+        for i, message in enumerate(messages):
+            if not message or message.content is None:
+                continue
+            if message.role == MessageRole.SYSTEM:
+                prompt += f"{self.B_SYS}\n\n{message.content.strip()}{self.E_SYS}"
+                has_system_message = True
+            else:
+                role_header = f"{self.B_INST}{message.role.value}{self.E_INST}"
+                prompt += f"{role_header}\n\n{message.content.strip()}{self.EOT}"
+
+            # Add assistant header if the last message is not from the assistant
+            if i == len(messages) - 1 and message.role != MessageRole.ASSISTANT:
+                prompt += f"{self.ASSISTANT_INST}\n\n"
+
+        # Add default system prompt if no system message was provided
+        if not has_system_message:
+            prompt = (
+                f"{self.BOS}{self.B_SYS}\n\n{self.DEFAULT_SYSTEM_PROMPT}{self.E_SYS}"
+                + prompt[len(self.BOS) :]
+            )
+
+        # TODO: Implement tool handling logic
+
+        return prompt
+
+    def _completion_to_prompt(self, completion: str) -> str:
+        return (
+            f"{self.BOS}{self.B_SYS}\n\n{self.DEFAULT_SYSTEM_PROMPT}{self.E_SYS}"
+            f"{self.B_INST}user{self.E_INST}\n\n{completion.strip()}{self.EOT}"
+            f"{self.ASSISTANT_INST}\n\n"
+        )
+
+
 class TagPromptStyle(AbstractPromptStyle):
     """Tag prompt style (used by Vigogne) that uses the prompt style `<|ROLE|>`.
 
@@ -219,7 +286,8 @@ class ChatMLPromptStyle(AbstractPromptStyle):
 
 
 def get_prompt_style(
-    prompt_style: Literal["default", "llama2", "tag", "mistral", "chatml"] | None
+    prompt_style: Literal["default", "llama2", "llama3", "tag", "mistral", "chatml"]
+    | None
 ) -> AbstractPromptStyle:
     """Get the prompt style to use from the given string.
 
@@ -230,6 +298,8 @@ def get_prompt_style(
         return DefaultPromptStyle()
     elif prompt_style == "llama2":
         return Llama2PromptStyle()
+    elif prompt_style == "llama3":
+        return Llama3PromptStyle()
     elif prompt_style == "tag":
         return TagPromptStyle()
     elif prompt_style == "mistral":

private_gpt/settings/settings.py

@@ -111,12 +111,15 @@ class LLMSettings(BaseModel):
         0.1,
         description="The temperature of the model. Increasing the temperature will make the model answer more creatively. A value of 0.1 would be more factual.",
     )
-    prompt_style: Literal["default", "llama2", "tag", "mistral", "chatml"] = Field(
+    prompt_style: Literal[
+        "default", "llama2", "llama3", "tag", "mistral", "chatml"
+    ] = Field(
         "llama2",
         description=(
             "The prompt style to use for the chat engine. "
             "If `default` - use the default prompt style from the llama_index. It should look like `role: message`.\n"
             "If `llama2` - use the llama2 prompt style from the llama_index. Based on `<s>`, `[INST]` and `<<SYS>>`.\n"
+            "If `llama3` - use the llama3 prompt style from the llama_index."
             "If `tag` - use the `tag` prompt style. It should look like `<|role|>: message`. \n"
             "If `mistral` - use the `mistral prompt style. It shoudl look like <s>[INST] {System Prompt} [/INST]</s>[INST] { UserInstructions } [/INST]"
             "`llama2` is the historic behaviour. `default` might work better with your custom models."

pyproject.toml

@@ -124,7 +124,7 @@ target-version = ['py311']
 target-version = 'py311'
 
 # See all rules at https://beta.ruff.rs/docs/rules/
-select = [
+lint.select = [
     "E", # pycodestyle
     "W", # pycodestyle
     "F", # Pyflakes
@@ -141,7 +141,7 @@ select = [
     "RUF", # Ruff-specific rules
 ]
 
-ignore = [
+lint.ignore = [
     "E501", # "Line too long"
     # -> line length already regulated by black
     "PT011", # "pytest.raises() should specify expected exception"
@@ -159,24 +159,24 @@ ignore = [
     # -> "Missing docstring in public function too restrictive"
 ]
 
-[tool.ruff.pydocstyle]
+[tool.ruff.lint.pydocstyle]
 # Automatically disable rules that are incompatible with Google docstring convention
 convention = "google"
 
-[tool.ruff.pycodestyle]
+[tool.ruff.lint.pycodestyle]
 max-doc-length = 88
 
-[tool.ruff.flake8-tidy-imports]
+[tool.ruff.lint.flake8-tidy-imports]
 ban-relative-imports = "all"
 
-[tool.ruff.flake8-type-checking]
+[tool.ruff.lint.flake8-type-checking]
 strict = true
 runtime-evaluated-base-classes = ["pydantic.BaseModel"]
 # Pydantic needs to be able to evaluate types at runtime
 # see https://pypi.org/project/flake8-type-checking/ for flake8-type-checking documentation
 # see https://beta.ruff.rs/docs/settings/#flake8-type-checking-runtime-evaluated-base-classes for ruff documentation
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 # Allow missing docstrings for tests
 "tests/**/*.py" = ["D1"]
 

tests/test_prompt_helper.py

@@ -5,6 +5,7 @@ from private_gpt.components.llm.prompt_helper import (
     ChatMLPromptStyle,
     DefaultPromptStyle,
     Llama2PromptStyle,
+    Llama3PromptStyle,
     MistralPromptStyle,
     TagPromptStyle,
     get_prompt_style,
@@ -139,3 +140,57 @@ def test_llama2_prompt_style_with_system_prompt():
     )
 
     assert prompt_style.messages_to_prompt(messages) == expected_prompt
+
+
+def test_llama3_prompt_style_format():
+    prompt_style = Llama3PromptStyle()
+    messages = [
+        ChatMessage(content="You are a helpful assistant", role=MessageRole.SYSTEM),
+        ChatMessage(content="Hello, how are you doing?", role=MessageRole.USER),
+    ]
+
+    expected_prompt = (
+        "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n"
+        "You are a helpful assistant<|eot_id|>"
+        "<|start_header_id|>user<|end_header_id|>\n\n"
+        "Hello, how are you doing?<|eot_id|>"
+        "<|start_header_id|>assistant<|end_header_id|>\n\n"
+    )
+
+    assert prompt_style.messages_to_prompt(messages) == expected_prompt
+
+
+def test_llama3_prompt_style_with_default_system():
+    prompt_style = Llama3PromptStyle()
+    messages = [
+        ChatMessage(content="Hello!", role=MessageRole.USER),
+    ]
+    expected = (
+        "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n"
+        f"{prompt_style.DEFAULT_SYSTEM_PROMPT}<|eot_id|>"
+        "<|start_header_id|>user<|end_header_id|>\n\nHello!<|eot_id|>"
+        "<|start_header_id|>assistant<|end_header_id|>\n\n"
+    )
+    assert prompt_style._messages_to_prompt(messages) == expected
+
+
+def test_llama3_prompt_style_with_assistant_response():
+    prompt_style = Llama3PromptStyle()
+    messages = [
+        ChatMessage(content="You are a helpful assistant", role=MessageRole.SYSTEM),
+        ChatMessage(content="What is the capital of France?", role=MessageRole.USER),
+        ChatMessage(
+            content="The capital of France is Paris.", role=MessageRole.ASSISTANT
+        ),
+    ]
+
+    expected_prompt = (
+        "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n"
+        "You are a helpful assistant<|eot_id|>"
+        "<|start_header_id|>user<|end_header_id|>\n\n"
+        "What is the capital of France?<|eot_id|>"
+        "<|start_header_id|>assistant<|end_header_id|>\n\n"
+        "The capital of France is Paris.<|eot_id|>"
+    )
+
+    assert prompt_style.messages_to_prompt(messages) == expected_prompt