Add support for Claude 3.7 thinking mode

- Implemented support for Claude 3.7 thinking mode by adding reasoning effort and budget tokens.
- Added checks to ensure combined tokens do not exceed the maximum limit.
- Adjusted inference configuration to accommodate thinking mode requirements.
- Referenced implementation from https://github.com/open-webui/pipelines/blob/main/examples/pipelines/providers/anthropic_manifold_pipeline.py.

examples/pipelines/providers/aws_bedrock_claude_pipeline.py

@@ -23,6 +23,17 @@ import requests
 
 from utils.pipelines.main import pop_system_message
 
+REASONING_EFFORT_BUDGET_TOKEN_MAP = {
+    "none": None,
+    "low": 1024,
+    "medium": 4096,
+    "high": 16384,
+    "max": 32768,
+}
+
+# Maximum combined token limit for Claude 3.7
+MAX_COMBINED_TOKENS = 64000
+
 
 class Pipeline:
     class Valves(BaseModel):
@@ -170,7 +181,44 @@ class Pipeline:
                         },
                         "additionalModelRequestFields": {"top_k": body.get("top_k", 200)}
                        }
+
             if body.get("stream", False):
+                supports_thinking = "claude-3-7" in model_id
+                reasoning_effort = body.get("reasoning_effort", "none")
+                budget_tokens = REASONING_EFFORT_BUDGET_TOKEN_MAP.get(reasoning_effort)
+
+                # Allow users to input an integer value representing budget tokens
+                if (
+                    not budget_tokens
+                    and reasoning_effort not in REASONING_EFFORT_BUDGET_TOKEN_MAP.keys()
+                ):
+                    try:
+                        budget_tokens = int(reasoning_effort)
+                    except ValueError as e:
+                        print("Failed to convert reasoning effort to int", e)
+                        budget_tokens = None
+
+                if supports_thinking and budget_tokens:
+                    # Check if the combined tokens (budget_tokens + max_tokens) exceeds the limit
+                    max_tokens = payload.get("max_tokens", 4096)
+                    combined_tokens = budget_tokens + max_tokens
+
+                    if combined_tokens > MAX_COMBINED_TOKENS:
+                        error_message = f"Error: Combined tokens (budget_tokens {budget_tokens} + max_tokens {max_tokens} = {combined_tokens}) exceeds the maximum limit of {MAX_COMBINED_TOKENS}"
+                        print(error_message)
+                        return error_message
+
+                    payload["inferenceConfig"]["maxTokens"] = combined_tokens
+                    payload["additionalModelRequestFields"]["thinking"] = {
+                        "type": "enabled",
+                        "budget_tokens": budget_tokens,
+                    }
+                    # Thinking requires temperature 1.0 and does not support top_p, top_k
+                    payload["inferenceConfig"]["temperature"] = 1.0
+                    if "top_k" in payload["additionalModelRequestFields"]:
+                        del payload["additionalModelRequestFields"]["top_k"]
+                    if "topP" in payload["inferenceConfig"]:
+                        del payload["inferenceConfig"]["topP"]
                 return self.stream_response(model_id, payload)
             else:
                 return self.get_completion(model_id, payload)
@@ -194,11 +242,23 @@ class Pipeline:
 
     def stream_response(self, model_id: str, payload: dict) -> Generator:
         streaming_response = self.bedrock_runtime.converse_stream(**payload)
+
+        in_resasoning_context = False
         for chunk in streaming_response["stream"]:
-            if "contentBlockDelta" in chunk:
-                yield chunk["contentBlockDelta"]["delta"]["text"]
+            if in_resasoning_context and "contentBlockStop" in chunk:
+                in_resasoning_context = False
+                yield "\n </think> \n\n"
+            elif "contentBlockDelta" in chunk and "delta" in chunk["contentBlockDelta"]:
+                if "reasoningContent" in chunk["contentBlockDelta"]["delta"]:
+                    if not in_resasoning_context:
+                        yield "<think>"
+
+                    in_resasoning_context = True
+                    if "text" in chunk["contentBlockDelta"]["delta"]["reasoningContent"]:
+                        yield chunk["contentBlockDelta"]["delta"]["reasoningContent"]["text"]
+                elif "text" in chunk["contentBlockDelta"]["delta"]:
+                    yield chunk["contentBlockDelta"]["delta"]["text"]
 
     def get_completion(self, model_id: str, payload: dict) -> str:
         response = self.bedrock_runtime.converse(**payload)
         return response['output']['message']['content'][0]['text']
-