fixed streaming from Anthropic Client to OpenAI

tests/e2e/test_prompt_gateway.py

@@ -380,6 +380,65 @@ def test_claude_v1_messages_api():
     assert message.content[0].text == "Hello from Claude!"
 
 
+def test_claude_v1_messages_api_streaming():
+    base_url = LLM_GATEWAY_ENDPOINT.replace("/v1/chat/completions", "")
+
+    client = anthropic.Anthropic(api_key="test-key", base_url=base_url)
+
+    with client.messages.stream(
+        model="claude-sonnet-4-20250514",
+        max_tokens=50,
+        messages=[
+            {
+                "role": "user",
+                "content": "Hello, please respond with exactly: Hello from Claude!",
+            }
+        ],
+    ) as stream:
+        # This yields only text deltas in order
+        pieces = [t for t in stream.text_stream]
+        full_text = "".join(pieces)
+
+        # You can also get the fully-assembled Message object
+        final = stream.get_final_message()
+        # A safe way to reassemble text from the content blocks:
+        final_text = "".join(b.text for b in final.content if b.type == "text")
+
+    assert full_text == "Hello from Claude!"
+    assert final_text == "Hello from Claude!"
+
+
+def test_anthropic_client_with_openai_model_streaming():
+    """Test Anthropic client using /v1/messages API with OpenAI model (gpt-4o-mini)
+    This tests the transformation: OpenAI upstream -> Anthropic client format with proper event lines
+    """
+    base_url = LLM_GATEWAY_ENDPOINT.replace("/v1/chat/completions", "")
+
+    client = anthropic.Anthropic(api_key="test-key", base_url=base_url)
+
+    with client.messages.stream(
+        model="gpt-4o-mini",  # OpenAI model via Anthropic client
+        max_tokens=50,
+        messages=[
+            {
+                "role": "user",
+                "content": "Hello, please respond with exactly: Hello from GPT-4o-mini via Anthropic!",
+            }
+        ],
+    ) as stream:
+        # This yields only text deltas in order
+        pieces = [t for t in stream.text_stream]
+        full_text = "".join(pieces)
+
+        # You can also get the fully-assembled Message object
+        final = stream.get_final_message()
+        # A safe way to reassemble text from the content blocks:
+        final_text = "".join(b.text for b in final.content if b.type == "text")
+
+    assert full_text == "Hello from GPT-4o-mini via Anthropic!"
+    assert final_text == "Hello from GPT-4o-mini via Anthropic!"
+
+
 def test_openai_gpt4o_mini_v1_messages_api():
     """Test OpenAI GPT-4o-mini using /v1/chat/completions API through llm_gateway (port 12000)"""
     # Get the base URL from the LLM gateway endpoint
@@ -402,3 +461,72 @@ def test_openai_gpt4o_mini_v1_messages_api():
     )
 
     assert completion.choices[0].message.content == "Hello from GPT-4o-mini!"
+
+
+def test_openai_gpt4o_mini_v1_messages_api_streaming():
+    """Test OpenAI GPT-4o-mini using /v1/chat/completions API with streaming through llm_gateway (port 12000)"""
+    # Get the base URL from the LLM gateway endpoint
+    base_url = LLM_GATEWAY_ENDPOINT.replace("/v1/chat/completions", "")
+
+    client = openai.OpenAI(
+        api_key="test-key",  # Dummy key for testing
+        base_url=f"{base_url}/v1",  # OpenAI needs /v1 suffix in base_url
+    )
+
+    stream = client.chat.completions.create(
+        model="gpt-4o-mini",
+        max_tokens=50,
+        messages=[
+            {
+                "role": "user",
+                "content": "Hello, please respond with exactly: Hello from GPT-4o-mini!",
+            }
+        ],
+        stream=True,
+    )
+
+    # Collect all the streaming chunks
+    content_chunks = []
+    for chunk in stream:
+        if chunk.choices[0].delta.content:
+            content_chunks.append(chunk.choices[0].delta.content)
+
+    # Reconstruct the full message
+    full_content = "".join(content_chunks)
+    assert full_content == "Hello from GPT-4o-mini!"
+
+
+def test_openai_client_with_claude_model_streaming():
+    """Test OpenAI client using /v1/chat/completions API with Claude model (claude-sonnet-4-20250514)
+    This tests the transformation: Anthropic upstream -> OpenAI client format with proper chunk handling
+    """
+    # Get the base URL from the LLM gateway endpoint
+    base_url = LLM_GATEWAY_ENDPOINT.replace("/v1/chat/completions", "")
+
+    client = openai.OpenAI(
+        api_key="test-key",  # Dummy key for testing
+        base_url=f"{base_url}/v1",  # OpenAI needs /v1 suffix in base_url
+    )
+
+    stream = client.chat.completions.create(
+        model="claude-sonnet-4-20250514",  # Claude model via OpenAI client
+        max_tokens=50,
+        messages=[
+            {
+                "role": "user",
+                "content": "Who are you? ALWAYS RESPOND WITH:I appreciate the request, but I should clarify that I'm Claude, made by Anthropic, not OpenAI. I don't want to create confusion about my origins.",
+            }
+        ],
+        stream=True,
+        temperature=0.1,
+    )
+
+    # Collect all the streaming chunks
+    content_chunks = []
+    for chunk in stream:
+        if chunk.choices[0].delta.content:
+            content_chunks.append(chunk.choices[0].delta.content)
+
+    # Reconstruct the full message
+    full_content = "".join(content_chunks)
+    assert full_content is not None