anthropic_manifold_pipe--with-thinking-3-7.py

anthropic_manifold_pipe--with-thinking-3-7.diff

diff --git a/amp.py b/amp.py
index 2dfde0f..2de8bbd 100644
--- a/amp.py
+++ b/amp.py
@@ -21,6 +21,18 @@ class Pipe:
     class Valves(BaseModel):
         ANTHROPIC_API_KEY: str = Field(default="")
 
+    # Mapping for reasoning effort to token budgets
+    REASONING_EFFORT_BUDGET_TOKEN_MAP = {
+        "none": None,
+        "low": 1024,
+        "medium": 4096,
+        "high": 16384,
+        "max": 32768,
+    }
+
+    # Maximum combined token limit for Claude 3.7 models
+    MAX_COMBINED_TOKENS = 64000
+
     def __init__(self):
         self.type = "manifold"
         self.id = "anthropic"
@@ -32,6 +44,7 @@ class Pipe:
         pass
 
     def get_anthropic_models(self):
+        """Return list of available Anthropic models."""
         return [
             {"id": "claude-3-haiku-20240307", "name": "claude-3-haiku"},
             {"id": "claude-3-opus-20240229", "name": "claude-3-opus"},
@@ -45,6 +58,7 @@ class Pipe:
         ]
 
     def pipes(self) -> List[dict]:
+        """Return list of pipe configurations."""
         return self.get_anthropic_models()
 
     def process_image(self, image_data):
@@ -85,6 +99,7 @@ class Pipe:
             }
 
     def pipe(self, body: dict) -> Union[str, Generator, Iterator]:
+        """Process the input body and return a response."""
         system_message, messages = pop_system_message(body["messages"])
 
         processed_messages = []
@@ -93,6 +108,10 @@ class Pipe:
         for message in messages:
             processed_content = []
             if isinstance(message.get("content"), list):
+                # Check number of images per message (Anthropic limit: 5 per message)
+                image_count = sum(1 for item in message["content"] if item["type"] == "image_url")
+                if image_count > 5:
+                    raise ValueError("Maximum of 5 images per message exceeded")
                 for item in message["content"]:
                     if item["type"] == "text":
                         processed_content.append({"type": "text", "text": item["text"]})
@@ -137,6 +156,35 @@ class Pipe:
             "content-type": "application/json",
         }
 
+        # Add thinking support for Claude 3.7 models
+        model_id = payload["model"]
+        supports_thinking = model_id.startswith("claude-3-7")
+        reasoning_effort = body.get("reasoning_effort", "none")
+        budget_tokens = self.REASONING_EFFORT_BUDGET_TOKEN_MAP.get(reasoning_effort)
+
+        # Allow integer values for reasoning_effort
+        if budget_tokens is None and reasoning_effort not in self.REASONING_EFFORT_BUDGET_TOKEN_MAP:
+            try:
+                budget_tokens = int(reasoning_effort)
+            except (ValueError, TypeError):
+                budget_tokens = None
+
+        if supports_thinking and budget_tokens:
+            max_tokens = payload.get("max_tokens", 4096)
+            combined_tokens = budget_tokens + max_tokens
+            if combined_tokens > self.MAX_COMBINED_TOKENS:
+                return f"Error: Combined tokens (budget_tokens {budget_tokens} + max_tokens {max_tokens} = {combined_tokens}) exceeds the maximum limit of {self.MAX_COMBINED_TOKENS}"
+            payload["max_tokens"] = combined_tokens
+            payload["thinking"] = {
+                "type": "enabled",
+                "budget_tokens": budget_tokens,
+            }
+            payload["temperature"] = 1.0
+            if "top_k" in payload:
+                del payload["top_k"]
+            if "top_p" in payload:
+                del payload["top_p"]
+
         url = "https://api.anthropic.com/v1/messages"
 
         try:
@@ -168,9 +216,17 @@ class Pipe:
                             try:
                                 data = json.loads(line[6:])
                                 if data["type"] == "content_block_start":
-                                    yield data["content_block"]["text"]
+                                    if data["content_block"]["type"] == "thinking":
+                                        yield "<think>"
+                                    else:
+                                        yield data["content_block"]["text"]
                                 elif data["type"] == "content_block_delta":
-                                    yield data["delta"]["text"]
+                                    if data["delta"]["type"] == "thinking_delta":
+                                        yield data["delta"]["thinking"]
+                                    elif data["delta"]["type"] == "signature_delta":
+                                        yield "\n </think> \n\n"
+                                    else:
+                                        yield data["delta"]["text"]
                                 elif data["type"] == "message_stop":
                                     break
                                 elif data["type"] == "message":
@@ -195,6 +251,7 @@ class Pipe:
             yield f"Error: {e}"
 
     def non_stream_response(self, url, headers, payload):
+        """Get a non-streaming response from the Anthropic API."""
         try:
             response = requests.post(
                 url, headers=headers, json=payload, timeout=(3.05, 60)
@@ -203,10 +260,10 @@ class Pipe:
                 raise Exception(f"HTTP Error {response.status_code}: {response.text}")
 
             res = response.json()
-            return (
-                res["content"][0]["text"] if "content" in res and res["content"] else ""
-            )
+            for content in res.get("content", []):
+                if content.get("type") == "text":
+                    return content["text"]
+            return ""
         except requests.exceptions.RequestException as e:
             print(f"Failed non-stream request: {e}")
             return f"Error: {e}"
-

anthropic_manifold_pipe--with-thinking-3-7.py

"""
title: Anthropic Manifold Pipe
authors: justinh-rahb and christian-taillon
author_url: https://github.com/justinh-rahb
funding_url: https://github.com/open-webui
version: 0.2.4
required_open_webui_version: 0.3.17
license: MIT
"""

import os
import requests
import json
import time
from typing import List, Union, Generator, Iterator
from pydantic import BaseModel, Field
from open_webui.utils.misc import pop_system_message


class Pipe:
    class Valves(BaseModel):
        ANTHROPIC_API_KEY: str = Field(default="")

    # Mapping for reasoning effort to token budgets
    REASONING_EFFORT_BUDGET_TOKEN_MAP = {
        "none": None,
        "low": 1024,
        "medium": 4096,
        "high": 16384,
        "max": 32768,
    }

    # Maximum combined token limit for Claude 3.7 models
    MAX_COMBINED_TOKENS = 64000

    def __init__(self):
        self.type = "manifold"
        self.id = "anthropic"
        self.name = "anthropic/"
        self.valves = self.Valves(
            **{"ANTHROPIC_API_KEY": os.getenv("ANTHROPIC_API_KEY", "")}
        )
        self.MAX_IMAGE_SIZE = 5 * 1024 * 1024  # 5MB per image
        pass

    def get_anthropic_models(self):
        """Return list of available Anthropic models."""
        return [
            {"id": "claude-3-haiku-20240307", "name": "claude-3-haiku"},
            {"id": "claude-3-opus-20240229", "name": "claude-3-opus"},
            {"id": "claude-3-sonnet-20240229", "name": "claude-3-sonnet"},
            {"id": "claude-3-5-haiku-20241022", "name": "claude-3.5-haiku"},
            {"id": "claude-3-5-haiku-latest", "name": "claude-3.5-haiku"},
            {"id": "claude-3-5-sonnet-20240620", "name": "claude-3.5-sonnet"},
            {"id": "claude-3-5-sonnet-20241022", "name": "claude-3.5-sonnet"},
            {"id": "claude-3-5-sonnet-latest", "name": "claude-3.5-sonnet"},
            {"id": "claude-3-7-sonnet-20250219", "name": "claude-3.7-sonnet"},
        ]

    def pipes(self) -> List[dict]:
        """Return list of pipe configurations."""
        return self.get_anthropic_models()

    def process_image(self, image_data):
        """Process image data with size validation."""
        if image_data["image_url"]["url"].startswith("data:image"):
            mime_type, base64_data = image_data["image_url"]["url"].split(",", 1)
            media_type = mime_type.split(":")[1].split(";")[0]

            # Check base64 image size
            image_size = len(base64_data) * 3 / 4  # Convert base64 size to bytes
            if image_size > self.MAX_IMAGE_SIZE:
                raise ValueError(
                    f"Image size exceeds 5MB limit: {image_size / (1024 * 1024):.2f}MB"
                )

            return {
                "type": "image",
                "source": {
                    "type": "base64",
                    "media_type": media_type,
                    "data": base64_data,
                },
            }
        else:
            # For URL images, perform size check after fetching
            url = image_data["image_url"]["url"]
            response = requests.head(url, allow_redirects=True)
            content_length = int(response.headers.get("content-length", 0))

            if content_length > self.MAX_IMAGE_SIZE:
                raise ValueError(
                    f"Image at URL exceeds 5MB limit: {content_length / (1024 * 1024):.2f}MB"
                )

            return {
                "type": "image",
                "source": {"type": "url", "url": url},
            }

    def pipe(self, body: dict) -> Union[str, Generator, Iterator]:
        """Process the input body and return a response."""
        system_message, messages = pop_system_message(body["messages"])

        processed_messages = []
        total_image_size = 0

        for message in messages:
            processed_content = []
            if isinstance(message.get("content"), list):
                # Check number of images per message (Anthropic limit: 5 per message)
                image_count = sum(1 for item in message["content"] if item["type"] == "image_url")
                if image_count > 5:
                    raise ValueError("Maximum of 5 images per message exceeded")
                for item in message["content"]:
                    if item["type"] == "text":
                        processed_content.append({"type": "text", "text": item["text"]})
                    elif item["type"] == "image_url":
                        processed_image = self.process_image(item)
                        processed_content.append(processed_image)

                        # Track total size for base64 images
                        if processed_image["source"]["type"] == "base64":
                            image_size = len(processed_image["source"]["data"]) * 3 / 4
                            total_image_size += image_size
                            if (
                                total_image_size > 100 * 1024 * 1024
                            ):  # 100MB total limit
                                raise ValueError(
                                    "Total size of images exceeds 100 MB limit"
                                )
            else:
                processed_content = [
                    {"type": "text", "text": message.get("content", "")}
                ]

            processed_messages.append(
                {"role": message["role"], "content": processed_content}
            )

        payload = {
            "model": body["model"][body["model"].find(".") + 1 :],
            "messages": processed_messages,
            "max_tokens": body.get("max_tokens", 4096),
            "temperature": body.get("temperature", 0.8),
            "top_k": body.get("top_k", 40),
            "top_p": body.get("top_p", 0.9),
            "stop_sequences": body.get("stop", []),
            **({"system": str(system_message)} if system_message else {}),
            "stream": body.get("stream", False),
        }

        headers = {
            "x-api-key": self.valves.ANTHROPIC_API_KEY,
            "anthropic-version": "2023-06-01",
            "content-type": "application/json",
        }

        # Add thinking support for Claude 3.7 models
        model_id = payload["model"]
        supports_thinking = model_id.startswith("claude-3-7")
        reasoning_effort = body.get("reasoning_effort", "none")
        budget_tokens = self.REASONING_EFFORT_BUDGET_TOKEN_MAP.get(reasoning_effort)

        # Allow integer values for reasoning_effort
        if budget_tokens is None and reasoning_effort not in self.REASONING_EFFORT_BUDGET_TOKEN_MAP:
            try:
                budget_tokens = int(reasoning_effort)
            except (ValueError, TypeError):
                budget_tokens = None

        if supports_thinking and budget_tokens:
            max_tokens = payload.get("max_tokens", 4096)
            combined_tokens = budget_tokens + max_tokens
            if combined_tokens > self.MAX_COMBINED_TOKENS:
                return f"Error: Combined tokens (budget_tokens {budget_tokens} + max_tokens {max_tokens} = {combined_tokens}) exceeds the maximum limit of {self.MAX_COMBINED_TOKENS}"
            payload["max_tokens"] = combined_tokens
            payload["thinking"] = {
                "type": "enabled",
                "budget_tokens": budget_tokens,
            }
            payload["temperature"] = 1.0
            if "top_k" in payload:
                del payload["top_k"]
            if "top_p" in payload:
                del payload["top_p"]

        url = "https://api.anthropic.com/v1/messages"

        try:
            if body.get("stream", False):
                return self.stream_response(url, headers, payload)
            else:
                return self.non_stream_response(url, headers, payload)
        except requests.exceptions.RequestException as e:
            print(f"Request failed: {e}")
            return f"Error: Request failed: {e}"
        except Exception as e:
            print(f"Error in pipe method: {e}")
            return f"Error: {e}"

    def stream_response(self, url, headers, payload):
        try:
            with requests.post(
                url, headers=headers, json=payload, stream=True, timeout=(3.05, 60)
            ) as response:
                if response.status_code != 200:
                    raise Exception(
                        f"HTTP Error {response.status_code}: {response.text}"
                    )

                for line in response.iter_lines():
                    if line:
                        line = line.decode("utf-8")
                        if line.startswith("data: "):
                            try:
                                data = json.loads(line[6:])
                                if data["type"] == "content_block_start":
                                    if data["content_block"]["type"] == "thinking":
                                        yield "<think>"
                                    else:
                                        yield data["content_block"]["text"]
                                elif data["type"] == "content_block_delta":
                                    if data["delta"]["type"] == "thinking_delta":
                                        yield data["delta"]["thinking"]
                                    elif data["delta"]["type"] == "signature_delta":
                                        yield "\n </think> \n\n"
                                    else:
                                        yield data["delta"]["text"]
                                elif data["type"] == "message_stop":
                                    break
                                elif data["type"] == "message":
                                    for content in data.get("content", []):
                                        if content["type"] == "text":
                                            yield content["text"]

                                time.sleep(
                                    0.01
                                )  # Delay to avoid overwhelming the client

                            except json.JSONDecodeError:
                                print(f"Failed to parse JSON: {line}")
                            except KeyError as e:
                                print(f"Unexpected data structure: {e}")
                                print(f"Full data: {data}")
        except requests.exceptions.RequestException as e:
            print(f"Request failed: {e}")
            yield f"Error: Request failed: {e}"
        except Exception as e:
            print(f"General error in stream_response method: {e}")
            yield f"Error: {e}"

    def non_stream_response(self, url, headers, payload):
        """Get a non-streaming response from the Anthropic API."""
        try:
            response = requests.post(
                url, headers=headers, json=payload, timeout=(3.05, 60)
            )
            if response.status_code != 200:
                raise Exception(f"HTTP Error {response.status_code}: {response.text}")

            res = response.json()
            for content in res.get("content", []):
                if content.get("type") == "text":
                    return content["text"]
            return ""
        except requests.exceptions.RequestException as e:
            print(f"Failed non-stream request: {e}")
            return f"Error: {e}"