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Add DeekSeek API support #27

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62 changes: 47 additions & 15 deletions server.py
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Original file line number Diff line number Diff line change
Expand Up @@ -81,6 +81,7 @@ def format(self, record):
ANTHROPIC_API_KEY = os.environ.get("ANTHROPIC_API_KEY")
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
DEEPSEEK_API_KEY = os.environ.get("DEEPSEEK_API_KEY")

# Get preferred provider (default to openai)
PREFERRED_PROVIDER = os.environ.get("PREFERRED_PROVIDER", "openai").lower()
Expand Down Expand Up @@ -112,6 +113,12 @@ def format(self, record):
"gemini-2.0-flash"
]

# List of DeepSeek models
DEEPSEEK_MODELS = [
"deepseek-reasoner",
"deepseek-chat"
]

# Helper function to clean schema for Gemini
def clean_gemini_schema(schema: Any) -> Any:
"""Recursively removes unsupported fields from a JSON schema for Gemini."""
Expand Down Expand Up @@ -202,26 +209,32 @@ def validate_model_field(cls, v, info): # Renamed to avoid conflict
clean_v = clean_v[7:]
elif clean_v.startswith('gemini/'):
clean_v = clean_v[7:]
elif clean_v.startswith('deepseek/'):
clean_v = clean_v[9:]

# --- Mapping Logic --- START ---
mapped = False
# Map Haiku to SMALL_MODEL based on provider preference
if 'haiku' in clean_v.lower():
if PREFERRED_PROVIDER == "google" and SMALL_MODEL in GEMINI_MODELS:
# Check if SMALL_MODEL already has a provider prefix
if "/" in SMALL_MODEL:
new_model = SMALL_MODEL
elif PREFERRED_PROVIDER == "google" and SMALL_MODEL in GEMINI_MODELS:
new_model = f"gemini/{SMALL_MODEL}"
mapped = True
else:
new_model = f"openai/{SMALL_MODEL}"
mapped = True
mapped = True

# Map Sonnet to BIG_MODEL based on provider preference
elif 'sonnet' in clean_v.lower():
if PREFERRED_PROVIDER == "google" and BIG_MODEL in GEMINI_MODELS:
# Check if BIG_MODEL already has a provider prefix
if "/" in BIG_MODEL:
new_model = BIG_MODEL
elif PREFERRED_PROVIDER == "google" and BIG_MODEL in GEMINI_MODELS:
new_model = f"gemini/{BIG_MODEL}"
mapped = True
else:
new_model = f"openai/{BIG_MODEL}"
mapped = True
mapped = True

# Add prefixes to non-mapped models if they match known lists
elif not mapped:
Expand All @@ -231,13 +244,16 @@ def validate_model_field(cls, v, info): # Renamed to avoid conflict
elif clean_v in OPENAI_MODELS and not v.startswith('openai/'):
new_model = f"openai/{clean_v}"
mapped = True # Technically mapped to add prefix
elif clean_v in DEEPSEEK_MODELS and not v.startswith('deepseek/'):
new_model = f"deepseek/{clean_v}"
mapped = True # Technically mapped to add prefix
# --- Mapping Logic --- END ---

if mapped:
logger.debug(f"📌 MODEL MAPPING: '{original_model}' ➡️ '{new_model}'")
else:
# If no mapping occurred and no prefix exists, log warning or decide default
if not v.startswith(('openai/', 'gemini/', 'anthropic/')):
if not v.startswith(('openai/', 'gemini/', 'anthropic/', 'deepseek/')):
logger.warning(f"⚠️ No prefix or mapping rule for model: '{original_model}'. Using as is.")
new_model = v # Ensure we return the original if no rule applied

Expand Down Expand Up @@ -275,26 +291,32 @@ def validate_model_token_count(cls, v, info): # Renamed to avoid conflict
clean_v = clean_v[7:]
elif clean_v.startswith('gemini/'):
clean_v = clean_v[7:]
elif clean_v.startswith('deepseek/'):
clean_v = clean_v[9:]

# --- Mapping Logic --- START ---
mapped = False
# Map Haiku to SMALL_MODEL based on provider preference
if 'haiku' in clean_v.lower():
if PREFERRED_PROVIDER == "google" and SMALL_MODEL in GEMINI_MODELS:
# Check if SMALL_MODEL already has a provider prefix
if "/" in SMALL_MODEL:
new_model = SMALL_MODEL
elif PREFERRED_PROVIDER == "google" and SMALL_MODEL in GEMINI_MODELS:
new_model = f"gemini/{SMALL_MODEL}"
mapped = True
else:
new_model = f"openai/{SMALL_MODEL}"
mapped = True
mapped = True

# Map Sonnet to BIG_MODEL based on provider preference
elif 'sonnet' in clean_v.lower():
if PREFERRED_PROVIDER == "google" and BIG_MODEL in GEMINI_MODELS:
# Check if BIG_MODEL already has a provider prefix
if "/" in BIG_MODEL:
new_model = BIG_MODEL
elif PREFERRED_PROVIDER == "google" and BIG_MODEL in GEMINI_MODELS:
new_model = f"gemini/{BIG_MODEL}"
mapped = True
else:
new_model = f"openai/{BIG_MODEL}"
mapped = True
mapped = True

# Add prefixes to non-mapped models if they match known lists
elif not mapped:
Expand All @@ -304,12 +326,15 @@ def validate_model_token_count(cls, v, info): # Renamed to avoid conflict
elif clean_v in OPENAI_MODELS and not v.startswith('openai/'):
new_model = f"openai/{clean_v}"
mapped = True # Technically mapped to add prefix
elif clean_v in DEEPSEEK_MODELS and not v.startswith('deepseek/'):
new_model = f"deepseek/{clean_v}"
mapped = True # Technically mapped to add prefix
# --- Mapping Logic --- END ---

if mapped:
logger.debug(f"📌 TOKEN COUNT MAPPING: '{original_model}' ➡️ '{new_model}'")
else:
if not v.startswith(('openai/', 'gemini/', 'anthropic/')):
if not v.startswith(('openai/', 'gemini/', 'anthropic/', 'deepseek/')):
logger.warning(f"⚠️ No prefix or mapping rule for token count model: '{original_model}'. Using as is.")
new_model = v # Ensure we return the original if no rule applied

Expand Down Expand Up @@ -1097,6 +1122,8 @@ async def create_message(
clean_model = clean_model[len("anthropic/"):]
elif clean_model.startswith("openai/"):
clean_model = clean_model[len("openai/"):]
elif clean_model.startswith("deepseek/"):
clean_model = clean_model[len("deepseek/"):]

logger.debug(f"📊 PROCESSING REQUEST: Model={request.model}, Stream={request.stream}")

Expand All @@ -1110,6 +1137,9 @@ async def create_message(
elif request.model.startswith("gemini/"):
litellm_request["api_key"] = GEMINI_API_KEY
logger.debug(f"Using Gemini API key for model: {request.model}")
elif request.model.startswith("deepseek/"):
litellm_request["api_key"] = DEEPSEEK_API_KEY
logger.debug(f"Using DeepSeek API key for model: {request.model}")
else:
litellm_request["api_key"] = ANTHROPIC_API_KEY
logger.debug(f"Using Anthropic API key for model: {request.model}")
Expand Down Expand Up @@ -1354,6 +1384,8 @@ async def count_tokens(
clean_model = clean_model[len("anthropic/"):]
elif clean_model.startswith("openai/"):
clean_model = clean_model[len("openai/"):]
elif clean_model.startswith("deepseek/"):
clean_model = clean_model[len("deepseek/"):]

# Convert the messages to a format LiteLLM can understand
converted_request = convert_anthropic_to_litellm(
Expand Down Expand Up @@ -1462,4 +1494,4 @@ def log_request_beautifully(method, path, claude_model, openai_model, num_messag
sys.exit(0)

# Configure uvicorn to run with minimal logs
uvicorn.run(app, host="0.0.0.0", port=8082, log_level="error")
uvicorn.run(app, host="0.0.0.0", port=8082, log_level="error")