Update Readme

Signed-off-by: Kaiyuan Hu <kaiyuan.hu@zilliz.com>

README.md

@@ -20,10 +20,18 @@
 from towhee import AutoPipes, AutoConfig
 
 config = AutoConfig.load_config('eqa-search')
+config.openai_api_key = [your-openai-api-key]
 config.collection_name = 'chatbot'
+# The llm model source, openai or dolly
+config.llm_src = 'openai'
+# The llm model name
+config.llm_model = 'gpt-3.5-turbo'
+# The threshold to filter milvus search result
+config.threshold = 0.5
+
 
 p = AutoPipes.pipeline('eqa-search', config=config)
-res = p('https://raw.githubusercontent.com/towhee-io/towhee/main/README.md')
+res = p('https://github.com/towhee-io/towhee/blob/main/README.md', [])
 ```
 
 
@@ -76,6 +84,24 @@ The user name for [Cloud user](https://zilliz.com/cloud), defaults to `None`.
 
 The user password for [Cloud user](https://zilliz.com/cloud), defaults to `None`.
 
+### Configuration for Similarity Evaluation
+
+***threshold (Union[float, int]):***
+
+The threshold to filter the milvus search result.
+
+
+### Configuration for LLM
+
+***llm_src (str):***
+
+The llm model source, `openai` or `dolly`, defaults to `openai`.
+
+***llm_model (str):***
+
+The llm model name, defaults to `gpt-3.5-turbo` for `openai`, `databricks/dolly-v2-12b` for `dolly`.
+
+
 <br />
 
 

eqa_search.py

@@ -22,7 +22,7 @@ class EnhancedQASearchConfig:
     """
     def __init__(self):
         # config for sentence_embedding
-        self.model = 'all-MiniLM-L6-v2'
+        self.embedding_model = 'all-MiniLM-L6-v2'
         self.openai_api_key = None
         self.embedding_device = -1
         # config for search_milvus
@@ -35,7 +35,8 @@ class EnhancedQASearchConfig:
         # config for similarity evaluation
         self.threshold = 0.6
         # config for llm
-        self.llm_model = 'openai'
+        self.llm_src = 'openai'
+        self.llm_model = 'gpt-3.5-turbo' if self.llm_src.lower() == 'openai' else 'databricks/dolly-v2-12b'
 
 
 _hf_models = ops.sentence_embedding.transformers().get_op().supported_model_names()
@@ -51,22 +52,22 @@ def _get_embedding_op(config):
     else:
         device = config.embedding_device
 
-    if config.model in _hf_models:
+    if config.embedding_model in _hf_models:
         return True, ops.sentence_embedding.transformers(
-            model_name=config.model, device=device
+            model_name=config.embedding_model, device=device
         )
 
-    if config.model in _sbert_models:
+    if config.embedding_model in _sbert_models:
         return True, ops.sentence_embedding.sbert(
-            model_name=config.model, device=device
+            model_name=config.embedding_model, device=device
         )
 
-    if config.model in _openai_models:
+    if config.embedding_model in _openai_models:
         return False, ops.sentence_embedding.openai(
-            model_name=config.model, api_key=config.openai_api_key
+            model_name=config.embedding_model, api_key=config.openai_api_key
         )
 
-    raise RuntimeError('Unknown model: [%s], only support: %s' % (config.model, _hf_models + _openai_models))
+    raise RuntimeError('Unknown model: [%s], only support: %s' % (config.embedding_model, _hf_models + _openai_models))
 
 
 def _get_similarity_evaluation_op(config):
@@ -74,12 +75,12 @@ def _get_similarity_evaluation_op(config):
 
 
 def _get_llm_op(config):
-    if config.llm_model.lower() == 'openai':
-        return ops.LLM.OpenAI(api_key=config.openai_api_key)
-    if config.llm_model.lower() == 'dolly':
-        return ops.LLM.Dolly()
+    if config.llm_src.lower() == 'openai':
+        return ops.LLM.OpenAI(model_name=config.llm_model, api_key=config.openai_api_key)
+    if config.llm_src.lower() == 'dolly':
+        return ops.LLM.Dolly(model_name=config.llm_model)
 
-    raise RuntimeError('Unknown llm model: [%s], only support \'openai\' and \'dolly\'' % (config.model))
+    raise RuntimeError('Unknown llm source: [%s], only support \'openai\' and \'dolly\'' % (config.llm_src))
 
 
 @AutoPipes.register
@@ -119,7 +120,7 @@ def enhanced_qa_search_pipe(config):
 
     p = (
         p.map('result', 'docs', lambda x:[i[2] for i in x])
-            .map(('question', 'docs', 'history'), 'prompt', ops.prompt.question_answer(llm_name=config.llm_model))
+            .map(('question', 'docs', 'history'), 'prompt', ops.prompt.question_answer(llm_name=config.llm_src))
             .map('prompt', 'answer', llm_op)
     )