Merge pull request #364 from theroyallab/tool-calls
Streamline tool calling
This commit is contained in:
Brian
GitHub
commit
2419d2d0a3
7 changed files with 155 additions and 205 deletions
|
|
@ -4,6 +4,8 @@ import traceback
|
|||
import aiofiles
|
||||
import json
|
||||
import pathlib
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import datetime
|
||||
from importlib.metadata import version as package_version
|
||||
from typing import List, Optional
|
||||
from jinja2 import Template, TemplateError
|
||||
|
|
@ -11,7 +13,6 @@ from jinja2.ext import loopcontrols
|
|||
from jinja2.sandbox import ImmutableSandboxedEnvironment
|
||||
from loguru import logger
|
||||
from packaging import version
|
||||
from datetime import datetime
|
||||
|
||||
|
||||
from common.utils import unwrap
|
||||
|
|
@ -23,11 +24,12 @@ class TemplateLoadError(Exception):
|
|||
pass
|
||||
|
||||
|
||||
@dataclass
|
||||
class TemplateMetadata:
|
||||
"""Represents the parsed metadata from a template."""
|
||||
|
||||
stop_strings: List[str] = []
|
||||
tool_starts: List[str] = []
|
||||
stop_strings: List[str] = field(default_factory=list)
|
||||
tool_start: Optional[str] = None
|
||||
|
||||
|
||||
class PromptTemplate:
|
||||
|
|
@ -72,11 +74,7 @@ class PromptTemplate:
|
|||
|
||||
if hasattr(template_module, "tool_start"):
|
||||
if isinstance(template_module.tool_start, str):
|
||||
template_metadata.tool_starts.append(template_module.tool_start)
|
||||
|
||||
if hasattr(template_module, "tool_start_token"):
|
||||
if isinstance(template_module.tool_start_token, int):
|
||||
template_metadata.tool_starts.append(template_module.tool_start_token)
|
||||
template_metadata.tool_start = template_module.tool_start
|
||||
|
||||
self.metadata = template_metadata
|
||||
return template_metadata
|
||||
|
|
|
|||
|
|
@ -32,7 +32,7 @@ For example, if you are using a Llama 3.1 Family model you can simply modify you
|
|||
```yaml
|
||||
model:
|
||||
...
|
||||
prompt_template: chatml_with_headers_tool_calling
|
||||
prompt_template: tool_calls/chatml_with_headers
|
||||
```
|
||||
|
||||
If loading via `/v1/model/load`, you would also need to specify a tool-supporting `prompt_template`.
|
||||
|
|
@ -40,7 +40,6 @@ If loading via `/v1/model/load`, you would also need to specify a tool-supportin
|
|||
## Tool Template Variables
|
||||
|
||||
- `tools`: Tools object.
|
||||
- `tools_json`: Tools object as a JSON string.
|
||||
|
||||
## Creating a Tool Calling Prompt Template
|
||||
|
||||
|
|
@ -56,29 +55,36 @@ Here's how to create a TabbyAPI tool calling prompt template:
|
|||
|
||||
```jinja
|
||||
{# Metadata #}
|
||||
{% set stop_strings = ["<|im_start|>", "<|im_end|>"] %}
|
||||
{% set message_roles = ['system', 'user', 'assistant', 'tool'] %}
|
||||
{% set tool_start = "<|tool_start|>" %}
|
||||
{% set tool_end = "<|tool_end|>" %}
|
||||
{%- set stop_strings = ["<|im_start|>", "<|im_end|>"] -%}
|
||||
{%- set tool_start = "<|tool_start|>" -%}
|
||||
|
||||
{# Optional Metadata #}
|
||||
{%- set tool_end = "<|tool_end|>" -%}
|
||||
```
|
||||
|
||||
`tool_start` and `tool_end` should be selected based on which model you decide to use. For example, [Groq's Tool calling models](https://huggingface.co/Groq/Llama-3-Groq-70B-Tool-Use) expects `<tool_call>` and `</tool_call>` while [Llama3 FireFunctionV2's](https://huggingface.co/fireworks-ai/llama-3-firefunction-v2) model expects only `functools` to start the call, without a `tool_end`
|
||||
|
||||
2. Define an `initial_system_prompt`:
|
||||
|
||||
While the name of your `inital_system_prompt` can vary, it's purpose does not. This inital prompt is typically a simple instruction set followed by accessing the `tools_json` variable. This will contain the function specification the user provided to the `tools` endpoint in their client when the chat completion request. Inside the template we can call this like so: `{{ tools_json }}`.
|
||||
While the name of your `inital_system_prompt` can vary, it's purpose does not. This initial prompt is typically a simple instruction set followed by accessing the `tools` template variable.
|
||||
|
||||
Note: Depending on the model you are using, it's possible your model may expect a special set of tokens to surround the function specifications. Feel free to surround `tools_json` with these tokens.
|
||||
This will contain the function specification the user provided to the `tools` endpoint in their client when the chat completion request. Inside the template we can call this like so: `{{ tools | tojson }}`.
|
||||
|
||||
> [!NOTE]
|
||||
> Depending on the model you are using, it's possible your model may expect a special set of tokens to surround the function specifications. Feel free to surround `tools_json` with these tokens.
|
||||
|
||||
> [!NOTE]
|
||||
> To get a JSON representation of the tools variable, use `| tojson(indent=2)` in the assignment
|
||||
|
||||
```jinja
|
||||
{% set initial_system_prompt %}
|
||||
Your instructions here...
|
||||
Available functions:
|
||||
{{ tools_json }}
|
||||
{{ tools | tojson(indent=2) }}
|
||||
{% endset %}
|
||||
```
|
||||
|
||||
You'll then want to make sure to provide this to the model in the first message it recieves. Here is a simple example:
|
||||
You'll then want to make sure to provide this to the model in the first message it receives. Here is a simple example:
|
||||
|
||||
```jinja
|
||||
{%- if loop.first -%}
|
||||
|
|
@ -88,11 +94,11 @@ Here's how to create a TabbyAPI tool calling prompt template:
|
|||
{{ content }}{{ eos_token }}
|
||||
```
|
||||
|
||||
3. Handle messages with the `tool` role:
|
||||
4. Handle messages with the `tool` role:
|
||||
|
||||
After a tool call is made, a *well behaved* client will respond to the model with a new message containing the role `tool`. This is a response to a tool call containing the results of it's execution.
|
||||
|
||||
The simplest implementation of this will be to ensure your `message_roles` list within your prompt template contains `tool`. Further customization may be required for models that expect specific tokens surrounding tool reponses. An example of this customization is the Groq family of models from above. They expect special tokens surrounding their tool responses such as:
|
||||
The simplest implementation of this will be to ensure your `message_roles` list within your prompt template contains `tool`. Further customization may be required for models that expect specific tokens surrounding tool responses. An example of this customization is the Groq family of models from above. They expect special tokens surrounding their tool responses such as:
|
||||
|
||||
```jinja
|
||||
{% if role == 'tool' %}
|
||||
|
|
@ -100,51 +106,29 @@ Here's how to create a TabbyAPI tool calling prompt template:
|
|||
{% endif %}
|
||||
```
|
||||
|
||||
4. Preserve tool calls from prior messages:
|
||||
5. Preserve tool calls from prior messages:
|
||||
|
||||
When creating a tool calling `prompt_template`, ensure you handle previous tool calls from the model gracefully. Each `message` object within `messages` exposed within the `prompt_template` could also contain `tool_calls_json`. This field will contain tool calls made by the assistant in previous turns, and must be handled appropriatly so that the model understands what previous actions it has taken (and can properly identify what tool response ID belongs to which call).
|
||||
When creating a tool calling `prompt_template`, ensure you handle previous tool calls from the model gracefully. Each `message` object within `messages` exposed within the `prompt_template` could also contain `tool_calls`.
|
||||
|
||||
This will require using the `tool_start` (and possibly `tool_end`) from above to wrap the `tool_call_json` like so:
|
||||
This field will contain tool calls made by the assistant in previous turns, and must be handled appropriately so that the model understands what previous actions it has taken (and can properly identify what tool response ID belongs to which call).
|
||||
|
||||
This will require using the `tool_start` (and possibly `tool_end`) from above to wrap the `tool_call` object like so:
|
||||
|
||||
```jinja
|
||||
{% if 'tool_calls_json' in message and message['tool_calls_json'] %}
|
||||
{{ tool_start }}{{ message['tool_calls_json'] }}{{ tool_end }}
|
||||
{% if 'tool_calls' in message and message['tool_calls'] %}
|
||||
{{ tool_start }}{{ message['tool_calls'] | tojson(indent=2) }}{{ tool_end }}
|
||||
{% endif %}
|
||||
```
|
||||
|
||||
5. Handle tool call generation:
|
||||
6. Add the generation prompt check at the end:
|
||||
```jinja
|
||||
{% set tool_reminder %}
|
||||
Available Tools:
|
||||
{{ tools_json }}
|
||||
|
||||
Tool Call Format Example:
|
||||
{{ tool_start }}{{ example_tool_call }}
|
||||
|
||||
Prefix & Suffix: Begin tool calls with {{ tool_start }} and end with {{ tool_end }}.
|
||||
Argument Types: Use correct data types for arguments (e.g., strings in quotes, numbers without).
|
||||
{% endset %}
|
||||
|
||||
{% if tool_precursor %}
|
||||
{{ start_header }}system{{ end_header }}
|
||||
{{ tool_reminder }}{{ eos_token }}
|
||||
{{ start_header }}assistant{{ end_header }}
|
||||
{{ tool_precursor }}{{ tool_start }}
|
||||
{% else %}
|
||||
{% if add_generation_prompt %}
|
||||
{{ start_header }}assistant{{ end_header }}
|
||||
{% endif %}
|
||||
```
|
||||
|
||||
This clever bit of temporal manipulation allows us to slip in a reminder as a system message right before the model generates a tool call, but after it writes the `tool_start` token. This is possible due to TabbyAPI revisitng the `prompt_template` after a `tool_start` token is detected. Here's how it works:
|
||||
|
||||
- We detect `tool_precursor`, which signals the model is about to generate a tool call.
|
||||
- We then inject a system message with our `tool_reminder`.
|
||||
- Finally, we initialize an assistant message using `tool_precursor` as the content.
|
||||
|
||||
This creates the illusion that the model just happened to remember the available tools and proper formatting right before generating the tool call. It's like giving the model a little nudge at exactly the right moment, enhancing its performance without altering what the user sees.
|
||||
|
||||
When creating your own tool calling `prompt_template`, it's best to reference the default `chatml_with_headers_tool_calling.jinja` template as a starting point.
|
||||
|
||||
> [!NOTE]
|
||||
> When creating your own tool calling template, it's best to reference the default `chatml_with_headers` template as a starting point.
|
||||
## Support and Bug Reporting
|
||||
|
||||
For bugs, please create a detailed issue with the model, prompt template, and conversation that caused it. Alternatively, join our [Discord](https://discord.gg/sYQxnuD7Fj) and ask for Storm.
|
||||
|
|
|
|||
|
|
@ -1,11 +1,10 @@
|
|||
from pydantic import AliasChoices, BaseModel, Field, field_validator
|
||||
from pydantic.json_schema import SkipJsonSchema
|
||||
from time import time
|
||||
from typing import Literal, Union, List, Optional, Dict
|
||||
from uuid import uuid4
|
||||
|
||||
from endpoints.OAI.types.common import UsageStats, CommonCompletionRequest
|
||||
from endpoints.OAI.types.tools import ToolSpec, ToolCall, tool_call_schema
|
||||
from endpoints.OAI.types.tools import ToolSpec, ToolCall
|
||||
|
||||
|
||||
class ChatCompletionLogprob(BaseModel):
|
||||
|
|
@ -32,7 +31,7 @@ class ChatCompletionMessage(BaseModel):
|
|||
role: str = "user"
|
||||
content: Optional[Union[str, List[ChatCompletionMessagePart]]] = None
|
||||
tool_calls: Optional[List[ToolCall]] = None
|
||||
tool_calls_json: SkipJsonSchema[Optional[str]] = None
|
||||
tool_call_id: Optional[str] = None
|
||||
|
||||
|
||||
class ChatCompletionRespChoice(BaseModel):
|
||||
|
|
@ -56,7 +55,7 @@ class ChatCompletionStreamChoice(BaseModel):
|
|||
|
||||
# Inherited from common request
|
||||
class ChatCompletionRequest(CommonCompletionRequest):
|
||||
messages: List[ChatCompletionMessage] = Field(default_factory=list)
|
||||
messages: List[ChatCompletionMessage]
|
||||
prompt_template: Optional[str] = None
|
||||
add_generation_prompt: Optional[bool] = True
|
||||
template_vars: Optional[dict] = Field(
|
||||
|
|
@ -73,15 +72,6 @@ class ChatCompletionRequest(CommonCompletionRequest):
|
|||
tools: Optional[List[ToolSpec]] = None
|
||||
functions: Optional[List[Dict]] = None
|
||||
|
||||
# Typically collected from Chat Template.
|
||||
# Don't include this in the OpenAPI docs
|
||||
# TODO: Use these custom parameters
|
||||
tool_call_start: SkipJsonSchema[Optional[List[Union[str, int]]]] = Field(
|
||||
default_factory=list
|
||||
)
|
||||
tool_call_end: SkipJsonSchema[Optional[str]] = None
|
||||
tool_call_schema: SkipJsonSchema[Optional[dict]] = tool_call_schema
|
||||
|
||||
# Chat completions requests do not have a BOS token preference. Backend
|
||||
# respects the tokenization config for the individual model.
|
||||
add_bos_token: Optional[bool] = None
|
||||
|
|
|
|||
|
|
@ -1,29 +1,6 @@
|
|||
from pydantic import BaseModel
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Dict, Literal
|
||||
|
||||
tool_call_schema = {
|
||||
"$schema": "http://json-schema.org/draft-07/schema#",
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {"type": "string"},
|
||||
"function": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string"},
|
||||
"arguments": {
|
||||
# Converted to OAI's string in post process
|
||||
"type": "object"
|
||||
},
|
||||
},
|
||||
"required": ["name", "arguments"],
|
||||
},
|
||||
"type": {"type": "string", "enum": ["function"]},
|
||||
},
|
||||
"required": ["id", "function", "type"],
|
||||
},
|
||||
}
|
||||
from uuid import uuid4
|
||||
|
||||
|
||||
class Function(BaseModel):
|
||||
|
|
@ -53,6 +30,6 @@ class Tool(BaseModel):
|
|||
class ToolCall(BaseModel):
|
||||
"""Represents an OAI tool description."""
|
||||
|
||||
id: str
|
||||
id: str = Field(default_factory=lambda: str(uuid4()).replace("-", "")[:9])
|
||||
function: Tool
|
||||
type: Literal["function"]
|
||||
type: Literal["function"] = "function"
|
||||
|
|
|
|||
|
|
@ -1,7 +1,6 @@
|
|||
"""Chat completion utilities for OAI server."""
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import pathlib
|
||||
from asyncio import CancelledError
|
||||
from typing import List, Optional
|
||||
|
|
@ -30,7 +29,7 @@ from endpoints.OAI.types.chat_completion import (
|
|||
)
|
||||
from endpoints.OAI.types.common import UsageStats
|
||||
from endpoints.OAI.utils.completion import _parse_gen_request_id, _stream_collector
|
||||
from endpoints.OAI.utils.tools import ToolCallProcessor
|
||||
from endpoints.OAI.utils.tools import ToolCallProcessor, TOOL_CALL_SCHEMA
|
||||
|
||||
|
||||
def _create_response(
|
||||
|
|
@ -71,12 +70,11 @@ def _create_response(
|
|||
|
||||
logprob_response = ChatCompletionLogprobs(content=collected_token_probs)
|
||||
|
||||
# Initialize finish_reason with a default value or from generation data
|
||||
finish_reason = generation.get("finish_reason", "stop")
|
||||
|
||||
# If a tool call is present, mark the finish reason as such
|
||||
# Set finish reason
|
||||
if message.tool_calls:
|
||||
finish_reason = "tool_calls"
|
||||
else:
|
||||
finish_reason = generation.get("finish_reason", "stop")
|
||||
|
||||
choice = ChatCompletionRespChoice(
|
||||
index=index,
|
||||
|
|
@ -153,7 +151,6 @@ def _create_stream_chunk(
|
|||
choice.finish_reason = "tool_calls"
|
||||
|
||||
choices.append(choice)
|
||||
|
||||
else:
|
||||
message = ChatCompletionMessage(
|
||||
role="assistant", content=unwrap(generation.get("text"), "")
|
||||
|
|
@ -207,15 +204,11 @@ async def _append_template_metadata(data: ChatCompletionRequest, template_vars:
|
|||
if isinstance(data.stop, str):
|
||||
data.stop = [data.stop] + template_metadata.stop_strings
|
||||
else:
|
||||
data.stop += template_metadata.stop_strings
|
||||
data.stop.extend(template_metadata.stop_strings)
|
||||
|
||||
# Tool call start strings
|
||||
if template_metadata.tool_starts:
|
||||
if data.tool_call_start is None:
|
||||
data.tool_call_start = template_metadata.tool_starts
|
||||
|
||||
# Append to stop strings to halt for a tool call generation
|
||||
data.stop.extend(template_metadata.tool_starts)
|
||||
# if a tool start is present, append it to stopping strings
|
||||
if template_metadata.tool_start:
|
||||
data.stop.append(template_metadata.tool_start)
|
||||
|
||||
|
||||
async def format_messages_with_template(
|
||||
|
|
@ -242,13 +235,6 @@ async def format_messages_with_template(
|
|||
# Convert the message content into a concatenated string
|
||||
message.content = concatenated_content
|
||||
|
||||
if message.tool_calls:
|
||||
message.tool_calls_json = ToolCallProcessor.to_json(message.tool_calls)
|
||||
|
||||
# The tools variable is inspectable in the template, so
|
||||
# store the list of dicts rather than the ToolCallProcessor object.
|
||||
message.tool_calls = ToolCallProcessor.dump(message.tool_calls)
|
||||
|
||||
message_dicts.append(message.model_dump(exclude_none=True))
|
||||
|
||||
# Get all special tokens
|
||||
|
|
@ -260,9 +246,7 @@ async def format_messages_with_template(
|
|||
return prompt, mm_embeddings, template_vars
|
||||
|
||||
|
||||
async def apply_chat_template(
|
||||
data: ChatCompletionRequest, tool_precursor: Optional[str] = None
|
||||
):
|
||||
async def apply_chat_template(data: ChatCompletionRequest):
|
||||
"""
|
||||
Compile the prompt and get any additional stop strings from the template.
|
||||
Template stop strings can be overriden by sampler overrides if force is true.
|
||||
|
|
@ -276,10 +260,7 @@ async def apply_chat_template(
|
|||
{
|
||||
"add_generation_prompt": data.add_generation_prompt,
|
||||
"tools": tools,
|
||||
"tools_json": json.dumps(tools, indent=2),
|
||||
"functions": data.functions,
|
||||
"functions_json": json.dumps(data.functions, indent=2),
|
||||
"tool_precursor": tool_precursor,
|
||||
}
|
||||
)
|
||||
|
||||
|
|
@ -337,6 +318,7 @@ async def stream_generate_chat_completion(
|
|||
abort_event = asyncio.Event()
|
||||
gen_queue = asyncio.Queue()
|
||||
gen_tasks: List[asyncio.Task] = []
|
||||
tool_start = model.container.prompt_template.metadata.tool_start
|
||||
disconnect_task = asyncio.create_task(request_disconnect_loop(request))
|
||||
|
||||
try:
|
||||
|
|
@ -360,7 +342,7 @@ async def stream_generate_chat_completion(
|
|||
|
||||
gen_tasks.append(gen_task)
|
||||
|
||||
# We need to keep track of the text generated so we can resume the tool calls
|
||||
# Text accumulation for tool calls
|
||||
current_generation_text = ""
|
||||
|
||||
# Consumer loop
|
||||
|
|
@ -372,19 +354,23 @@ async def stream_generate_chat_completion(
|
|||
)
|
||||
|
||||
generation = await gen_queue.get()
|
||||
# lets only append the text if we need it for tool calls later
|
||||
if data.tool_call_start and "text" in generation:
|
||||
current_generation_text += generation["text"]
|
||||
|
||||
# check if we are running a tool model, and that we are at stop
|
||||
if data.tool_call_start and "stop_str" in generation:
|
||||
generations = await generate_tool_calls(
|
||||
data,
|
||||
[generation],
|
||||
request,
|
||||
current_generations=current_generation_text,
|
||||
)
|
||||
generation = generations[0] # We only have one generation in this case
|
||||
# Handle options if a tool model is present
|
||||
if tool_start:
|
||||
if "stop_str" in generation:
|
||||
generations = await generate_tool_calls(
|
||||
prompt,
|
||||
embeddings,
|
||||
data,
|
||||
[generation],
|
||||
request,
|
||||
current_generation_text=current_generation_text,
|
||||
)
|
||||
|
||||
# Only one generation present in this case
|
||||
generation = generations[0]
|
||||
elif "text" in generation:
|
||||
current_generation_text += generation["text"]
|
||||
|
||||
# Stream collector will push an exception to the queue if it fails
|
||||
if isinstance(generation, Exception):
|
||||
|
|
@ -433,6 +419,7 @@ async def generate_chat_completion(
|
|||
model_path: pathlib.Path,
|
||||
):
|
||||
gen_tasks: List[asyncio.Task] = []
|
||||
tool_start = model.container.prompt_template.metadata.tool_start
|
||||
|
||||
try:
|
||||
logger.info(f"Received chat completion request {request.state.id}")
|
||||
|
|
@ -453,9 +440,11 @@ async def generate_chat_completion(
|
|||
|
||||
generations = await asyncio.gather(*gen_tasks)
|
||||
|
||||
# Let's not waste our time if we arn't running a tool model
|
||||
if data.tool_call_start:
|
||||
generations = await generate_tool_calls(data, generations, request)
|
||||
# Check all the generations and see if a tool call is required
|
||||
if tool_start:
|
||||
generations = await generate_tool_calls(
|
||||
prompt, embeddings, data, generations, request
|
||||
)
|
||||
|
||||
response = _create_response(request.state.id, generations, model_path.name)
|
||||
|
||||
|
|
@ -474,54 +463,55 @@ async def generate_chat_completion(
|
|||
|
||||
|
||||
async def generate_tool_calls(
|
||||
prompt: str,
|
||||
embeddings: MultimodalEmbeddingWrapper,
|
||||
data: ChatCompletionRequest,
|
||||
generations: List[str],
|
||||
request: Request,
|
||||
current_generations: str = None,
|
||||
current_generation_text: str = None,
|
||||
):
|
||||
gen_tasks: List[asyncio.Task] = []
|
||||
tool_start = model.container.prompt_template.metadata.tool_start
|
||||
|
||||
# Tracks which generations asked for a tool call
|
||||
tool_idx: List[int] = []
|
||||
|
||||
# Copy to make sure the parent JSON schema doesn't get modified
|
||||
# FIXME: May not be necessary depending on how the codebase evolves
|
||||
tool_data = data.model_copy(deep=True)
|
||||
tool_data.json_schema = tool_data.tool_call_schema
|
||||
tool_data.json_schema = TOOL_CALL_SCHEMA
|
||||
|
||||
for idx, gen in enumerate(generations):
|
||||
if gen["stop_str"] in tool_data.tool_call_start:
|
||||
logger.info(
|
||||
f"Detected tool call in chat completion request {request.state.id}"
|
||||
)
|
||||
if gen["stop_str"] != tool_start:
|
||||
continue
|
||||
|
||||
if "text" in gen:
|
||||
# non streaming, all generations will have the text they generated
|
||||
pre_tool_prompt, embeddings = await apply_chat_template(
|
||||
data, gen["text"]
|
||||
)
|
||||
elif current_generations is not None:
|
||||
# streaming, we wont have text in the generation,
|
||||
# we'll have to use the current_generations
|
||||
pre_tool_prompt, embeddings = await apply_chat_template(
|
||||
data, current_generations
|
||||
)
|
||||
logger.info(f"Detected tool call in chat completion request {request.state.id}")
|
||||
|
||||
request_id = _parse_gen_request_id(data.n, request.state.id, idx)
|
||||
# Append the existing generation text if present
|
||||
precursor_text = current_generation_text or gen.get("text")
|
||||
if precursor_text:
|
||||
prompt = prompt + precursor_text
|
||||
|
||||
gen_tasks.append(
|
||||
asyncio.create_task(
|
||||
model.container.generate(
|
||||
request_id,
|
||||
pre_tool_prompt,
|
||||
tool_data,
|
||||
mm_embeddings=embeddings,
|
||||
)
|
||||
gen_request_id = _parse_gen_request_id(data.n, request.state.id, idx)
|
||||
tool_request_id = f"{gen_request_id}-tool"
|
||||
|
||||
gen_tasks.append(
|
||||
asyncio.create_task(
|
||||
model.container.generate(
|
||||
tool_request_id,
|
||||
prompt,
|
||||
tool_data,
|
||||
mm_embeddings=embeddings,
|
||||
)
|
||||
)
|
||||
tool_idx.append(idx)
|
||||
)
|
||||
|
||||
tool_calls = await asyncio.gather(*gen_tasks)
|
||||
for outer_idx in range(0, len(tool_idx)):
|
||||
gen_idx = tool_idx[outer_idx]
|
||||
generations[gen_idx]["tool_calls"] = tool_calls[outer_idx]["text"]
|
||||
tool_idx.append(idx)
|
||||
|
||||
if len(tool_idx) > 0:
|
||||
tool_calls = await asyncio.gather(*gen_tasks)
|
||||
|
||||
# Map tool calls to their appropriate generation
|
||||
for gen_idx, tool_call in zip(tool_idx, tool_calls, strict=True):
|
||||
generations[gen_idx]["tool_calls"] = tool_call["text"]
|
||||
|
||||
return generations
|
||||
|
|
|
|||
|
|
@ -5,6 +5,29 @@ from typing import List
|
|||
from endpoints.OAI.types.tools import ToolCall
|
||||
|
||||
|
||||
TOOL_CALL_SCHEMA = {
|
||||
"$schema": "http://json-schema.org/draft-07/schema#",
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"function": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"name": {"type": "string"},
|
||||
"arguments": {
|
||||
# Converted to OAI's string in post process
|
||||
"type": "object"
|
||||
},
|
||||
},
|
||||
"required": ["name", "arguments"],
|
||||
},
|
||||
},
|
||||
"required": ["function"],
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
class ToolCallProcessor:
|
||||
@staticmethod
|
||||
def from_json(tool_calls_str: str) -> List[ToolCall]:
|
||||
|
|
|
|||
|
|
@ -1,12 +1,14 @@
|
|||
{# Metadata #}
|
||||
{%- set stop_strings = ["<|im_start|>", "<|im_end|>"] -%}
|
||||
{%- set message_roles = ['system', 'user', 'assistant', 'tool'] -%}
|
||||
{%- set tool_start = "<|tool_start|>" -%}
|
||||
|
||||
{# Variables #}
|
||||
{%- set message_roles = ['system', 'user', 'assistant', 'tool'] -%}
|
||||
{%- set tool_end = "<|tool_end|>" -%}
|
||||
{%- set start_header = "<|start_header_id|>" -%}
|
||||
{%- set end_header = "<|end_header_id|>\n" -%}
|
||||
|
||||
{%- set example_tool_call = '[
|
||||
{%- set example_tool_call -%}[
|
||||
{
|
||||
"id": "tool_id_1342",
|
||||
"function": {
|
||||
|
|
@ -23,28 +25,19 @@
|
|||
},
|
||||
"type": "function"
|
||||
}
|
||||
]' -%}
|
||||
]
|
||||
{%- endset -%}
|
||||
|
||||
{%- set inital_system_prompt = 'You are an assistant that has access to the following set of tools, to call a tool:
|
||||
1. Prefix calls with ' + tool_start + ' and end calls with ' + tool_end + '
|
||||
{%- set inital_system_prompt -%}You are an assistant that has access to the following set of tools, to call a tool:
|
||||
1. Prefix calls with '{{ tool_start }}' and end calls with '{{ tool_end }}'
|
||||
2. Ensure you use the correct type for arguments. For example, if the argument is a string, ensure it is enclosed in quotes, otherwise, it should not be.
|
||||
3. Generate all calls using the following json tool call format. Here is a multi tool call example:
|
||||
|
||||
' + tool_start + example_tool_call + tool_end + '
|
||||
{{ tool_start }}{{ example_tool_call }}{{ tool_end }}
|
||||
|
||||
Here are the tools available for you to call:
|
||||
' + tools_json -%}
|
||||
|
||||
{%- set tool_reminder = 'Available Tools:
|
||||
' + tools_json + '
|
||||
|
||||
Tool Call Format Example:
|
||||
' + tool_start + example_tool_call + '
|
||||
|
||||
Prefix & Suffix: Begin tool calls with ' + tool_start + ' and end with ' + tool_end + '.
|
||||
Argument Types: Use correct data types for arguments (e.g., strings in quotes, numbers without).' -%}
|
||||
|
||||
{# Template #}
|
||||
{{ tools | tojson(indent=2) }}
|
||||
{%- endset -%}
|
||||
|
||||
{%- for message in messages -%}
|
||||
{%- set role = message['role'] | lower -%}
|
||||
|
|
@ -54,28 +47,23 @@ Argument Types: Use correct data types for arguments (e.g., strings in quotes, n
|
|||
|
||||
{%- set content = message['content'] if message['content'] is defined else '' | trim -%}
|
||||
{%- if loop.first -%}
|
||||
{{ bos_token }}{{ start_header }}{{ role }}{{ end_header }}
|
||||
{{ inital_system_prompt }}
|
||||
{{- bos_token }}{{ start_header }}{{ role }}{{ end_header }}
|
||||
{{- inital_system_prompt + "\n\n" }}
|
||||
|
||||
{{ content }}{{ eos_token }}
|
||||
{{- content }}{{ eos_token }}
|
||||
{%- endif -%}
|
||||
|
||||
{%- if not loop.first -%}
|
||||
{{ start_header }}{{ role }}{{ end_header }}
|
||||
{{ content }}
|
||||
{%- if 'tool_calls_json' in message and message['tool_calls_json'] -%}
|
||||
{{ tool_start }}{{ message['tool_calls_json']}}{{ tool_end }}
|
||||
{{- start_header }}{{ role }}{{ end_header }}
|
||||
{{- content }}
|
||||
{%- if 'tool_calls' in message and message['tool_calls'] -%}
|
||||
{{- tool_start }}{{ message['tool_calls'] | tojson(indent=2) }}{{ tool_end }}
|
||||
{%- endif -%}
|
||||
{{ eos_token }}
|
||||
{{- eos_token }}
|
||||
|
||||
{%- endif -%}
|
||||
{%- endfor -%}
|
||||
|
||||
{%- if tool_precursor -%}
|
||||
{{ start_header }}system{{ end_header }}
|
||||
{{ tool_reminder }}{{ eos_token }}
|
||||
{{ start_header }}assistant{{ end_header }}
|
||||
{{ tool_precursor }}{{ tool_start }}
|
||||
{%- else -%}
|
||||
{{ start_header }}assistant{{ end_header }}
|
||||
{%- endif -%}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- start_header }}assistant{{ end_header }}
|
||||
{%- endif %}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue