fix: improve tool type, bump pydantic and outlines (#1650)

This PR resolves a couple 

- [X] adjusts the tool response to align with openai's tools response
type
- [X] bumps pydantic to `2.6.4` in all apps (resolves dependency issue
when running tests)
- [X] bump `outlines` version and fix import for new name

Cargo.lock

@@ -377,6 +377,12 @@ version = "1.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"
 
+[[package]]
+name = "cfg_aliases"
+version = "0.1.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "fd16c4719339c4530435d38e511904438d07cce7950afa3718a84ac36c10e89e"
+
 [[package]]
 name = "clap"
 version = "4.5.1"
@@ -545,7 +551,7 @@ version = "3.4.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b467862cc8610ca6fc9a1532d7777cee0804e678ab45410897b9396495994a0b"
 dependencies = [
- "nix",
+ "nix 0.27.1",
  "windows-sys 0.52.0",
 ]
 
@@ -1613,6 +1619,18 @@ dependencies = [
  "libc",
 ]
 
+[[package]]
+name = "nix"
+version = "0.28.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ab2156c4fce2f8df6c499cc1c763e4394b7482525bf2a9701c9d79d215f519e4"
+dependencies = [
+ "bitflags 2.4.2",
+ "cfg-if",
+ "cfg_aliases",
+ "libc",
+]
+
 [[package]]
 name = "nohash-hasher"
 version = "0.2.0"
@@ -3000,7 +3018,7 @@ dependencies = [
  "clap",
  "ctrlc",
  "float_eq",
- "nix",
+ "nix 0.28.0",
  "reqwest",
  "serde",
  "serde_json",

clients/python/pyproject.toml

@@ -12,7 +12,7 @@ repository = "https://github.com/huggingface/text-generation-inference"
 
 [tool.poetry.dependencies]
 python = "^3.7"
-pydantic = "> 1.10, < 3"
+pydantic = "> 2, < 3"
 aiohttp = "^3.8"
 huggingface-hub = ">= 0.12, < 1.0"
 

clients/python/text_generation/types.py

 from enum import Enum
-from pydantic import BaseModel, validator
+from pydantic import BaseModel, field_validator
 from typing import Optional, List, Union, Any
 
 from text_generation.errors import ValidationError
@@ -32,7 +32,7 @@ class Message(BaseModel):
     # Role of the message sender
     role: str
     # Content of the message
-    content: Optional[str]
+    content: Optional[str] = None
     # Optional name of the message sender
     name: Optional[str] = None
     # Tool calls associated with the chat completion
@@ -56,7 +56,7 @@ class ChatCompletionComplete(BaseModel):
     # Reason for completion
     finish_reason: str
     # Usage details of the chat completion
-    usage: Any
+    usage: Optional[Any] = None
 
 
 class Function(BaseModel):
@@ -73,7 +73,7 @@ class ChoiceDeltaToolCall(BaseModel):
 
 class ChoiceDelta(BaseModel):
     role: str
-    content: Optional[str]
+    content: Optional[str] = None
     tool_calls: Optional[ChoiceDeltaToolCall]
 
 
@@ -176,74 +176,74 @@ class Parameters(BaseModel):
     # grammar to use for generation
     grammar: Optional[Grammar] = None
 
-    @validator("best_of")
+    @field_validator("best_of")
     def valid_best_of(cls, field_value, values):
         if field_value is not None:
             if field_value <= 0:
                 raise ValidationError("`best_of` must be strictly positive")
-            if field_value > 1 and values["seed"] is not None:
+            if field_value > 1 and values.data["seed"] is not None:
                 raise ValidationError("`seed` must not be set when `best_of` is > 1")
             sampling = (
-                values["do_sample"]
-                | (values["temperature"] is not None)
-                | (values["top_k"] is not None)
-                | (values["top_p"] is not None)
-                | (values["typical_p"] is not None)
+                values.data["do_sample"]
+                | (values.data["temperature"] is not None)
+                | (values.data["top_k"] is not None)
+                | (values.data["top_p"] is not None)
+                | (values.data["typical_p"] is not None)
             )
             if field_value > 1 and not sampling:
                 raise ValidationError("you must use sampling when `best_of` is > 1")
 
         return field_value
 
-    @validator("repetition_penalty")
+    @field_validator("repetition_penalty")
     def valid_repetition_penalty(cls, v):
         if v is not None and v <= 0:
             raise ValidationError("`repetition_penalty` must be strictly positive")
         return v
 
-    @validator("seed")
+    @field_validator("seed")
     def valid_seed(cls, v):
         if v is not None and v < 0:
             raise ValidationError("`seed` must be positive")
         return v
 
-    @validator("temperature")
+    @field_validator("temperature")
     def valid_temp(cls, v):
         if v is not None and v <= 0:
             raise ValidationError("`temperature` must be strictly positive")
         return v
 
-    @validator("top_k")
+    @field_validator("top_k")
     def valid_top_k(cls, v):
         if v is not None and v <= 0:
             raise ValidationError("`top_k` must be strictly positive")
         return v
 
-    @validator("top_p")
+    @field_validator("top_p")
     def valid_top_p(cls, v):
         if v is not None and (v <= 0 or v >= 1.0):
             raise ValidationError("`top_p` must be > 0.0 and < 1.0")
         return v
 
-    @validator("truncate")
+    @field_validator("truncate")
     def valid_truncate(cls, v):
         if v is not None and v <= 0:
             raise ValidationError("`truncate` must be strictly positive")
         return v
 
-    @validator("typical_p")
+    @field_validator("typical_p")
     def valid_typical_p(cls, v):
         if v is not None and (v <= 0 or v >= 1.0):
             raise ValidationError("`typical_p` must be > 0.0 and < 1.0")
         return v
 
-    @validator("top_n_tokens")
+    @field_validator("top_n_tokens")
     def valid_top_n_tokens(cls, v):
         if v is not None and v <= 0:
             raise ValidationError("`top_n_tokens` must be strictly positive")
         return v
 
-    @validator("grammar")
+    @field_validator("grammar")
     def valid_grammar(cls, v):
         if v is not None:
             if v.type == GrammarType.Regex and not v.value:
@@ -261,15 +261,15 @@ class Request(BaseModel):
     # Whether to stream output tokens
     stream: bool = False
 
-    @validator("inputs")
+    @field_validator("inputs")
     def valid_input(cls, v):
         if not v:
             raise ValidationError("`inputs` cannot be empty")
         return v
 
-    @validator("stream")
+    @field_validator("stream")
     def valid_best_of_stream(cls, field_value, values):
-        parameters = values["parameters"]
+        parameters = values.data["parameters"]
         if (
             parameters is not None
             and parameters.best_of is not None

integration-tests/conftest.py

@@ -25,6 +25,7 @@ from text_generation.types import (
     Grammar,
     ChatComplete,
     ChatCompletionChunk,
+    ChatCompletionComplete,
 )
 
 DOCKER_IMAGE = os.getenv("DOCKER_IMAGE", None)
@@ -42,11 +43,16 @@ class ResponseComparator(JSONSnapshotExtension):
         exclude=None,
         matcher=None,
     ):
-        if isinstance(data, Response):
-            data = data.dict()
+        if (
+            isinstance(data, Response)
+            or isinstance(data, ChatComplete)
+            or isinstance(data, ChatCompletionChunk)
+            or isinstance(data, ChatCompletionComplete)
+        ):
+            data = data.model_dump()
 
         if isinstance(data, List):
-            data = [d.dict() for d in data]
+            data = [d.model_dump() for d in data]
 
         data = self._filter(
             data=data, depth=0, path=(), exclude=exclude, matcher=matcher

integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_no_tools.json

@@ -13,7 +13,7 @@
       "usage": null
     }
   ],
-  "created": 1708957015,
+  "created": 1710795556,
   "id": "",
   "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
   "object": "text_completion",

integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools.json

@@ -8,7 +8,8 @@
         "content": null,
         "name": null,
         "role": "assistant",
-        "tool_calls": {
+        "tool_calls": [
+          {
             "function": {
               "description": null,
               "name": "tools",
@@ -21,11 +22,12 @@
             "id": 0,
             "type": "function"
           }
+        ]
       },
       "usage": null
     }
   ],
-  "created": 1709079417,
+  "created": 1710795556,
   "id": "",
   "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
   "object": "text_completion",

integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools_auto.json

@@ -8,7 +8,8 @@
         "content": null,
         "name": null,
         "role": "assistant",
-        "tool_calls": {
+        "tool_calls": [
+          {
             "function": {
               "description": null,
               "name": "tools",
@@ -21,11 +22,12 @@
             "id": 0,
             "type": "function"
           }
+        ]
       },
       "usage": null
     }
   ],
-  "created": 1709079492,
+  "created": 1710795557,
   "id": "",
   "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
   "object": "text_completion",

integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools_choice.json

@@ -8,7 +8,8 @@
         "content": null,
         "name": null,
         "role": "assistant",
-        "tool_calls": {
+        "tool_calls": [
+          {
             "function": {
               "description": null,
               "name": "tools",
@@ -20,11 +21,12 @@
             "id": 0,
             "type": "function"
           }
+        ]
       },
       "usage": null
     }
   ],
-  "created": 1709079493,
+  "created": 1710795557,
   "id": "",
   "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
   "object": "text_completion",

integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools_stream.json

@@ -10,16 +10,16 @@
             "name": null
           },
           "id": "",
-          "index": 20,
+          "index": 0,
           "type": "function"
         }
       },
       "finish_reason": "eos_token",
-      "index": 20,
+      "index": 0,
       "logprobs": null
     }
   ],
-  "created": 1709087088,
+  "created": 1710795499,
   "id": "",
   "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
   "object": "text_completion",

integration-tests/models/test_tools_llama.py

@@ -119,7 +119,8 @@ async def test_flash_llama_grammar_tools(flash_llama_grammar_tools, response_sna
         ],
     )
     assert response.choices[0].message.content == None
-    assert response.choices[0].message.tool_calls == {
+    assert response.choices[0].message.tool_calls == [
+        {
             "function": {
                 "description": None,
                 "name": "tools",
@@ -132,6 +133,7 @@ async def test_flash_llama_grammar_tools(flash_llama_grammar_tools, response_sna
             "id": 0,
             "type": "function",
         }
+    ]
     assert response == response_snapshot
 
 
@@ -159,7 +161,8 @@ async def test_flash_llama_grammar_tools_auto(
         ],
     )
     assert response.choices[0].message.content == None
-    assert response.choices[0].message.tool_calls == {
+    assert response.choices[0].message.tool_calls == [
+        {
             "function": {
                 "description": None,
                 "name": "tools",
@@ -172,6 +175,7 @@ async def test_flash_llama_grammar_tools_auto(
             "id": 0,
             "type": "function",
         }
+    ]
     assert response == response_snapshot
 
 
@@ -199,7 +203,8 @@ async def test_flash_llama_grammar_tools_choice(
         ],
     )
     assert response.choices[0].message.content == None
-    assert response.choices[0].message.tool_calls == {
+    assert response.choices[0].message.tool_calls == [
+        {
             "id": 0,
             "type": "function",
             "function": {
@@ -208,6 +213,7 @@ async def test_flash_llama_grammar_tools_choice(
                 "parameters": {"format": "celsius", "location": "New York, NY"},
             },
         }
+    ]
     assert response == response_snapshot
 
 

integration-tests/pyproject.toml

@@ -5,6 +5,7 @@ description = "Text Generation Inference integration tests"
 authors = ["Nicolas Patry <nicolas@huggingface.co>"]
 
 [tool.poetry.dependencies]
+pydantic = "> 2, < 3"
 python = ">=3.9,<3.13"
 syrupy = "4.0.1"
 text-generation = "^0.6.0"

integration-tests/requirements.txt

 aiohttp==3.8.5 ; python_version >= "3.9" and python_version < "3.13"
 aiosignal==1.3.1 ; python_version >= "3.9" and python_version < "3.13"
+annotated-types==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
 async-timeout==4.0.3 ; python_version >= "3.9" and python_version < "3.13"
 attrs==23.1.0 ; python_version >= "3.9" and python_version < "3.13"
 certifi==2023.7.22 ; python_version >= "3.9" and python_version < "3.13"
@@ -17,14 +18,15 @@ iniconfig==2.0.0 ; python_version >= "3.9" and python_version < "3.13"
 multidict==6.0.4 ; python_version >= "3.9" and python_version < "3.13"
 packaging==23.1 ; python_version >= "3.9" and python_version < "3.13"
 pluggy==1.3.0 ; python_version >= "3.9" and python_version < "3.13"
-pydantic==1.10.12 ; python_version >= "3.9" and python_version < "3.13"
+pydantic-core==2.16.3 ; python_version >= "3.9" and python_version < "3.13"
+pydantic==2.6.4 ; python_version >= "3.9" and python_version < "3.13"
 pytest-asyncio==0.21.1 ; python_version >= "3.9" and python_version < "3.13"
 pytest==7.4.0 ; python_version >= "3.9" and python_version < "3.13"
 pywin32==306 ; python_version >= "3.9" and python_version < "3.13" and sys_platform == "win32"
 pyyaml==6.0.1 ; python_version >= "3.9" and python_version < "3.13"
 requests==2.31.0 ; python_version >= "3.9" and python_version < "3.13"
 syrupy==4.0.1 ; python_version >= "3.9" and python_version < "3.13"
-text-generation==0.6.0 ; python_version >= "3.9" and python_version < "3.13"
+text-generation==0.6.1 ; python_version >= "3.9" and python_version < "3.13"
 tomli==2.0.1 ; python_version >= "3.9" and python_version < "3.11"
 tqdm==4.66.1 ; python_version >= "3.9" and python_version < "3.13"
 typing-extensions==4.7.1 ; python_version >= "3.9" and python_version < "3.13"

router/src/lib.rs

@@ -433,7 +433,7 @@ impl ChatCompletion {
         created: u64,
         details: Details,
         return_logprobs: bool,
-        tool_calls: Option<ToolCall>,
+        tool_calls: Option<Vec<ToolCall>>,
     ) -> Self {
         Self {
             id: String::new(),
@@ -781,7 +781,7 @@ pub(crate) struct Message {
     #[schema(example = "\"David\"")]
     pub name: Option<String>,
     #[serde(default, skip_serializing_if = "Option::is_none")]
-    pub tool_calls: Option<ToolCall>,
+    pub tool_calls: Option<Vec<ToolCall>>,
 }
 
 #[derive(Clone, Debug, Deserialize, ToSchema)]

router/src/server.rs

@@ -942,7 +942,7 @@ async fn chat_completions(
                     )
                 })?;
 
-            let tool_call = Some(ToolCall {
+            let tool_calls = vec![ToolCall {
                 id: 0,
                 r#type: "function".to_string(),
                 function: FunctionDefinition {
@@ -963,8 +963,8 @@ async fn chat_completions(
                         |f| Ok(f.clone()),
                     )?,
                 },
-            });
-            (tool_call, None)
+            }];
+            (Some(tool_calls), None)
         } else {
             (None, Some(generation.generated_text))
         };

server/pyproject.toml

@@ -34,7 +34,7 @@ peft = { version = "^0.9.0", optional = true }
 torch = { version = "^2.1.1", optional = true }
 scipy = "^1.11.1"
 pillow = "^10.0.0"
-outlines= { version = "^0.0.27", optional = true }
+outlines= { version = "^0.0.36", optional = true }
 
 [tool.poetry.extras]
 torch = ["torch"]

server/text_generation_server/utils/logits_process.py

@@ -6,7 +6,7 @@ from typing import Dict, Union
 from text_generation_server.pb.generate_pb2 import GrammarType
 
 from outlines.fsm.fsm import RegexFSM
-from outlines.fsm.json_schema import build_regex_from_object
+from outlines.fsm.json_schema import build_regex_from_schema
 from functools import lru_cache
 from typing import List, Optional, DefaultDict
 import time
@@ -512,7 +512,7 @@ class GrammarLogitProcessor(LogitsProcessor):
     def _cached_compile_fsm(grammar_type, schema, tokenizer):
         start_time = time.time()
         if grammar_type == GrammarType.GRAMMAR_TYPE_JSON:
-            schema = build_regex_from_object(schema)
+            schema = build_regex_from_schema(schema)
         elif grammar_type == GrammarType.GRAMMAR_TYPE_REGEX:
             pass  # schema is already a regex just here for clarity
         fsm = RegexFSM(schema, tokenizer)