dstars commited on
Commit
bc017bc
·
1 Parent(s): 4daa93a

依赖冲突太麻烦了

Browse files
.ipynb_checkpoints/download_hf-checkpoint.py ADDED
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+ import os
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+
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+ # 设置环境变量
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+ os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'
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+
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+ # 下载模型
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+ os.system('huggingface-cli download --resume-download sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 --local-dir /root/model/sentence-transformer')
.ipynb_checkpoints/llamaindex_RAG-checkpoint.py ADDED
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+ import os
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+ os.environ['NLTK_DATA'] = '/root/nltk_data'
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+
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+ from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
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+ from llama_index.core.settings import Settings
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+ from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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+ from llama_index.legacy.callbacks import CallbackManager
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+ from llama_index.llms.openai_like import OpenAILike
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+
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+
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+ # Create an instance of CallbackManager
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+ callback_manager = CallbackManager()
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+
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+ api_base_url = "https://internlm-chat.intern-ai.org.cn/puyu/api/v1/"
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+ model = "internlm2.5-latest"
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+ api_key = os.getenv("API_KEY")
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+
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+ # api_base_url = "https://api.siliconflow.cn/v1"
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+ # model = "internlm/internlm2_5-7b-chat"
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+ # api_key = "请填写 API Key"
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+
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+
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+
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+ llm =OpenAILike(model=model, api_base=api_base_url, api_key=api_key, is_chat_model=True,callback_manager=callback_manager)
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+
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+
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+ #初始化一个HuggingFaceEmbedding对象,用于将文本转换为向量表示
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+ embed_model = HuggingFaceEmbedding(
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+ #指定了一个预训练的sentence-transformer模型的路径
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+ model_name="/root/model/sentence-transformer"
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+ )
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+ #将创建的嵌入模型赋值给全局设置的embed_model属性,
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+ #这样在后续的索引构建过程中就会使用这个模型。
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+ Settings.embed_model = embed_model
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+
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+ #初始化llm
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+ Settings.llm = llm
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+
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+ #从指定目录读取所有文档,并加载数据到内存中
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+ documents = SimpleDirectoryReader("/root/llamaindex_demo/data").load_data()
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+ #创建一个VectorStoreIndex,并使用之前加载的文档来构建索引。
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+ # 此索引将文档转换为向量,并存储这些向量以便于快速检索。
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+ index = VectorStoreIndex.from_documents(documents)
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+ # 创建一个查询引擎,这个引擎可以接收查询并返回相关文档的响应。
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+ query_engine = index.as_query_engine()
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+ response = query_engine.query("Qwen2Attention是什么?")
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+
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+ print(response)
.ipynb_checkpoints/requirements-checkpoint.txt CHANGED
@@ -1,119 +1,6 @@
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- aiohappyeyeballs==2.4.3
2
- aiohttp==3.11.7
3
- aiosignal==1.3.1
4
- altair==5.5.0
5
- annotated-types==0.7.0
6
- anyio==4.6.2.post1
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- async-timeout==5.0.1
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- attrs==24.2.0
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- beautifulsoup4==4.12.3
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- blinker==1.9.0
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- cachetools==5.5.0
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- certifi==2024.8.30
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- charset-normalizer==3.4.0
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- click==8.1.7
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- dataclasses-json==0.6.7
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- deprecated==1.2.15
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- dirtyjson==1.0.8
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- distro==1.9.0
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- einops==0.7.0
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- exceptiongroup==1.2.2
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- filelock==3.16.1
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- filetype==1.2.0
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- frozenlist==1.5.0
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- fsspec==2024.10.0
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- gitdb==4.0.11
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- gitpython==3.1.43
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- greenlet==3.1.1
28
- h11==0.14.0
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- httpcore==1.0.7
30
- httpx==0.27.2
31
- huggingface-hub==0.26.2
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- idna==3.10
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- instructorembedding==1.0.1
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- jinja2==3.1.4
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- jiter==0.7.1
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- joblib==1.4.2
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- jsonschema==4.23.0
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- jsonschema-specifications==2024.10.1
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- llama-cloud==0.1.5
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  llama-index==0.11.20
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- llama-index-agent-openai==0.3.4
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- llama-index-cli==0.3.1
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- llama-index-core==0.11.23
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  llama-index-embeddings-huggingface==0.3.1
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  llama-index-embeddings-instructor==0.2.1
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- llama-index-embeddings-openai==0.2.5
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- llama-index-indices-managed-llama-cloud==0.6.0
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- llama-index-legacy==0.9.48.post4
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- llama-index-llms-openai==0.2.16
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- llama-index-llms-openai-like==0.2.0
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- llama-index-llms-replicate==0.3.0
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- llama-index-multi-modal-llms-openai==0.2.3
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- llama-index-program-openai==0.2.0
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- llama-index-question-gen-openai==0.2.0
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- llama-index-readers-file==0.2.2
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- llama-index-readers-llama-parse==0.3.0
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- llama-parse==0.5.15
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- markdown-it-py==3.0.0
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- markupsafe==3.0.2
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- marshmallow==3.23.1
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- mdurl==0.1.2
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- mpmath==1.3.0
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- multidict==6.1.0
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- mypy-extensions==1.0.0
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- narwhals==1.14.2
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- nest-asyncio==1.6.0
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- networkx==3.4.2
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- nltk==3.9.1
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- numpy==1.26.4
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- openai==1.55.0
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- packaging==24.2
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- pandas==2.2.3
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- pillow==10.4.0
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- propcache==0.2.0
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- protobuf==5.26.1
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- pyarrow==18.0.0
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- pydantic==2.10.1
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- pydantic-core==2.27.1
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- pydeck==0.9.1
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- pygments==2.18.0
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- pypdf==4.3.1
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- python-dateutil==2.9.0.post0
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- pytz==2024.2
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- pyyaml==6.0.2
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- referencing==0.35.1
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- regex==2024.11.6
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- requests==2.32.3
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- rich==13.9.4
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- rpds-py==0.21.0
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- safetensors==0.4.5
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- scikit-learn==1.5.2
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- scipy==1.14.1
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- sentence-transformers==2.7.0
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- six==1.16.0
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- smmap==5.0.1
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- sniffio==1.3.1
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- soupsieve==2.6
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- sqlalchemy==2.0.36
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- streamlit==1.39.0
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- striprtf==0.0.26
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- sympy==1.13.1
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- tenacity==8.5.0
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- threadpoolctl==3.5.0
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- tiktoken==0.8.0
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- tokenizers==0.13.3
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- torch==2.1.2
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- torchaudio==2.1.2
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- torchvision==0.16.0
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- tornado==6.4.2
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- tqdm==4.67.1
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- transformers==4.46.3
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- triton
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- typing-extensions==4.12.2
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- typing-inspect==0.9.0
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- tzdata==2024.2
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- urllib3==2.2.3
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- watchdog==5.0.3
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- wrapt==1.17.0
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- yarl==1.18.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  llama-index==0.11.20
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+ llama-index-llms-replicate==0.3.0
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+ llama-index-llms-openai-like==0.2.0
 
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  llama-index-embeddings-huggingface==0.3.1
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  llama-index-embeddings-instructor==0.2.1
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+ streamlit==1.39.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
.ipynb_checkpoints/test_internlm-checkpoint.py ADDED
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+ from openai import OpenAI
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+ import os
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+
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+ base_url = "https://internlm-chat.intern-ai.org.cn/puyu/api/v1/"
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+ # api_key = "sk-请填写准确的 token!"
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+ api_key = os.getenv("API_KEY")
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+ model="internlm2.5-latest"
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+
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+ # base_url = "https://api.siliconflow.cn/v1"
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+ # api_key = "sk-请填写准确的 token!"
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+ # model="internlm/internlm2_5-7b-chat"
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+
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+ client = OpenAI(
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+ api_key=api_key ,
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+ base_url=base_url,
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+ )
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+
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+ chat_rsp = client.chat.completions.create(
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+ model=model,
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+ messages=[{"role": "user", "content": "Qwen2Attention是什么?"}],
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+ )
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+
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+ for choice in chat_rsp.choices:
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+ print(choice.message.content)
requirements.txt ADDED
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+ llama-index==0.11.20
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+ llama-index-llms-replicate==0.3.0
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+ llama-index-llms-openai-like==0.2.0
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+ llama-index-embeddings-huggingface==0.3.1
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+ llama-index-embeddings-instructor==0.2.1
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+ streamlit==1.39.0