Unroll notify error into generate response (#2597)

* feat: unroll notify_error if no tool is choosen

* fix: expect simple message when no tool is selected

* fix: improve test to avoid notify_error

* fix: improve docs and indicate change in expected response

* fix: adjust linting in test file

docs/source/basic_tutorials/using_guidance.md

@@ -311,11 +311,13 @@ print(chat.choices[0].message.tool_calls)
 
 ```
 
-### OpenAI integration
+### OpenAI Integration
 
-TGI exposes an OpenAI-compatible API, which means you can use OpenAI's client libraries to interact with TGI's Messages API and Tool functions.
+Text Generation Inference (TGI) offers seamless integration with OpenAI's client libraries, allowing developers to interact with TGI's Messages API and Tool functions in a familiar way. This compatibility simplifies the implementation of advanced features, such as tools and grammar, within your applications using OpenAI’s client.
 
-However there are some minor differences in the API, for example `tool_choice="auto"` will ALWAYS choose the tool for you. This is different from OpenAI's API where `tool_choice="auto"` will choose a tool if the model thinks it's necessary.
+Previously, TGI handled tool selection differently than OpenAI’s API—`tool_choice="auto"` would always pick a tool for you. However, as of the latest version, TGI now mimics OpenAI’s behavior more closely: `tool_choice="auto"` selects a tool only when the model deems it necessary, aligning with how OpenAI's API works. This enhancement ensures a smoother and more predictable integration experience.
+
+Additionally, error notifications like `notify_error`, which previously indicated that no tool was chosen, are no longer returned. Instead, TGI will proceed with generating a response as if no tool was selected, further improving consistency with OpenAI's API.
 
 ```python
 from openai import OpenAI

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

@@ -1,38 +1,26 @@
 {
   "choices": [
     {
-      "finish_reason": "eos_token",
+      "finish_reason": "stop",
       "index": 0,
       "logprobs": null,
       "message": {
-        "content": null,
+        "content": "There is a huge storm in the ocean",
         "name": null,
         "role": "assistant",
-        "tool_calls": [
+        "tool_calls": null
-          {
-            "function": {
-              "arguments": {
-                "error": "Cannot get current weather forecast from specified location and temperature unit. Please try again with different options."
-              },
-              "description": null,
-              "name": "notify_error"
-            },
-            "id": 0,
-            "type": "function"
-          }
-        ]
       },
       "usage": null
     }
   ],
-  "created": 1712852597,
+  "created": 1727796440,
   "id": "",
-  "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+  "model": "meta-llama/Llama-3.1-8B-Instruct",
-  "object": "text_completion",
+  "object": "chat.completion",
-  "system_fingerprint": "1.4.5-native",
+  "system_fingerprint": "2.3.1-dev0-native",
   "usage": {
-    "completion_tokens": 39,
+    "completion_tokens": 25,
-    "prompt_tokens": 496,
+    "prompt_tokens": 600,
-    "total_tokens": 535
+    "total_tokens": 625
   }
 }

integration-tests/models/test_tools_llama.py

@@ -225,10 +225,6 @@ async def test_flash_llama_grammar_tools_insufficient_information(
         tools=tools,
         tool_choice="auto",
         messages=[
-            {
-                "role": "system",
-                "content": "STRICTLY ONLY RESPOND IF THE USER ASKS A WEATHER RELATED QUESTION",
-            },
             {
                 "role": "user",
                 "content": "Tell me a story about 3 sea creatures",
@@ -237,8 +233,5 @@ async def test_flash_llama_grammar_tools_insufficient_information(
         stream=False,
     )
 
-    assert responses.choices[0].message.content is None
+    assert responses.choices[0].message.content == "There is a huge storm in the ocean"
-    assert (
-        responses.choices[0].message.tool_calls[0]["function"]["name"] == "notify_error"
-    )
     assert responses == response_snapshot

router/src/server.rs

@@ -1246,17 +1246,33 @@ async fn chat_completions(
             if let Value::Object(ref mut props) = arguments {
                 props.remove("_name");
             }
-
+            match name.as_str() {
-            let tool_calls = vec![ToolCall {
+                "notify_error" => {
-                id: "0".to_string(),
+                    // parse the error message
-                r#type: "function".to_string(),
+                    let error_message = arguments
-                function: FunctionDefinition {
+                        .get("error")
-                    description: None,
+                        .and_then(Value::as_str)
-                    name,
+                        .ok_or_else(|| {
-                    arguments,
+                            InferError::ToolError(
-                },
+                                "No error message found in generated text".to_string(),
-            }];
+                            )
-            (Some(tool_calls), None)
+                        })?
+                        .to_string();
+                    (None, Some(error_message))
+                }
+                _ => {
+                    let tool_calls = vec![ToolCall {
+                        id: "0".to_string(),
+                        r#type: "function".to_string(),
+                        function: FunctionDefinition {
+                            description: None,
+                            name,
+                            arguments,
+                        },
+                    }];
+                    (Some(tool_calls), None)
+                }
+            }
         } else {
             (None, Some(generation.generated_text))
         };