Add tool completion to batch inference (#461)

* test

* Impl

* remove logging

* lints

* fix tests

* fix

* fix

* try fix unit test

* fix

* no cover

* stop sequences

Author: yunfeng-scale

model-engine/model_engine_server/common/dtos/llms.py

@@ -429,6 +429,30 @@ class CreateBatchCompletionsModelConfig(BaseModel):
     """
 
 
+class ToolConfig(BaseModel):
+    """
+    Configuration for tool use.
+    NOTE: this config is highly experimental and signature will change significantly in future iterations.
+    """
+
+    name: str
+    """
+    Name of the tool to use for the batch inference.
+    """
+    max_iterations: Optional[int] = 10
+    """
+    Maximum number of iterations to run the tool.
+    """
+    execution_timeout_seconds: Optional[int] = 60
+    """
+    Maximum runtime of the tool in seconds.
+    """
+    should_retry_on_error: Optional[bool] = True
+    """
+    Whether to retry the tool on error.
+    """
+
+
 class CreateBatchCompletionsRequest(BaseModel):
     """
     Request object for batch completions.
@@ -456,6 +480,11 @@ class CreateBatchCompletionsRequest(BaseModel):
     """
     Maximum runtime of the batch inference in seconds. Default to one day.
     """
+    tool_config: Optional[ToolConfig] = None
+    """
+    Configuration for tool use.
+    NOTE: this config is highly experimental and signature will change significantly in future iterations.
+    """
 
 
 class CreateBatchCompletionsResponse(BaseModel):

model-engine/model_engine_server/domain/use_cases/llm_model_endpoint_use_cases.py

@@ -2275,6 +2275,11 @@ async def execute(
             hardware.gpus = max(hardware.gpus, request.model_config.num_shards)
         request.model_config.num_shards = hardware.gpus
 
+        if request.tool_config and request.tool_config.name != "code_evaluator":
+            raise ObjectHasInvalidValueException(
+                "Only code_evaluator tool is supported for batch completions."
+            )
+
         batch_bundle = await self.create_batch_job_bundle(user, request, hardware)
 
         validate_resource_requests(

model-engine/model_engine_server/inference/batch_inference/generate_tool_sample_data.py

@@ -0,0 +1,79 @@
+import json
+
+COMPLETION_PROMPT1 = """\
+FYI: you can write code like this: 
+```python
+import math
+print(math.sqrt(2))
+```
+1.41...
+>>>
+
+For reference, the third digit of 4.32 is 2. Also, use "Final Answer: X" to indicate your final answer.
+
+### Problem:
+
+What is the 4th digit of pi?
+
+### Answer:
+```python
+import math
+print(math.pi)
+```
+3.141592653589793
+>>>
+
+Final Answer: 1
+
+### Problem:
+
+What is the 4th digit of the square root of 2?
+
+### Answer: 
+"""
+
+COMPLETION_PROMPT2 = """\
+FYI: you can write code like this: 
+```python
+import math
+print(math.sqrt(2))
+```
+1.41...
+>>>
+
+For reference, the third digit of 4.32 is 2. Also, use "Final Answer: X" to indicate your final answer.
+
+### Problem:
+
+What is the 4th digit of pi?
+
+### Answer:
+```python
+import math
+print(math.pi)
+```
+3.141592653589793
+>>>
+
+Final Answer: 1
+
+### Problem:
+
+What is the 5th digit of the square root of 2?
+
+### Answer: 
+"""
+
+data = {
+    "prompts": [
+        COMPLETION_PROMPT1,
+        COMPLETION_PROMPT2,
+        "what is deep learning",
+    ],
+    "max_new_tokens": 100,
+    "temperature": 0.0,
+    "return_token_log_probs": True,
+    "stop_sequences": ["</s>", "\n### Problem:\n", ">>>\n"],
+}
+
+json.dump(data, open("sample_data_tool.json", "w"))

model-engine/model_engine_server/inference/batch_inference/requirements.txt

@@ -2,4 +2,6 @@ vllm==0.2.5
 pydantic==1.10.13
 boto3==1.34.15
 smart-open==6.4.0
-ddtrace==2.4.0
+ddtrace==2.4.0
+docker==7.0.0
+func-timeout==4.3.5

model-engine/model_engine_server/inference/batch_inference/sample_config_tool.json

@@ -0,0 +1,14 @@
+{
+    "input_data_path":"./sample_data_tool.json",
+    "output_data_path":"./sample_output_tool.json",
+    "model_config":{
+        "model":"mistral-7b",
+        "checkpoint_path":"s3://scale-ml/models/mistral-7b",
+        "num_shards": 1,
+        "labels": {"team": "my_team"}
+    },
+    "data_parallelism":2,
+    "tool_config": {
+        "name": "code_evaluator"
+    }
+}

model-engine/model_engine_server/inference/batch_inference/sample_data_tool.json

@@ -0,0 +1,15 @@
+{
+    "prompts": [
+        "FYI: you can write code like this: \n```python\nimport math\nprint(math.sqrt(2))\n```\n1.41...\n>>>\n\nFor reference, the third digit of 4.32 is 2. Also, use \"Final Answer: X\" to indicate your final answer.\n\n### Problem:\n\nWhat is the 4th digit of pi?\n\n### Answer:\n```python\nimport math\nprint(math.pi)\n```\n3.141592653589793\n>>>\n\nFinal Answer: 1\n\n### Problem:\n\nWhat is the 4th digit of the square root of 2?\n\n### Answer: \n",
+        "FYI: you can write code like this: \n```python\nimport math\nprint(math.sqrt(2))\n```\n1.41...\n>>>\n\nFor reference, the third digit of 4.32 is 2. Also, use \"Final Answer: X\" to indicate your final answer.\n\n### Problem:\n\nWhat is the 4th digit of pi?\n\n### Answer:\n```python\nimport math\nprint(math.pi)\n```\n3.141592653589793\n>>>\n\nFinal Answer: 1\n\n### Problem:\n\nWhat is the 5th digit of the square root of 2?\n\n### Answer: \n",
+        "what is deep learning"
+    ],
+    "max_new_tokens": 100,
+    "temperature": 0.0,
+    "return_token_log_probs": true,
+    "stop_sequences": [
+        "</s>",
+        "\n### Problem:\n",
+        ">>>\n"
+    ]
+}