prompt QA done

Author: MAsuamah

fern/docs.yml

@@ -695,7 +695,6 @@ navigation:
                   - page: Prompt A Structured Q&A Response Using LLM Gateway
                     path: pages/05-guides/cookbooks/lemur/task-endpoint-structured-QA.mdx
                     slug: task-endpoint-structured-QA
-                    hidden: true
                   - page: Estimate Input Token Costs for LLM Gateway
                     path: pages/05-guides/cookbooks/lemur/counting-tokens.mdx
                     slug: counting-tokens

fern/pages/05-guides/cookbooks/lemur/task-endpoint-structured-QA.mdx

@@ -209,7 +209,7 @@ while True:
         time.sleep(3)
 ```
 
-Construct a formatted string to structure the questions. This includes the question text, context, an answer format, and any answer options, then returns the formatted string.
+Construct a formatted string to structure the questions. This includes the question text, context, an answer format, any answer options, then returns the formatted string.
 
 ```python
 # -------------------------------
@@ -506,28 +506,6 @@ llm_output = response_json["choices"][0]["message"]["content"]
 
 Clean the XML output and print the question and answer pairs.
 
-```python
-# -------------------------------
-# Step 5: Query LLM Gateway
-# -------------------------------
-headers = {"authorization": API_KEY}
-
-response = requests.post(
-    "https://llm-gateway.assemblyai.com/v1/chat/completions",
-    headers=headers,
-    json={
-        "model": "claude-sonnet-4-5-20250929",
-        "messages": [{"role": "user", "content": prompt}],
-        "max_tokens": 2000,
-    },
-)
-
-response_json = response.json()
-llm_output = response_json["choices"][0]["message"]["content"]
-```
-
-Clean the XML output and print the question and answer pairs.
-
 ```python
 # -------------------------------
 # Step 6: Parse and print XML response