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Merge pull request #1457 from KennyDizi/main
Support deepseek-chat model
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@ -166,6 +166,25 @@ drop_params = true
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AWS session is automatically authenticated from your environment, but you can also explicitly set `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY` and `AWS_REGION_NAME` environment variables. Please refer to [this document](https://litellm.vercel.app/docs/providers/bedrock) for more details.
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### DeepSeek
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To use deepseek-chat model with DeepSeek, for example, set:
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```toml
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[config] # in configuration.toml
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model = "deepseek/deepseek-chat"
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fallback_models=["deepseek/deepseek-chat"]
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```
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and fill up your key
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```toml
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[deepseek] # in .secrets.toml
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key = ...
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```
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(you can obtain a deepseek-chat key from [here](https://platform.deepseek.com))
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### Custom models
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If the relevant model doesn't appear [here](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/algo/__init__.py), you can still use it as a custom model:
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@ -29,6 +29,7 @@ MAX_TOKENS = {
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'claude-instant-1': 100000,
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'claude-2': 100000,
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'command-nightly': 4096,
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'deepseek/deepseek-chat': 128000, # 128K, but may be limited by config.max_model_tokens
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'replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1': 4096,
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'meta-llama/Llama-2-7b-chat-hf': 4096,
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'vertex_ai/codechat-bison': 6144,
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@ -90,6 +90,10 @@ class LiteLLMAIHandler(BaseAiHandler):
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if get_settings().get("GOOGLE_AI_STUDIO.GEMINI_API_KEY", None):
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os.environ["GEMINI_API_KEY"] = get_settings().google_ai_studio.gemini_api_key
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# Support deepseek models
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if get_settings().get("DEEPSEEK.KEY", None):
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os.environ['DEEPSEEK_API_KEY'] = get_settings().get("DEEPSEEK.KEY")
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def prepare_logs(self, response, system, user, resp, finish_reason):
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response_log = response.dict().copy()
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response_log['system'] = system
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@ -91,3 +91,6 @@ pat = ""
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# Optional, uncomment if you want to use Azure devops webhooks. Value assinged when you create the webhook
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# webhook_username = "<basic auth user>"
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# webhook_password = "<basic auth password>"
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[deepseek]
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key = ""
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