feat- add retrieve_batch()

litellm/batches/main.py

@@ -216,8 +216,91 @@ def create_batch(
         raise e
 
 
-def retrieve_batch():
-    pass
+def retrieve_batch(
+    batch_id: str,
+    custom_llm_provider: Literal["openai"] = "openai",
+    metadata: Optional[Dict[str, str]] = None,
+    extra_headers: Optional[Dict[str, str]] = None,
+    extra_body: Optional[Dict[str, str]] = None,
+    **kwargs,
+):
+    """
+    Retrieves a batch.
+
+    LiteLLM Equivalent of GET https://api.openai.com/v1/batches/{batch_id}
+    """
+    try:
+        optional_params = GenericLiteLLMParams(**kwargs)
+        if custom_llm_provider == "openai":
+
+            # for deepinfra/perplexity/anyscale/groq we check in get_llm_provider and pass in the api base from there
+            api_base = (
+                optional_params.api_base
+                or litellm.api_base
+                or os.getenv("OPENAI_API_BASE")
+                or "https://api.openai.com/v1"
+            )
+            organization = (
+                optional_params.organization
+                or litellm.organization
+                or os.getenv("OPENAI_ORGANIZATION", None)
+                or None  # default - https://github.com/openai/openai-python/blob/284c1799070c723c6a553337134148a7ab088dd8/openai/util.py#L105
+            )
+            # set API KEY
+            api_key = (
+                optional_params.api_key
+                or litellm.api_key  # for deepinfra/perplexity/anyscale we check in get_llm_provider and pass in the api key from there
+                or litellm.openai_key
+                or os.getenv("OPENAI_API_KEY")
+            )
+            ### TIMEOUT LOGIC ###
+            timeout = (
+                optional_params.timeout or kwargs.get("request_timeout", 600) or 600
+            )
+            # set timeout for 10 minutes by default
+
+            if (
+                timeout is not None
+                and isinstance(timeout, httpx.Timeout)
+                and supports_httpx_timeout(custom_llm_provider) == False
+            ):
+                read_timeout = timeout.read or 600
+                timeout = read_timeout  # default 10 min timeout
+            elif timeout is not None and not isinstance(timeout, httpx.Timeout):
+                timeout = float(timeout)  # type: ignore
+            elif timeout is None:
+                timeout = 600.0
+
+            _retrieve_batch_request = RetrieveBatchRequest(
+                batch_id=batch_id,
+                extra_headers=extra_headers,
+                extra_body=extra_body,
+            )
+
+            response = openai_batches_instance.retrieve_batch(
+                retrieve_batch_data=_retrieve_batch_request,
+                api_base=api_base,
+                api_key=api_key,
+                organization=organization,
+                timeout=timeout,
+                max_retries=optional_params.max_retries,
+            )
+        else:
+            raise litellm.exceptions.BadRequestError(
+                message="LiteLLM doesn't support {} for 'create_batch'. Only 'openai' is supported.".format(
+                    custom_llm_provider
+                ),
+                model="n/a",
+                llm_provider=custom_llm_provider,
+                response=httpx.Response(
+                    status_code=400,
+                    content="Unsupported provider",
+                    request=httpx.Request(method="create_thread", url="https://github.com/BerriAI/litellm"),  # type: ignore
+                ),
+            )
+        return response
+    except Exception as e:
+        raise e
 
 
 def cancel_batch():

litellm/tests/test_openai_batches.py

@@ -14,6 +14,7 @@ from litellm import (
     create_batch,
     create_file,
 )
+import time
 
 
 def test_create_batch():
@@ -34,7 +35,7 @@ def test_create_batch():
         batch_input_file_id is not None
     ), "Failed to create file, expected a non null file_id but got {batch_input_file_id}"
 
-    response = litellm.create_batch(
+    create_batch_response = litellm.create_batch(
         completion_window="24h",
         endpoint="/v1/chat/completions",
         input_file_id=batch_input_file_id,
@@ -42,17 +43,28 @@ def test_create_batch():
         metadata={"key1": "value1", "key2": "value2"},
     )
 
-    print("response from litellm.create_batch=", response)
+    print("response from litellm.create_batch=", create_batch_response)
 
     assert (
-        response.id is not None
-    ), f"Failed to create batch, expected a non null batch_id but got {response.id}"
+        create_batch_response.id is not None
+    ), f"Failed to create batch, expected a non null batch_id but got {create_batch_response.id}"
     assert (
-        response.endpoint == "/v1/chat/completions"
-    ), f"Failed to create batch, expected endpoint to be /v1/chat/completions but got {response.endpoint}"
+        create_batch_response.endpoint == "/v1/chat/completions"
+    ), f"Failed to create batch, expected endpoint to be /v1/chat/completions but got {create_batch_response.endpoint}"
     assert (
-        response.input_file_id == batch_input_file_id
-    ), f"Failed to create batch, expected input_file_id to be {batch_input_file_id} but got {response.input_file_id}"
+        create_batch_response.input_file_id == batch_input_file_id
+    ), f"Failed to create batch, expected input_file_id to be {batch_input_file_id} but got {create_batch_response.input_file_id}"
+
+    time.sleep(30)
+
+    retrieved_batch = litellm.retrieve_batch(
+        batch_id=create_batch_response.id, custom_llm_provider="openai"
+    )
+    print("retrieved batch=", retrieved_batch)
+    # just assert that we retrieved a non None batch
+
+    assert retrieved_batch.id == create_batch_response.id
+
     pass