✨ Added support for Anthropic, updated to latest langchain 0.3.7;

config/config_default.yml

@@ -48,8 +48,8 @@ eval:
     error_threshold: 0.5
 
 llm:
-    type: 'OpenAI'
     name: 'gpt-4-1106-preview' # This is the meta-prompt LLM, it should be a strong model. For example, using GPT-3.5 will cause an error in many cases.
+    type: 'OpenAI' # Can be OpenAI, Anthropic, Google, Azure
     temperature: 0.8
 
 stop_criteria:

config/llm_env.yml

@@ -1,3 +1,5 @@
+anthropic:
+  ANTHROPIC_API_KEY: ''
 openai:
   OPENAI_API_KEY: ''
   OPENAI_API_BASE: ''

environment_dev.yml

@@ -6,6 +6,7 @@ dependencies:
   - python=3.10.13
   - pip>=2.22.0
   - openai
+  - anthropic
   - langchain
   - pandas
   - wandb
@@ -19,5 +20,4 @@ dependencies:
       - schedule
       - pandas
       - easydict
-      - pillow==10.2.0
-      - langchain-google-genai==0.0.9
+      - pillow==10.2.0

requirements.txt

@@ -3,14 +3,19 @@ schedule==1.2.1
 pandas==1.5.3
 tqdm==4.66.1
 prodict==0.8.18
-langchain==0.1.9
-openai==1.1.0
+langchain==0.3.7
+openai==1.54.4
+anthropic==0.39.0
 tiktoken==0.5.1
 easydict==1.11
-wandb==0.16.0
+wandb==0.18.7
 transformers==4.35.2
 scikit-learn==1.3.2
 faiss-cpu==1.7.4
 sentence-transformers==2.2.2
-langchain-google-genai==0.0.9
+langchain-core==0.3.18
+langchain-openai==0.2.8
+langchain-anthropic==0.3.0
+langchain-community==0.3.7
+langchain-google-genai==2.0.4
 pillow==10.2.0

utils/config.py

@@ -57,6 +57,12 @@ def get_llm(config: dict):
         return ChatGoogleGenerativeAI(temperature=temperature, model=config['name'],
                               google_api_key=LLM_ENV['google']['GOOGLE_API_KEY'],
                               model_kwargs=model_kwargs)
+
+    elif config['type'].lower() == 'anthropic':
+        from langchain_anthropic import ChatAnthropic
+        return ChatAnthropic(temperature=temperature, model=config['name'],
+                              api_key=LLM_ENV['anthropic']['ANTHROPIC_API_KEY'],
+                              model_kwargs=model_kwargs)
 
 
     elif config['type'].lower() == 'huggingfacepipeline':

utils/llm_chain.py

@@ -156,8 +156,8 @@ def build_chain(self):
         """
         Build the chain according to the LLM type
         """
-        if (self.llm_config.type.lower() == 'openai' or self.llm_config.type.lower() == 'azure') and self.json_schema is not None:
-            self.chain = create_structured_output_runnable(self.json_schema, self.llm, self.prompt)
+        if (self.llm_config.type.lower() in ['openai', 'azure', 'anthropic']) and self.json_schema is not None:
+            self.chain = self.prompt | self.llm.with_structured_output(self.json_schema)
         else:
             self.chain = LLMChain(llm=self.llm, prompt=self.prompt)