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import os
import json
from fastapi import FastAPI, Request, HTTPException
from fastapi.responses import StreamingResponse
from fastapi import APIRouter
from anthropic import Anthropic
from .utils import handle_attachments
router = APIRouter()
ANTHROPIC_API_KEY = os.environ.get("ANTHROPIC_API_KEY")
attachments_in_anthropic = {}
@router.post("/anthropic_stream")
async def anthropic_stream(request: Request):
"""
Stream responses from Anthropic's Claude models.
"""
print("Received request for Anthropic streaming")
# Parse the request body
body = await request.json()
conversation = body.get("messages", [])
temperature = body.get("temperature", 0.7)
max_tokens = body.get("max_tokens", 1024)
model = body.get("model", "claude-3-opus-20240229")
# Get session ID from the request
session_id = request.headers.get("X-Session-ID")
if session_id not in attachments_in_anthropic: attachments_in_anthropic[session_id] = {}
if not session_id:
raise HTTPException(status_code=400, detail="Missing 'session_id' in payload")
# Handle file attachments if present
conversation = await handle_attachments(session_id, conversation, remove_content=False)
anthropic_messages = []
for msg in conversation:
role = "user" if msg["role"] == "user" else "assistant"
pdf_base64s = []
if "attachments" in msg:
for attachment in msg["attachments"]:
if attachment["file_path"].endswith(".pdf"):
print(attachment)
if attachment["file_path"] not in attachments_in_anthropic[session_id]:
pdf_base64 = {"type": "document", "source": {"type": "base64", "media_type": "application/pdf", "data": attachment["content"]}}
pdf_base64s.append(pdf_base64)
attachments_in_anthropic[session_id][attachment["name"]] = pdf_base64
else:
pdf_base64s.append(attachments_in_anthropic[session_id][attachment["name"]])
anthropic_messages.append({"role": role, "content": pdf_base64s + [{"type": "text", "text": msg["content"]}]})
line_count = 0
async def event_generator():
try:
# Initialize Anthropic client
client = Anthropic(api_key=ANTHROPIC_API_KEY)
# Start the streaming response
with client.messages.stream(
model=model,
messages=anthropic_messages,
max_tokens=max_tokens,
temperature=temperature
) as stream:
for chunk in stream:
if hasattr(chunk, 'delta') and hasattr(chunk.delta, 'text') and chunk.delta.text:
content = chunk.delta.text
nonlocal line_count
line_count += 1
if line_count % 10 == 0:
print(f"Processed {line_count} Anthropic stream chunks")
# Format the response to match OpenAI format for client compatibility
response_json = json.dumps({
"choices": [{"delta": {"content": content}}]
})
yield f"data: {response_json}\n\n"
# Send the [DONE] marker
print("Anthropic stream completed successfully")
yield "data: [DONE]\n\n"
except Exception as e:
print(f"Error during Anthropic streaming: {str(e)}")
yield f"data: {{\"error\": \"{str(e)}\"}}\n\n"
finally:
print(f"Anthropic stream ended after processing {line_count if 'line_count' in locals() else 0} chunks")
print("Returning StreamingResponse from Anthropic to client")
return StreamingResponse(event_generator(), media_type="text/event-stream") |