chore(llmobs): extract bedrock LLMObs tests to separate file (#9408)

This PR moves LLMObs tests from the test_bedrock.py file into
test_bedrock_llmobs.py to ease maintainability for LLMObs tests in the
future. No functionality is added/removed.

## Checklist

- [x] Change(s) are motivated and described in the PR description
- [x] Testing strategy is described if automated tests are not included
in the PR
- [x] Risks are described (performance impact, potential for breakage,
maintainability)
- [x] Change is maintainable (easy to change, telemetry, documentation)
- [x] [Library release note
guidelines](https://ddtrace.readthedocs.io/en/stable/releasenotes.html)
are followed or label `changelog/no-changelog` is set
- [x] Documentation is included (in-code, generated user docs, [public
corp docs](https://github.com/DataDog/documentation/))
- [x] Backport labels are set (if
[applicable](https://ddtrace.readthedocs.io/en/latest/contributing.html#backporting))
- [x] If this PR changes the public interface, I've notified
`@DataDog/apm-tees`.

## Reviewer Checklist

- [x] Title is accurate
- [x] All changes are related to the pull request's stated goal
- [x] Description motivates each change
- [x] Avoids breaking
[API](https://ddtrace.readthedocs.io/en/stable/versioning.html#interfaces)
changes
- [x] Testing strategy adequately addresses listed risks
- [x] Change is maintainable (easy to change, telemetry, documentation)
- [x] Release note makes sense to a user of the library
- [x] Author has acknowledged and discussed the performance implications
of this PR as reported in the benchmarks PR comment
- [x] Backport labels are set in a manner that is consistent with the
[release branch maintenance
policy](https://ddtrace.readthedocs.io/en/latest/contributing.html#backporting)

tests/contrib/botocore/bedrock_utils.py

@@ -0,0 +1,88 @@
+import os
+
+
+try:
+    import vcr
+except ImportError:
+    vcr = None
+    get_request_vcr = None
+
+
+_MODELS = {
+    "ai21": "ai21.j2-mid-v1",
+    "amazon": "amazon.titan-tg1-large",
+    "anthropic": "anthropic.claude-instant-v1",
+    "anthropic_message": "anthropic.claude-3-sonnet-20240229-v1:0",
+    "cohere": "cohere.command-light-text-v14",
+    "meta": "meta.llama2-13b-chat-v1",
+}
+
+_REQUEST_BODIES = {
+    "ai21": {
+        "prompt": "Explain like I'm a five-year old: what is a neural network?",
+        "temperature": 0.9,
+        "topP": 1.0,
+        "maxTokens": 10,
+        "stopSequences": [],
+    },
+    "amazon": {
+        "inputText": "Command: can you explain what Datadog is to someone not in the tech industry?",
+        "textGenerationConfig": {"maxTokenCount": 50, "stopSequences": [], "temperature": 0, "topP": 0.9},
+    },
+    "anthropic": {
+        "prompt": "\n\nHuman: %s\n\nAssistant: What makes you better than Chat-GPT or LLAMA?",
+        "temperature": 0.9,
+        "top_p": 1,
+        "top_k": 250,
+        "max_tokens_to_sample": 50,
+        "stop_sequences": ["\n\nHuman:"],
+    },
+    "anthropic_message": {
+        "messages": [
+            {
+                "role": "user",
+                "content": [{"type": "text", "text": "summarize the plot to the lord of the rings in a dozen words"}],
+            }
+        ],
+        "anthropic_version": "bedrock-2023-05-31",
+        "max_tokens": 50,
+        "temperature": 0,
+    },
+    "cohere": {
+        "prompt": "\n\nHuman: %s\n\nAssistant: Can you explain what a LLM chain is?",
+        "temperature": 0.9,
+        "p": 1.0,
+        "k": 0,
+        "max_tokens": 10,
+        "stop_sequences": [],
+        "stream": False,
+        "num_generations": 1,
+    },
+    "meta": {
+        "prompt": "What does 'lorem ipsum' mean?",
+        "temperature": 0.9,
+        "top_p": 1.0,
+        "max_gen_len": 60,
+    },
+}
+
+
+# VCR is used to capture and store network requests made to OpenAI and other APIs.
+# This is done to avoid making real calls to the API which could introduce
+# flakiness and cost.
+# To (re)-generate the cassettes: pass a real API key with
+# {PROVIDER}_API_KEY, delete the old cassettes and re-run the tests.
+# NOTE: be sure to check that the generated cassettes don't contain your
+#       API key. Keys should be redacted by the filter_headers option below.
+# NOTE: that different cassettes have to be used between sync and async
+#       due to this issue: https://github.com/kevin1024/vcrpy/issues/463
+#       between cassettes generated for requests and aiohttp.
+def get_request_vcr():
+    return vcr.VCR(
+        cassette_library_dir=os.path.join(os.path.dirname(__file__), "bedrock_cassettes/"),
+        record_mode="once",
+        match_on=["path"],
+        filter_headers=["authorization", "X-Amz-Security-Token"],
+        # Ignore requests to the agent
+        ignore_localhost=True,
+    )